Sample records for quantitative metabolic flux

  1. MetaFluxNet: the management of metabolic reaction information and quantitative metabolic flux analysis.

    PubMed

    Lee, Dong-Yup; Yun, Hongsoek; Park, Sunwon; Lee, Sang Yup

    2003-11-01

    MetaFluxNet is a program package for managing information on the metabolic reaction network and for quantitatively analyzing metabolic fluxes in an interactive and customized way. It allows users to interpret and examine metabolic behavior in response to genetic and/or environmental modifications. As a result, quantitative in silico simulations of metabolic pathways can be carried out to understand the metabolic status and to design the metabolic engineering strategies. The main features of the program include a well-developed model construction environment, user-friendly interface for metabolic flux analysis (MFA), comparative MFA of strains having different genotypes under various environmental conditions, and automated pathway layout creation. http://mbel.kaist.ac.kr/ A manual for MetaFluxNet is available as PDF file.

  2. Quantitation of Cellular Metabolic Fluxes of Methionine

    PubMed Central

    Shlomi, Tomer; Fan, Jing; Tang, Baiqing; Kruger, Warren D.; Rabinowitz, Joshua D.

    2014-01-01

    Methionine is an essential proteogenic amino acid. In addition, it is a methyl donor for DNA and protein methylation and a propylamine donor for polyamine biosyn-thesis. Both the methyl and propylamine donation pathways involve metabolic cycles, and methods are needed to quantitate these cycles. Here, we describe an analytical approach for quantifying methionine metabolic fluxes that accounts for the mixing of intracellular and extracellular methionine pools. We observe that such mixing prevents isotope tracing experiments from reaching the steady state due to the large size of the media pools and hence precludes the use of standard stationary metabolic flux analysis. Our approach is based on feeding cells with 13C methionine and measuring the isotope-labeling kinetics of both intracellular and extracellular methionine by liquid chromatography−mass spectrometry (LC-MS). We apply this method to quantify methionine metabolism in a human fibrosarcoma cell line and study how methionine salvage pathway enzyme methylthioadenosine phosphorylase (MTAP), frequently deleted in cancer, affects methionine metabolism. We find that both transmethylation and propylamine transfer fluxes amount to roughly 15% of the net methionine uptake, with no major changes due to MTAP deletion. Our method further enables the quantification of flux through the pro-tumorigenic enzyme ornithine decarboxylase, and this flux increases 2-fold following MTAP deletion. The analytical approach used to quantify methionine metabolic fluxes is applicable for other metabolic systems affected by mixing of intracellular and extracellular metabolite pools. PMID:24397525

  3. Quantitative Analysis of NAD Synthesis-Breakdown Fluxes.

    PubMed

    Liu, Ling; Su, Xiaoyang; Quinn, William J; Hui, Sheng; Krukenberg, Kristin; Frederick, David W; Redpath, Philip; Zhan, Le; Chellappa, Karthikeyani; White, Eileen; Migaud, Marie; Mitchison, Timothy J; Baur, Joseph A; Rabinowitz, Joshua D

    2018-05-01

    The redox cofactor nicotinamide adenine dinucleotide (NAD) plays a central role in metabolism and is a substrate for signaling enzymes including poly-ADP-ribose-polymerases (PARPs) and sirtuins. NAD concentration falls during aging, which has triggered intense interest in strategies to boost NAD levels. A limitation in understanding NAD metabolism has been reliance on concentration measurements. Here, we present isotope-tracer methods for NAD flux quantitation. In cell lines, NAD was made from nicotinamide and consumed largely by PARPs and sirtuins. In vivo, NAD was made from tryptophan selectively in the liver, which then excreted nicotinamide. NAD fluxes varied widely across tissues, with high flux in the small intestine and spleen and low flux in the skeletal muscle. Intravenous administration of nicotinamide riboside or mononucleotide delivered intact molecules to multiple tissues, but the same agents given orally were metabolized to nicotinamide in the liver. Thus, flux analysis can reveal tissue-specific NAD metabolism. Copyright © 2018 Elsevier Inc. All rights reserved.

  4. Two-Scale 13C Metabolic Flux Analysis for Metabolic Engineering.

    PubMed

    Ando, David; Garcia Martin, Hector

    2018-01-01

    Accelerating the Design-Build-Test-Learn (DBTL) cycle in synthetic biology is critical to achieving rapid and facile bioengineering of organisms for the production of, e.g., biofuels and other chemicals. The Learn phase involves using data obtained from the Test phase to inform the next Design phase. As part of the Learn phase, mathematical models of metabolic fluxes give a mechanistic level of comprehension to cellular metabolism, isolating the principle drivers of metabolic behavior from the peripheral ones, and directing future experimental designs and engineering methodologies. Furthermore, the measurement of intracellular metabolic fluxes is specifically noteworthy as providing a rapid and easy-to-understand picture of how carbon and energy flow throughout the cell. Here, we present a detailed guide to performing metabolic flux analysis in the Learn phase of the DBTL cycle, where we show how one can take the isotope labeling data from a 13 C labeling experiment and immediately turn it into a determination of cellular fluxes that points in the direction of genetic engineering strategies that will advance the metabolic engineering process.For our modeling purposes we use the Joint BioEnergy Institute (JBEI) Quantitative Metabolic Modeling (jQMM) library, which provides an open-source, python-based framework for modeling internal metabolic fluxes and making actionable predictions on how to modify cellular metabolism for specific bioengineering goals. It presents a complete toolbox for performing different types of flux analysis such as Flux Balance Analysis, 13 C Metabolic Flux Analysis, and it introduces the capability to use 13 C labeling experimental data to constrain comprehensive genome-scale models through a technique called two-scale 13 C Metabolic Flux Analysis (2S- 13 C MFA) [1]. In addition to several other capabilities, the jQMM is also able to predict the effects of knockouts using the MoMA and ROOM methodologies. The use of the jQMM library is

  5. 13C-based metabolic flux analysis: fundamentals and practice.

    PubMed

    Yang, Tae Hoon

    2013-01-01

    Isotope-based metabolic flux analysis is one of the emerging technologies applied to system level metabolic phenotype characterization in metabolic engineering. Among the developed approaches, (13)C-based metabolic flux analysis has been established as a standard tool and has been widely applied to quantitative pathway characterization of diverse biological systems. To implement (13)C-based metabolic flux analysis in practice, comprehending the underlying mathematical and computational modeling fundamentals is of importance along with carefully conducted experiments and analytical measurements. Such knowledge is also crucial when designing (13)C-labeling experiments and properly acquiring key data sets essential for in vivo flux analysis implementation. In this regard, the modeling fundamentals of (13)C-labeling systems and analytical data processing are the main topics we will deal with in this chapter. Along with this, the relevant numerical optimization techniques are addressed to help implementation of the entire computational procedures aiming at (13)C-based metabolic flux analysis in vivo.

  6. Parallel labeling experiments for pathway elucidation and (13)C metabolic flux analysis.

    PubMed

    Antoniewicz, Maciek R

    2015-12-01

    Metabolic pathway models provide the foundation for quantitative studies of cellular physiology through the measurement of intracellular metabolic fluxes. For model organisms metabolic models are well established, with many manually curated genome-scale model reconstructions, gene knockout studies and stable-isotope tracing studies. However, for non-model organisms a similar level of knowledge is often lacking. Compartmentation of cellular metabolism in eukaryotic systems also presents significant challenges for quantitative (13)C-metabolic flux analysis ((13)C-MFA). Recently, innovative (13)C-MFA approaches have been developed based on parallel labeling experiments, the use of multiple isotopic tracers and integrated data analysis, that allow more rigorous validation of pathway models and improved quantification of metabolic fluxes. Applications of these approaches open new research directions in metabolic engineering, biotechnology and medicine. Copyright © 2015 Elsevier Ltd. All rights reserved.

  7. Retrobiosynthetic nuclear magnetic resonance analysis of amino acid biosynthesis and intermediary metabolism. Metabolic flux in developing maize kernels.

    PubMed

    Glawischnig, E; Gierl, A; Tomas, A; Bacher, A; Eisenreich, W

    2001-03-01

    Information on metabolic networks could provide the basis for the design of targets for metabolic engineering. To study metabolic flux in cereals, developing maize (Zea mays) kernels were grown in sterile culture on medium containing [U-(13)C(6)]glucose or [1,2-(13)C(2)]acetate. After growth, amino acids, lipids, and sitosterol were isolated from kernels as well as from the cobs, and their (13)C isotopomer compositions were determined by quantitative nuclear magnetic resonance spectroscopy. The highly specific labeling patterns were used to analyze the metabolic pathways leading to amino acids and the triterpene on a quantitative basis. The data show that serine is generated from phosphoglycerate, as well as from glycine. Lysine is formed entirely via the diaminopimelate pathway and sitosterol is synthesized entirely via the mevalonate route. The labeling data of amino acids and sitosterol were used to reconstruct the labeling patterns of key metabolic intermediates (e.g. acetyl-coenzyme A, pyruvate, phosphoenolpyruvate, erythrose 4-phosphate, and Rib 5-phosphate) that revealed quantitative information about carbon flux in the intermediary metabolism of developing maize kernels. Exogenous acetate served as an efficient precursor of sitosterol, as well as of amino acids of the aspartate and glutamate family; in comparison, metabolites formed in the plastidic compartments showed low acetate incorporation.

  8. Transcript abundance on its own cannot be used to infer fluxes in central metabolism

    DOE PAGES

    Schwender, Jorg; Konig, Christina; Klapperstuck, Matthias; ...

    2014-11-28

    An attempt has been made to define the extent to which metabolic flux in central plant metabolism is reflected by changes in the transcriptome and metabolome, based on an analysis of in vitro cultured immature embryos of two oilseed rape (Brassica napus) accessions which contrast for seed lipid accumulation. Metabolic flux analysis (MFA) was used to constrain a flux balance metabolic model which included 671 biochemical and transport reactions within the central metabolism. This highly confident flux information was eventually used for comparative analysis of flux vs. transcript (metabolite). Metabolite profiling succeeded in identifying 79 intermediates within the central metabolism,more » some of which differed quantitatively between the two accessions and displayed a significant shift corresponding to flux. An RNA-Seq based transcriptome analysis revealed a large number of genes which were differentially transcribed in the two accessions, including some enzymes/proteins active in major metabolic pathways. With a few exceptions, differential activity in the major pathways (glycolysis, TCA cycle, amino acid, and fatty acid synthesis) was not reflected in contrasting abundances of the relevant transcripts. The conclusion was that transcript abundance on its own cannot be used to infer metabolic activity/fluxes in central plant metabolism. Lastly, this limitation needs to be borne in mind in evaluating transcriptome data and designing metabolic engineering experiments.« less

  9. 3D TOCSY-HSQC NMR for metabolic flux analysis using non-uniform sampling

    DOE PAGES

    Reardon, Patrick N.; Marean-Reardon, Carrie L.; Bukovec, Melanie A.; ...

    2016-02-05

    13C-Metabolic Flux Analysis ( 13C-MFA) is rapidly being recognized as the authoritative method for determining fluxes through metabolic networks. Site-specific 13C enrichment information obtained using NMR spectroscopy is a valuable input for 13C-MFA experiments. Chemical shift overlaps in the 1D or 2D NMR experiments typically used for 13C-MFA frequently hinder assignment and quantitation of site-specific 13C enrichment. Here we propose the use of a 3D TOCSY-HSQC experiment for 13C-MFA. We employ Non-Uniform Sampling (NUS) to reduce the acquisition time of the experiment to a few hours, making it practical for use in 13C-MFA experiments. Our data show that the NUSmore » experiment is linear and quantitative. Identification of metabolites in complex mixtures, such as a biomass hydrolysate, is simplified by virtue of the 13C chemical shift obtained in the experiment. In addition, the experiment reports 13C-labeling information that reveals the position specific labeling of subsets of isotopomers. As a result, the information provided by this technique will enable more accurate estimation of metabolic fluxes in larger metabolic networks.« less

  10. Metabolic-flux dependent regulation of microbial physiology.

    PubMed

    Litsios, Athanasios; Ortega, Álvaro D; Wit, Ernst C; Heinemann, Matthias

    2018-04-01

    According to the most prevalent notion, changes in cellular physiology primarily occur in response to altered environmental conditions. Yet, recent studies have shown that changes in metabolic fluxes can also trigger phenotypic changes even when environmental conditions are unchanged. This suggests that cells have mechanisms in place to assess the magnitude of metabolic fluxes, that is, the rate of metabolic reactions, and use this information to regulate their physiology. In this review, we describe recent evidence for metabolic flux-sensing and flux-dependent regulation. Furthermore, we discuss how such sensing and regulation can be mechanistically achieved and present a set of new candidates for flux-signaling metabolites. Similar to metabolic-flux sensing, we argue that cells can also sense protein translation flux. Finally, we elaborate on the advantages that flux-based regulation can confer to cells. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

  11. Structural Control of Metabolic Flux

    PubMed Central

    Sajitz-Hermstein, Max; Nikoloski, Zoran

    2013-01-01

    Organisms have to continuously adapt to changing environmental conditions or undergo developmental transitions. To meet the accompanying change in metabolic demands, the molecular mechanisms of adaptation involve concerted interactions which ultimately induce a modification of the metabolic state, which is characterized by reaction fluxes and metabolite concentrations. These state transitions are the effect of simultaneously manipulating fluxes through several reactions. While metabolic control analysis has provided a powerful framework for elucidating the principles governing this orchestrated action to understand metabolic control, its applications are restricted by the limited availability of kinetic information. Here, we introduce structural metabolic control as a framework to examine individual reactions' potential to control metabolic functions, such as biomass production, based on structural modeling. The capability to carry out a metabolic function is determined using flux balance analysis (FBA). We examine structural metabolic control on the example of the central carbon metabolism of Escherichia coli by the recently introduced framework of functional centrality (FC). This framework is based on the Shapley value from cooperative game theory and FBA, and we demonstrate its superior ability to assign “share of control” to individual reactions with respect to metabolic functions and environmental conditions. A comparative analysis of various scenarios illustrates the usefulness of FC and its relations to other structural approaches pertaining to metabolic control. We propose a Monte Carlo algorithm to estimate FCs for large networks, based on the enumeration of elementary flux modes. We further give detailed biological interpretation of FCs for production of lactate and ATP under various respiratory conditions. PMID:24367246

  12. Metabolic cartography: experimental quantification of metabolic fluxes from isotopic labelling studies.

    PubMed

    O'Grady, John; Schwender, Jörg; Shachar-Hill, Yair; Morgan, John A

    2012-03-01

    For the past decade, flux maps have provided researchers with an in-depth perspective on plant metabolism. As a rapidly developing field, significant headway has been made recently in computation, experimentation, and overall understanding of metabolic flux analysis. These advances are particularly applicable to the study of plant metabolism. New dynamic computational methods such as non-stationary metabolic flux analysis are finding their place in the toolbox of metabolic engineering, allowing more organisms to be studied and decreasing the time necessary for experimentation, thereby opening new avenues by which to explore the vast diversity of plant metabolism. Also, improved methods of metabolite detection and measurement have been developed, enabling increasingly greater resolution of flux measurements and the analysis of a greater number of the multitude of plant metabolic pathways. Methods to deconvolute organelle-specific metabolism are employed with increasing effectiveness, elucidating the compartmental specificity inherent in plant metabolism. Advances in metabolite measurements have also enabled new types of experiments, such as the calculation of metabolic fluxes based on (13)CO(2) dynamic labelling data, and will continue to direct plant metabolic engineering. Newly calculated metabolic flux maps reveal surprising and useful information about plant metabolism, guiding future genetic engineering of crops to higher yields. Due to the significant level of complexity in plants, these methods in combination with other systems biology measurements are necessary to guide plant metabolic engineering in the future.

  13. Inference and Prediction of Metabolic Network Fluxes

    PubMed Central

    Nikoloski, Zoran; Perez-Storey, Richard; Sweetlove, Lee J.

    2015-01-01

    In this Update, we cover the basic principles of the estimation and prediction of the rates of the many interconnected biochemical reactions that constitute plant metabolic networks. This includes metabolic flux analysis approaches that utilize the rates or patterns of redistribution of stable isotopes of carbon and other atoms to estimate fluxes, as well as constraints-based optimization approaches such as flux balance analysis. Some of the major insights that have been gained from analysis of fluxes in plants are discussed, including the functioning of metabolic pathways in a network context, the robustness of the metabolic phenotype, the importance of cell maintenance costs, and the mechanisms that enable energy and redox balancing at steady state. We also discuss methodologies to exploit 'omic data sets for the construction of tissue-specific metabolic network models and to constrain the range of permissible fluxes in such models. Finally, we consider the future directions and challenges faced by the field of metabolic network flux phenotyping. PMID:26392262

  14. Elucidating dynamic metabolic physiology through network integration of quantitative time-course metabolomics

    DOE PAGES

    Bordbar, Aarash; Yurkovich, James T.; Paglia, Giuseppe; ...

    2017-04-07

    In this study, the increasing availability of metabolomics data necessitates novel methods for deeper data analysis and interpretation. We present a flux balance analysis method that allows for the computation of dynamic intracellular metabolic changes at the cellular scale through integration of time-course absolute quantitative metabolomics. This approach, termed “unsteady-state flux balance analysis” (uFBA), is applied to four cellular systems: three dynamic and one steady-state as a negative control. uFBA and FBA predictions are contrasted, and uFBA is found to be more accurate in predicting dynamic metabolic flux states for red blood cells, platelets, and Saccharomyces cerevisiae. Notably, only uFBAmore » predicts that stored red blood cells metabolize TCA intermediates to regenerate important cofactors, such as ATP, NADH, and NADPH. These pathway usage predictions were subsequently validated through 13C isotopic labeling and metabolic flux analysis in stored red blood cells. Utilizing time-course metabolomics data, uFBA provides an accurate method to predict metabolic physiology at the cellular scale for dynamic systems.« less

  15. Elucidating dynamic metabolic physiology through network integration of quantitative time-course metabolomics

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Bordbar, Aarash; Yurkovich, James T.; Paglia, Giuseppe

    In this study, the increasing availability of metabolomics data necessitates novel methods for deeper data analysis and interpretation. We present a flux balance analysis method that allows for the computation of dynamic intracellular metabolic changes at the cellular scale through integration of time-course absolute quantitative metabolomics. This approach, termed “unsteady-state flux balance analysis” (uFBA), is applied to four cellular systems: three dynamic and one steady-state as a negative control. uFBA and FBA predictions are contrasted, and uFBA is found to be more accurate in predicting dynamic metabolic flux states for red blood cells, platelets, and Saccharomyces cerevisiae. Notably, only uFBAmore » predicts that stored red blood cells metabolize TCA intermediates to regenerate important cofactors, such as ATP, NADH, and NADPH. These pathway usage predictions were subsequently validated through 13C isotopic labeling and metabolic flux analysis in stored red blood cells. Utilizing time-course metabolomics data, uFBA provides an accurate method to predict metabolic physiology at the cellular scale for dynamic systems.« less

  16. Metabolic network flux analysis for engineering plant systems.

    PubMed

    Shachar-Hill, Yair

    2013-04-01

    Metabolic network flux analysis (NFA) tools have proven themselves to be powerful aids to metabolic engineering of microbes by providing quantitative insights into the flows of material and energy through cellular systems. The development and application of NFA tools to plant systems has advanced in recent years and are yielding significant insights and testable predictions. Plants present substantial opportunities for the practical application of NFA but they also pose serious challenges related to the complexity of plant metabolic networks and to deficiencies in our knowledge of their structure and regulation. By considering the tools available and selected examples, this article attempts to assess where and how NFA is most likely to have a real impact on plant biotechnology. Copyright © 2013 Elsevier Ltd. All rights reserved.

  17. Rerouting of carbon flux in a glycogen mutant of cyanobacteria assessed via isotopically non-stationary 13 C metabolic flux analysis.

    PubMed

    Hendry, John I; Prasannan, Charulata; Ma, Fangfang; Möllers, K Benedikt; Jaiswal, Damini; Digmurti, Madhuri; Allen, Doug K; Frigaard, Niels-Ulrik; Dasgupta, Santanu; Wangikar, Pramod P

    2017-10-01

    Cyanobacteria, which constitute a quantitatively dominant phylum, have attracted attention in biofuel applications due to favorable physiological characteristics, high photosynthetic efficiency and amenability to genetic manipulations. However, quantitative aspects of cyanobacterial metabolism have received limited attention. In the present study, we have performed isotopically non-stationary 13 C metabolic flux analysis (INST- 13 C-MFA) to analyze rerouting of carbon in a glycogen synthase deficient mutant strain (glgA-I glgA-II) of the model cyanobacterium Synechococcus sp. PCC 7002. During balanced photoautotrophic growth, 10-20% of the fixed carbon is stored in the form of glycogen via a pathway that is conserved across the cyanobacterial phylum. Our results show that deletion of glycogen synthase gene orchestrates cascading effects on carbon distribution in various parts of the metabolic network. Carbon that was originally destined to be incorporated into glycogen gets partially diverted toward alternate storage molecules such as glucosylglycerol and sucrose. The rest is partitioned within the metabolic network, primarily via glycolysis and tricarboxylic acid cycle. A lowered flux toward carbohydrate synthesis and an altered distribution at the glucose-1-phosphate node indicate flexibility in the network. Further, reversibility of glycogen biosynthesis reactions points toward the presence of futile cycles. Similar redistribution of carbon was also predicted by Flux Balance Analysis. The results are significant to metabolic engineering efforts with cyanobacteria where fixed carbon needs to be re-routed to products of interest. Biotechnol. Bioeng. 2017;114: 2298-2308. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

  18. Metabolic flux analysis of Cyanothece sp. ATCC 51142 under mixotrophic conditions.

    PubMed

    Alagesan, Swathi; Gaudana, Sandeep B; Sinha, Avinash; Wangikar, Pramod P

    2013-11-01

    Cyanobacteria are a group of photosynthetic prokaryotes capable of utilizing solar energy to fix atmospheric carbon dioxide to biomass. Despite several "proof of principle" studies, low product yield is an impediment in commercialization of cyanobacteria-derived biofuels. Estimation of intracellular reaction rates by (13)C metabolic flux analysis ((13)C-MFA) would be a step toward enhancing biofuel yield via metabolic engineering. We report (13)C-MFA for Cyanothece sp. ATCC 51142, a unicellular nitrogen-fixing cyanobacterium, known for enhanced hydrogen yield under mixotrophic conditions. Rates of reactions in the central carbon metabolism under nitrogen-fixing and -non-fixing conditions were estimated by monitoring the competitive incorporation of (12)C and (13)C from unlabeled CO2 and uniformly labeled glycerol, respectively, into terminal metabolites such as amino acids. The observed labeling patterns suggest mixotrophic growth under both the conditions, with a larger fraction of unlabeled carbon in nitrate-sufficient cultures asserting a greater contribution of carbon fixation by photosynthesis and an anaplerotic pathway. Indeed, flux analysis complements the higher growth observed under nitrate-sufficient conditions. On the other hand, the flux through the oxidative pentose phosphate pathway and tricarboxylic acid cycle was greater in nitrate-deficient conditions, possibly to supply the precursors and reducing equivalents needed for nitrogen fixation. In addition, an enhanced flux through fructose-6-phosphate phosphoketolase possibly suggests the organism's preferred mode under nitrogen-fixing conditions. The (13)C-MFA results complement the reported predictions by flux balance analysis and provide quantitative insight into the organism's distinct metabolic features under nitrogen-fixing and -non-fixing conditions.

  19. From elementary flux modes to elementary flux vectors: Metabolic pathway analysis with arbitrary linear flux constraints.

    PubMed

    Klamt, Steffen; Regensburger, Georg; Gerstl, Matthias P; Jungreuthmayer, Christian; Schuster, Stefan; Mahadevan, Radhakrishnan; Zanghellini, Jürgen; Müller, Stefan

    2017-04-01

    Elementary flux modes (EFMs) emerged as a formal concept to describe metabolic pathways and have become an established tool for constraint-based modeling and metabolic network analysis. EFMs are characteristic (support-minimal) vectors of the flux cone that contains all feasible steady-state flux vectors of a given metabolic network. EFMs account for (homogeneous) linear constraints arising from reaction irreversibilities and the assumption of steady state; however, other (inhomogeneous) linear constraints, such as minimal and maximal reaction rates frequently used by other constraint-based techniques (such as flux balance analysis [FBA]), cannot be directly integrated. These additional constraints further restrict the space of feasible flux vectors and turn the flux cone into a general flux polyhedron in which the concept of EFMs is not directly applicable anymore. For this reason, there has been a conceptual gap between EFM-based (pathway) analysis methods and linear optimization (FBA) techniques, as they operate on different geometric objects. One approach to overcome these limitations was proposed ten years ago and is based on the concept of elementary flux vectors (EFVs). Only recently has the community started to recognize the potential of EFVs for metabolic network analysis. In fact, EFVs exactly represent the conceptual development required to generalize the idea of EFMs from flux cones to flux polyhedra. This work aims to present a concise theoretical and practical introduction to EFVs that is accessible to a broad audience. We highlight the close relationship between EFMs and EFVs and demonstrate that almost all applications of EFMs (in flux cones) are possible for EFVs (in flux polyhedra) as well. In fact, certain properties can only be studied with EFVs. Thus, we conclude that EFVs provide a powerful and unifying framework for constraint-based modeling of metabolic networks.

  20. From elementary flux modes to elementary flux vectors: Metabolic pathway analysis with arbitrary linear flux constraints

    PubMed Central

    Klamt, Steffen; Gerstl, Matthias P.; Jungreuthmayer, Christian; Mahadevan, Radhakrishnan; Müller, Stefan

    2017-01-01

    Elementary flux modes (EFMs) emerged as a formal concept to describe metabolic pathways and have become an established tool for constraint-based modeling and metabolic network analysis. EFMs are characteristic (support-minimal) vectors of the flux cone that contains all feasible steady-state flux vectors of a given metabolic network. EFMs account for (homogeneous) linear constraints arising from reaction irreversibilities and the assumption of steady state; however, other (inhomogeneous) linear constraints, such as minimal and maximal reaction rates frequently used by other constraint-based techniques (such as flux balance analysis [FBA]), cannot be directly integrated. These additional constraints further restrict the space of feasible flux vectors and turn the flux cone into a general flux polyhedron in which the concept of EFMs is not directly applicable anymore. For this reason, there has been a conceptual gap between EFM-based (pathway) analysis methods and linear optimization (FBA) techniques, as they operate on different geometric objects. One approach to overcome these limitations was proposed ten years ago and is based on the concept of elementary flux vectors (EFVs). Only recently has the community started to recognize the potential of EFVs for metabolic network analysis. In fact, EFVs exactly represent the conceptual development required to generalize the idea of EFMs from flux cones to flux polyhedra. This work aims to present a concise theoretical and practical introduction to EFVs that is accessible to a broad audience. We highlight the close relationship between EFMs and EFVs and demonstrate that almost all applications of EFMs (in flux cones) are possible for EFVs (in flux polyhedra) as well. In fact, certain properties can only be studied with EFVs. Thus, we conclude that EFVs provide a powerful and unifying framework for constraint-based modeling of metabolic networks. PMID:28406903

  1. Quantitative Multilevel Analysis of Central Metabolism in Developing Oilseeds of Oilseed Rape During In Vitro Culture

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Schwender, Jorg; Hebbelmann, Inga; Heinzel, Nicholas

    Seeds provide the basis for many food, feed, and fuel products. Continued increases in seed yield, composition, and quality require an improved understanding of how the developing seed converts carbon and nitrogen supplies into storage. Current knowledge of this process is often based on the premise that transcriptional regulation directly translates via enzyme concentration into flux. In an attempt to highlight metabolic control, we explore genotypic differences in carbon partitioning for in vitro cultured developing embryos of oilseed rape (Brassica napus). We determined biomass composition as well as 79 net fluxes, the levels of 77 metabolites, and 26 enzyme activitiesmore » with specific focus on central metabolism in nine selected germplasm accessions. We observed a tradeoff between the biomass component fractions of lipid and starch. With increasing lipid content over the spectrum of genotypes, plastidic fatty acid synthesis and glycolytic flux increased concomitantly, while glycolytic intermediates decreased. The lipid/starch tradeoff was not reflected at the proteome level, pointing to the significance of (posttranslational) metabolic control. Enzyme activity/flux and metabolite/flux correlations suggest that plastidic pyruvate kinase exerts flux control and that the lipid/starch tradeoff is most likely mediated by allosteric feedback regulation of phosphofructokinase and ADP-glucose pyrophosphorylase. Also, quantitative data were used to calculate in vivo mass action ratios, reaction equilibria, and metabolite turnover times. Compounds like cyclic 3',5'-AMP and sucrose-6-phosphate were identified to potentially be involved in so far unknown mechanisms of metabolic control. This study provides a rich source of quantitative data for those studying central metabolism..« less

  2. Modeling Neisseria meningitidis metabolism: from genome to metabolic fluxes

    PubMed Central

    Baart, Gino JE; Zomer, Bert; de Haan, Alex; van der Pol, Leo A; Beuvery, E Coen; Tramper, Johannes; Martens, Dirk E

    2007-01-01

    Background Neisseria meningitidis is a human pathogen that can infect diverse sites within the human host. The major diseases caused by N. meningitidis are responsible for death and disability, especially in young infants. In general, most of the recent work on N. meningitidis focuses on potential antigens and their functions, immunogenicity, and pathogenicity mechanisms. Very little work has been carried out on Neisseria primary metabolism over the past 25 years. Results Using the genomic database of N. meningitidis serogroup B together with biochemical and physiological information in the literature we constructed a genome-scale flux model for the primary metabolism of N. meningitidis. The validity of a simplified metabolic network derived from the genome-scale metabolic network was checked using flux-balance analysis in chemostat cultures. Several useful predictions were obtained from in silico experiments, including substrate preference. A minimal medium for growth of N. meningitidis was designed and tested succesfully in batch and chemostat cultures. Conclusion The verified metabolic model describes the primary metabolism of N. meningitidis in a chemostat in steady state. The genome-scale model is valuable because it offers a framework to study N. meningitidis metabolism as a whole, or certain aspects of it, and it can also be used for the purpose of vaccine process development (for example, the design of growth media). The flux distribution of the main metabolic pathways (that is, the pentose phosphate pathway and the Entner-Douderoff pathway) indicates that the major part of pyruvate (69%) is synthesized through the ED-cleavage, a finding that is in good agreement with literature. PMID:17617894

  3. Thermodynamics-Based Metabolic Flux Analysis

    PubMed Central

    Henry, Christopher S.; Broadbelt, Linda J.; Hatzimanikatis, Vassily

    2007-01-01

    A new form of metabolic flux analysis (MFA) called thermodynamics-based metabolic flux analysis (TMFA) is introduced with the capability of generating thermodynamically feasible flux and metabolite activity profiles on a genome scale. TMFA involves the use of a set of linear thermodynamic constraints in addition to the mass balance constraints typically used in MFA. TMFA produces flux distributions that do not contain any thermodynamically infeasible reactions or pathways, and it provides information about the free energy change of reactions and the range of metabolite activities in addition to reaction fluxes. TMFA is applied to study the thermodynamically feasible ranges for the fluxes and the Gibbs free energy change, ΔrG′, of the reactions and the activities of the metabolites in the genome-scale metabolic model of Escherichia coli developed by Palsson and co-workers. In the TMFA of the genome scale model, the metabolite activities and reaction ΔrG′ are able to achieve a wide range of values at optimal growth. The reaction dihydroorotase is identified as a possible thermodynamic bottleneck in E. coli metabolism with a ΔrG′ constrained close to zero while numerous reactions are identified throughout metabolism for which ΔrG′ is always highly negative regardless of metabolite concentrations. As it has been proposed previously, these reactions with exclusively negative ΔrG′ might be candidates for cell regulation, and we find that a significant number of these reactions appear to be the first steps in the linear portion of numerous biosynthesis pathways. The thermodynamically feasible ranges for the concentration ratios ATP/ADP, NAD(P)/NAD(P)H, and \\documentclass[10pt]{article} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{pmc} \\pagestyle{empty} \\oddsidemargin -1.0in \\begin{document} \\begin

  4. Using metabolic flux data to further constrain the metabolic solution space and predict internal flux patterns: the Escherichia coli spectrum.

    PubMed

    Wiback, Sharon J; Mahadevan, Radhakrishnan; Palsson, Bernhard Ø

    2004-05-05

    Constraint-based metabolic modeling has been used to capture the genome-scale, systems properties of an organism's metabolism. The first generation of these models has been built on annotated gene sequence. To further this field, we now need to develop methods to incorporate additional "omic" data types including transcriptomics, metabolomics, and fluxomics to further facilitate the construction, validation, and predictive capabilities of these models. The work herein combines metabolic flux data with an in silico model of central metabolism of Escherichia coli for model centric integration of the flux data. The extreme pathways for this network, which define the allowable solution space for all possible flux distributions, are analyzed using the alpha-spectrum. The alpha-spectrum determines which extreme pathways can and cannot contribute to the metabolic flux distribution for a given condition and gives the allowable range of weightings on each extreme pathway that can contribute. Since many extreme pathways cannot be used under certain conditions, the result is a "condition-specific" solution space that is a subset of the original solution space. The alpha-spectrum results are used to create a "condition-specific" extreme pathway matrix that can be analyzed using singular value decomposition (SVD). The first mode of the SVD analysis characterizes the solution space for a given condition. We show that SVD analysis of the alpha-spectrum extreme pathway matrix that incorporates measured uptake and byproduct secretion rates, can predict internal flux trends for different experimental conditions. These predicted internal flux trends are, in general, consistent with the flux trends measured using experimental metabolic flux analysis techniques. Copyright 2004 Wiley Periodicals, Inc.

  5. Finding elementary flux modes in metabolic networks based on flux balance analysis and flux coupling analysis: application to the analysis of Escherichia coli metabolism.

    PubMed

    Tabe-Bordbar, Shayan; Marashi, Sayed-Amir

    2013-12-01

    Elementary modes (EMs) are steady-state metabolic flux vectors with minimal set of active reactions. Each EM corresponds to a metabolic pathway. Therefore, studying EMs is helpful for analyzing the production of biotechnologically important metabolites. However, memory requirements for computing EMs may hamper their applicability as, in most genome-scale metabolic models, no EM can be computed due to running out of memory. In this study, we present a method for computing randomly sampled EMs. In this approach, a network reduction algorithm is used for EM computation, which is based on flux balance-based methods. We show that this approach can be used to recover the EMs in the medium- and genome-scale metabolic network models, while the EMs are sampled in an unbiased way. The applicability of such results is shown by computing “estimated” control-effective flux values in Escherichia coli metabolic network.

  6. 13C metabolic flux analysis at a genome-scale.

    PubMed

    Gopalakrishnan, Saratram; Maranas, Costas D

    2015-11-01

    Metabolic models used in 13C metabolic flux analysis generally include a limited number of reactions primarily from central metabolism. They typically omit degradation pathways, complete cofactor balances, and atom transition contributions for reactions outside central metabolism. This study addresses the impact on prediction fidelity of scaling-up mapping models to a genome-scale. The core mapping model employed in this study accounts for (75 reactions and 65 metabolites) primarily from central metabolism. The genome-scale metabolic mapping model (GSMM) (697 reaction and 595 metabolites) is constructed using as a basis the iAF1260 model upon eliminating reactions guaranteed not to carry flux based on growth and fermentation data for a minimal glucose growth medium. Labeling data for 17 amino acid fragments obtained from cells fed with glucose labeled at the second carbon was used to obtain fluxes and ranges. Metabolic fluxes and confidence intervals are estimated, for both core and genome-scale mapping models, by minimizing the sum of square of differences between predicted and experimentally measured labeling patterns using the EMU decomposition algorithm. Overall, we find that both topology and estimated values of the metabolic fluxes remain largely consistent between core and GSM model. Stepping up to a genome-scale mapping model leads to wider flux inference ranges for 20 key reactions present in the core model. The glycolysis flux range doubles due to the possibility of active gluconeogenesis, the TCA flux range expanded by 80% due to the availability of a bypass through arginine consistent with labeling data, and the transhydrogenase reaction flux was essentially unresolved due to the presence of as many as five routes for the inter-conversion of NADPH to NADH afforded by the genome-scale model. By globally accounting for ATP demands in the GSMM model the unused ATP decreased drastically with the lower bound matching the maintenance ATP requirement. A non

  7. Quantitative Multilevel Analysis of Central Metabolism in Developing Oilseeds of Oilseed Rape during in Vitro Culture1[OPEN

    PubMed Central

    Schwender, Jörg; Hebbelmann, Inga; Heinzel, Nicolas; Hildebrandt, Tatjana; Rogers, Alistair; Klapperstück, Matthias; Schreiber, Falk; Borisjuk, Ljudmilla; Rolletschek, Hardy

    2015-01-01

    Seeds provide the basis for many food, feed, and fuel products. Continued increases in seed yield, composition, and quality require an improved understanding of how the developing seed converts carbon and nitrogen supplies into storage. Current knowledge of this process is often based on the premise that transcriptional regulation directly translates via enzyme concentration into flux. In an attempt to highlight metabolic control, we explore genotypic differences in carbon partitioning for in vitro cultured developing embryos of oilseed rape (Brassica napus). We determined biomass composition as well as 79 net fluxes, the levels of 77 metabolites, and 26 enzyme activities with specific focus on central metabolism in nine selected germplasm accessions. Overall, we observed a tradeoff between the biomass component fractions of lipid and starch. With increasing lipid content over the spectrum of genotypes, plastidic fatty acid synthesis and glycolytic flux increased concomitantly, while glycolytic intermediates decreased. The lipid/starch tradeoff was not reflected at the proteome level, pointing to the significance of (posttranslational) metabolic control. Enzyme activity/flux and metabolite/flux correlations suggest that plastidic pyruvate kinase exerts flux control and that the lipid/starch tradeoff is most likely mediated by allosteric feedback regulation of phosphofructokinase and ADP-glucose pyrophosphorylase. Quantitative data were also used to calculate in vivo mass action ratios, reaction equilibria, and metabolite turnover times. Compounds like cyclic 3′,5′-AMP and sucrose-6-phosphate were identified to potentially be involved in so far unknown mechanisms of metabolic control. This study provides a rich source of quantitative data for those studying central metabolism. PMID:25944824

  8. Non-stationary (13)C-metabolic flux ratio analysis.

    PubMed

    Hörl, Manuel; Schnidder, Julian; Sauer, Uwe; Zamboni, Nicola

    2013-12-01

    (13)C-metabolic flux analysis ((13)C-MFA) has become a key method for metabolic engineering and systems biology. In the most common methodology, fluxes are calculated by global isotopomer balancing and iterative fitting to stationary (13)C-labeling data. This approach requires a closed carbon balance, long-lasting metabolic steady state, and the detection of (13)C-patterns in a large number of metabolites. These restrictions mostly reduced the application of (13)C-MFA to the central carbon metabolism of well-studied model organisms grown in minimal media with a single carbon source. Here we introduce non-stationary (13)C-metabolic flux ratio analysis as a novel method for (13)C-MFA to allow estimating local, relative fluxes from ultra-short (13)C-labeling experiments and without the need for global isotopomer balancing. The approach relies on the acquisition of non-stationary (13)C-labeling data exclusively for metabolites in the proximity of a node of converging fluxes and a local parameter estimation with a system of ordinary differential equations. We developed a generalized workflow that takes into account reaction types and the availability of mass spectrometric data on molecular ions or fragments for data processing, modeling, parameter and error estimation. We demonstrated the approach by analyzing three key nodes of converging fluxes in central metabolism of Bacillus subtilis. We obtained flux estimates that are in agreement with published results obtained from steady state experiments, but reduced the duration of the necessary (13)C-labeling experiment to less than a minute. These results show that our strategy enables to formally estimate relative pathway fluxes on extremely short time scale, neglecting cellular carbon balancing. Hence this approach paves the road to targeted (13)C-MFA in dynamic systems with multiple carbon sources and towards rich media. © 2013 Wiley Periodicals, Inc.

  9. Metabolic flux analysis using 13C peptide label measurements

    USDA-ARS?s Scientific Manuscript database

    13C metabolic flux analysis (MFA) has become the experimental method of choice to investigate cellular metabolism. MFA has established flux maps of central metabolism for dozens of microbes, cell cultures, and plant seeds. Steady-state MFA utilizes isotopic labeling measurements of amino acids obtai...

  10. Flux balance analysis of primary metabolism in Chlamydomonas reinhardtii.

    PubMed

    Boyle, Nanette R; Morgan, John A

    2009-01-07

    Photosynthetic organisms convert atmospheric carbon dioxide into numerous metabolites along the pathways to make new biomass. Aquatic photosynthetic organisms, which fix almost half of global inorganic carbon, have great potential: as a carbon dioxide fixation method, for the economical production of chemicals, or as a source for lipids and starch which can then be converted to biofuels. To harness this potential through metabolic engineering and to maximize production, a more thorough understanding of photosynthetic metabolism must first be achieved. A model algal species, C. reinhardtii, was chosen and the metabolic network reconstructed. Intracellular fluxes were then calculated using flux balance analysis (FBA). The metabolic network of primary metabolism for a green alga, C. reinhardtii, was reconstructed using genomic and biochemical information. The reconstructed network accounts for the intracellular localization of enzymes to three compartments and includes 484 metabolic reactions and 458 intracellular metabolites. Based on BLAST searches, one newly annotated enzyme (fructose-1,6-bisphosphatase) was added to the Chlamydomonas reinhardtii database. FBA was used to predict metabolic fluxes under three growth conditions, autotrophic, heterotrophic and mixotrophic growth. Biomass yields ranged from 28.9 g per mole C for autotrophic growth to 15 g per mole C for heterotrophic growth. The flux balance analysis model of central and intermediary metabolism in C. reinhardtii is the first such model for algae and the first model to include three metabolically active compartments. In addition to providing estimates of intracellular fluxes, metabolic reconstruction and modelling efforts also provide a comprehensive method for annotation of genome databases. As a result of our reconstruction, one new enzyme was annotated in the database and several others were found to be missing; implying new pathways or non-conserved enzymes. The use of FBA to estimate intracellular

  11. Beyond topology: coevolution of structure and flux in metabolic networks.

    PubMed

    Morrison, E S; Badyaev, A V

    2017-10-01

    Interactions between the structure of a metabolic network and its functional properties underlie its evolutionary diversification, but the mechanism by which such interactions arise remains elusive. Particularly unclear is whether metabolic fluxes that determine the concentrations of compounds produced by a metabolic network, are causally linked to a network's structure or emerge independently of it. A direct empirical study of populations where both structural and functional properties vary among individuals' metabolic networks is required to establish whether changes in structure affect the distribution of metabolic flux. In a population of house finches (Haemorhous mexicanus), we reconstructed full carotenoid metabolic networks for 442 individuals and uncovered 11 structural variants of this network with different compounds and reactions. We examined the consequences of this structural diversity for the concentrations of plumage-bound carotenoids produced by flux in these networks. We found that concentrations of metabolically derived, but not dietary carotenoids, depended on network structure. Flux was partitioned similarly among compounds in individuals of the same network structure: within each network, compound concentrations were closely correlated. The highest among-individual variation in flux occurred in networks with the strongest among-compound correlations, suggesting that changes in the magnitude, but not the distribution of flux, underlie individual differences in compound concentrations on a static network structure. These findings indicate that the distribution of flux in carotenoid metabolism closely follows network structure. Thus, evolutionary diversification and local adaptations in carotenoid metabolism may depend more on the gain or loss of enzymatic reactions than on changes in flux within a network structure. © 2017 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2017 European Society For Evolutionary Biology.

  12. Metabolic flux profiling of recombinant protein secreting Pichia pastoris growing on glucose:methanol mixtures

    PubMed Central

    2012-01-01

    Background The methylotrophic yeast Pichia pastoris has emerged as one of the most promising yeast hosts for the production of heterologous proteins. Mixed feeds of methanol and a multicarbon source instead of methanol as sole carbon source have been shown to improve product productivities and alleviate metabolic burden derived from protein production. Nevertheless, systematic quantitative studies on the relationships between the central metabolism and recombinant protein production in P. pastoris are still rather limited, particularly when growing this yeast on mixed carbon sources, thus hampering future metabolic network engineering strategies for improved protein production. Results The metabolic flux distribution in the central metabolism of P. pastoris growing on a mixed feed of glucose and methanol was analyzed by Metabolic Flux Analysis (MFA) using 13C-NMR-derived constraints. For this purpose, we defined new flux ratios for methanol assimilation pathways in P. pastoris cells growing on glucose:methanol mixtures. By using this experimental approach, the metabolic burden caused by the overexpression and secretion of a Rhizopus oryzae lipase (Rol) in P. pastoris was further analyzed. This protein has been previously shown to trigger the unfolded protein response in P. pastoris. A series of 13C-tracer experiments were performed on aerobic chemostat cultivations with a control and two different Rol producing strains growing at a dilution rate of 0.09 h−1 using a glucose:methanol 80:20 (w/w) mix as carbon source. The MFA performed in this study reveals a significant redistristribution of carbon fluxes in the central carbon metabolism when comparing the two recombinant strains vs the control strain, reflected in increased glycolytic, TCA cycle and NADH regeneration fluxes, as well as higher methanol dissimilation rates. Conclusions Overall, a further 13C-based MFA development to characterise the central metabolism of methylotrophic yeasts when growing on mixed

  13. The Inheritance of Metabolic Flux: Expressions for the within-Sibship Mean and Variance Given the Parental Genotypes

    PubMed Central

    Ward, P. J.

    1990-01-01

    Recent developments have related quantitative trait expression to metabolic flux. The present paper investigates some implications of this for statistical aspects of polygenic inheritance. Expressions are derived for the within-sibship genetic mean and genetic variance of metabolic flux given a pair of parental, diploid, n-locus genotypes. These are exact and hold for arbitrary numbers of gene loci, arbitrary allelic values at each locus, and for arbitrary recombination fractions between adjacent gene loci. The within-sibship, genetic variance is seen to be simply a measure of parental heterozygosity plus a measure of the degree of linkage coupling within the parental genotypes. Approximations are given for the within-sibship phenotypic mean and variance of metabolic flux. These results are applied to the problem of attaining adequate statistical power in a test of association between allozymic variation and inter-individual variation in metabolic flux. Simulations indicate that statistical power can be greatly increased by augmenting the data with predictions and observations on progeny statistics in relation to parental allozyme genotypes. Adequate power may thus be attainable at small sample sizes, and when allozymic variation is scored at a only small fraction of the total set of loci whose catalytic products determine the flux. PMID:2379825

  14. Metabolic flux estimation using particle swarm optimization with penalty function.

    PubMed

    Long, Hai-Xia; Xu, Wen-Bo; Sun, Jun

    2009-01-01

    Metabolic flux estimation through 13C trace experiment is crucial for quantifying the intracellular metabolic fluxes. In fact, it corresponds to a constrained optimization problem that minimizes a weighted distance between measured and simulated results. In this paper, we propose particle swarm optimization (PSO) with penalty function to solve 13C-based metabolic flux estimation problem. The stoichiometric constraints are transformed to an unconstrained one, by penalizing the constraints and building a single objective function, which in turn is minimized using PSO algorithm for flux quantification. The proposed algorithm is applied to estimate the central metabolic fluxes of Corynebacterium glutamicum. From simulation results, it is shown that the proposed algorithm has superior performance and fast convergence ability when compared to other existing algorithms.

  15. Synergy between (13)C-metabolic flux analysis and flux balance analysis for understanding metabolic adaptation to anaerobiosis in E. coli.

    PubMed

    Chen, Xuewen; Alonso, Ana P; Allen, Doug K; Reed, Jennifer L; Shachar-Hill, Yair

    2011-01-01

    Genome-based Flux Balance Analysis (FBA) and steady-state isotopic-labeling-based Metabolic Flux Analysis (MFA) are complimentary approaches to predicting and measuring the operation and regulation of metabolic networks. Here, genome-derived models of Escherichia coli (E. coli) metabolism were used for FBA and ¹³C-MFA analyses of aerobic and anaerobic growths of wild-type E. coli (K-12 MG1655) cells. Validated MFA flux maps reveal that the fraction of maintenance ATP consumption in total ATP production is about 14% higher under anaerobic (51.1%) than aerobic conditions (37.2%). FBA revealed that an increased ATP utilization is consumed by ATP synthase to secrete protons from fermentation. The TCA cycle is shown to be incomplete in aerobically growing cells and submaximal growth is due to limited oxidative phosphorylation. An FBA was successful in predicting product secretion rates in aerobic culture if both glucose and oxygen uptake measurement were constrained, but the most-frequently predicted values of internal fluxes yielded from sampling the feasible space differ substantially from MFA-derived fluxes. © 2010 Elsevier Inc. All rights reserved.

  16. E-Flux2 and SPOT: Validated Methods for Inferring Intracellular Metabolic Flux Distributions from Transcriptomic Data.

    PubMed

    Kim, Min Kyung; Lane, Anatoliy; Kelley, James J; Lun, Desmond S

    2016-01-01

    Several methods have been developed to predict system-wide and condition-specific intracellular metabolic fluxes by integrating transcriptomic data with genome-scale metabolic models. While powerful in many settings, existing methods have several shortcomings, and it is unclear which method has the best accuracy in general because of limited validation against experimentally measured intracellular fluxes. We present a general optimization strategy for inferring intracellular metabolic flux distributions from transcriptomic data coupled with genome-scale metabolic reconstructions. It consists of two different template models called DC (determined carbon source model) and AC (all possible carbon sources model) and two different new methods called E-Flux2 (E-Flux method combined with minimization of l2 norm) and SPOT (Simplified Pearson cOrrelation with Transcriptomic data), which can be chosen and combined depending on the availability of knowledge on carbon source or objective function. This enables us to simulate a broad range of experimental conditions. We examined E. coli and S. cerevisiae as representative prokaryotic and eukaryotic microorganisms respectively. The predictive accuracy of our algorithm was validated by calculating the uncentered Pearson correlation between predicted fluxes and measured fluxes. To this end, we compiled 20 experimental conditions (11 in E. coli and 9 in S. cerevisiae), of transcriptome measurements coupled with corresponding central carbon metabolism intracellular flux measurements determined by 13C metabolic flux analysis (13C-MFA), which is the largest dataset assembled to date for the purpose of validating inference methods for predicting intracellular fluxes. In both organisms, our method achieves an average correlation coefficient ranging from 0.59 to 0.87, outperforming a representative sample of competing methods. Easy-to-use implementations of E-Flux2 and SPOT are available as part of the open-source package MOST (http

  17. Constraining Genome-Scale Models to Represent the Bow Tie Structure of Metabolism for 13C Metabolic Flux Analysis

    PubMed Central

    Ando, David; Singh, Jahnavi; Keasling, Jay D.; García Martín, Héctor

    2018-01-01

    Determination of internal metabolic fluxes is crucial for fundamental and applied biology because they map how carbon and electrons flow through metabolism to enable cell function. 13C Metabolic Flux Analysis (13C MFA) and Two-Scale 13C Metabolic Flux Analysis (2S-13C MFA) are two techniques used to determine such fluxes. Both operate on the simplifying approximation that metabolic flux from peripheral metabolism into central “core” carbon metabolism is minimal, and can be omitted when modeling isotopic labeling in core metabolism. The validity of this “two-scale” or “bow tie” approximation is supported both by the ability to accurately model experimental isotopic labeling data, and by experimentally verified metabolic engineering predictions using these methods. However, the boundaries of core metabolism that satisfy this approximation can vary across species, and across cell culture conditions. Here, we present a set of algorithms that (1) systematically calculate flux bounds for any specified “core” of a genome-scale model so as to satisfy the bow tie approximation and (2) automatically identify an updated set of core reactions that can satisfy this approximation more efficiently. First, we leverage linear programming to simultaneously identify the lowest fluxes from peripheral metabolism into core metabolism compatible with the observed growth rate and extracellular metabolite exchange fluxes. Second, we use Simulated Annealing to identify an updated set of core reactions that allow for a minimum of fluxes into core metabolism to satisfy these experimental constraints. Together, these methods accelerate and automate the identification of a biologically reasonable set of core reactions for use with 13C MFA or 2S-13C MFA, as well as provide for a substantially lower set of flux bounds for fluxes into the core as compared with previous methods. We provide an open source Python implementation of these algorithms at https

  18. Metabolic flux analysis of heterotrophic growth in Chlamydomonas reinhardtii.

    PubMed

    Boyle, Nanette R; Sengupta, Neelanjan; Morgan, John A

    2017-01-01

    Despite the wealth of knowledge available for C. reinhardtii, the central metabolic fluxes of growth on acetate have not yet been determined. In this study, 13C-metabolic flux analysis (13C-MFA) was used to determine and quantify the metabolic pathways of primary metabolism in C. reinhardtii cells grown under heterotrophic conditions with acetate as the sole carbon source. Isotopic labeling patterns of compartment specific biomass derived metabolites were used to calculate the fluxes. It was found that acetate is ligated with coenzyme A in the three subcellular compartments (cytosol, mitochondria and plastid) included in the model. Two citrate synthases were found to potentially be involved in acetyl-coA metabolism; one localized in the mitochondria and the other acting outside the mitochondria. Labeling patterns demonstrate that Acetyl-coA synthesized in the plastid is directly incorporated in synthesis of fatty acids. Despite having a complete TCA cycle in the mitochondria, it was also found that a majority of the malate flux is shuttled to the cytosol and plastid where it is converted to oxaloacetate providing reducing equivalents to these compartments. When compared to predictions by flux balance analysis, fluxes measured with 13C-MFA were found to be suboptimal with respect to biomass yield; C. reinhardtii sacrifices biomass yield to produce ATP and reducing equivalents.

  19. Elucidating the role of copper in CHO cell energy metabolism using (13)C metabolic flux analysis.

    PubMed

    Nargund, Shilpa; Qiu, Jinshu; Goudar, Chetan T

    2015-01-01

    (13)C-metabolic flux analysis was used to understand copper deficiency-related restructuring of energy metabolism, which leads to excessive lactate production in recombinant protein-producing CHO cells. Stationary-phase labeling experiments with U-(13)C glucose were conducted on CHO cells grown under high and limiting copper in 3 L fed-batch bioreactors. The resultant labeling patterns of soluble metabolites were measured by GC-MS and used to estimate metabolic fluxes in the central carbon metabolism pathways using OpenFlux. Fluxes were evaluated 300 times from stoichiometrically feasible random guess values and their confidence intervals calculated by Monte Carlo simulations. Results from metabolic flux analysis exhibited significant carbon redistribution throughout the metabolic network in cells under Cu deficiency. Specifically, glycolytic fluxes increased (25%-79% relative to glucose uptake) whereas fluxes through the TCA and pentose phosphate pathway (PPP) were lower (15%-23% and 74%, respectively) compared with the Cu-containing condition. Furthermore, under Cu deficiency, 33% of the flux entering TCA via the pyruvate node was redirected to lactate and malate production. Based on these results, we hypothesize that Cu deficiency disrupts the electron transport chain causing ATP deficiency, redox imbalance, and oxidative stress, which in turn drive copper-deficient CHO cells to produce energy via aerobic glycolysis, which is associated with excessive lactate production, rather than the more efficient route of oxidative phosphorylation. © 2015 American Institute of Chemical Engineers.

  20. Isotopically nonstationary 13C flux analysis of changes in Arabidopsis thaliana leaf metabolism due to high light acclimation

    PubMed Central

    Ma, Fangfang; Jazmin, Lara J.; Young, Jamey D.; Allen, Doug K.

    2014-01-01

    Improving plant productivity is an important aim for metabolic engineering. There are few comprehensive methods that quantitatively describe leaf metabolism, although such information would be valuable for increasing photosynthetic capacity, enhancing biomass production, and rerouting carbon flux toward desirable end products. Isotopically nonstationary metabolic flux analysis (INST-MFA) has been previously applied to map carbon fluxes in photoautotrophic bacteria, which involves model-based regression of transient 13C-labeling patterns of intracellular metabolites. However, experimental and computational difficulties have hindered its application to terrestrial plant systems. We performed in vivo isotopic labeling of Arabidopsis thaliana rosettes with 13CO2 and estimated fluxes throughout leaf photosynthetic metabolism by INST-MFA. Plants grown at 200 µmol m-2s−1 light were compared with plants acclimated for 9 d at an irradiance of 500 µmol⋅m−2⋅s−1. Approximately 1,400 independent mass isotopomer measurements obtained from analysis of 37 metabolite fragment ions were regressed to estimate 136 total fluxes (54 free fluxes) under each condition. The results provide a comprehensive description of changes in carbon partitioning and overall photosynthetic flux after long-term developmental acclimation of leaves to high light. Despite a doubling in the carboxylation rate, the photorespiratory flux increased from 17 to 28% of net CO2 assimilation with high-light acclimation (Vc/Vo: 3.5:1 vs. 2.3:1, respectively). This study highlights the potential of 13C INST-MFA to describe emergent flux phenotypes that respond to environmental conditions or plant physiology and cannot be obtained by other complementary approaches. PMID:25368168

  1. The JBEI quantitative metabolic modeling library (jQMM): a python library for modeling microbial metabolism.

    PubMed

    Birkel, Garrett W; Ghosh, Amit; Kumar, Vinay S; Weaver, Daniel; Ando, David; Backman, Tyler W H; Arkin, Adam P; Keasling, Jay D; Martín, Héctor García

    2017-04-05

    Modeling of microbial metabolism is a topic of growing importance in biotechnology. Mathematical modeling helps provide a mechanistic understanding for the studied process, separating the main drivers from the circumstantial ones, bounding the outcomes of experiments and guiding engineering approaches. Among different modeling schemes, the quantification of intracellular metabolic fluxes (i.e. the rate of each reaction in cellular metabolism) is of particular interest for metabolic engineering because it describes how carbon and energy flow throughout the cell. In addition to flux analysis, new methods for the effective use of the ever more readily available and abundant -omics data (i.e. transcriptomics, proteomics and metabolomics) are urgently needed. The jQMM library presented here provides an open-source, Python-based framework for modeling internal metabolic fluxes and leveraging other -omics data for the scientific study of cellular metabolism and bioengineering purposes. Firstly, it presents a complete toolbox for simultaneously performing two different types of flux analysis that are typically disjoint: Flux Balance Analysis and 13 C Metabolic Flux Analysis. Moreover, it introduces the capability to use 13 C labeling experimental data to constrain comprehensive genome-scale models through a technique called two-scale 13 C Metabolic Flux Analysis (2S- 13 C MFA). In addition, the library includes a demonstration of a method that uses proteomics data to produce actionable insights to increase biofuel production. Finally, the use of the jQMM library is illustrated through the addition of several Jupyter notebook demonstration files that enhance reproducibility and provide the capability to be adapted to the user's specific needs. jQMM will facilitate the design and metabolic engineering of organisms for biofuels and other chemicals, as well as investigations of cellular metabolism and leveraging -omics data. As an open source software project, we hope it will

  2. Flux analysis and metabolomics for systematic metabolic engineering of microorganisms.

    PubMed

    Toya, Yoshihiro; Shimizu, Hiroshi

    2013-11-01

    Rational engineering of metabolism is important for bio-production using microorganisms. Metabolic design based on in silico simulations and experimental validation of the metabolic state in the engineered strain helps in accomplishing systematic metabolic engineering. Flux balance analysis (FBA) is a method for the prediction of metabolic phenotype, and many applications have been developed using FBA to design metabolic networks. Elementary mode analysis (EMA) and ensemble modeling techniques are also useful tools for in silico strain design. The metabolome and flux distribution of the metabolic pathways enable us to evaluate the metabolic state and provide useful clues to improve target productivity. Here, we reviewed several computational applications for metabolic engineering by using genome-scale metabolic models of microorganisms. We also discussed the recent progress made in the field of metabolomics and (13)C-metabolic flux analysis techniques, and reviewed these applications pertaining to bio-production development. Because these in silico or experimental approaches have their respective advantages and disadvantages, the combined usage of these methods is complementary and effective for metabolic engineering. Copyright © 2013 Elsevier Inc. All rights reserved.

  3. Synergizing 13C Metabolic Flux Analysis and Metabolic Engineering for Biochemical Production.

    PubMed

    Guo, Weihua; Sheng, Jiayuan; Feng, Xueyang

    Metabolic engineering of industrial microorganisms to produce chemicals, fuels, and drugs has attracted increasing interest as it provides an environment-friendly and renewable route that does not depend on depleting petroleum sources. However, the microbial metabolism is so complex that metabolic engineering efforts often have difficulty in achieving a satisfactory yield, titer, or productivity of the target chemical. To overcome this challenge, 13 C Metabolic Flux Analysis ( 13 C-MFA) has been developed to investigate rigorously the cell metabolism and quantify the carbon flux distribution in central metabolic pathways. In the past decade, 13 C-MFA has been widely used in academic labs and the biotechnology industry to pinpoint the key issues related to microbial-based chemical production and to guide the development of the appropriate metabolic engineering strategies for improving the biochemical production. In this chapter we introduce the basics of 13 C-MFA and illustrate how 13 C-MFA has been applied to synergize with metabolic engineering to identify and tackle the rate-limiting steps in biochemical production.

  4. Stepwise inference of likely dynamic flux distributions from metabolic time series data.

    PubMed

    Faraji, Mojdeh; Voit, Eberhard O

    2017-07-15

    Most metabolic pathways contain more reactions than metabolites and therefore have a wide stoichiometric matrix that corresponds to infinitely many possible flux distributions that are perfectly compatible with the dynamics of the metabolites in a given dataset. This under-determinedness poses a challenge for the quantitative characterization of flux distributions from time series data and thus for the design of adequate, predictive models. Here we propose a method that reduces the degrees of freedom in a stepwise manner and leads to a dynamic flux distribution that is, in a statistical sense, likely to be close to the true distribution. We applied the proposed method to the lignin biosynthesis pathway in switchgrass. The system consists of 16 metabolites and 23 enzymatic reactions. It has seven degrees of freedom and therefore admits a large space of dynamic flux distributions that all fit a set of metabolic time series data equally well. The proposed method reduces this space in a systematic and biologically reasonable manner and converges to a likely dynamic flux distribution in just a few iterations. The estimated solution and the true flux distribution, which is known in this case, show excellent agreement and thereby lend support to the method. The computational model was implemented in MATLAB (version R2014a, The MathWorks, Natick, MA). The source code is available at https://github.gatech.edu/VoitLab/Stepwise-Inference-of-Likely-Dynamic-Flux-Distributions and www.bst.bme.gatech.edu/research.php . mojdeh@gatech.edu or eberhard.voit@bme.gatech.edu. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

  5. The JBEI quantitative metabolic modeling library (jQMM): a python library for modeling microbial metabolism

    DOE PAGES

    Birkel, Garrett W.; Ghosh, Amit; Kumar, Vinay S.; ...

    2017-04-05

    Modeling of microbial metabolism is a topic of growing importance in biotechnology. Mathematical modeling helps provide a mechanistic understanding for the studied process, separating the main drivers from the circumstantial ones, bounding the outcomes of experiments and guiding engineering approaches. Among different modeling schemes, the quantification of intracellular metabolic fluxes (i.e. the rate of each reaction in cellular metabolism) is of particular interest for metabolic engineering because it describes how carbon and energy flow throughout the cell. In addition to flux analysis, new methods for the effective use of the ever more readily available and abundant -omics data (i.e. transcriptomics,more » proteomics and metabolomics) are urgently needed. The jQMM library presented here provides an open-source, Python-based framework for modeling internal metabolic fluxes and leveraging other -omics data for the scientific study of cellular metabolism and bioengineering purposes. Firstly, it presents a complete toolbox for simultaneously performing two different types of flux analysis that are typically disjoint: Flux Balance Analysis and 13C Metabolic Flux Analysis. Moreover, it introduces the capability to use 13C labeling experimental data to constrain comprehensive genome-scale models through a technique called two-scale 13C Metabolic Flux Analysis (2S- 13C MFA). In addition, the library includes a demonstration of a method that uses proteomics data to produce actionable insights to increase biofuel production. Finally, the use of the jQMM library is illustrated through the addition of several Jupyter notebook demonstration files that enhance reproducibility and provide the capability to be adapted to the user's specific needs. jQMM will facilitate the design and metabolic engineering of organisms for biofuels and other chemicals, as well as investigations of cellular metabolism and leveraging -omics data. As an open source software project, we hope it

  6. The JBEI quantitative metabolic modeling library (jQMM): a python library for modeling microbial metabolism

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Birkel, Garrett W.; Ghosh, Amit; Kumar, Vinay S.

    Modeling of microbial metabolism is a topic of growing importance in biotechnology. Mathematical modeling helps provide a mechanistic understanding for the studied process, separating the main drivers from the circumstantial ones, bounding the outcomes of experiments and guiding engineering approaches. Among different modeling schemes, the quantification of intracellular metabolic fluxes (i.e. the rate of each reaction in cellular metabolism) is of particular interest for metabolic engineering because it describes how carbon and energy flow throughout the cell. In addition to flux analysis, new methods for the effective use of the ever more readily available and abundant -omics data (i.e. transcriptomics,more » proteomics and metabolomics) are urgently needed. The jQMM library presented here provides an open-source, Python-based framework for modeling internal metabolic fluxes and leveraging other -omics data for the scientific study of cellular metabolism and bioengineering purposes. Firstly, it presents a complete toolbox for simultaneously performing two different types of flux analysis that are typically disjoint: Flux Balance Analysis and 13C Metabolic Flux Analysis. Moreover, it introduces the capability to use 13C labeling experimental data to constrain comprehensive genome-scale models through a technique called two-scale 13C Metabolic Flux Analysis (2S- 13C MFA). In addition, the library includes a demonstration of a method that uses proteomics data to produce actionable insights to increase biofuel production. Finally, the use of the jQMM library is illustrated through the addition of several Jupyter notebook demonstration files that enhance reproducibility and provide the capability to be adapted to the user's specific needs. jQMM will facilitate the design and metabolic engineering of organisms for biofuels and other chemicals, as well as investigations of cellular metabolism and leveraging -omics data. As an open source software project, we hope it

  7. Isotopically nonstationary 13C flux analysis of changes in Arabidopsis thaliana leaf metabolism due to high light acclimation

    DOE PAGES

    Ma, Fangfang; Jazmin, Lara J.; Young, Jamey D.; ...

    2014-11-03

    Improving plant productivity is an important aim for metabolic engineering. There are few comprehensive methods that quantitatively describe leaf metabolism, although such information would be valuable for increasing photosynthetic capacity, enhancing biomass production, and rerouting carbon flux toward desirable end products. Isotopically nonstationary metabolic flux analysis (INST-MFA) has been previously applied to map carbon fluxes in photoautotrophic bacteria, which involves model-based regression of transient 13C-labeling patterns of intracellular metabolites. However, experimental and computational difficulties have hindered its application to terrestrial plant systems. Here, we performed in vivo isotopic labeling of Arabidopsis thaliana rosettes with 13CO 2 and estimated fluxes throughoutmore » leaf photosynthetic metabolism by INST-MFA. Plants grown at 200 µmol m $-$2s $-$1 light were compared with plants acclimated for 9 d at an irradiance of 500 µmol∙m $-$2∙s $-$1. Approximately 1,400 independent mass isotopomer measurements obtained from analysis of 37 metabolite fragment ions were regressed to estimate 136 total fluxes (54 free fluxes) under each condition. The results provide a comprehensive description of changes in carbon partitioning and overall photosynthetic flux after long-term developmental acclimation of leaves to high light. Despite a doubling in the carboxylation rate, the photorespiratory flux increased from 17 to 28% of net CO 2 assimilation with high-light acclimation (Vc/Vo: 3.5:1 vs. 2.3:1, respectively). In conclusion, this study highlights the potential of 13C INST-MFA to describe emergent flux phenotypes that respond to environmental conditions or plant physiology and cannot be obtained by other complementary approaches.« less

  8. Experimental determination of group flux control coefficients in metabolic networks

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Simpson, T.W.; Shimizu, Hiroshi; Stephanopoulos, G.

    1998-04-20

    Grouping of reactions around key metabolite branch points can facilitate the study of metabolic control of complex metabolic networks. This top-down Metabolic Control Analysis is exemplified through the introduction of group control coefficients whose magnitudes provide a measure of the relative impact of each reaction group on the overall network flux, as well as on the overall network stability, following enzymatic amplification. In this article, the authors demonstrate the application of previously developed theory to the determination of group flux control coefficients. Experimental data for the changes in metabolic fluxes obtained in response to the introduction of six different environmentalmore » perturbations are used to determine the group flux control coefficients for three reaction groups formed around the phosphoenolpyruvate/pyruvate branch point. The consistency of the obtained group flux control coefficient estimates is systematically analyzed to ensure that all necessary conditions are satisfied. The magnitudes of the determined control coefficients suggest that the control of lysine production flux in Corynebacterium glutamicum cells at a growth base state resides within the lysine biosynthetic pathway that begins with the PEP/PYR carboxylation anaplorotic pathway.« less

  9. PFA toolbox: a MATLAB tool for Metabolic Flux Analysis.

    PubMed

    Morales, Yeimy; Bosque, Gabriel; Vehí, Josep; Picó, Jesús; Llaneras, Francisco

    2016-07-11

    Metabolic Flux Analysis (MFA) is a methodology that has been successfully applied to estimate metabolic fluxes in living cells. However, traditional frameworks based on this approach have some limitations, particularly when measurements are scarce and imprecise. This is very common in industrial environments. The PFA Toolbox can be used to face those scenarios. Here we present the PFA (Possibilistic Flux Analysis) Toolbox for MATLAB, which simplifies the use of Interval and Possibilistic Metabolic Flux Analysis. The main features of the PFA Toolbox are the following: (a) It provides reliable MFA estimations in scenarios where only a few fluxes can be measured or those available are imprecise. (b) It provides tools to easily plot the results as interval estimates or flux distributions. (c) It is composed of simple functions that MATLAB users can apply in flexible ways. (d) It includes a Graphical User Interface (GUI), which provides a visual representation of the measurements and their uncertainty. (e) It can use stoichiometric models in COBRA format. In addition, the PFA Toolbox includes a User's Guide with a thorough description of its functions and several examples. The PFA Toolbox for MATLAB is a freely available Toolbox that is able to perform Interval and Possibilistic MFA estimations.

  10. Fluxes through plant metabolic networks: measurements, predictions, insights and challenges.

    PubMed

    Kruger, Nicholas J; Ratcliffe, R George

    2015-01-01

    Although the flows of material through metabolic networks are central to cell function, they are not easy to measure other than at the level of inputs and outputs. This is particularly true in plant cells, where the network spans multiple subcellular compartments and where the network may function either heterotrophically or photoautotrophically. For many years, kinetic modelling of pathways provided the only method for describing the operation of fragments of the network. However, more recently, it has become possible to map the fluxes in central carbon metabolism using the stable isotope labelling techniques of metabolic flux analysis (MFA), and to predict intracellular fluxes using constraints-based modelling procedures such as flux balance analysis (FBA). These approaches were originally developed for the analysis of microbial metabolism, but over the last decade, they have been adapted for the more demanding analysis of plant metabolic networks. Here, the principal features of MFA and FBA as applied to plants are outlined, followed by a discussion of the insights that have been gained into plant metabolic networks through the application of these time-consuming and non-trivial methods. The discussion focuses on how a system-wide view of plant metabolism has increased our understanding of network structure, metabolic perturbations and the provision of reducing power and energy for cell function. Current methodological challenges that limit the scope of plant MFA are discussed and particular emphasis is placed on the importance of developing methods for cell-specific MFA.

  11. A detailed view on sulphur metabolism at the cellular and whole-plant level illustrates challenges in metabolite flux analyses.

    PubMed

    Rennenberg, Heinz; Herschbach, Cornelia

    2014-11-01

    Understanding the dynamics of physiological process in the systems biology era requires approaches at the genome, transcriptome, proteome, and metabolome levels. In this context, metabolite flux experiments have been used in mapping metabolite pathways and analysing metabolic control. In the present review, sulphur metabolism was taken to illustrate current challenges of metabolic flux analyses. At the cellular level, restrictions in metabolite flux analyses originate from incomplete knowledge of the compartmentation network of metabolic pathways. Transport of metabolites through membranes is usually not considered in flux experiments but may be involved in controlling the whole pathway. Hence, steady-state and snapshot readings need to be expanded to time-course studies in combination with compartment-specific metabolite analyses. Because of species-specific differences, differences between tissues, and stress-related responses, the quantitative significance of different sulphur sinks has to be elucidated; this requires the development of methods for whole-sulphur metabolome approaches. Different cell types can contribute to metabolite fluxes to different extents at the tissue and organ level. Cell type-specific analyses are needed to characterize these contributions. Based on such approaches, metabolite flux analyses can be expanded to the whole-plant level by considering long-distance transport and, thus, the interaction of roots and the shoot in metabolite fluxes. However, whole-plant studies need detailed empirical and mathematical modelling that have to be validated by experimental analyses. © The Author 2014. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

  12. A metabolite-centric view on flux distributions in genome-scale metabolic models

    PubMed Central

    2013-01-01

    Background Genome-scale metabolic models are important tools in systems biology. They permit the in-silico prediction of cellular phenotypes via mathematical optimisation procedures, most importantly flux balance analysis. Current studies on metabolic models mostly consider reaction fluxes in isolation. Based on a recently proposed metabolite-centric approach, we here describe a set of methods that enable the analysis and interpretation of flux distributions in an integrated metabolite-centric view. We demonstrate how this framework can be used for the refinement of genome-scale metabolic models. Results We applied the metabolite-centric view developed here to the most recent metabolic reconstruction of Escherichia coli. By compiling the balance sheets of a small number of currency metabolites, we were able to fully characterise the energy metabolism as predicted by the model and to identify a possibility for model refinement in NADPH metabolism. Selected branch points were examined in detail in order to demonstrate how a metabolite-centric view allows identifying functional roles of metabolites. Fructose 6-phosphate aldolase and the sedoheptulose bisphosphate bypass were identified as enzymatic reactions that can carry high fluxes in the model but are unlikely to exhibit significant activity in vivo. Performing a metabolite essentiality analysis, unconstrained import and export of iron ions could be identified as potentially problematic for the quality of model predictions. Conclusions The system-wide analysis of split ratios and branch points allows a much deeper insight into the metabolic network than reaction-centric analyses. Extending an earlier metabolite-centric approach, the methods introduced here establish an integrated metabolite-centric framework for the interpretation of flux distributions in genome-scale metabolic networks that can complement the classical reaction-centric framework. Analysing fluxes and their metabolic context simultaneously opens

  13. Including metabolite concentrations into flux balance analysis: thermodynamic realizability as a constraint on flux distributions in metabolic networks

    PubMed Central

    Hoppe, Andreas; Hoffmann, Sabrina; Holzhütter, Hermann-Georg

    2007-01-01

    Background In recent years, constrained optimization – usually referred to as flux balance analysis (FBA) – has become a widely applied method for the computation of stationary fluxes in large-scale metabolic networks. The striking advantage of FBA as compared to kinetic modeling is that it basically requires only knowledge of the stoichiometry of the network. On the other hand, results of FBA are to a large degree hypothetical because the method relies on plausible but hardly provable optimality principles that are thought to govern metabolic flux distributions. Results To augment the reliability of FBA-based flux calculations we propose an additional side constraint which assures thermodynamic realizability, i.e. that the flux directions are consistent with the corresponding changes of Gibb's free energies. The latter depend on metabolite levels for which plausible ranges can be inferred from experimental data. Computationally, our method results in the solution of a mixed integer linear optimization problem with quadratic scoring function. An optimal flux distribution together with a metabolite profile is determined which assures thermodynamic realizability with minimal deviations of metabolite levels from their expected values. We applied our novel approach to two exemplary metabolic networks of different complexity, the metabolic core network of erythrocytes (30 reactions) and the metabolic network iJR904 of Escherichia coli (931 reactions). Our calculations show that increasing network complexity entails increasing sensitivity of predicted flux distributions to variations of standard Gibb's free energy changes and metabolite concentration ranges. We demonstrate the usefulness of our method for assessing critical concentrations of external metabolites preventing attainment of a metabolic steady state. Conclusion Our method incorporates the thermodynamic link between flux directions and metabolite concentrations into a practical computational algorithm. The

  14. Modeling and experimental design for metabolic flux analysis of lysine-producing Corynebacteria by mass spectrometry.

    PubMed

    Wittmann, C; Heinzle, E

    2001-04-01

    Experimental design of (13)C-tracer studies for metabolic flux analysis with mass spectrometric determination of labeling patterns was performed for the central metabolism of Corynebacterium glutamicum comprising various flux scenarios. Ratio measurement of mass isotopomer pools of Corynebacterium products lysine, alanine, and trehalose is sufficient to quantify the flux partitioning ratios (i) between glycolysis and pentose phosphate pathways (Phi(PPP)), (ii) between the split pathways in the lysine biosynthesis (Phi(DH)), (iii) at the pyruvate node (Phi(PC)), and reversibilities of (iv) glucose 6-phosphate isomerase (zeta(PGI)), (v) at the pyruvate node (zeta(PC/PEPCK)), and (vi) of transaldolase and transketolases in the PPP. Weighted sensitivities for flux parameters were derived from partial derivatives to quantitatively evaluate experimental approaches and predict precision for estimated flux parameters. Deviation of intensity ratios from ideal values of 1 was used as weighting function. Weighted flux sensitivities can be used to identify optimal type and degree of tracer labeling or potential intensity ratios to be measured. Experimental design for lysine-producing strain C. glutamicum MH 20-22B (Marx et al., Biotechnol. Bioeng. 49, 111-129, 1996) and various potential mutants with different alterations in the flux pattern showed that specific tracer labelings are optimal to quantify a certain flux parameter uninfluenced by the overall flux situation. Identified substrates of choice are [1-(13)C]glucose for the estimation of Phi(PPP) and zeta(PGI) and a 1 : 1 mixture of [U-(12)C/U-(13)C]glucose for the determination of zeta(PC/PEPCK). Phi(PC) can be quantified by feeding [4-(13)C]glucose or [U-(12)C/U-(13)C]glucose (1 : 1), whereas Phi(DH) is accessible via [4-(13)C]glucose. The sensitivity for the quantification of a certain flux parameter can be influenced by superposition through other flux parameters in the network, but substrate and measured mass

  15. SUMOFLUX: A Generalized Method for Targeted 13C Metabolic Flux Ratio Analysis

    PubMed Central

    Kogadeeva, Maria

    2016-01-01

    Metabolic fluxes are a cornerstone of cellular physiology that emerge from a complex interplay of enzymes, carriers, and nutrients. The experimental assessment of in vivo intracellular fluxes using stable isotopic tracers is essential if we are to understand metabolic function and regulation. Flux estimation based on 13C or 2H labeling relies on complex simulation and iterative fitting; processes that necessitate a level of expertise that ordinarily preclude the non-expert user. To overcome this, we have developed SUMOFLUX, a methodology that is broadly applicable to the targeted analysis of 13C-metabolic fluxes. By combining surrogate modeling and machine learning, we trained a predictor to specialize in estimating flux ratios from measurable 13C-data. SUMOFLUX targets specific flux features individually, which makes it fast, user-friendly, applicable to experimental design and robust in terms of experimental noise and exchange flux magnitude. Collectively, we predict that SUMOFLUX's properties realistically pave the way to high-throughput flux analyses. PMID:27626798

  16. Metabolic Flux Analysis during the Exponential Growth Phase of Saccharomyces cerevisiae in Wine Fermentations

    PubMed Central

    Quirós, Manuel; Martínez-Moreno, Rubén; Albiol, Joan; Morales, Pilar; Vázquez-Lima, Felícitas; Barreiro-Vázquez, Antonio; Ferrer, Pau; Gonzalez, Ramon

    2013-01-01

    As a consequence of the increase in global average temperature, grapes with the adequate phenolic and aromatic maturity tend to be overripe by the time of harvest, resulting in increased sugar concentrations and imbalanced C/N ratios in fermenting musts. This fact sets obvious additional hurdles in the challenge of obtaining wines with reduced alcohols levels, a new trend in consumer demands. It would therefore be interesting to understand Saccharomyces cerevisiae physiology during the fermentation of must with these altered characteristics. The present study aims to determine the distribution of metabolic fluxes during the yeast exponential growth phase, when both carbon and nitrogen sources are in excess, using continuous cultures. Two different sugar concentrations were studied under two different winemaking temperature conditions. Although consumption and production rates for key metabolites were severely affected by the different experimental conditions studied, the general distribution of fluxes in central carbon metabolism was basically conserved in all cases. It was also observed that temperature and sugar concentration exerted a higher effect on the pentose phosphate pathway and glycerol formation than on glycolysis and ethanol production. Additionally, nitrogen uptake, both quantitatively and qualitatively, was strongly influenced by environmental conditions. This work provides the most complete stoichiometric model used for Metabolic Flux Analysis of S. cerevisiae in wine fermentations employed so far, including the synthesis and release of relevant aroma compounds and could be used in the design of optimal nitrogen supplementation of wine fermentations. PMID:23967264

  17. OpenMebius: an open source software for isotopically nonstationary 13C-based metabolic flux analysis.

    PubMed

    Kajihata, Shuichi; Furusawa, Chikara; Matsuda, Fumio; Shimizu, Hiroshi

    2014-01-01

    The in vivo measurement of metabolic flux by (13)C-based metabolic flux analysis ((13)C-MFA) provides valuable information regarding cell physiology. Bioinformatics tools have been developed to estimate metabolic flux distributions from the results of tracer isotopic labeling experiments using a (13)C-labeled carbon source. Metabolic flux is determined by nonlinear fitting of a metabolic model to the isotopic labeling enrichment of intracellular metabolites measured by mass spectrometry. Whereas (13)C-MFA is conventionally performed under isotopically constant conditions, isotopically nonstationary (13)C metabolic flux analysis (INST-(13)C-MFA) has recently been developed for flux analysis of cells with photosynthetic activity and cells at a quasi-steady metabolic state (e.g., primary cells or microorganisms under stationary phase). Here, the development of a novel open source software for INST-(13)C-MFA on the Windows platform is reported. OpenMebius (Open source software for Metabolic flux analysis) provides the function of autogenerating metabolic models for simulating isotopic labeling enrichment from a user-defined configuration worksheet. Analysis using simulated data demonstrated the applicability of OpenMebius for INST-(13)C-MFA. Confidence intervals determined by INST-(13)C-MFA were less than those determined by conventional methods, indicating the potential of INST-(13)C-MFA for precise metabolic flux analysis. OpenMebius is the open source software for the general application of INST-(13)C-MFA.

  18. OptFlux: an open-source software platform for in silico metabolic engineering.

    PubMed

    Rocha, Isabel; Maia, Paulo; Evangelista, Pedro; Vilaça, Paulo; Soares, Simão; Pinto, José P; Nielsen, Jens; Patil, Kiran R; Ferreira, Eugénio C; Rocha, Miguel

    2010-04-19

    Over the last few years a number of methods have been proposed for the phenotype simulation of microorganisms under different environmental and genetic conditions. These have been used as the basis to support the discovery of successful genetic modifications of the microbial metabolism to address industrial goals. However, the use of these methods has been restricted to bioinformaticians or other expert researchers. The main aim of this work is, therefore, to provide a user-friendly computational tool for Metabolic Engineering applications. OptFlux is an open-source and modular software aimed at being the reference computational application in the field. It is the first tool to incorporate strain optimization tasks, i.e., the identification of Metabolic Engineering targets, using Evolutionary Algorithms/Simulated Annealing metaheuristics or the previously proposed OptKnock algorithm. It also allows the use of stoichiometric metabolic models for (i) phenotype simulation of both wild-type and mutant organisms, using the methods of Flux Balance Analysis, Minimization of Metabolic Adjustment or Regulatory on/off Minimization of Metabolic flux changes, (ii) Metabolic Flux Analysis, computing the admissible flux space given a set of measured fluxes, and (iii) pathway analysis through the calculation of Elementary Flux Modes. OptFlux also contemplates several methods for model simplification and other pre-processing operations aimed at reducing the search space for optimization algorithms. The software supports importing/exporting to several flat file formats and it is compatible with the SBML standard. OptFlux has a visualization module that allows the analysis of the model structure that is compatible with the layout information of Cell Designer, allowing the superimposition of simulation results with the model graph. The OptFlux software is freely available, together with documentation and other resources, thus bridging the gap from research in strain optimization

  19. OptFlux: an open-source software platform for in silico metabolic engineering

    PubMed Central

    2010-01-01

    Background Over the last few years a number of methods have been proposed for the phenotype simulation of microorganisms under different environmental and genetic conditions. These have been used as the basis to support the discovery of successful genetic modifications of the microbial metabolism to address industrial goals. However, the use of these methods has been restricted to bioinformaticians or other expert researchers. The main aim of this work is, therefore, to provide a user-friendly computational tool for Metabolic Engineering applications. Results OptFlux is an open-source and modular software aimed at being the reference computational application in the field. It is the first tool to incorporate strain optimization tasks, i.e., the identification of Metabolic Engineering targets, using Evolutionary Algorithms/Simulated Annealing metaheuristics or the previously proposed OptKnock algorithm. It also allows the use of stoichiometric metabolic models for (i) phenotype simulation of both wild-type and mutant organisms, using the methods of Flux Balance Analysis, Minimization of Metabolic Adjustment or Regulatory on/off Minimization of Metabolic flux changes, (ii) Metabolic Flux Analysis, computing the admissible flux space given a set of measured fluxes, and (iii) pathway analysis through the calculation of Elementary Flux Modes. OptFlux also contemplates several methods for model simplification and other pre-processing operations aimed at reducing the search space for optimization algorithms. The software supports importing/exporting to several flat file formats and it is compatible with the SBML standard. OptFlux has a visualization module that allows the analysis of the model structure that is compatible with the layout information of Cell Designer, allowing the superimposition of simulation results with the model graph. Conclusions The OptFlux software is freely available, together with documentation and other resources, thus bridging the gap from

  20. Conservation of high-flux backbone in alternate optimal and near-optimal flux distributions of metabolic networks.

    PubMed

    Samal, Areejit

    2008-12-01

    Constraint-based flux balance analysis (FBA) has proven successful in predicting the flux distribution of metabolic networks in diverse environmental conditions. FBA finds one of the alternate optimal solutions that maximizes the biomass production rate. Almaas et al. have shown that the flux distribution follows a power law, and it is possible to associate with most metabolites two reactions which maximally produce and consume a given metabolite, respectively. This observation led to the concept of high-flux backbone (HFB) in metabolic networks. In previous work, the HFB has been computed using a particular optima obtained using FBA. In this paper, we investigate the conservation of HFB of a particular solution for a given medium across different alternate optima and near-optima in metabolic networks of E. coli and S. cerevisiae. Using flux variability analysis (FVA), we propose a method to determine reactions that are guaranteed to be in HFB regardless of alternate solutions. We find that the HFB of a particular optima is largely conserved across alternate optima in E. coli, while it is only moderately conserved in S. cerevisiae. However, the HFB of a particular near-optima shows a large variation across alternate near-optima in both organisms. We show that the conserved set of reactions in HFB across alternate near-optima has a large overlap with essential reactions and reactions which are both uniquely consuming (UC) and uniquely producing (UP). Our findings suggest that the structure of the metabolic network admits a high degree of redundancy and plasticity in near-optimal flow patterns enhancing system robustness for a given environmental condition.

  1. 13C-Metabolic Flux Analysis: An Accurate Approach to Demystify Microbial Metabolism for Biochemical Production

    PubMed Central

    Guo, Weihua; Sheng, Jiayuan; Feng, Xueyang

    2015-01-01

    Metabolic engineering of various industrial microorganisms to produce chemicals, fuels, and drugs has raised interest since it is environmentally friendly, sustainable, and independent of nonrenewable resources. However, microbial metabolism is so complex that only a few metabolic engineering efforts have been able to achieve a satisfactory yield, titer or productivity of the target chemicals for industrial commercialization. In order to overcome this challenge, 13C Metabolic Flux Analysis (13C-MFA) has been continuously developed and widely applied to rigorously investigate cell metabolism and quantify the carbon flux distribution in central metabolic pathways. In the past decade, many 13C-MFA studies have been performed in academic labs and biotechnology industries to pinpoint key issues related to microbe-based chemical production. Insightful information about the metabolic rewiring has been provided to guide the development of the appropriate metabolic engineering strategies for improving the biochemical production. In this review, we will introduce the basics of 13C-MFA and illustrate how 13C-MFA has been applied via integration with metabolic engineering to identify and tackle the rate-limiting steps in biochemical production for various host microorganisms PMID:28952565

  2. Determination of the fluxes in the central metabolism of Corynebacterium glutamicum by nuclear magnetic resonance spectroscopy combined with metabolite balancing.

    PubMed

    Marx, A; de Graaf, A A; Wiechert, W; Eggeling, L; Sahm, H

    1996-01-20

    To determine the in vivo fluxes of the central metabolism we have developed a comprehensive approach exclusively based on the fundamental enzyme reactions known to be present, the fate of the carbon atoms of individual reactions, and the metabolite balance of the culture. No information on the energy balance is required, nor information on enzyme activities, or the directionalities of reactions. Our approach combines the power of (1)H-detected (13)C nuclear magnetic resonance spectroscopy to follow individual carbons with the simplicity of establishing carbon balances of bacterial cultures. We grew a lysine-producing strain of Corynebacterium glutamicum to the metabolic and isotopic steady state with [1-(13)C]glucose and determined the fractional enrichments in 27 carbon atoms of 11 amino acids isolated from the cell. Since precursor metabolites of the central metabolism are incorporated in an exactly defined manner in the carbon skeleton of amino acids, the fractional enrichments in carbons of precursor metabolites (oxaloacetate, glyceraldehyde 3-phosphate, erythrose 4-phosphate, etc.) became directly accessible. A concise and generally applicable mathematical model was established using matrix calculus to express all metabolite mass and carbon labeling balances. An appropriate all-purpose software for the iterative solution of the equations is supplied. Applying this comprehensive methodology to C. glutamicum, all major fluxes within the central metabolism were determined. The result is that the flux through the pentose phosphate pathway is 66.4% (relative to the glucose input flux of 1.49 mmol/g dry weight h), that of entry into the tricarboxylic acid cycle 62.2%, and the contribution of the succinylase pathway of lysine synthesis 13.7%. Due to the large amount and high quality of measured data in vivo exchange reactions could also be quantitated with particularly high exchange rates within the pentose phosphate pathway for the ribose 5-phosphate transketolase

  3. Metstoich--Teaching Quantitative Metabolism and Energetics in Biochemical Engineering

    ERIC Educational Resources Information Center

    Wong, Kelvin W. W.; Barford, John P.

    2010-01-01

    Metstoich, a metabolic calculator developed for teaching, can provide a novel way to teach quantitative metabolism to biochemical engineering students. It can also introduce biochemistry/life science students to the quantitative aspects of life science subjects they have studied. Metstoich links traditional biochemistry-based metabolic approaches…

  4. Phototransduction Influences Metabolic Flux and Nucleotide Metabolism in Mouse Retina.

    PubMed

    Du, Jianhai; Rountree, Austin; Cleghorn, Whitney M; Contreras, Laura; Lindsay, Ken J; Sadilek, Martin; Gu, Haiwei; Djukovic, Danijel; Raftery, Dan; Satrústegui, Jorgina; Kanow, Mark; Chan, Lawrence; Tsang, Stephen H; Sweet, Ian R; Hurley, James B

    2016-02-26

    Production of energy in a cell must keep pace with demand. Photoreceptors use ATP to maintain ion gradients in darkness, whereas in light they use it to support phototransduction. Matching production with consumption can be accomplished by coupling production directly to consumption. Alternatively, production can be set by a signal that anticipates demand. In this report we investigate the hypothesis that signaling through phototransduction controls production of energy in mouse retinas. We found that respiration in mouse retinas is not coupled tightly to ATP consumption. By analyzing metabolic flux in mouse retinas, we also found that phototransduction slows metabolic flux through glycolysis and through intermediates of the citric acid cycle. We also evaluated the relative contributions of regulation of the activities of α-ketoglutarate dehydrogenase and the aspartate-glutamate carrier 1. In addition, a comprehensive analysis of the retinal metabolome showed that phototransduction also influences steady-state concentrations of 5'-GMP, ribose-5-phosphate, ketone bodies, and purines. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

  5. Bidirectionality and compartmentation of metabolic fluxes are revealed in the dynamics of isotopomer networks.

    PubMed

    Schryer, David W; Peterson, Pearu; Paalme, Toomas; Vendelin, Marko

    2009-04-17

    Isotope labeling is one of the few methods of revealing the in vivo bidirectionality and compartmentalization of metabolic fluxes within metabolic networks. We argue that a shift from steady state to dynamic isotopomer analysis is required to deal with these cellular complexities and provide a review of dynamic studies of compartmentalized energy fluxes in eukaryotic cells including cardiac muscle, plants, and astrocytes. Knowledge of complex metabolic behaviour on a molecular level is prerequisite for the intelligent design of genetically modified organisms able to realize their potential of revolutionizing food, energy, and pharmaceutical production. We describe techniques to explore the bidirectionality and compartmentalization of metabolic fluxes using information contained in the isotopic transient, and discuss the integration of kinetic models with MFA. The flux parameters of an example metabolic network were optimized to examine the compartmentalization of metabolites and and the bidirectionality of fluxes in the TCA cycle of Saccharomyces uvarum for steady-state respiratory growth.

  6. Study of AMPK-Regulated Metabolic Fluxes in Neurons Using the Seahorse XFe Analyzer.

    PubMed

    Marinangeli, Claudia; Kluza, Jérome; Marchetti, Philippe; Buée, Luc; Vingtdeux, Valérie

    2018-01-01

    AMP-activated protein kinase (AMPK) is the intracellular master energy sensor and metabolic regulator. AMPK is involved in cell energy homeostasis through the regulation of glycolytic flux and mitochondrial biogenesis. Interestingly, metabolic dysfunctions and AMPK deregulations are observed in many neurodegenerative diseases, including Alzheimer's. While these deregulations could play a key role in the development of these diseases, the study of metabolic fluxes has remained quite challenging and time-consuming. In this chapter, we describe the Seahorse XFe respirometry assay as a fundamental experimental tool to investigate the role of AMPK in controlling and modulating cell metabolic fluxes in living and intact differentiated primary neurons. The Seahorse XFe respirometry assay allows the real-time monitoring of glycolytic flux and mitochondrial respiration from different kind of cells, tissues, and isolated mitochondria. Here, we specify a protocol optimized for primary neuronal cells using several energy substrates such as glucose, pyruvate, lactate, glutamine, and ketone bodies. Nevertheless, this protocol can easily be adapted to monitor metabolic fluxes from other types of cells, tissues, or isolated mitochondria by taking into account the notes proposed for each key step of this assay.

  7. FCDECOMP: decomposition of metabolic networks based on flux coupling relations.

    PubMed

    Rezvan, Abolfazl; Marashi, Sayed-Amir; Eslahchi, Changiz

    2014-10-01

    A metabolic network model provides a computational framework to study the metabolism of a cell at the system level. Due to their large sizes and complexity, rational decomposition of these networks into subsystems is a strategy to obtain better insight into the metabolic functions. Additionally, decomposing metabolic networks paves the way to use computational methods that will be otherwise very slow when run on the original genome-scale network. In the present study, we propose FCDECOMP decomposition method based on flux coupling relations (FCRs) between pairs of reaction fluxes. This approach utilizes a genetic algorithm (GA) to obtain subsystems that can be analyzed in isolation, i.e. without considering the reactions of the original network in the analysis. Therefore, we propose that our method is useful for discovering biologically meaningful modules in metabolic networks. As a case study, we show that when this method is applied to the metabolic networks of barley seeds and yeast, the modules are in good agreement with the biological compartments of these networks.

  8. Quantitative Assessment of Thermodynamic Constraints on the Solution Space of Genome-Scale Metabolic Models

    PubMed Central

    Hamilton, Joshua J.; Dwivedi, Vivek; Reed, Jennifer L.

    2013-01-01

    Constraint-based methods provide powerful computational techniques to allow understanding and prediction of cellular behavior. These methods rely on physiochemical constraints to eliminate infeasible behaviors from the space of available behaviors. One such constraint is thermodynamic feasibility, the requirement that intracellular flux distributions obey the laws of thermodynamics. The past decade has seen several constraint-based methods that interpret this constraint in different ways, including those that are limited to small networks, rely on predefined reaction directions, and/or neglect the relationship between reaction free energies and metabolite concentrations. In this work, we utilize one such approach, thermodynamics-based metabolic flux analysis (TMFA), to make genome-scale, quantitative predictions about metabolite concentrations and reaction free energies in the absence of prior knowledge of reaction directions, while accounting for uncertainties in thermodynamic estimates. We applied TMFA to a genome-scale network reconstruction of Escherichia coli and examined the effect of thermodynamic constraints on the flux space. We also assessed the predictive performance of TMFA against gene essentiality and quantitative metabolomics data, under both aerobic and anaerobic, and optimal and suboptimal growth conditions. Based on these results, we propose that TMFA is a useful tool for validating phenotypes and generating hypotheses, and that additional types of data and constraints can improve predictions of metabolite concentrations. PMID:23870272

  9. The role of metabolism in modulating CO2 fluxes in boreal lakes

    NASA Astrophysics Data System (ADS)

    Bogard, Matthew J.; del Giorgio, Paul A.

    2016-10-01

    Lake CO2 emissions are increasingly recognized as an important component of the global CO2 cycle, yet the origin of these emissions is not clear, as specific contributions from metabolism and in-lake cycling, versus external inputs, are not well defined. To assess the coupling of lake metabolism with CO2 concentrations and fluxes, we estimated steady state ratios of gross primary production to respiration (GPP:R) and rates of net ecosystem production (NEP = GPP-R) from surface water O2 dynamics (concentration and stable isotopes) in 187 boreal lakes spanning long environmental gradients. Our findings suggest that internal metabolism plays a dominant role in regulating CO2 fluxes in most lakes, but this pattern only emerges when examined at a resolution that accounts for the vastly differing relationships between lake metabolism and CO2 fluxes. Fluxes of CO2 exceeded those from NEP in over half the lakes, but unexpectedly, these effects were most common and typically largest in a subset ( 30% of total) of net autotrophic lakes that nevertheless emitted CO2. Equally surprising, we found no environmental characteristics that distinguished this category from the more common net heterotrophic, CO2 outgassing lakes. Excess CO2 fluxes relative to NEP were best predicted by catchment structure and hydrologic properties, and we infer from a combination of methods that both catchment inputs and internal anaerobic processes may have contributed this excess CO2. Together, our findings show that the link between lake metabolism and CO2 fluxes is often strong but can vary widely across the boreal biome, having important implications for catchment-wide C budgets.

  10. Assessing compartmentalized flux in lipid metabolism with isotopes

    DOE PAGES

    Allen, Doug K.

    2016-03-18

    Metabolism in plants takes place across multiple cell types and within distinct organelles. The distributions equate to spatial heterogeneity; though the limited means to experimentally assess metabolism frequently involve homogenizing tissues and mixing metabolites from different locations.Most current isotope investigations of metabolism therefore lack the ability to resolve spatially distinct events. Recognition of this limitation has resulted in inspired efforts to advance metabolic flux analysis and isotopic labeling techniques. Though a number of these efforts have been applied to studies in central metabolism; recent advances in instrumentation and techniques present an untapped opportunity to make similar progress in lipid metabolismmore » where the use of stable isotopes has been more limited. These efforts will benefit from sophisticated radiolabeling reports that continue to enrich our knowledge on lipid biosynthetic pathways and provide some direction for stable isotope experimental design and extension of MFA. Evidence for this assertion is presented through the review of several elegant stable isotope studies and by taking stock of what has been learned from radioisotope investigations when spatial aspects of metabolism were considered. The studies emphasize that glycerolipid production occurs across several locations with assembly of lipids in the ER or plastid, fatty acid biosynthesis occurring in the plastid, and the generation of acetyl-CoA and glycerol-3-phosphate taking place at multiple sites. Considering metabolism in this context underscores the cellular and subcellular organization that is important to enhanced production of glycerolipids in plants. An attempt is made to unify salient features from a number of reports into a diagrammatic model of lipid metabolism and propose where stable isotope labeling experiments and further flux analysis may help address questions in the field.« less

  11. Assessing compartmentalized flux in lipid metabolism with isotopes

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Allen, Doug K.

    Metabolism in plants takes place across multiple cell types and within distinct organelles. The distributions equate to spatial heterogeneity; though the limited means to experimentally assess metabolism frequently involve homogenizing tissues and mixing metabolites from different locations.Most current isotope investigations of metabolism therefore lack the ability to resolve spatially distinct events. Recognition of this limitation has resulted in inspired efforts to advance metabolic flux analysis and isotopic labeling techniques. Though a number of these efforts have been applied to studies in central metabolism; recent advances in instrumentation and techniques present an untapped opportunity to make similar progress in lipid metabolismmore » where the use of stable isotopes has been more limited. These efforts will benefit from sophisticated radiolabeling reports that continue to enrich our knowledge on lipid biosynthetic pathways and provide some direction for stable isotope experimental design and extension of MFA. Evidence for this assertion is presented through the review of several elegant stable isotope studies and by taking stock of what has been learned from radioisotope investigations when spatial aspects of metabolism were considered. The studies emphasize that glycerolipid production occurs across several locations with assembly of lipids in the ER or plastid, fatty acid biosynthesis occurring in the plastid, and the generation of acetyl-CoA and glycerol-3-phosphate taking place at multiple sites. Considering metabolism in this context underscores the cellular and subcellular organization that is important to enhanced production of glycerolipids in plants. An attempt is made to unify salient features from a number of reports into a diagrammatic model of lipid metabolism and propose where stable isotope labeling experiments and further flux analysis may help address questions in the field.« less

  12. Integrated metabolic flux and omics analysis of Synechocystis sp. PCC 6803 under mixotrophic and photoheterotrophic conditions.

    PubMed

    Nakajima, Tsubasa; Kajihata, Shuichi; Yoshikawa, Katsunori; Matsuda, Fumio; Furusawa, Chikara; Hirasawa, Takashi; Shimizu, Hiroshi

    2014-09-01

    Cyanobacteria have flexible metabolic capability that enables them to adapt to various environments. To investigate their underlying metabolic regulation mechanisms, we performed an integrated analysis of metabolic flux using transcriptomic and metabolomic data of a cyanobacterium Synechocystis sp. PCC 6803, under mixotrophic and photoheterotrophic conditions. The integrated analysis indicated drastic metabolic flux changes, with much smaller changes in gene expression levels and metabolite concentrations between the conditions, suggesting that the flux change was not caused mainly by the expression levels of the corresponding genes. Under photoheterotrophic conditions, created by the addition of the photosynthesis inhibitor atrazine in mixotrophic conditions, the result of metabolic flux analysis indicated the significant repression of carbon fixation and the activation of the oxidative pentose phosphate pathway (PPP). Moreover, we observed gluconeogenic activity of upstream of glycolysis, which enhanced the flux of the oxidative PPP to compensate for NADPH depletion due to the inhibition of the light reaction of photosynthesis. 'Omics' data suggested that these changes were probably caused by the repression of the gap1 gene, which functions as a control valve in the metabolic network. Since metabolic flux is the outcome of a complicated interplay of cellular components, integrating metabolic flux with other 'omics' layers can identify metabolic changes and narrow down these regulatory mechanisms more effectively. © The Author 2014. Published by Oxford University Press on behalf of Japanese Society of Plant Physiologists. All rights reserved. For permissions, please email: journals.permissions@oup.com.

  13. Integration of a constraint-based metabolic model of Brassica napus developing seeds with 13C-metabolic flux analysis

    PubMed Central

    Hay, Jordan O.; Shi, Hai; Heinzel, Nicolas; Hebbelmann, Inga; Rolletschek, Hardy; Schwender, Jorg

    2014-01-01

    The use of large-scale or genome-scale metabolic reconstructions for modeling and simulation of plant metabolism and integration of those models with large-scale omics and experimental flux data is becoming increasingly important in plant metabolic research. Here we report an updated version of bna572, a bottom-up reconstruction of oilseed rape (Brassica napus L.; Brassicaceae) developing seeds with emphasis on representation of biomass-component biosynthesis. New features include additional seed-relevant pathways for isoprenoid, sterol, phenylpropanoid, flavonoid, and choline biosynthesis. Being now based on standardized data formats and procedures for model reconstruction, bna572+ is available as a COBRA-compliant Systems Biology Markup Language (SBML) model and conforms to the Minimum Information Requested in the Annotation of Biochemical Models (MIRIAM) standards for annotation of external data resources. Bna572+ contains 966 genes, 671 reactions, and 666 metabolites distributed among 11 subcellular compartments. It is referenced to the Arabidopsis thaliana genome, with gene-protein-reaction (GPR) associations resolving subcellular localization. Detailed mass and charge balancing and confidence scoring were applied to all reactions. Using B. napus seed specific transcriptome data, expression was verified for 78% of bna572+ genes and 97% of reactions. Alongside bna572+ we also present a revised carbon centric model for 13C-Metabolic Flux Analysis (13C-MFA) with all its reactions being referenced to bna572+ based on linear projections. By integration of flux ratio constraints obtained from 13C-MFA and by elimination of infinite flux bounds around thermodynamically infeasible loops based on COBRA loopless methods, we demonstrate improvements in predictive power of Flux Variability Analysis (FVA). Using this combined approach we characterize the difference in metabolic flux of developing seeds of two B. napus genotypes contrasting in starch and oil content. PMID

  14. Integration of a constraint-based metabolic model of Brassica napus developing seeds with 13C-metabolic flux analysis

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Hay, Jordan O.; Shi, Hai; Heinzel, Nicolas

    The use of large-scale or genome-scale metabolic reconstructions for modeling and simulation of plant metabolism and integration of those models with large-scale omics and experimental flux data is becoming increasingly important in plant metabolic research. Here we report an updated version of bna572, a bottom-up reconstruction of oilseed rape (Brassica napus L.; Brassicaceae) developing seeds with emphasis on representation of biomass-component biosynthesis. New features include additional seed-relevant pathways for isoprenoid, sterol, phenylpropanoid, flavonoid, and choline biosynthesis. Being now based on standardized data formats and procedures for model reconstruction, bna572+ is available as a COBRA-compliant Systems Biology Markup Language (SBML) modelmore » and conforms to the Minimum Information Requested in the Annotation of Biochemical Models (MIRIAM) standards for annotation of external data resources. Bna572+ contains 966 genes, 671 reactions, and 666 metabolites distributed among 11 subcellular compartments. It is referenced to the Arabidopsis thaliana genome, with gene-protein-reaction (GPR) associations resolving subcellular localization. Detailed mass and charge balancing and confidence scoring were applied to all reactions. Using B. napus seed specific transcriptome data, expression was verified for 78% of bna572+ genes and 97% of reactions. Alongside bna572+ we also present a revised carbon centric model for 13C-Metabolic Flux Analysis ( 13C-MFA) with all its reactions being referenced to bna572+ based on linear projections. By integration of flux ratio constraints obtained from 13C-MFA and by elimination of infinite flux bounds around thermodynamically infeasible loops based on COBRA loopless methods, we demonstrate improvements in predictive power of Flux Variability Analysis (FVA). In conclusion, using this combined approach we characterize the difference in metabolic flux of developing seeds of two B. napus genotypes contrasting in starch

  15. Integration of a constraint-based metabolic model of Brassica napus developing seeds with 13C-metabolic flux analysis

    DOE PAGES

    Hay, Jordan O.; Shi, Hai; Heinzel, Nicolas; ...

    2014-12-19

    The use of large-scale or genome-scale metabolic reconstructions for modeling and simulation of plant metabolism and integration of those models with large-scale omics and experimental flux data is becoming increasingly important in plant metabolic research. Here we report an updated version of bna572, a bottom-up reconstruction of oilseed rape (Brassica napus L.; Brassicaceae) developing seeds with emphasis on representation of biomass-component biosynthesis. New features include additional seed-relevant pathways for isoprenoid, sterol, phenylpropanoid, flavonoid, and choline biosynthesis. Being now based on standardized data formats and procedures for model reconstruction, bna572+ is available as a COBRA-compliant Systems Biology Markup Language (SBML) modelmore » and conforms to the Minimum Information Requested in the Annotation of Biochemical Models (MIRIAM) standards for annotation of external data resources. Bna572+ contains 966 genes, 671 reactions, and 666 metabolites distributed among 11 subcellular compartments. It is referenced to the Arabidopsis thaliana genome, with gene-protein-reaction (GPR) associations resolving subcellular localization. Detailed mass and charge balancing and confidence scoring were applied to all reactions. Using B. napus seed specific transcriptome data, expression was verified for 78% of bna572+ genes and 97% of reactions. Alongside bna572+ we also present a revised carbon centric model for 13C-Metabolic Flux Analysis ( 13C-MFA) with all its reactions being referenced to bna572+ based on linear projections. By integration of flux ratio constraints obtained from 13C-MFA and by elimination of infinite flux bounds around thermodynamically infeasible loops based on COBRA loopless methods, we demonstrate improvements in predictive power of Flux Variability Analysis (FVA). In conclusion, using this combined approach we characterize the difference in metabolic flux of developing seeds of two B. napus genotypes contrasting in starch

  16. Reconstructing metabolic flux vectors from extreme pathways: defining the alpha-spectrum.

    PubMed

    Wiback, Sharon J; Mahadevan, Radhakrishnan; Palsson, Bernhard Ø

    2003-10-07

    The move towards genome-scale analysis of cellular functions has necessitated the development of analytical (in silico) methods to understand such large and complex biochemical reaction networks. One such method is extreme pathway analysis that uses stoichiometry and thermodynamic irreversibly to define mathematically unique, systemic metabolic pathways. These extreme pathways form the edges of a high-dimensional convex cone in the flux space that contains all the attainable steady state solutions, or flux distributions, for the metabolic network. By definition, any steady state flux distribution can be described as a nonnegative linear combination of the extreme pathways. To date, much effort has been focused on calculating, defining, and understanding these extreme pathways. However, little work has been performed to determine how these extreme pathways contribute to a given steady state flux distribution. This study represents an initial effort aimed at defining how physiological steady state solutions can be reconstructed from a network's extreme pathways. In general, there is not a unique set of nonnegative weightings on the extreme pathways that produce a given steady state flux distribution but rather a range of possible values. This range can be determined using linear optimization to maximize and minimize the weightings of a particular extreme pathway in the reconstruction, resulting in what we have termed the alpha-spectrum. The alpha-spectrum defines which extreme pathways can and cannot be included in the reconstruction of a given steady state flux distribution and to what extent they individually contribute to the reconstruction. It is shown that accounting for transcriptional regulatory constraints can considerably shrink the alpha-spectrum. The alpha-spectrum is computed and interpreted for two cases; first, optimal states of a skeleton representation of core metabolism that include transcriptional regulation, and second for human red blood cell

  17. A Peptide-Based Method for 13C Metabolic Flux Analysis in Microbial Communities

    PubMed Central

    Ghosh, Amit; Nilmeier, Jerome; Weaver, Daniel; Adams, Paul D.; Keasling, Jay D.; Mukhopadhyay, Aindrila; Petzold, Christopher J.; Martín, Héctor García

    2014-01-01

    The study of intracellular metabolic fluxes and inter-species metabolite exchange for microbial communities is of crucial importance to understand and predict their behaviour. The most authoritative method of measuring intracellular fluxes, 13C Metabolic Flux Analysis (13C MFA), uses the labeling pattern obtained from metabolites (typically amino acids) during 13C labeling experiments to derive intracellular fluxes. However, these metabolite labeling patterns cannot easily be obtained for each of the members of the community. Here we propose a new type of 13C MFA that infers fluxes based on peptide labeling, instead of amino acid labeling. The advantage of this method resides in the fact that the peptide sequence can be used to identify the microbial species it originates from and, simultaneously, the peptide labeling can be used to infer intracellular metabolic fluxes. Peptide identity and labeling patterns can be obtained in a high-throughput manner from modern proteomics techniques. We show that, using this method, it is theoretically possible to recover intracellular metabolic fluxes in the same way as through the standard amino acid based 13C MFA, and quantify the amount of information lost as a consequence of using peptides instead of amino acids. We show that by using a relatively small number of peptides we can counter this information loss. We computationally tested this method with a well-characterized simple microbial community consisting of two species. PMID:25188426

  18. Quantitative assessment of thermodynamic constraints on the solution space of genome-scale metabolic models.

    PubMed

    Hamilton, Joshua J; Dwivedi, Vivek; Reed, Jennifer L

    2013-07-16

    Constraint-based methods provide powerful computational techniques to allow understanding and prediction of cellular behavior. These methods rely on physiochemical constraints to eliminate infeasible behaviors from the space of available behaviors. One such constraint is thermodynamic feasibility, the requirement that intracellular flux distributions obey the laws of thermodynamics. The past decade has seen several constraint-based methods that interpret this constraint in different ways, including those that are limited to small networks, rely on predefined reaction directions, and/or neglect the relationship between reaction free energies and metabolite concentrations. In this work, we utilize one such approach, thermodynamics-based metabolic flux analysis (TMFA), to make genome-scale, quantitative predictions about metabolite concentrations and reaction free energies in the absence of prior knowledge of reaction directions, while accounting for uncertainties in thermodynamic estimates. We applied TMFA to a genome-scale network reconstruction of Escherichia coli and examined the effect of thermodynamic constraints on the flux space. We also assessed the predictive performance of TMFA against gene essentiality and quantitative metabolomics data, under both aerobic and anaerobic, and optimal and suboptimal growth conditions. Based on these results, we propose that TMFA is a useful tool for validating phenotypes and generating hypotheses, and that additional types of data and constraints can improve predictions of metabolite concentrations. Copyright © 2013 Biophysical Society. Published by Elsevier Inc. All rights reserved.

  19. [Metabolic flux analysis of L-serine synthesis by Corynebacterium glutamicum SYPS-062].

    PubMed

    Zhang, Xiaomei; Dou, Wenfang; Xu, Hongyu; Xu, Zhenghong

    2010-10-01

    Corynebacterium glutamicum SYPS-062 was an L-serine producing strain stored at our lab and could produce L-serine directly from sugar. We studied the effects of cofactors in one carbon unit metabolism-folate and VB12 on the cell growth, sucrose consumption and L-serine production by SYPS-062. In the same time, the metabolic flux distribution was determined in different conditions. The supplementation of folate or VB12 enhanced the cell growth, energy synthesis, and finally increased the flux of pentose phosphate pathway (HMP), whereas the carbon flux to L-serine was decreased. The addition of VB12 not only increased the ratio of L-serine synthesis pathway on G3P joint, but also caused the insufficiency of tricarboxylic acid cycle (TCA) flux, which needed more anaplerotic reaction flux to replenish TCA cycle, that was an important limiting factor for the further increasing of the L-serine productivity.

  20. Interaction of storage carbohydrates and other cyclic fluxes with central metabolism: A quantitative approach by non-stationary 13C metabolic flux analysis.

    PubMed

    Suarez-Mendez, C A; Hanemaaijer, M; Ten Pierick, Angela; Wolters, J C; Heijnen, J J; Wahl, S A

    2016-12-01

    13 C labeling experiments in aerobic glucose limited cultures of Saccharomyces cerevisiae at four different growth rates (0.054; 0.101, 0.207, 0.307 h -1 ) are used for calculating fluxes that include intracellular cycles (e.g., storage carbohydrate cycles, exchange fluxes with amino acids), which are rearranged depending on the growth rate. At low growth rates the impact of the storage carbohydrate recycle is relatively more significant than at high growth rates due to a higher concentration of these materials in the cell (up to 560-fold) and higher fluxes relative to the glucose uptake rate (up to 16%). Experimental observations suggest that glucose can be exported to the extracellular space, and that its source is related to storage carbohydrates, most likely via the export and subsequent extracellular breakdown of trehalose. This hypothesis is strongly supported by 13 C-labeling experimental data, measured extracellular trehalose, and the corresponding flux estimations.

  1. 13C tracer experiments and metabolite balancing for metabolic flux analysis: comparing two approaches

    PubMed

    Schmidt; Marx; de Graaf AA; Wiechert; Sahm; Nielsen; Villadsen

    1998-04-05

    Conventional metabolic flux analysis uses the information gained from determination of measurable fluxes and a steady-state assumption for intracellular metabolites to calculate the metabolic fluxes in a given metabolic network. The determination of intracellular fluxes depends heavily on the correctness of the assumed stoichiometry including the presence of all reactions with a noticeable impact on the model metabolite balances. Determination of fluxes in complex metabolic networks often requires the inclusion of NADH and NADPH balances, which are subject to controversial debate. Transhydrogenation reactions that transfer reduction equivalents from NADH to NADPH or vice versa can usually not be included in the stoichiometric model, because they result in singularities in the stoichiometric matrix. However, it is the NADPH balance that, to a large extent, determines the calculated flux through the pentose phosphate pathway. Hence, wrong assumptions on the presence or activity of transhydrogenation reactions will result in wrong estimations of the intracellular flux distribution. Using 13C tracer experiments and NMR analysis, flux analysis can be performed on the basis of only well established stoichiometric equations and measurements of the labeling state of intracellular metabolites. Neither NADH/NADPH balancing nor assumptions on energy yields need to be included to determine the intracellular fluxes. Because metabolite balancing methods and the use of 13C labeling measurements are two different approaches to the determination of intracellular fluxes, both methods can be used to verify each other or to discuss the origin and significance of deviations in the results. Flux analysis based entirely on metabolite balancing and flux analysis, including labeling information, have been performed independently for a wild-type strain of Aspergillus oryzae producing alpha-amylase. Two different nitrogen sources, NH4+ and NO3-, have been used to investigate the influence of

  2. Isotopically Nonstationary Metabolic Flux Analysis (INST-MFA) of Photosynthesis and Photorespiration in Plants.

    PubMed

    Ma, Fangfang; Jazmin, Lara J; Young, Jamey D; Allen, Doug K

    2017-01-01

    Photorespiration is a central component of photosynthesis; however to better understand its role it should be viewed in the context of an integrated metabolic network rather than a series of individual reactions that operate independently. Isotopically nonstationary 13 C metabolic flux analysis (INST-MFA), which is based on transient labeling studies at metabolic steady state, offers a comprehensive platform to quantify plant central metabolism. In this chapter, we describe the application of INST-MFA to investigate metabolism in leaves. Leaves are an autotrophic tissue, assimilating CO 2 over a diurnal period implying that the metabolic steady state is limited to less than 12 h and thus requiring an INST-MFA approach. This strategy results in a comprehensive unified description of photorespiration, Calvin cycle, sucrose and starch synthesis, tricarboxylic acid (TCA) cycle, and amino acid biosynthetic fluxes. We present protocols of the experimental aspects for labeling studies: transient 13 CO 2 labeling of leaf tissue, sample quenching and extraction, mass spectrometry (MS) analysis of isotopic labeling data, measurement of sucrose and amino acids in vascular exudates, and provide details on the computational flux estimation using INST-MFA.

  3. 13C metabolic flux analysis: optimal design of isotopic labeling experiments.

    PubMed

    Antoniewicz, Maciek R

    2013-12-01

    Measuring fluxes by 13C metabolic flux analysis (13C-MFA) has become a key activity in chemical and pharmaceutical biotechnology. Optimal design of isotopic labeling experiments is of central importance to 13C-MFA as it determines the precision with which fluxes can be estimated. Traditional methods for selecting isotopic tracers and labeling measurements did not fully utilize the power of 13C-MFA. Recently, new approaches were developed for optimal design of isotopic labeling experiments based on parallel labeling experiments and algorithms for rational selection of tracers. In addition, advanced isotopic labeling measurements were developed based on tandem mass spectrometry. Combined, these approaches can dramatically improve the quality of 13C-MFA results with important applications in metabolic engineering and biotechnology. Copyright © 2013 Elsevier Ltd. All rights reserved.

  4. Flux-Enabled Exploration of the Role of Sip1 in Galactose Yeast Metabolism

    DOE PAGES

    Shymansky, Christopher M.; Wang, George; Baidoo, Edward E. K.; ...

    2017-05-24

    13C metabolic flux analysis ( 13C MFA) is an important systems biology technique that has been used to investigate microbial metabolism for decades. The heterotrimer Snf1 kinase complex plays a key role in the preference Saccharomyces cerevisiae exhibits for glucose over galactose, a phenomenon known as glucose repression or carbon catabolite repression. The SIP1 gene, encoding a part of this complex, has received little attention, presumably, because its knockout lacks a growth phenotype. We present a fluxomic investigation of the relative effects of the presence of galactose in classically glucose-repressing media and/or knockout of SIP1 using a multi-scale variant ofmore » 13C MFA known as 2-Scale 13C metabolic flux analysis (2S- 13C MFA). In this study, all strains have the galactose metabolism deactivated (gal1Δ background) so as to be able to separate the metabolic effects purely related to glucose repression from those arising from galactose metabolism. The resulting flux profiles reveal that the presence of galactose in classically glucose-repressing conditions, for a CEN.PK113-7D gal1Δ background, results in a substantial decrease in pentose phosphate pathway (PPP) flux and increased flow from cytosolic pyruvate and malate through the mitochondria toward cytosolic branched-chain amino acid biosynthesis. These fluxomic redistributions are accompanied by a higher maximum specific growth rate, both seemingly in violation of glucose repression. Deletion of SIP1 in the CEN.PK113-7D gal1Δ cells grown in mixed glucose/galactose medium results in a further increase. Knockout of this gene in cells grown in glucose-only medium results in no change in growth rate and a corresponding decrease in glucose and ethanol exchange fluxes and flux through pathways involved in aspartate/threonine biosynthesis. Glucose repression appears to be violated at a 1/10 ratio of galactose-to-glucose. Based on the scientific literature, we may have conducted our experiments near a

  5. Flux-Enabled Exploration of the Role of Sip1 in Galactose Yeast Metabolism

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Shymansky, Christopher M.; Wang, George; Baidoo, Edward E. K.

    13C metabolic flux analysis ( 13C MFA) is an important systems biology technique that has been used to investigate microbial metabolism for decades. The heterotrimer Snf1 kinase complex plays a key role in the preference Saccharomyces cerevisiae exhibits for glucose over galactose, a phenomenon known as glucose repression or carbon catabolite repression. The SIP1 gene, encoding a part of this complex, has received little attention, presumably, because its knockout lacks a growth phenotype. We present a fluxomic investigation of the relative effects of the presence of galactose in classically glucose-repressing media and/or knockout of SIP1 using a multi-scale variant ofmore » 13C MFA known as 2-Scale 13C metabolic flux analysis (2S- 13C MFA). In this study, all strains have the galactose metabolism deactivated (gal1Δ background) so as to be able to separate the metabolic effects purely related to glucose repression from those arising from galactose metabolism. The resulting flux profiles reveal that the presence of galactose in classically glucose-repressing conditions, for a CEN.PK113-7D gal1Δ background, results in a substantial decrease in pentose phosphate pathway (PPP) flux and increased flow from cytosolic pyruvate and malate through the mitochondria toward cytosolic branched-chain amino acid biosynthesis. These fluxomic redistributions are accompanied by a higher maximum specific growth rate, both seemingly in violation of glucose repression. Deletion of SIP1 in the CEN.PK113-7D gal1Δ cells grown in mixed glucose/galactose medium results in a further increase. Knockout of this gene in cells grown in glucose-only medium results in no change in growth rate and a corresponding decrease in glucose and ethanol exchange fluxes and flux through pathways involved in aspartate/threonine biosynthesis. Glucose repression appears to be violated at a 1/10 ratio of galactose-to-glucose. Based on the scientific literature, we may have conducted our experiments near a

  6. Flux-Enabled Exploration of the Role of Sip1 in Galactose Yeast Metabolism

    PubMed Central

    Shymansky, Christopher M.; Wang, George; Baidoo, Edward E. K.; Gin, Jennifer; Apel, Amanda Reider; Mukhopadhyay, Aindrila; García Martín, Héctor; Keasling, Jay D.

    2017-01-01

    13C metabolic flux analysis (13C MFA) is an important systems biology technique that has been used to investigate microbial metabolism for decades. The heterotrimer Snf1 kinase complex plays a key role in the preference Saccharomyces cerevisiae exhibits for glucose over galactose, a phenomenon known as glucose repression or carbon catabolite repression. The SIP1 gene, encoding a part of this complex, has received little attention, presumably, because its knockout lacks a growth phenotype. We present a fluxomic investigation of the relative effects of the presence of galactose in classically glucose-repressing media and/or knockout of SIP1 using a multi-scale variant of 13C MFA known as 2-Scale 13C metabolic flux analysis (2S-13C MFA). In this study, all strains have the galactose metabolism deactivated (gal1Δ background) so as to be able to separate the metabolic effects purely related to glucose repression from those arising from galactose metabolism. The resulting flux profiles reveal that the presence of galactose in classically glucose-repressing conditions, for a CEN.PK113-7D gal1Δ background, results in a substantial decrease in pentose phosphate pathway (PPP) flux and increased flow from cytosolic pyruvate and malate through the mitochondria toward cytosolic branched-chain amino acid biosynthesis. These fluxomic redistributions are accompanied by a higher maximum specific growth rate, both seemingly in violation of glucose repression. Deletion of SIP1 in the CEN.PK113-7D gal1Δ cells grown in mixed glucose/galactose medium results in a further increase. Knockout of this gene in cells grown in glucose-only medium results in no change in growth rate and a corresponding decrease in glucose and ethanol exchange fluxes and flux through pathways involved in aspartate/threonine biosynthesis. Glucose repression appears to be violated at a 1/10 ratio of galactose-to-glucose. Based on the scientific literature, we may have conducted our experiments near a critical

  7. Reconstruction and flux analysis of coupling between metabolic pathways of astrocytes and neurons: application to cerebral hypoxia

    PubMed Central

    Çakιr, Tunahan; Alsan, Selma; Saybaşιlι, Hale; Akιn, Ata; Ülgen, Kutlu Ö

    2007-01-01

    Background It is a daunting task to identify all the metabolic pathways of brain energy metabolism and develop a dynamic simulation environment that will cover a time scale ranging from seconds to hours. To simplify this task and make it more practicable, we undertook stoichiometric modeling of brain energy metabolism with the major aim of including the main interacting pathways in and between astrocytes and neurons. Model The constructed model includes central metabolism (glycolysis, pentose phosphate pathway, TCA cycle), lipid metabolism, reactive oxygen species (ROS) detoxification, amino acid metabolism (synthesis and catabolism), the well-known glutamate-glutamine cycle, other coupling reactions between astrocytes and neurons, and neurotransmitter metabolism. This is, to our knowledge, the most comprehensive attempt at stoichiometric modeling of brain metabolism to date in terms of its coverage of a wide range of metabolic pathways. We then attempted to model the basal physiological behaviour and hypoxic behaviour of the brain cells where astrocytes and neurons are tightly coupled. Results The reconstructed stoichiometric reaction model included 217 reactions (184 internal, 33 exchange) and 216 metabolites (183 internal, 33 external) distributed in and between astrocytes and neurons. Flux balance analysis (FBA) techniques were applied to the reconstructed model to elucidate the underlying cellular principles of neuron-astrocyte coupling. Simulation of resting conditions under the constraints of maximization of glutamate/glutamine/GABA cycle fluxes between the two cell types with subsequent minimization of Euclidean norm of fluxes resulted in a flux distribution in accordance with literature-based findings. As a further validation of our model, the effect of oxygen deprivation (hypoxia) on fluxes was simulated using an FBA-derivative approach, known as minimization of metabolic adjustment (MOMA). The results show the power of the constructed model to simulate

  8. Foraging theory predicts predator-prey energy fluxes.

    PubMed

    Brose, U; Ehnes, R B; Rall, B C; Vucic-Pestic, O; Berlow, E L; Scheu, S

    2008-09-01

    1. In natural communities, populations are linked by feeding interactions that make up complex food webs. The stability of these complex networks is critically dependent on the distribution of energy fluxes across these feeding links. 2. In laboratory experiments with predatory beetles and spiders, we studied the allometric scaling (body-mass dependence) of metabolism and per capita consumption at the level of predator individuals and per link energy fluxes at the level of feeding links. 3. Despite clear power-law scaling of the metabolic and per capita consumption rates with predator body mass, the per link predation rates on individual prey followed hump-shaped relationships with the predator-prey body mass ratios. These results contrast with the current metabolic paradigm, and find better support in foraging theory. 4. This suggests that per link energy fluxes from prey populations to predator individuals peak at intermediate body mass ratios, and total energy fluxes from prey to predator populations decrease monotonically with predator and prey mass. Surprisingly, contrary to predictions of metabolic models, this suggests that for any prey species, the per link and total energy fluxes to its largest predators are smaller than those to predators of intermediate body size. 5. An integration of metabolic and foraging theory may enable a quantitative and predictive understanding of energy flux distributions in natural food webs.

  9. ReMatch: a web-based tool to construct, store and share stoichiometric metabolic models with carbon maps for metabolic flux analysis.

    PubMed

    Pitkänen, Esa; Akerlund, Arto; Rantanen, Ari; Jouhten, Paula; Ukkonen, Esko

    2008-08-25

    ReMatch is a web-based, user-friendly tool that constructs stoichiometric network models for metabolic flux analysis, integrating user-developed models into a database collected from several comprehensive metabolic data resources, including KEGG, MetaCyc and CheBI. Particularly, ReMatch augments the metabolic reactions of the model with carbon mappings to facilitate (13)C metabolic flux analysis. The construction of a network model consisting of biochemical reactions is the first step in most metabolic modelling tasks. This model construction can be a tedious task as the required information is usually scattered to many separate databases whose interoperability is suboptimal, due to the heterogeneous naming conventions of metabolites in different databases. Another, particularly severe data integration problem is faced in (13)C metabolic flux analysis, where the mappings of carbon atoms from substrates into products in the model are required. ReMatch has been developed to solve the above data integration problems. First, ReMatch matches the imported user-developed model against the internal ReMatch database while considering a comprehensive metabolite name thesaurus. This, together with wild card support, allows the user to specify the model quickly without having to look the names up manually. Second, ReMatch is able to augment reactions of the model with carbon mappings, obtained either from the internal database or given by the user with an easy-touse tool. The constructed models can be exported into 13C-FLUX and SBML file formats. Further, a stoichiometric matrix and visualizations of the network model can be generated. The constructed models of metabolic networks can be optionally made available to the other users of ReMatch. Thus, ReMatch provides a common repository for metabolic network models with carbon mappings for the needs of metabolic flux analysis community. ReMatch is freely available for academic use at http://www.cs.helsinki.fi/group/sysfys/software/rematch/.

  10. Metabolite-balancing techniques vs. 13C tracer experiments to determine metabolic fluxes in hybridoma cells.

    PubMed

    Bonarius, H P; Timmerarends, B; de Gooijer, C D; Tramper, J

    The estimation of intracellular fluxes of mammalian cells using only mass balances of the relevant metabolites is not possible because the set of linear equations defined by these mass balances is underdetermined. In order to quantify fluxes in cyclic pathways the mass balance equations can be complemented with several constraints: (1) the mass balances of co-metabolites, such as ATP or NAD(P)H, (2) linear objective functions, (3) flux data obtained by isotopic-tracer experiments. Here, these three methods are compared for the analysis of fluxes in the primary metabolism of continuously cultured hybridoma cells. The significance of different theoretical constraints and different objective functions is discussed after comparing their resulting flux distributions to the fluxes determined using 13CO2 and 13C-lactate measurements of 1 - 13C-glucose-fed hybridoma cells. Metabolic fluxes estimated using the objective functions "maximize ATP" and "maximize NADH" are relatively similar to the experimentally determined fluxes. This is consistent with the observation that cancer cells, such as hybridomas, are metabolically hyperactive, and produce ATP and NADH regardless of the need for these cofactors. Copyright 1998 John Wiley & Sons, Inc.

  11. 13C Metabolic Flux Analysis for Systematic Metabolic Engineering of S. cerevisiae for Overproduction of Fatty Acids

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Ghosh, Amit; Ando, David; Gin, Jennifer

    Efficient redirection of microbial metabolism into the abundant production of desired bioproducts remains non-trivial. Here, we used flux-based modeling approaches to improve yields of fatty acids in Saccharomyces cerevisiae. We combined 13C labeling data with comprehensive genome-scale models to shed light onto microbial metabolism and improve metabolic engineering efforts. We concentrated on studying the balance of acetyl-CoA, a precursor metabolite for the biosynthesis of fatty acids. A genome-wide acetyl-CoA balance study showed ATP citrate lyase from Yarrowia lipolytica as a robust source of cytoplasmic acetyl-CoA and malate synthase as a desirable target for downregulation in terms of acetyl-CoA consumption. Thesemore » genetic modifications were applied to S. cerevisiae WRY2, a strain that is capable of producing 460 mg/L of free fatty acids. With the addition of ATP citrate lyase and downregulation of malate synthase, the engineered strain produced 26% more free fatty acids. Further increases in free fatty acid production of 33% were obtained by knocking out the cytoplasmic glycerol-3-phosphate dehydrogenase, which flux analysis had shown was competing for carbon flux upstream with the carbon flux through the acetyl-CoA production pathway in the cytoplasm. In total, the genetic interventions applied in this work increased fatty acid production by ~70%.« less

  12. 13C Metabolic Flux Analysis for Systematic Metabolic Engineering of S. cerevisiae for Overproduction of Fatty Acids

    DOE PAGES

    Ghosh, Amit; Ando, David; Gin, Jennifer; ...

    2016-10-05

    Efficient redirection of microbial metabolism into the abundant production of desired bioproducts remains non-trivial. Here, we used flux-based modeling approaches to improve yields of fatty acids in Saccharomyces cerevisiae. We combined 13C labeling data with comprehensive genome-scale models to shed light onto microbial metabolism and improve metabolic engineering efforts. We concentrated on studying the balance of acetyl-CoA, a precursor metabolite for the biosynthesis of fatty acids. A genome-wide acetyl-CoA balance study showed ATP citrate lyase from Yarrowia lipolytica as a robust source of cytoplasmic acetyl-CoA and malate synthase as a desirable target for downregulation in terms of acetyl-CoA consumption. Thesemore » genetic modifications were applied to S. cerevisiae WRY2, a strain that is capable of producing 460 mg/L of free fatty acids. With the addition of ATP citrate lyase and downregulation of malate synthase, the engineered strain produced 26% more free fatty acids. Further increases in free fatty acid production of 33% were obtained by knocking out the cytoplasmic glycerol-3-phosphate dehydrogenase, which flux analysis had shown was competing for carbon flux upstream with the carbon flux through the acetyl-CoA production pathway in the cytoplasm. In total, the genetic interventions applied in this work increased fatty acid production by ~70%.« less

  13. Flux coupling and transcriptional regulation within the metabolic network of the photosynthetic bacterium Synechocystis sp. PCC6803.

    PubMed

    Montagud, Arnau; Zelezniak, Aleksej; Navarro, Emilio; de Córdoba, Pedro Fernández; Urchueguía, Javier F; Patil, Kiran Raosaheb

    2011-03-01

    Synechocystis sp. PCC6803 is a model cyanobacterium capable of producing biofuels with CO(2) as carbon source and with its metabolism fueled by light, for which it stands as a potential production platform of socio-economic importance. Compilation and characterization of Synechocystis genome-scale metabolic model is a pre-requisite toward achieving a proficient photosynthetic cell factory. To this end, we report iSyn811, an upgraded genome-scale metabolic model of Synechocystis sp. PCC6803 consisting of 956 reactions and accounting for 811 genes. To gain insights into the interplay between flux activities and metabolic physiology, flux coupling analysis was performed for iSyn811 under four different growth conditions, viz., autotrophy, mixotrophy, heterotrophy, and light-activated heterotrophy (LH). Initial steps of carbon acquisition and catabolism formed the versatile center of the flux coupling networks, surrounded by a stable core of pathways leading to biomass building blocks. This analysis identified potential bottlenecks for hydrogen and ethanol production. Integration of transcriptomic data with the Synechocystis flux coupling networks lead to identification of reporter flux coupling pairs and reporter flux coupling groups - regulatory hot spots during metabolic shifts triggered by the availability of light. Overall, flux coupling analysis provided insight into the structural organization of Synechocystis sp. PCC6803 metabolic network toward designing of a photosynthesis-based production platform. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  14. Temporal fluxomics reveals oscillations in TCA cycle flux throughout the mammalian cell cycle.

    PubMed

    Ahn, Eunyong; Kumar, Praveen; Mukha, Dzmitry; Tzur, Amit; Shlomi, Tomer

    2017-11-06

    Cellular metabolic demands change throughout the cell cycle. Nevertheless, a characterization of how metabolic fluxes adapt to the changing demands throughout the cell cycle is lacking. Here, we developed a temporal-fluxomics approach to derive a comprehensive and quantitative view of alterations in metabolic fluxes throughout the mammalian cell cycle. This is achieved by combining pulse-chase LC-MS-based isotope tracing in synchronized cell populations with computational deconvolution and metabolic flux modeling. We find that TCA cycle fluxes are rewired as cells progress through the cell cycle with complementary oscillations of glucose versus glutamine-derived fluxes: Oxidation of glucose-derived flux peaks in late G1 phase, while oxidative and reductive glutamine metabolism dominates S phase. These complementary flux oscillations maintain a constant production rate of reducing equivalents and oxidative phosphorylation flux throughout the cell cycle. The shift from glucose to glutamine oxidation in S phase plays an important role in cell cycle progression and cell proliferation. © 2017 The Authors. Published under the terms of the CC BY 4.0 license.

  15. 13C labeling analysis of sugars by high resolution-mass spectrometry for metabolic flux analysis.

    PubMed

    Acket, Sébastien; Degournay, Anthony; Merlier, Franck; Thomasset, Brigitte

    2017-06-15

    Metabolic flux analysis is particularly complex in plant cells because of highly compartmented metabolism. Analysis of free sugars is interesting because it provides data to define fluxes around hexose, pentose, and triose phosphate pools in different compartment. In this work, we present a method to analyze the isotopomer distribution of free sugars labeled with carbon 13 using a liquid chromatography-high resolution mass spectrometry, without derivatized procedure, adapted for Metabolic flux analysis. Our results showed a good sensitivity, reproducibility and better accuracy to determine isotopic enrichments of free sugars compared to our previous methods [5, 6]. Copyright © 2017 Elsevier Inc. All rights reserved.

  16. The avian cell line AGE1.CR.pIX characterized by metabolic flux analysis

    PubMed Central

    2014-01-01

    Background In human vaccine manufacturing some pathogens such as Modified Vaccinia Virus Ankara, measles, mumps virus as well as influenza viruses are still produced on primary material derived from embryonated chicken eggs. Processes depending on primary cell culture, however, are difficult to adapt to modern vaccine production. Therefore, we derived previously a continuous suspension cell line, AGE1.CR.pIX, from muscovy duck and established chemically-defined media for virus propagation. Results To better understand vaccine production processes, we developed a stoichiometric model of the central metabolism of AGE1.CR.pIX cells and applied flux variability and metabolic flux analysis. Results were compared to literature dealing with mammalian and insect cell culture metabolism focusing on the question whether cultured avian cells differ in metabolism. Qualitatively, the observed flux distribution of this avian cell line was similar to distributions found for mammalian cell lines (e.g. CHO, MDCK cells). In particular, glucose was catabolized inefficiently and glycolysis and TCA cycle seem to be only weakly connected. Conclusions A distinguishing feature of the avian cell line is that glutaminolysis plays only a minor role in energy generation and production of precursors, resulting in low extracellular ammonia concentrations. This metabolic flux study is the first for a continuous avian cell line. It provides a basis for further metabolic analyses to exploit the biotechnological potential of avian and vertebrate cell lines and to develop specific optimized cell culture processes, e.g. vaccine production processes. PMID:25077436

  17. The avian cell line AGE1.CR.pIX characterized by metabolic flux analysis.

    PubMed

    Lohr, Verena; Hädicke, Oliver; Genzel, Yvonne; Jordan, Ingo; Büntemeyer, Heino; Klamt, Steffen; Reichl, Udo

    2014-07-30

    In human vaccine manufacturing some pathogens such as Modified Vaccinia Virus Ankara, measles, mumps virus as well as influenza viruses are still produced on primary material derived from embryonated chicken eggs. Processes depending on primary cell culture, however, are difficult to adapt to modern vaccine production. Therefore, we derived previously a continuous suspension cell line, AGE1.CR.pIX, from muscovy duck and established chemically-defined media for virus propagation. To better understand vaccine production processes, we developed a stoichiometric model of the central metabolism of AGE1.CR.pIX cells and applied flux variability and metabolic flux analysis. Results were compared to literature dealing with mammalian and insect cell culture metabolism focusing on the question whether cultured avian cells differ in metabolism. Qualitatively, the observed flux distribution of this avian cell line was similar to distributions found for mammalian cell lines (e.g. CHO, MDCK cells). In particular, glucose was catabolized inefficiently and glycolysis and TCA cycle seem to be only weakly connected. A distinguishing feature of the avian cell line is that glutaminolysis plays only a minor role in energy generation and production of precursors, resulting in low extracellular ammonia concentrations. This metabolic flux study is the first for a continuous avian cell line. It provides a basis for further metabolic analyses to exploit the biotechnological potential of avian and vertebrate cell lines and to develop specific optimized cell culture processes, e.g. vaccine production processes.

  18. Metabolic flux phenotype of tobacco hairy roots engineered for increased geraniol production.

    PubMed

    Masakapalli, Shyam K; Ritala, Anneli; Dong, Lemeng; van der Krol, Alexander R; Oksman-Caldentey, Kirsi-Marja; Ratcliffe, R George; Sweetlove, Lee J

    2014-03-01

    The goal of this study was to characterise the metabolic flux phenotype of transgenic tobacco (Nicotiana tabacum) hairy roots engineered for increased biosynthesis of geraniol, an intermediate of the terpenoid indole alkaloid pathway. Steady state, stable isotope labelling was used to determine flux maps of central carbon metabolism for transgenic lines over-expressing (i) plastid-targeted geraniol synthase (pGES) from Valeriana officinalis, and (ii) pGES in combination with plastid-targeted geranyl pyrophosphate synthase from Arabidopsis thaliana (pGES+pGPPS), as well as for wild type and control-vector-transformed roots. Fluxes were constrained by the redistribution of label from [1-¹³C]-, [2-¹³C]- or [¹³C6]glucose into amino acids, sugars and organic acids at isotopic steady state, and by biomass output fluxes determined from the fractionation of [U-¹⁴C]glucose into insoluble polymers. No significant differences in growth and biomass composition were observed between the lines. The pGES line accumulated significant amounts of geraniol/geraniol glycosides (151±24 ng/mg dry weight) and the de novo synthesis of geraniol in pGES was confirmed by ¹³C labelling analysis. The pGES+pGPPS also accumulated geraniol and geraniol glycosides, but to lower levels than the pGES line. Although there was a distinct impact of the transgenes at the level of geraniol synthesis, other network fluxes were unaffected, reflecting the capacity of central metabolism to meet the relatively modest demand for increased precursors in the transgenic lines. It is concluded that re-engineering of the terpenoid indole alkaloid pathway will only require simultaneous manipulation of the steps producing the pathway precursors that originate in central metabolism in tissues engineered to produce at least an order of magnitude more geraniol than has been achieved so far. Copyright © 2013 Elsevier Ltd. All rights reserved.

  19. Quantitative Analysis of Energy Metabolic Pathways in MCF-7 Breast Cancer Cells by Selected Reaction Monitoring Assay*

    PubMed Central

    Drabovich, Andrei P.; Pavlou, Maria P.; Dimitromanolakis, Apostolos; Diamandis, Eleftherios P.

    2012-01-01

    To investigate the quantitative response of energy metabolic pathways in human MCF-7 breast cancer cells to hypoxia, glucose deprivation, and estradiol stimulation, we developed a targeted proteomics assay for accurate quantification of protein expression in glycolysis/gluconeogenesis, TCA cycle, and pentose phosphate pathways. Cell growth conditions were selected to roughly mimic the exposure of cells in the cancer tissue to the intermittent hypoxia, glucose deprivation, and hormonal stimulation. Targeted proteomics assay allowed for reproducible quantification of 76 proteins in four different growth conditions after 24 and 48 h of perturbation. Differential expression of a number of control and metabolic pathway proteins in response to the change of growth conditions was found. Elevated expression of the majority of glycolytic enzymes was observed in hypoxia. Cancer cells, as opposed to near-normal MCF-10A cells, exhibited significantly increased expression of key energy metabolic pathway enzymes (FBP1, IDH2, and G6PD) that are known to redirect cellular metabolism and increase carbon flux through the pentose phosphate pathway. Our quantitative proteomic protocol is based on a mass spectrometry-compatible acid-labile detergent and is described in detail. Optimized parameters of a multiplex selected reaction monitoring (SRM) assay for 76 proteins, 134 proteotypic peptides, and 401 transitions are included and can be downloaded and used with any SRM-compatible mass spectrometer. The presented workflow is an integrated tool for hypothesis-driven studies of mammalian cells as well as functional studies of proteins, and can greatly complement experimental methods in systems biology, metabolic engineering, and metabolic transformation of cancer cells. PMID:22535206

  20. FluxPyt: a Python-based free and open-source software for 13C-metabolic flux analyses.

    PubMed

    Desai, Trunil S; Srivastava, Shireesh

    2018-01-01

    13 C-Metabolic flux analysis (MFA) is a powerful approach to estimate intracellular reaction rates which could be used in strain analysis and design. Processing and analysis of labeling data for calculation of fluxes and associated statistics is an essential part of MFA. However, various software currently available for data analysis employ proprietary platforms and thus limit accessibility. We developed FluxPyt, a Python-based truly open-source software package for conducting stationary 13 C-MFA data analysis. The software is based on the efficient elementary metabolite unit framework. The standard deviations in the calculated fluxes are estimated using the Monte-Carlo analysis. FluxPyt also automatically creates flux maps based on a template for visualization of the MFA results. The flux distributions calculated by FluxPyt for two separate models: a small tricarboxylic acid cycle model and a larger Corynebacterium glutamicum model, were found to be in good agreement with those calculated by a previously published software. FluxPyt was tested in Microsoft™ Windows 7 and 10, as well as in Linux Mint 18.2. The availability of a free and open 13 C-MFA software that works in various operating systems will enable more researchers to perform 13 C-MFA and to further modify and develop the package.

  1. FluxPyt: a Python-based free and open-source software for 13C-metabolic flux analyses

    PubMed Central

    Desai, Trunil S.

    2018-01-01

    13C-Metabolic flux analysis (MFA) is a powerful approach to estimate intracellular reaction rates which could be used in strain analysis and design. Processing and analysis of labeling data for calculation of fluxes and associated statistics is an essential part of MFA. However, various software currently available for data analysis employ proprietary platforms and thus limit accessibility. We developed FluxPyt, a Python-based truly open-source software package for conducting stationary 13C-MFA data analysis. The software is based on the efficient elementary metabolite unit framework. The standard deviations in the calculated fluxes are estimated using the Monte-Carlo analysis. FluxPyt also automatically creates flux maps based on a template for visualization of the MFA results. The flux distributions calculated by FluxPyt for two separate models: a small tricarboxylic acid cycle model and a larger Corynebacterium glutamicum model, were found to be in good agreement with those calculated by a previously published software. FluxPyt was tested in Microsoft™ Windows 7 and 10, as well as in Linux Mint 18.2. The availability of a free and open 13C-MFA software that works in various operating systems will enable more researchers to perform 13C-MFA and to further modify and develop the package. PMID:29736347

  2. Flux Balance Analysis of Cyanobacterial Metabolism: The Metabolic Network of Synechocystis sp. PCC 6803

    PubMed Central

    Knoop, Henning; Gründel, Marianne; Zilliges, Yvonne; Lehmann, Robert; Hoffmann, Sabrina; Lockau, Wolfgang; Steuer, Ralf

    2013-01-01

    Cyanobacteria are versatile unicellular phototrophic microorganisms that are highly abundant in many environments. Owing to their capability to utilize solar energy and atmospheric carbon dioxide for growth, cyanobacteria are increasingly recognized as a prolific resource for the synthesis of valuable chemicals and various biofuels. To fully harness the metabolic capabilities of cyanobacteria necessitates an in-depth understanding of the metabolic interconversions taking place during phototrophic growth, as provided by genome-scale reconstructions of microbial organisms. Here we present an extended reconstruction and analysis of the metabolic network of the unicellular cyanobacterium Synechocystis sp. PCC 6803. Building upon several recent reconstructions of cyanobacterial metabolism, unclear reaction steps are experimentally validated and the functional consequences of unknown or dissenting pathway topologies are discussed. The updated model integrates novel results with respect to the cyanobacterial TCA cycle, an alleged glyoxylate shunt, and the role of photorespiration in cellular growth. Going beyond conventional flux-balance analysis, we extend the computational analysis to diurnal light/dark cycles of cyanobacterial metabolism. PMID:23843751

  3. Metabolic Flux Analysis of the Synechocystis sp. PCC 6803 ΔnrtABCD Mutant Reveals a Mechanism for Metabolic Adaptation to Nitrogen-Limited Conditions.

    PubMed

    Nakajima, Tsubasa; Yoshikawa, Katsunori; Toya, Yoshihiro; Matsuda, Fumio; Shimizu, Hiroshi

    2017-03-01

    Metabolic flux redirection during nitrogen-limited growth was investigated in the Synechocystis sp. PCC 6803 glucose-tolerant (GT) strain under photoautotrophic conditions by isotopically non-stationary metabolic flux analysis (INST-MFA). A ΔnrtABCD mutant of Synechocystis sp. PCC 6803 was constructed to reproduce phenotypes arising during nitrogen starvation. The ΔnrtABCD mutant and the wild-type GT strain were cultured under photoautotrophic conditions by a photobioreactor. Intracellular metabolites were labeled over a time course using NaH13CO3 as a carbon source. Based on these data, the metabolic flux distributions in the wild-type and ΔnrtABCD cells were estimated by INST-MFA. The wild-type GT and ΔnrtABCD strains displayed similar distribution patterns, although the absolute levels of metabolic flux were lower in ΔnrtABCD. Furthermore, the relative flux levels for glycogen metabolism, anaplerotic reactions and the oxidative pentose phosphate pathway were increased in ΔnrtABCD. This was probably due to the increased expression of enzyme genes that respond to nitrogen depletion. Additionally, we found that the ratio of ATP/NADPH demand increased slightly in the ΔnrtABCD mutant. These results indicated that futile ATP consumption increases under nitrogen-limited conditions because the Calvin-Benson cycle and the oxidative pentose phosphate pathway form a metabolic futile cycle that consumes ATP without CO2 fixation and NADPH regeneration. © The Author 2017. Published by Oxford University Press on behalf of Japanese Society of Plant Physiologists. All rights reserved. For permissions, please email: journals.permissions@oup.com.

  4. Metabolic networks in motion: 13C-based flux analysis

    PubMed Central

    Sauer, Uwe

    2006-01-01

    Many properties of complex networks cannot be understood from monitoring the components—not even when comprehensively monitoring all protein or metabolite concentrations—unless such information is connected and integrated through mathematical models. The reason is that static component concentrations, albeit extremely informative, do not contain functional information per se. The functional behavior of a network emerges only through the nonlinear gene, protein, and metabolite interactions across multiple metabolic and regulatory layers. I argue here that intracellular reaction rates are the functional end points of these interactions in metabolic networks, hence are highly relevant for systems biology. Methods for experimental determination of metabolic fluxes differ fundamentally from component concentration measurements; that is, intracellular reaction rates cannot be detected directly, but must be estimated through computer model-based interpretation of stable isotope patterns in products of metabolism. PMID:17102807

  5. Identifying model error in metabolic flux analysis - a generalized least squares approach.

    PubMed

    Sokolenko, Stanislav; Quattrociocchi, Marco; Aucoin, Marc G

    2016-09-13

    The estimation of intracellular flux through traditional metabolic flux analysis (MFA) using an overdetermined system of equations is a well established practice in metabolic engineering. Despite the continued evolution of the methodology since its introduction, there has been little focus on validation and identification of poor model fit outside of identifying "gross measurement error". The growing complexity of metabolic models, which are increasingly generated from genome-level data, has necessitated robust validation that can directly assess model fit. In this work, MFA calculation is framed as a generalized least squares (GLS) problem, highlighting the applicability of the common t-test for model validation. To differentiate between measurement and model error, we simulate ideal flux profiles directly from the model, perturb them with estimated measurement error, and compare their validation to real data. Application of this strategy to an established Chinese Hamster Ovary (CHO) cell model shows how fluxes validated by traditional means may be largely non-significant due to a lack of model fit. With further simulation, we explore how t-test significance relates to calculation error and show that fluxes found to be non-significant have 2-4 fold larger error (if measurement uncertainty is in the 5-10 % range). The proposed validation method goes beyond traditional detection of "gross measurement error" to identify lack of fit between model and data. Although the focus of this work is on t-test validation and traditional MFA, the presented framework is readily applicable to other regression analysis methods and MFA formulations.

  6. (13)C metabolic flux analysis in neurons utilizing a model that accounts for hexose phosphate recycling within the pentose phosphate pathway.

    PubMed

    Gebril, Hoda M; Avula, Bharathi; Wang, Yan-Hong; Khan, Ikhlas A; Jekabsons, Mika B

    2016-02-01

    Glycolysis, mitochondrial substrate oxidation, and the pentose phosphate pathway (PPP) are critical for neuronal bioenergetics and oxidation-reduction homeostasis, but quantitating their fluxes remains challenging, especially when processes such as hexose phosphate (i.e., glucose/fructose-6-phosphate) recycling in the PPP are considered. A hexose phosphate recycling model was developed which exploited the rates of glucose consumption, lactate production, and mitochondrial respiration to infer fluxes through the major glucose consuming pathways of adherent cerebellar granule neurons by replicating [(13)C]lactate labeling from metabolism of [1,2-(13)C2]glucose. Flux calculations were predicated on a steady-state system with reactions having known stoichiometries and carbon atom transitions. Non-oxidative PPP activity and consequent hexose phosphate recycling, as well as pyruvate production by cytoplasmic malic enzyme, were optimized by the model and found to account for 28 ± 2% and 7.7 ± 0.2% of hexose phosphate and pyruvate labeling, respectively. From the resulting fluxes, 52 ± 6% of glucose was metabolized by glycolysis, compared to 19 ± 2% by the combined oxidative/non-oxidative pentose cycle that allows for hexose phosphate recycling, and 29 ± 8% by the combined oxidative PPP/de novo nucleotide synthesis reactions. By extension, 62 ± 6% of glucose was converted to pyruvate, the metabolism of which resulted in 16 ± 1% of glucose oxidized by mitochondria and 46 ± 6% exported as lactate. The results indicate a surprisingly high proportion of glucose utilized by the pentose cycle and the reactions synthesizing nucleotides, and exported as lactate. While the in vitro conditions to which the neurons were exposed (high glucose, no lactate or other exogenous substrates) limit extrapolating these results to the in vivo state, the approach provides a means of assessing a number of metabolic fluxes within the context of hexose phosphate recycling in the PPP from a

  7. Batch culture characterization and metabolic flux analysis of succinate-producing Escherichia coli strains.

    PubMed

    Sánchez, Ailen M; Bennett, George N; San, Ka-Yiu

    2006-05-01

    This study presents an in-depth analysis of the anaerobic metabolic fluxes of various mutant strains of Escherichia coli overexpressing the Lactococcus lactis pyruvate carboxylase (PYC) for the production of succinate. Previously, a metabolic network design that includes an active glyoxylate pathway implemented in vivo increased succinate yield from glucose in an E. coli mutant to 1.6 mol/mol under fully anaerobic conditions. The design consists of a dual succinate synthesis route, which diverts required quantities of NADH through the traditional fermentative pathway and maximizes the carbon converted to succinate by balancing the carbon flux through the fermentative pathway and the glyoxylate pathway (which has a lower NADH requirement). Mutant strains previously constructed during the development of high-yield succinate-producing strains were selected for further characterization to understand their metabolic response as a result of several genetic manipulations and to determine the significance of the fermentative and the glyoxylate pathways in the production of succinate. Measured fluxes obtained under batch cultivation conditions were used to estimate intracellular fluxes and identify critical branch point flux split ratios. The comparison of changes in branch point flux split ratios to the glyoxylate pathway and the fermentative pathway at the oxaloacetate (OAA) node as a result of different mutations revealed the sensitivity of succinate yield to these manipulations. The most favorable split ratio to obtain the highest succinate yield was the fractional partition of OAA to glyoxylate of 0.32 and 0.68 to the fermentative pathway obtained in strains SBS550MG (pHL413) and SBS990MG (pHL413). The succinate yields achieved in these two strains were 1.6 and 1.7 mol/mol, respectively. In addition, an active glyoxylate pathway in an ldhA, adhE, ack-pta mutant strain is shown to be responsible for the high succinate yields achieved anaerobically. Furthermore, in vitro

  8. Metabolic flux ratio analysis and cell staining suggest the existence of C4 photosynthesis in Phaeodactylum tricornutum.

    PubMed

    Huang, A; Liu, L; Zhao, P; Yang, C; Wang, G C

    2016-03-01

    Mechanisms for carbon fixation via photosynthesis in the diatom Phaeodactylum tricornutum Bohlin were studied recently but there remains a long-standing debate concerning the occurrence of C4 photosynthesis in this species. A thorough investigation of carbon metabolism and the evidence for C4 photosynthesis based on organelle partitioning was needed. In this study, we identified the flux ratios between C3 and C4 compounds in P. tricornutum using (13)C-labelling metabolic flux ratio analysis, and stained cells with various cell-permeant fluorescent probes to investigate the likely organelle partitioning required for single-cell C4 photosynthesis. Metabolic flux ratio analysis indicated the C3/C4 exchange ratios were high. Cell staining indicated organelle partitioning required for single-cell C4 photosynthesis might exist in P. tricornutum. The results of (13)C-labelling metabolic flux ratio analysis and cell staining suggest single-cell C4 photosynthesis exists in P. tricornutum. This study provides insights into photosynthesis patterns of P. tricornutum and the evidence for C4 photosynthesis based on (13)C-labelling metabolic flux ratio analysis and organelle partitioning. © 2015 The Society for Applied Microbiology.

  9. Development of Computational Tools for Metabolic Model Curation, Flux Elucidation and Strain Design

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Maranas, Costas D

    An overarching goal of the Department of Energy mission is the efficient deployment and engineering of microbial and plant systems to enable biomass conversion in pursuit of high energy density liquid biofuels. This has spurred the pace at which new organisms are sequenced and annotated. This torrent of genomic information has opened the door to understanding metabolism in not just skeletal pathways and a handful of microorganisms but for truly genome-scale reconstructions derived for hundreds of microbes and plants. Understanding and redirecting metabolism is crucial because metabolic fluxes are unique descriptors of cellular physiology that directly assess the current cellularmore » state and quantify the effect of genetic engineering interventions. At the same time, however, trying to keep pace with the rate of genomic data generation has ushered in a number of modeling and computational challenges related to (i) the automated assembly, testing and correction of genome-scale metabolic models, (ii) metabolic flux elucidation using labeled isotopes, and (iii) comprehensive identification of engineering interventions leading to the desired metabolism redirection.« less

  10. Metabolic flux and nodes control analysis of brewer's yeasts under different fermentation temperature during beer brewing.

    PubMed

    Yu, Zhimin; Zhao, Haifeng; Zhao, Mouming; Lei, Hongjie; Li, Huiping

    2012-12-01

    The aim of this work was to further investigate the glycolysis performance of lager and ale brewer's yeasts under different fermentation temperature using a combined analysis of metabolic flux, glycolytic enzyme activities, and flux control. The results indicated that the fluxes through glycolytic pathway decreased with the change of the fermentation temperature from 15 °C to 10 °C, which resulted in the prolonged fermentation times. The maximum activities (V (max)) of hexokinase (HK), phosphofructokinase (PFK), and pyruvate kinase (PK) at key nodes of glycolytic pathway decreased with decreasing fermentation temperature, which was estimated to have different control extent (22-84 %) on the glycolytic fluxes in exponential or flocculent phase. Moreover, the decrease of V (max) of PFK or PK displayed the crucial role in down-regulation of flux in flocculent phase. In addition, the metabolic state of ale strain was more sensitive to the variation of temperature than that of lager strain. The results of the metabolic flux and nodes control analysis in brewer's yeasts under different fermentation temperature may provide an alternative approach to regulate glycolytic flux by changing V (max) and improve the production efficiency and beer quality.

  11. Quantitative method for measuring heat flux emitted from a cryogenic object

    DOEpatents

    Duncan, Robert V.

    1993-01-01

    The present invention is a quantitative method for measuring the total heat flux, and of deriving the total power dissipation, of a heat-fluxing object which includes the steps of placing an electrical noise-emitting heat-fluxing object in a liquid helium bath and measuring the superfluid transition temperature of the bath. The temperature of the liquid helium bath is thereafter reduced until some measurable parameter, such as the electrical noise, exhibited by the heat-fluxing object or a temperature-dependent resistive thin film in intimate contact with the heat-fluxing object, becomes greatly reduced. The temperature of the liquid helum bath is measured at this point. The difference between the superfluid transition temperature of the liquid helium bath surrounding the heat-fluxing object, and the temperature of the liquid helium bath when the electrical noise emitted by the heat-fluxing object becomes greatly reduced, is determined. The total heat flux from the heat-fluxing object is determined as a function of this difference between these temperatures. In certain applications, the technique can be used to optimize thermal design parameters of cryogenic electronics, for example, Josephson junction and infra-red sensing devices.

  12. Quantitative method for measuring heat flux emitted from a cryogenic object

    DOEpatents

    Duncan, R.V.

    1993-03-16

    The present invention is a quantitative method for measuring the total heat flux, and of deriving the total power dissipation, of a heat-fluxing object which includes the steps of placing an electrical noise-emitting heat-fluxing object in a liquid helium bath and measuring the superfluid transition temperature of the bath. The temperature of the liquid helium bath is thereafter reduced until some measurable parameter, such as the electrical noise, exhibited by the heat-fluxing object or a temperature-dependent resistive thin film in intimate contact with the heat-fluxing object, becomes greatly reduced. The temperature of the liquid helum bath is measured at this point. The difference between the superfluid transition temperature of the liquid helium bath surrounding the heat-fluxing object, and the temperature of the liquid helium bath when the electrical noise emitted by the heat-fluxing object becomes greatly reduced, is determined. The total heat flux from the heat-fluxing object is determined as a function of this difference between these temperatures. In certain applications, the technique can be used to optimize thermal design parameters of cryogenic electronics, for example, Josephson junction and infrared sensing devices.

  13. Isotopically nonstationary metabolic flux analysis (INST-MFA) of photosynthesis and photorespiration in plants

    USDA-ARS?s Scientific Manuscript database

    Photorespiration is a central component of photosynthesis; however to better understand its role it should be viewed in the context of an integrated metabolic network rather than a series of individual reactions that operate independently. Isotopically nonstationary 13C metabolic flux analysis (INST...

  14. Glucose metabolic flux distribution of Lactobacillus amylophilus during lactic acid production using kitchen waste saccharified solution.

    PubMed

    Liu, Jianguo; Wang, Qunhui; Zou, Hui; Liu, Yingying; Wang, Juan; Gan, Kemin; Xiang, Juan

    2013-11-01

    The (13) C isotope tracer method was used to investigate the glucose metabolic flux distribution and regulation in Lactobacillus amylophilus to improve lactic acid production using kitchen waste saccharified solution (KWSS). The results demonstrate that L. amylophilus is a homofermentative bacterium. In synthetic medium, 60.6% of the glucose entered the Embden-Meyerhof-Parnas (EMP) to produce lactic acid, whereas 36.4% of the glucose entered the pentose phosphate metabolic pathway (HMP). After solid-liquid separation of the KWSS, the addition of Fe(3+) during fermentation enhanced the NADPH production efficiency and increased the NADH content. The flux to the EMP was also effectively increased. Compared with the control (60.6% flux to EMP without Fe(3+) addition), the flux to the EMP with the addition of Fe(3+) (74.3%) increased by 23.8%. In the subsequent pyruvate metabolism, Fe(3+) also increased lactate dehydrogenase activity, and inhibited alcohol dehydrogenase, pyruvate dehydrogenase and pyruvate carboxylase, thereby increasing the lactic acid production to 9.03 g l(-1) , an increase of 8% compared with the control. All other organic acid by-products were lower than in the control. However, the addition of Zn(2+) showed an opposite effect, decreasing the lactic acid production. In conclusion it is feasible and effective means using GC-MS, isotope experiment and MATLAB software to integrate research the metabolic flux distribution of lactic acid bacteria, and the results provide the theoretical foundation for similar metabolic flux distribution. © 2013 The Authors. Microbial Biotechnology published by John Wiley & Sons Ltd and Society for Applied Microbiology.

  15. Detection of Metabolic Fluxes of O and H Atoms into Intracellular Water in Mammalian Cells

    PubMed Central

    Kreuzer, Helen W.; Quaroni, Luca; Podlesak, David W.; Zlateva, Theodora; Bollinger, Nikki; McAllister, Aaron; Lott, Michael J.; Hegg, Eric L.

    2012-01-01

    Metabolic processes result in the release and exchange of H and O atoms from organic material as well as some inorganic salts and gases. These fluxes of H and O atoms into intracellular water result in an isotopic gradient that can be measured experimentally. Using isotope ratio mass spectroscopy, we revealed that slightly over 50% of the H and O atoms in the intracellular water of exponentially-growing cultured Rat-1 fibroblasts were isotopically distinct from growth medium water. We then employed infrared spectromicroscopy to detect in real time the flux of H atoms in these same cells. Importantly, both of these techniques indicate that the H and O fluxes are dependent on metabolic processes; cells that are in lag phase or are quiescent exhibit a much smaller flux. In addition, water extracted from the muscle tissue of rats contained a population of H and O atoms that were isotopically distinct from body water, consistent with the results obtained using the cultured Rat-1 fibroblasts. Together these data demonstrate that metabolic processes produce fluxes of H and O atoms into intracellular water, and that these fluxes can be detected and measured in both cultured mammalian cells and in mammalian tissue. PMID:22848359

  16. Multi-objective experimental design for (13)C-based metabolic flux analysis.

    PubMed

    Bouvin, Jeroen; Cajot, Simon; D'Huys, Pieter-Jan; Ampofo-Asiama, Jerry; Anné, Jozef; Van Impe, Jan; Geeraerd, Annemie; Bernaerts, Kristel

    2015-10-01

    (13)C-based metabolic flux analysis is an excellent technique to resolve fluxes in the central carbon metabolism but costs can be significant when using specialized tracers. This work presents a framework for cost-effective design of (13)C-tracer experiments, illustrated on two different networks. Linear and non-linear optimal input mixtures are computed for networks for Streptomyces lividans and a carcinoma cell line. If only glucose tracers are considered as labeled substrate for a carcinoma cell line or S. lividans, the best parameter estimation accuracy is obtained by mixtures containing high amounts of 1,2-(13)C2 glucose combined with uniformly labeled glucose. Experimental designs are evaluated based on a linear (D-criterion) and non-linear approach (S-criterion). Both approaches generate almost the same input mixture, however, the linear approach is favored due to its low computational effort. The high amount of 1,2-(13)C2 glucose in the optimal designs coincides with a high experimental cost, which is further enhanced when labeling is introduced in glutamine and aspartate tracers. Multi-objective optimization gives the possibility to assess experimental quality and cost at the same time and can reveal excellent compromise experiments. For example, the combination of 100% 1,2-(13)C2 glucose with 100% position one labeled glutamine and the combination of 100% 1,2-(13)C2 glucose with 100% uniformly labeled glutamine perform equally well for the carcinoma cell line, but the first mixture offers a decrease in cost of $ 120 per ml-scale cell culture experiment. We demonstrated the validity of a multi-objective linear approach to perform optimal experimental designs for the non-linear problem of (13)C-metabolic flux analysis. Tools and a workflow are provided to perform multi-objective design. The effortless calculation of the D-criterion can be exploited to perform high-throughput screening of possible (13)C-tracers, while the illustrated benefit of multi

  17. Towards High Resolution Analysis of Metabolic Flux in Cells and Tissues

    PubMed Central

    Sims, James K; Manteiga, Sara; Lee, Kyongbum

    2013-01-01

    Metabolism extracts chemical energy from nutrients, uses this energy to form building blocks for biosynthesis, and interconverts between various small molecules that coordinate the activities of cellular pathways. The metabolic state of a cell is increasingly recognized to determine the phenotype of not only metabolically active cell types such as liver, muscle, and adipose, but also other specialized cell types such as neurons and immune cells. This review focuses on methods to quantify intracellular reaction flux as a measure of cellular metabolic activity, with emphasis on studies involving cells of mammalian tissue. Two key areas are highlighted for future development, single cell metabolomics and noninvasive imaging, which could enable spatiotemporally resolved analysis and thereby overcome issues of heterogeneity, a distinctive feature of tissue metabolism. PMID:23906926

  18. Constrained Allocation Flux Balance Analysis

    PubMed Central

    Mori, Matteo; Hwa, Terence; Martin, Olivier C.

    2016-01-01

    New experimental results on bacterial growth inspire a novel top-down approach to study cell metabolism, combining mass balance and proteomic constraints to extend and complement Flux Balance Analysis. We introduce here Constrained Allocation Flux Balance Analysis, CAFBA, in which the biosynthetic costs associated to growth are accounted for in an effective way through a single additional genome-wide constraint. Its roots lie in the experimentally observed pattern of proteome allocation for metabolic functions, allowing to bridge regulation and metabolism in a transparent way under the principle of growth-rate maximization. We provide a simple method to solve CAFBA efficiently and propose an “ensemble averaging” procedure to account for unknown protein costs. Applying this approach to modeling E. coli metabolism, we find that, as the growth rate increases, CAFBA solutions cross over from respiratory, growth-yield maximizing states (preferred at slow growth) to fermentative states with carbon overflow (preferred at fast growth). In addition, CAFBA allows for quantitatively accurate predictions on the rate of acetate excretion and growth yield based on only 3 parameters determined by empirical growth laws. PMID:27355325

  19. Quantifying plant phenotypes with isotopic labeling and metabolic flux analysis

    USDA-ARS?s Scientific Manuscript database

    Analyses of metabolic flux using stable isotopes in plants have traditionally been restricted to tissues with presumed homogeneous cell populations such as developing seeds, cell suspensions, or cultured roots and root tips. It is now possible to describe these and other more complex tissues such a...

  20. Systems analysis of iron metabolism: the network of iron pools and fluxes

    PubMed Central

    2010-01-01

    Background Every cell of the mammalian organism needs iron as trace element in numerous oxido-reductive processes as well as for transport and storage of oxygen. The very versatility of ionic iron makes it a toxic entity which can catalyze the production of radicals that damage vital membranous and macromolecular assemblies in the cell. The mammalian organism maintains therefore a complex regulatory network of iron uptake, excretion and intra-body distribution. Intracellular regulation in different cell types is intertwined with a global hormonal signalling structure. Iron deficiency as well as excess of iron are frequent and serious human disorders. They can affect every cell, but also the organism as a whole. Results Here, we present a kinematic model of the dynamic system of iron pools and fluxes. It is based on ferrokinetic data and chemical measurements in C57BL6 wild-type mice maintained on iron-deficient, iron-adequate, or iron-loaded diet. The tracer iron levels in major tissues and organs (16 compartment) were followed for 28 days. The evaluation resulted in a whole-body model of fractional clearance rates. The analysis permits calculation of absolute flux rates in the steady-state, of iron distribution into different organs, of tracer-accessible pool sizes and of residence times of iron in the different compartments in response to three states of iron-repletion induced by the dietary regime. Conclusions This mathematical model presents a comprehensive physiological picture of mice under three different diets with varying iron contents. The quantitative results reflect systemic properties of iron metabolism: dynamic closedness, hierarchy of time scales, switch-over response and dynamics of iron storage in parenchymal organs. Therefore, we could assess which parameters will change under dietary perturbations and study in quantitative terms when those changes take place. PMID:20704761

  1. A scientific workflow framework for (13)C metabolic flux analysis.

    PubMed

    Dalman, Tolga; Wiechert, Wolfgang; Nöh, Katharina

    2016-08-20

    Metabolic flux analysis (MFA) with (13)C labeling data is a high-precision technique to quantify intracellular reaction rates (fluxes). One of the major challenges of (13)C MFA is the interactivity of the computational workflow according to which the fluxes are determined from the input data (metabolic network model, labeling data, and physiological rates). Here, the workflow assembly is inevitably determined by the scientist who has to consider interacting biological, experimental, and computational aspects. Decision-making is context dependent and requires expertise, rendering an automated evaluation process hardly possible. Here, we present a scientific workflow framework (SWF) for creating, executing, and controlling on demand (13)C MFA workflows. (13)C MFA-specific tools and libraries, such as the high-performance simulation toolbox 13CFLUX2, are wrapped as web services and thereby integrated into a service-oriented architecture. Besides workflow steering, the SWF features transparent provenance collection and enables full flexibility for ad hoc scripting solutions. To handle compute-intensive tasks, cloud computing is supported. We demonstrate how the challenges posed by (13)C MFA workflows can be solved with our approach on the basis of two proof-of-concept use cases. Copyright © 2015 Elsevier B.V. All rights reserved.

  2. Investigate the Metabolic Reprogramming of Saccharomyces cerevisiae for Enhanced Resistance to Mixed Fermentation Inhibitors via 13C Metabolic Flux Analysis

    PubMed Central

    Guo, Weihua; Chen, Yingying; Wei, Na; Feng, Xueyang

    2016-01-01

    The fermentation inhibitors from the pretreatment of lignocellulosic materials, e.g., acetic acid and furfural, are notorious due to their negative effects on the cell growth and chemical production. However, the metabolic reprogramming of the cells under these stress conditions, especially metabolic response for resistance to mixed inhibitors, has not been systematically investigated and remains mysterious. Therefore, in this study, 13C metabolic flux analysis (13C-MFA), a powerful tool to elucidate the intracellular carbon flux distributions, has been applied to two Saccharomyces cerevisiae strains with different tolerances to the inhibitors under acetic acid, furfural, and mixed (i.e., acetic acid and furfural) stress conditions to unravel the key metabolic responses. By analyzing the intracellular carbon fluxes as well as the energy and cofactor utilization under different conditions, we uncovered varied metabolic responses to different inhibitors. Under acetate stress, ATP and NADH production was slightly impaired, while NADPH tended towards overproduction. Under furfural stress, ATP and cofactors (including both NADH and NADPH) tended to be overproduced. However, under dual-stress condition, production of ATP and cofactors was severely impaired due to synergistic stress caused by the simultaneous addition of two fermentation inhibitors. Such phenomenon indicated the pivotal role of the energy and cofactor utilization in resisting the mixed inhibitors of acetic acid and furfural. Based on the discoveries, valuable insights are provided to improve the tolerance of S. cerevisiae strain and further enhance lignocellulosic fermentation. PMID:27532329

  3. Metabolic flux analysis of the mixotrophic metabolisms in the green sulfur bacterium Chlorobaculum tepidum.

    PubMed

    Feng, Xueyang; Tang, Kuo-Hsiang; Blankenship, Robert E; Tang, Yinjie J

    2010-12-10

    The photosynthetic green sulfur bacterium Chlorobaculum tepidum assimilates CO(2) and organic carbon sources (acetate or pyruvate) during mixotrophic growth conditions through a unique carbon and energy metabolism. Using a (13)C-labeling approach, this study examined biosynthetic pathways and flux distributions in the central metabolism of C. tepidum. The isotopomer patterns of proteinogenic amino acids revealed an alternate pathway for isoleucine synthesis (via citramalate synthase, CimA, CT0612). A (13)C-assisted flux analysis indicated that carbons in biomass were mostly derived from CO(2) fixation via three key routes: the reductive tricarboxylic acid (RTCA) cycle, the pyruvate synthesis pathway via pyruvate:ferredoxin oxidoreductase, and the CO(2)-anaplerotic pathway via phosphoenolpyruvate carboxylase. During mixotrophic growth with acetate or pyruvate as carbon sources, acetyl-CoA was mainly produced from acetate (via acetyl-CoA synthetase) or citrate (via ATP citrate lyase). Pyruvate:ferredoxin oxidoreductase converted acetyl-CoA and CO(2) to pyruvate, and this growth-rate control reaction is driven by reduced ferredoxin generated during phototrophic growth. Most reactions in the RTCA cycle were reversible. The relative fluxes through the RTCA cycle were 80∼100 units for mixotrophic cultures grown on acetate and 200∼230 units for cultures grown on pyruvate. Under the same light conditions, the flux results suggested a trade-off between energy-demanding CO(2) fixation and biomass growth rate; C. tepidum fixed more CO(2) and had a higher biomass yield (Y(X/S), mole carbon in biomass/mole substrate) in pyruvate culture (Y(X/S) = 9.2) than in acetate culture (Y(X/S) = 6.4), but the biomass growth rate was slower in pyruvate culture than in acetate culture.

  4. Integrating tracer-based metabolomics data and metabolic fluxes in a linear fashion via Elementary Carbon Modes.

    PubMed

    Pey, Jon; Rubio, Angel; Theodoropoulos, Constantinos; Cascante, Marta; Planes, Francisco J

    2012-07-01

    Constraints-based modeling is an emergent area in Systems Biology that includes an increasing set of methods for the analysis of metabolic networks. In order to refine its predictions, the development of novel methods integrating high-throughput experimental data is currently a key challenge in the field. In this paper, we present a novel set of constraints that integrate tracer-based metabolomics data from Isotope Labeling Experiments and metabolic fluxes in a linear fashion. These constraints are based on Elementary Carbon Modes (ECMs), a recently developed concept that generalizes Elementary Flux Modes at the carbon level. To illustrate the effect of our ECMs-based constraints, a Flux Variability Analysis approach was applied to a previously published metabolic network involving the main pathways in the metabolism of glucose. The addition of our ECMs-based constraints substantially reduced the under-determination resulting from a standard application of Flux Variability Analysis, which shows a clear progress over the state of the art. In addition, our approach is adjusted to deal with combinatorial explosion of ECMs in genome-scale metabolic networks. This extension was applied to infer the maximum biosynthetic capacity of non-essential amino acids in human metabolism. Finally, as linearity is the hallmark of our approach, its importance is discussed at a methodological, computational and theoretical level and illustrated with a practical application in the field of Isotope Labeling Experiments. Copyright © 2012 Elsevier Inc. All rights reserved.

  5. Towards high resolution analysis of metabolic flux in cells and tissues.

    PubMed

    Sims, James K; Manteiga, Sara; Lee, Kyongbum

    2013-10-01

    Metabolism extracts chemical energy from nutrients, uses this energy to form building blocks for biosynthesis, and interconverts between various small molecules that coordinate the activities of cellular pathways. The metabolic state of a cell is increasingly recognized to determine the phenotype of not only metabolically active cell types such as liver, muscle, and adipose, but also other specialized cell types such as neurons and immune cells. This review focuses on methods to quantify intracellular reaction flux as a measure of cellular metabolic activity, with emphasis on studies involving cells of mammalian tissue. Two key areas are highlighted for future development, single cell metabolomics and noninvasive imaging, which could enable spatiotemporally resolved analysis and thereby overcome issues of heterogeneity, a distinctive feature of tissue metabolism. Copyright © 2013 Elsevier Ltd. All rights reserved.

  6. The Protein Cost of Metabolic Fluxes: Prediction from Enzymatic Rate Laws and Cost Minimization.

    PubMed

    Noor, Elad; Flamholz, Avi; Bar-Even, Arren; Davidi, Dan; Milo, Ron; Liebermeister, Wolfram

    2016-11-01

    Bacterial growth depends crucially on metabolic fluxes, which are limited by the cell's capacity to maintain metabolic enzymes. The necessary enzyme amount per unit flux is a major determinant of metabolic strategies both in evolution and bioengineering. It depends on enzyme parameters (such as kcat and KM constants), but also on metabolite concentrations. Moreover, similar amounts of different enzymes might incur different costs for the cell, depending on enzyme-specific properties such as protein size and half-life. Here, we developed enzyme cost minimization (ECM), a scalable method for computing enzyme amounts that support a given metabolic flux at a minimal protein cost. The complex interplay of enzyme and metabolite concentrations, e.g. through thermodynamic driving forces and enzyme saturation, would make it hard to solve this optimization problem directly. By treating enzyme cost as a function of metabolite levels, we formulated ECM as a numerically tractable, convex optimization problem. Its tiered approach allows for building models at different levels of detail, depending on the amount of available data. Validating our method with measured metabolite and protein levels in E. coli central metabolism, we found typical prediction fold errors of 4.1 and 2.6, respectively, for the two kinds of data. This result from the cost-optimized metabolic state is significantly better than randomly sampled metabolite profiles, supporting the hypothesis that enzyme cost is important for the fitness of E. coli. ECM can be used to predict enzyme levels and protein cost in natural and engineered pathways, and could be a valuable computational tool to assist metabolic engineering projects. Furthermore, it establishes a direct connection between protein cost and thermodynamics, and provides a physically plausible and computationally tractable way to include enzyme kinetics into constraint-based metabolic models, where kinetics have usually been ignored or oversimplified.

  7. The Protein Cost of Metabolic Fluxes: Prediction from Enzymatic Rate Laws and Cost Minimization

    PubMed Central

    Noor, Elad; Flamholz, Avi; Bar-Even, Arren; Davidi, Dan; Milo, Ron; Liebermeister, Wolfram

    2016-01-01

    Bacterial growth depends crucially on metabolic fluxes, which are limited by the cell’s capacity to maintain metabolic enzymes. The necessary enzyme amount per unit flux is a major determinant of metabolic strategies both in evolution and bioengineering. It depends on enzyme parameters (such as kcat and KM constants), but also on metabolite concentrations. Moreover, similar amounts of different enzymes might incur different costs for the cell, depending on enzyme-specific properties such as protein size and half-life. Here, we developed enzyme cost minimization (ECM), a scalable method for computing enzyme amounts that support a given metabolic flux at a minimal protein cost. The complex interplay of enzyme and metabolite concentrations, e.g. through thermodynamic driving forces and enzyme saturation, would make it hard to solve this optimization problem directly. By treating enzyme cost as a function of metabolite levels, we formulated ECM as a numerically tractable, convex optimization problem. Its tiered approach allows for building models at different levels of detail, depending on the amount of available data. Validating our method with measured metabolite and protein levels in E. coli central metabolism, we found typical prediction fold errors of 4.1 and 2.6, respectively, for the two kinds of data. This result from the cost-optimized metabolic state is significantly better than randomly sampled metabolite profiles, supporting the hypothesis that enzyme cost is important for the fitness of E. coli. ECM can be used to predict enzyme levels and protein cost in natural and engineered pathways, and could be a valuable computational tool to assist metabolic engineering projects. Furthermore, it establishes a direct connection between protein cost and thermodynamics, and provides a physically plausible and computationally tractable way to include enzyme kinetics into constraint-based metabolic models, where kinetics have usually been ignored or oversimplified

  8. Genome-Based Metabolic Mapping and 13C Flux Analysis Reveal Systematic Properties of an Oleaginous Microalga Chlorella protothecoides

    DOE PAGES

    Wu, Chao; Xiong, Wei; Dai, Junbiao; ...

    2014-12-15

    We report that integrated and genome-based flux balance analysis, metabolomics, and 13C-label profiling of phototrophic and heterotrophic metabolism in Chlorella protothecoides, an oleaginous green alga for biofuel. The green alga Chlorella protothecoides, capable of autotrophic and heterotrophic growth with rapid lipid synthesis, is a promising candidate for biofuel production. Based on the newly available genome knowledge of the alga, we reconstructed the compartmentalized metabolic network consisting of 272 metabolic reactions, 270 enzymes, and 461 encoding genes and simulated the growth in different cultivation conditions with flux balance analysis. Phenotype-phase plane analysis shows conditions achieving theoretical maximum of the biomass andmore » corresponding fatty acid-producing rate for phototrophic cells (the ratio of photon uptake rate to CO 2 uptake rate equals 8.4) and heterotrophic ones (the glucose uptake rate to O 2 consumption rate reaches 2.4), respectively. Isotope-assisted liquid chromatography-mass spectrometry/mass spectrometry reveals higher metabolite concentrations in the glycolytic pathway and the tricarboxylic acid cycle in heterotrophic cells compared with autotrophic cells. We also observed enhanced levels of ATP, nicotinamide adenine dinucleotide (phosphate), reduced, acetyl-Coenzyme A, and malonyl-Coenzyme A in heterotrophic cells consistently, consistent with a strong activity of lipid synthesis. To profile the flux map in experimental conditions, we applied nonstationary 13C metabolic flux analysis as a complementing strategy to flux balance analysis. We found that the result reveals negligible photorespiratory fluxes and a metabolically low active tricarboxylic acid cycle in phototrophic C. protothecoides. In comparison, high throughput of amphibolic reactions and the tricarboxylic acid cycle with no glyoxylate shunt activities were measured for heterotrophic cells. Lastly, taken together, the metabolic network modeling

  9. Optimal tracers for parallel labeling experiments and 13C metabolic flux analysis: A new precision and synergy scoring system.

    PubMed

    Crown, Scott B; Long, Christopher P; Antoniewicz, Maciek R

    2016-11-01

    13 C-Metabolic flux analysis ( 13 C-MFA) is a widely used approach in metabolic engineering for quantifying intracellular metabolic fluxes. The precision of fluxes determined by 13 C-MFA depends largely on the choice of isotopic tracers and the specific set of labeling measurements. A recent advance in the field is the use of parallel labeling experiments for improved flux precision and accuracy. However, as of today, no systemic methods exist for identifying optimal tracers for parallel labeling experiments. In this contribution, we have addressed this problem by introducing a new scoring system and evaluating thousands of different isotopic tracer schemes. Based on this extensive analysis we have identified optimal tracers for 13 C-MFA. The best single tracers were doubly 13 C-labeled glucose tracers, including [1,6- 13 C]glucose, [5,6- 13 C]glucose and [1,2- 13 C]glucose, which consistently produced the highest flux precision independent of the metabolic flux map (here, 100 random flux maps were evaluated). Moreover, we demonstrate that pure glucose tracers perform better overall than mixtures of glucose tracers. For parallel labeling experiments the optimal isotopic tracers were [1,6- 13 C]glucose and [1,2- 13 C]glucose. Combined analysis of [1,6- 13 C]glucose and [1,2- 13 C]glucose labeling data improved the flux precision score by nearly 20-fold compared to widely use tracer mixture 80% [1- 13 C]glucose +20% [U- 13 C]glucose. Copyright © 2016 International Metabolic Engineering Society. Published by Elsevier Inc. All rights reserved.

  10. Dynamic regulation of metabolic flux in engineered bacteria using a pathway-independent quorum-sensing circuit

    PubMed Central

    Gupta, Apoorv; Brockman Reizman, Irene M.; Reisch, Christopher R.; Prather, Kristala L. J.

    2017-01-01

    Metabolic engineering of microorganisms to produce desirable products on an industrial scale can result in unbalanced cellular metabolic networks that reduce productivity and yield. Metabolic fluxes can be rebalanced using dynamic pathway regulation, but few broadly applicable tools are available to achieve this. We present a pathway-independent genetic control module that can be used to dynamically regulate the expression of target genes. We applied our module to identify the optimal point to redirect glycolytic flux into heterologous engineered pathways in Escherichia coli, resulting in 5.5-fold increased titres of myo-inositol and titers of glucaric acid that improved from unmeasurable quantities to >0.8 g/L. Scaled-up production in benchtop bioreactors resulted in almost 10-fold and 5-fold increases in titers of myo-inositol and glucaric acid. We also used our module to control flux into aromatic amino acid biosynthesis to increase titers of shikimate in E. coli from unmeasurable quantities to >100 mg/L. PMID:28191902

  11. Quantitative flux analysis reveals folate-dependent NADPH production

    NASA Astrophysics Data System (ADS)

    Fan, Jing; Ye, Jiangbin; Kamphorst, Jurre J.; Shlomi, Tomer; Thompson, Craig B.; Rabinowitz, Joshua D.

    2014-06-01

    ATP is the dominant energy source in animals for mechanical and electrical work (for example, muscle contraction or neuronal firing). For chemical work, there is an equally important role for NADPH, which powers redox defence and reductive biosynthesis. The most direct route to produce NADPH from glucose is the oxidative pentose phosphate pathway, with malic enzyme sometimes also important. Although the relative contribution of glycolysis and oxidative phosphorylation to ATP production has been extensively analysed, similar analysis of NADPH metabolism has been lacking. Here we demonstrate the ability to directly track, by liquid chromatography-mass spectrometry, the passage of deuterium from labelled substrates into NADPH, and combine this approach with carbon labelling and mathematical modelling to measure NADPH fluxes. In proliferating cells, the largest contributor to cytosolic NADPH is the oxidative pentose phosphate pathway. Surprisingly, a nearly comparable contribution comes from serine-driven one-carbon metabolism, in which oxidation of methylene tetrahydrofolate to 10-formyl-tetrahydrofolate is coupled to reduction of NADP+ to NADPH. Moreover, tracing of mitochondrial one-carbon metabolism revealed complete oxidation of 10-formyl-tetrahydrofolate to make NADPH. As folate metabolism has not previously been considered an NADPH producer, confirmation of its functional significance was undertaken through knockdown of methylenetetrahydrofolate dehydrogenase (MTHFD) genes. Depletion of either the cytosolic or mitochondrial MTHFD isozyme resulted in decreased cellular NADPH/NADP+ and reduced/oxidized glutathione ratios (GSH/GSSG) and increased cell sensitivity to oxidative stress. Thus, although the importance of folate metabolism for proliferating cells has been long recognized and attributed to its function of producing one-carbon units for nucleic acid synthesis, another crucial function of this pathway is generating reducing power.

  12. Metabolic network reconstruction of Chlamydomonas offers insight into light-driven algal metabolism

    PubMed Central

    Chang, Roger L; Ghamsari, Lila; Manichaikul, Ani; Hom, Erik F Y; Balaji, Santhanam; Fu, Weiqi; Shen, Yun; Hao, Tong; Palsson, Bernhard Ø; Salehi-Ashtiani, Kourosh; Papin, Jason A

    2011-01-01

    Metabolic network reconstruction encompasses existing knowledge about an organism's metabolism and genome annotation, providing a platform for omics data analysis and phenotype prediction. The model alga Chlamydomonas reinhardtii is employed to study diverse biological processes from photosynthesis to phototaxis. Recent heightened interest in this species results from an international movement to develop algal biofuels. Integrating biological and optical data, we reconstructed a genome-scale metabolic network for this alga and devised a novel light-modeling approach that enables quantitative growth prediction for a given light source, resolving wavelength and photon flux. We experimentally verified transcripts accounted for in the network and physiologically validated model function through simulation and generation of new experimental growth data, providing high confidence in network contents and predictive applications. The network offers insight into algal metabolism and potential for genetic engineering and efficient light source design, a pioneering resource for studying light-driven metabolism and quantitative systems biology. PMID:21811229

  13. ¹³C-based metabolic flux analysis of Saccharomyces cerevisiae with a reduced Crabtree effect.

    PubMed

    Kajihata, Shuichi; Matsuda, Fumio; Yoshimi, Mika; Hayakawa, Kenshi; Furusawa, Chikara; Kanda, Akihisa; Shimizu, Hiroshi

    2015-08-01

    Saccharomyces cerevisiae shows a Crabtree effect that produces ethanol in a high glucose concentration even under fully aerobic condition. For efficient production of cake yeast or compressed yeast for baking, ethanol by-production is not desired since glucose limited chemostat or fed-batch cultivations are performed to suppress the Crabtree effect. In this study, the (13)C-based metabolic flux analysis ((13)C-MFA) was performed for the S288C derived S. cerevisiae strain to characterize a metabolic state under the reduced Crabtree effect. S. cerevisiae cells were cultured at a low dilution rate (0.1 h(-1)) under the glucose-limited chemostat condition. The estimated metabolic flux distribution showed that the acetyl-CoA in mitochondria was mainly produced from pyruvate by pyruvate dehydrogenase (PDH) reaction and that the level of the metabolic flux through the pentose phosphate pathway was much higher than that of the Embden-Meyerhof-Parnas pathway, which contributes to high biomass yield at low dilution rate by supplying NADPH required for cell growth. Copyright © 2015 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

  14. Improvements in metabolic flux analysis using carbon bond labeling experiments: bondomer balancing and Boolean function mapping.

    PubMed

    Sriram, Ganesh; Shanks, Jacqueline V

    2004-04-01

    The biosynthetically directed fractional (13)C labeling method for metabolic flux evaluation relies on performing a 2-D [(13)C, (1)H] NMR experiment on extracts from organisms cultured on a uniformly labeled carbon substrate. This article focuses on improvements in the interpretation of data obtained from such an experiment by employing the concept of bondomers. Bondomers take into account the natural abundance of (13)C; therefore many bondomers in a real network are zero, and can be precluded a priori--thus resulting in fewer balances. Using this method, we obtained a set of linear equations which can be solved to obtain analytical formulas for NMR-measurable quantities in terms of fluxes in glycolysis and the pentose phosphate pathways. For a specific case of this network with four degrees of freedom, a priori identifiability of the fluxes was shown possible for any set of fluxes. For a more general case with five degrees of freedom, the fluxes were shown identifiable for a representative set of fluxes. Minimal sets of measurements which best identify the fluxes are listed. Furthermore, we have delineated Boolean function mapping, a new method to iteratively simulate bondomer abundances or efficiently convert carbon skeleton rearrangement information to mapping matrices. The efficiency of this method is expected to be valuable while analyzing metabolic networks which are not completely known (such as in plant metabolism) or while implementing iterative bondomer balancing methods.

  15. Skeletal scintigraphy and quantitative tracer studies in metabolic bone disease

    NASA Astrophysics Data System (ADS)

    Fogelman, Ignac

    Bone scan imaging with the current bone seeking radiopharmaceuticals, the technetium-99m labelled diphosphonates, has dramatically improved our ability to evaluate skeletal pathology. In this thesis, chapter 1 presents a review of the history of bone scanning, summarises present concepts as to the mechanism of uptake of bone seeking agents and briefly illustrates the role of bone scanning in clinical practice. In chapter 2 the applications of bone scan imaging and quantitative tracer techniques derived from the bone scan in the detection of metabolic bone disease are discussed. Since skeletal uptake of Tc-99m diphosphonate depends upon skeletal metabolism one might expect that the bone scan would be of considerable value in the assessment of metabolic bone disease. However in these disorders the whole skeleton is often diffusely involved by the metabolic process and simple visual inspection of the scan image may not reveal the uniformly increased uptake of tracer. Certain patterns of bone scan abnormality have, however, been reported in patients with primary hyperparathyroidism and renal osteo-dystrophy; the present studies extend these observations and introduce the concept of "metabolic features" which are often recognisable in conditions with generalised increased bone turnover. As an aid to systematic recognition of these features on a given bone scan image a semi-quantitative scoring system, the metabolic index, was introduced. The metabolic index allowed differentiation between various groups of patients with metabolic disorders and a control population. In addition, in a bone scan study of patients with acromegaly, it was found that the metabolic index correlated well with disease activity as measured by serum growth hormone levels. The metabolic index was, however, found to be a relatively insensitive means of identifying disease in individual patients. Patients with increased bone turnover will have an absolute increase in skeletal uptake of tracer. As a

  16. Characterizing the optimal flux space of genome-scale metabolic reconstructions through modified latin-hypercube sampling.

    PubMed

    Chaudhary, Neha; Tøndel, Kristin; Bhatnagar, Rakesh; dos Santos, Vítor A P Martins; Puchałka, Jacek

    2016-03-01

    Genome-Scale Metabolic Reconstructions (GSMRs), along with optimization-based methods, predominantly Flux Balance Analysis (FBA) and its derivatives, are widely applied for assessing and predicting the behavior of metabolic networks upon perturbation, thereby enabling identification of potential novel drug targets and biotechnologically relevant pathways. The abundance of alternate flux profiles has led to the evolution of methods to explore the complete solution space aiming to increase the accuracy of predictions. Herein we present a novel, generic algorithm to characterize the entire flux space of GSMR upon application of FBA, leading to the optimal value of the objective (the optimal flux space). Our method employs Modified Latin-Hypercube Sampling (LHS) to effectively border the optimal space, followed by Principal Component Analysis (PCA) to identify and explain the major sources of variability within it. The approach was validated with the elementary mode analysis of a smaller network of Saccharomyces cerevisiae and applied to the GSMR of Pseudomonas aeruginosa PAO1 (iMO1086). It is shown to surpass the commonly used Monte Carlo Sampling (MCS) in providing a more uniform coverage for a much larger network in less number of samples. Results show that although many fluxes are identified as variable upon fixing the objective value, majority of the variability can be reduced to several main patterns arising from a few alternative pathways. In iMO1086, initial variability of 211 reactions could almost entirely be explained by 7 alternative pathway groups. These findings imply that the possibilities to reroute greater portions of flux may be limited within metabolic networks of bacteria. Furthermore, the optimal flux space is subject to change with environmental conditions. Our method may be a useful device to validate the predictions made by FBA-based tools, by describing the optimal flux space associated with these predictions, thus to improve them.

  17. A Quantitative Study of Oxygen as a Metabolic Regulator

    NASA Technical Reports Server (NTRS)

    Radhakrishnan, Krishnan; LaManna, Joseph C.; Cabera, Marco E.

    2000-01-01

    An acute reduction in oxygen delivery to a tissue is associated with metabolic changes aimed at maintaining ATP homeostasis. However, given the complexity of the human bio-energetic system, it is difficult to determine quantitatively how cellular metabolic processes interact to maintain ATP homeostasis during stress (e.g., hypoxia, ischemia, and exercise). In particular, we are interested in determining mechanisms relating cellular oxygen concentration to observed metabolic responses at the cellular, tissue, organ, and whole body levels and in quantifying how changes in tissue oxygen availability affect the pathways of ATP synthesis and the metabolites that control these pathways. In this study; we extend a previously developed mathematical model of human bioenergetics, to provide a physicochemical framework that permits quantitative understanding of oxygen as a metabolic regulator. Specifically, the enhancement - sensitivity analysis - permits studying the effects of variations in tissue oxygenation and parameters controlling cellular respiration on glycolysis, lactate production, and pyruvate oxidation. The analysis can distinguish between parameters that must be determined accurately and those that require less precision, based on their effects on model predictions. This capability may prove to be important in optimizing experimental design, thus reducing use of animals.

  18. Integrated analysis of gene expression and metabolic fluxes in PHA-producing Pseudomonas putida grown on glycerol.

    PubMed

    Beckers, Veronique; Poblete-Castro, Ignacio; Tomasch, Jürgen; Wittmann, Christoph

    2016-05-03

    Given its high surplus and low cost, glycerol has emerged as interesting carbon substrate for the synthesis of value-added chemicals. The soil bacterium Pseudomonas putida KT2440 can use glycerol to synthesize medium-chain-length poly(3-hydroxyalkanoates) (mcl-PHA), a class of biopolymers of industrial interest. Here, glycerol metabolism in P. putida KT2440 was studied on the level of gene expression (transcriptome) and metabolic fluxes (fluxome), using precisely adjusted chemostat cultures, growth kinetics and stoichiometry, to gain a systematic understanding of the underlying metabolic and regulatory network. Glycerol-grown P. putida KT2440 has a maintenance energy requirement [0.039 (mmolglycerol (gCDW h)(-1))] that is about sixteen times lower than that of other bacteria, such as Escherichia coli, which provides a great advantage to use this substrate commercially. The shift from carbon (glycerol) to nitrogen (ammonium) limitation drives the modulation of specific genes involved in glycerol metabolism, transport electron chain, sensors to assess the energy level of the cell, and PHA synthesis, as well as changes in flux distribution to increase the precursor availability for PHA synthesis (Entner-Doudoroff pathway and pyruvate metabolism) and to reduce respiration (glyoxylate shunt). Under PHA-producing conditions (N-limitation), a higher PHA yield was achieved at low dilution rate (29.7 wt% of CDW) as compared to a high rate (12.8 wt% of CDW). By-product formation (succinate, malate) was specifically modulated under these regimes. On top of experimental data, elementary flux mode analysis revealed the metabolic potential of P. putida KT2440 to synthesize PHA and identified metabolic engineering targets towards improved production performance on glycerol. This study revealed the complex interplay of gene expression levels and metabolic fluxes under PHA- and non-PHA producing conditions using the attractive raw material glycerol as carbon substrate. This

  19. Advances in Quantitative Proteomics of Microbes and Microbial Communities

    NASA Astrophysics Data System (ADS)

    Waldbauer, J.; Zhang, L.; Rizzo, A. I.

    2015-12-01

    Quantitative measurements of gene expression are key to developing a mechanistic, predictive understanding of how microbial metabolism drives many biogeochemical fluxes and responds to environmental change. High-throughput RNA-sequencing can afford a wealth of information about transcript-level expression patterns, but it is becoming clear that expression dynamics are often very different at the protein level where biochemistry actually occurs. These divergent dynamics between levels of biological organization necessitate quantitative proteomic measurements to address many biogeochemical questions. The protein-level expression changes that underlie shifts in the magnitude, or even the direction, of metabolic and biogeochemical fluxes can be quite subtle and test the limits of current quantitative proteomics techniques. Here we describe methodologies for high-precision, whole-proteome quantification that are applicable to both model organisms of biogeochemical interest that may not be genetically tractable, and to complex community samples from natural environments. Employing chemical derivatization of peptides with multiple isotopically-coded tags, this strategy is rapid and inexpensive, can be implemented on a wide range of mass spectrometric instrumentation, and is relatively insensitive to chromatographic variability. We demonstrate the utility of this quantitative proteomics approach in application to both isolates and natural communities of sulfur-metabolizing and photosynthetic microbes.

  20. Carbon and Nitrogen Provisions Alter the Metabolic Flux in Developing Soybean Embryos1[W][OA

    PubMed Central

    Allen, Doug K.; Young, Jamey D.

    2013-01-01

    Soybean (Glycine max) seeds store significant amounts of their biomass as protein, levels of which reflect the carbon and nitrogen received by the developing embryo. The relationship between carbon and nitrogen supply during filling and seed composition was examined through a series of embryo-culturing experiments. Three distinct ratios of carbon to nitrogen supply were further explored through metabolic flux analysis. Labeling experiments utilizing [U-13C5]glutamine, [U-13C4]asparagine, and [1,2-13C2]glucose were performed to assess embryo metabolism under altered feeding conditions and to create corresponding flux maps. Additionally, [U-14C12]sucrose, [U-14C6]glucose, [U-14C5]glutamine, and [U-14C4]asparagine were used to monitor differences in carbon allocation. The analyses revealed that: (1) protein concentration as a percentage of total soybean embryo biomass coincided with the carbon-to-nitrogen ratio; (2) altered nitrogen supply did not dramatically impact relative amino acid or storage protein subunit profiles; and (3) glutamine supply contributed 10% to 23% of the carbon for biomass production, including 9% to 19% of carbon to fatty acid biosynthesis and 32% to 46% of carbon to amino acids. Seed metabolism accommodated different levels of protein biosynthesis while maintaining a consistent rate of dry weight accumulation. Flux through ATP-citrate lyase, combined with malic enzyme activity, contributed significantly to acetyl-coenzyme A production. These fluxes changed with plastidic pyruvate kinase to maintain a supply of pyruvate for amino and fatty acids. The flux maps were independently validated by nitrogen balancing and highlight the robustness of primary metabolism. PMID:23314943

  1. Quantitative assessment of brain glucose metabolic rates using in vivo deuterium magnetic resonance spectroscopy.

    PubMed

    Lu, Ming; Zhu, Xiao-Hong; Zhang, Yi; Mateescu, Gheorghe; Chen, Wei

    2017-11-01

    Quantitative assessment of cerebral glucose consumption rate (CMR glc ) and tricarboxylic acid cycle flux (V TCA ) is crucial for understanding neuroenergetics under physiopathological conditions. In this study, we report a novel in vivo Deuterium ( 2 H) MRS (DMRS) approach for simultaneously measuring and quantifying CMR glc and V TCA in rat brains at 16.4 Tesla. Following a brief infusion of deuterated glucose, dynamic changes of isotope-labeled glucose, glutamate/glutamine (Glx) and water contents in the brain can be robustly monitored from their well-resolved 2 H resonances. Dynamic DMRS glucose and Glx data were employed to determine CMR glc and V TCA concurrently. To test the sensitivity of this method in response to altered glucose metabolism, two brain conditions with different anesthetics were investigated. Increased CMR glc (0.46 vs. 0.28 µmol/g/min) and V TCA (0.96 vs. 0.6 µmol/g/min) were found in rats under morphine as compared to deeper anesthesia using 2% isoflurane. This study demonstrates the feasibility and new utility of the in vivo DMRS approach to assess cerebral glucose metabolic rates at high/ultrahigh field. It provides an alternative MRS tool for in vivo study of metabolic coupling relationship between aerobic and anaerobic glucose metabolisms in brain under physiopathological states.

  2. Metabolism estimates in small boreal lakes: the importance of accounting for vertical fluxes of oxygen

    NASA Astrophysics Data System (ADS)

    Klaus, M.; MacIntyre, S.; Hotchkiss, E. R.; Bergström, A. K.; Karlsson, J.

    2015-12-01

    Lake metabolism models based on the diel oxygen technique often assume that oxygen dynamics are mainly controlled by metabolic processes, only accounting for wind-driven atmospheric gas exchange. However, oxygen dynamics can also be affected by abiotic mass fluxes across oxygen gradients within lakes and atmospheric gas exchange driven by convection. Here, we quantify how much vertical fluxes of oxygen modify epilimnetic metabolism estimates for three pairs of small Swedish boreal lakes, one of each fertilized with nitrate, with dissolved organic carbon (DOC) concentrations of 7 to 22 mg l-1. Oxygen concentrations were measured every 10 min at 50 cm depth and biweekly across depths profiles during one full open water period. Based on additional two weeks of ten-minute oxygen profiling we calculated vertical fluxes of oxygen using equations for atmospheric gas exchange caused by wind shear (F1) and convection (F2), and lake-internal gas exchange caused by diffusion and mixed layer deepening (F3). We ran three inverse Bayesian models to estimate daily metabolism: (M1) accounting for F1, (M2) accounting for F1 and F2, and (M3) accounting for F1 and F3. Initial results suggest that gross primary production (GPP), ecosystem respiration (ER) and net ecosystem production (NEP) ranged from 0.1 to 0.2, -0.3 to -0.5 and -0.2 to -0.4 g C m-2 d-1, respectively. GPP and R were higher in fertilized lakes and at the lower end of previous worldwide estimates. Accounting for convection-driven gas exchange increased ER estimates by 10-40% (M2 vs. M1). This bias increased with DOC concentration but was not affected by fertilization. Including lake-internal vertical oxygen fluxes changed GPP and ER estimates by up to ±40% (M3 vs. M1), with inconsistent trends along the DOC-gradient. We conclude that vertical fluxes of oxygen can significantly affect diel oxygen dynamics in oligotrophic humic systems and should therefore be included in metabolism models applied to small boreal lakes.

  3. Parallel labeling experiments and metabolic flux analysis: Past, present and future methodologies.

    PubMed

    Crown, Scott B; Antoniewicz, Maciek R

    2013-03-01

    Radioactive and stable isotopes have been applied for decades to elucidate metabolic pathways and quantify carbon flow in cellular systems using mass and isotope balancing approaches. Isotope-labeling experiments can be conducted as a single tracer experiment, or as parallel labeling experiments. In the latter case, several experiments are performed under identical conditions except for the choice of substrate labeling. In this review, we highlight robust approaches for probing metabolism and addressing metabolically related questions though parallel labeling experiments. In the first part, we provide a brief historical perspective on parallel labeling experiments, from the early metabolic studies when radioisotopes were predominant to present-day applications based on stable-isotopes. We also elaborate on important technical and theoretical advances that have facilitated the transition from radioisotopes to stable-isotopes. In the second part of the review, we focus on parallel labeling experiments for (13)C-metabolic flux analysis ((13)C-MFA). Parallel experiments offer several advantages that include: tailoring experiments to resolve specific fluxes with high precision; reducing the length of labeling experiments by introducing multiple entry-points of isotopes; validating biochemical network models; and improving the performance of (13)C-MFA in systems where the number of measurements is limited. We conclude by discussing some challenges facing the use of parallel labeling experiments for (13)C-MFA and highlight the need to address issues related to biological variability, data integration, and rational tracer selection. Copyright © 2012 Elsevier Inc. All rights reserved.

  4. Combining graph and flux-based structures to decipher phenotypic essential metabolites within metabolic networks.

    PubMed

    Laniau, Julie; Frioux, Clémence; Nicolas, Jacques; Baroukh, Caroline; Cortes, Maria-Paz; Got, Jeanne; Trottier, Camille; Eveillard, Damien; Siegel, Anne

    2017-01-01

    The emergence of functions in biological systems is a long-standing issue that can now be addressed at the cell level with the emergence of high throughput technologies for genome sequencing and phenotyping. The reconstruction of complete metabolic networks for various organisms is a key outcome of the analysis of these data, giving access to a global view of cell functioning. The analysis of metabolic networks may be carried out by simply considering the architecture of the reaction network or by taking into account the stoichiometry of reactions. In both approaches, this analysis is generally centered on the outcome of the network and considers all metabolic compounds to be equivalent in this respect. As in the case of genes and reactions, about which the concept of essentiality has been developed, it seems, however, that some metabolites play crucial roles in system responses, due to the cell structure or the internal wiring of the metabolic network. We propose a classification of metabolic compounds according to their capacity to influence the activation of targeted functions (generally the growth phenotype) in a cell. We generalize the concept of essentiality to metabolites and introduce the concept of the phenotypic essential metabolite (PEM) which influences the growth phenotype according to sustainability, producibility or optimal-efficiency criteria. We have developed and made available a tool, Conquests , which implements a method combining graph-based and flux-based analysis, two approaches that are usually considered separately. The identification of PEMs is made effective by using a logical programming approach. The exhaustive study of phenotypic essential metabolites in six genome-scale metabolic models suggests that the combination and the comparison of graph, stoichiometry and optimal flux-based criteria allows some features of the metabolic network functionality to be deciphered by focusing on a small number of compounds. By considering the best

  5. Combining graph and flux-based structures to decipher phenotypic essential metabolites within metabolic networks

    PubMed Central

    Frioux, Clémence; Nicolas, Jacques; Baroukh, Caroline; Cortes, Maria-Paz; Got, Jeanne; Trottier, Camille; Eveillard, Damien

    2017-01-01

    Background The emergence of functions in biological systems is a long-standing issue that can now be addressed at the cell level with the emergence of high throughput technologies for genome sequencing and phenotyping. The reconstruction of complete metabolic networks for various organisms is a key outcome of the analysis of these data, giving access to a global view of cell functioning. The analysis of metabolic networks may be carried out by simply considering the architecture of the reaction network or by taking into account the stoichiometry of reactions. In both approaches, this analysis is generally centered on the outcome of the network and considers all metabolic compounds to be equivalent in this respect. As in the case of genes and reactions, about which the concept of essentiality has been developed, it seems, however, that some metabolites play crucial roles in system responses, due to the cell structure or the internal wiring of the metabolic network. Results We propose a classification of metabolic compounds according to their capacity to influence the activation of targeted functions (generally the growth phenotype) in a cell. We generalize the concept of essentiality to metabolites and introduce the concept of the phenotypic essential metabolite (PEM) which influences the growth phenotype according to sustainability, producibility or optimal-efficiency criteria. We have developed and made available a tool, Conquests, which implements a method combining graph-based and flux-based analysis, two approaches that are usually considered separately. The identification of PEMs is made effective by using a logical programming approach. Conclusion The exhaustive study of phenotypic essential metabolites in six genome-scale metabolic models suggests that the combination and the comparison of graph, stoichiometry and optimal flux-based criteria allows some features of the metabolic network functionality to be deciphered by focusing on a small number of

  6. In vivo 13C MRS in the mouse brain at 14.1 Tesla and metabolic flux quantification under infusion of [1,6-13C2]glucose.

    PubMed

    Lai, Marta; Lanz, Bernard; Poitry-Yamate, Carole; Romero, Jackeline F; Berset, Corina M; Cudalbu, Cristina; Gruetter, Rolf

    2017-01-01

    In vivo 13 C magnetic resonance spectroscopy (MRS) enables the investigation of cerebral metabolic compartmentation while, e.g. infusing 13 C-labeled glucose. Metabolic flux analysis of 13 C turnover previously yielded quantitative information of glutamate and glutamine metabolism in humans and rats, while the application to in vivo mouse brain remains exceedingly challenging. In the present study, 13 C direct detection at 14.1 T provided highly resolved in vivo spectra of the mouse brain while infusing [1,6- 13 C 2 ]glucose for up to 5 h. 13 C incorporation to glutamate and glutamine C4, C3, and C2 and aspartate C3 were detected dynamically and fitted to a two-compartment model: flux estimation of neuron-glial metabolism included tricarboxylic acid cycle (TCA) flux in astrocytes (V g  = 0.16 ± 0.03 µmol/g/min) and neurons (V TCA n  = 0.56 ± 0.03 µmol/g/min), pyruvate carboxylase activity (V PC  = 0.041 ± 0.003 µmol/g/min) and neurotransmission rate (V NT  = 0.084 ± 0.008 µmol/g/min), resulting in a cerebral metabolic rate of glucose (CMR glc ) of 0.38 ± 0.02 µmol/g/min, in excellent agreement with that determined with concomitant 18 F-fluorodeoxyglucose positron emission tomography ( 18 FDG PET).We conclude that modeling of neuron-glial metabolism in vivo is accessible in the mouse brain from 13 C direct detection with an unprecedented spatial resolution under [1,6- 13 C 2 ]glucose infusion.

  7. Metabolic flux profiling of MDCK cells during growth and canine adenovirus vector production.

    PubMed

    Carinhas, Nuno; Pais, Daniel A M; Koshkin, Alexey; Fernandes, Paulo; Coroadinha, Ana S; Carrondo, Manuel J T; Alves, Paula M; Teixeira, Ana P

    2016-03-23

    Canine adenovirus vector type 2 (CAV2) represents an alternative to human adenovirus vectors for certain gene therapy applications, particularly neurodegenerative diseases. However, more efficient production processes, assisted by a greater understanding of the effect of infection on producer cells, are required. Combining [1,2-(13)C]glucose and [U-(13)C]glutamine, we apply for the first time (13)C-Metabolic flux analysis ((13)C-MFA) to study E1-transformed Madin-Darby Canine Kidney (MDCK) cells metabolism during growth and CAV2 production. MDCK cells displayed a marked glycolytic and ammoniagenic metabolism, and (13)C data revealed a large fraction of glutamine-derived labelling in TCA cycle intermediates, emphasizing the role of glutamine anaplerosis. (13)C-MFA demonstrated the importance of pyruvate cycling in balancing glycolytic and TCA cycle activities, as well as occurrence of reductive alphaketoglutarate (AKG) carboxylation. By turn, CAV2 infection significantly upregulated fluxes through most central metabolism, including glycolysis, pentose-phosphate pathway, glutamine anaplerosis and, more prominently, reductive AKG carboxylation and cytosolic acetyl-coenzyme A formation, suggestive of increased lipogenesis. Based on these results, we suggest culture supplementation strategies to stimulate nucleic acid and lipid biosynthesis for improved canine adenoviral vector production.

  8. Metabolic flux analysis of carbon balance in Lactobacillus strains.

    PubMed

    Zhang, Yixing; Zeng, Fan; Hohn, Keith; Vadlani, Praveen V

    2016-11-01

    Metabolic flux analyses were performed based on the carbon balance of six different Lactobacillus strains used in this study. Results confirmed that L. delbrueckii, L. plantarum ATCC 21028, L. plantarum NCIMB 8826 ΔldhL1, L. plantarum NCIMB 8826 ΔldhL1-pCU-PxylAB, and L. plantarum NCIMB 8826 ΔldhL1-pLEM415-xylAB metabolized glucose via EMP: whereas, L. brevis metabolized glucose via PK pathway. Xylose was metabolized through the PK pathway in L. brevis, L. plantarum NCIMB 8826 ΔldhL1-pCU-PxylAB and L. plantarum NCIMB 8826 ΔldhL1-pLEM415-xylAB. Operation of both EMP and PK pathways was found in L. brevis, L. plantarum NCIMB 8826 ΔldhL1-pCU-PxylAB, and L. plantarum NCIMB 8826 ΔldhL1-pLEM415-xylAB when glucose plus xylose were used as carbon source. The information of detailed carbon flow may help the strain and biomass selection in a designed process of lactic acid biosynthesis. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:1397-1403, 2016. © 2016 American Institute of Chemical Engineers.

  9. Modular decomposition of metabolic reaction networks based on flux analysis and pathway projection.

    PubMed

    Yoon, Jeongah; Si, Yaguang; Nolan, Ryan; Lee, Kyongbum

    2007-09-15

    The rational decomposition of biochemical networks into sub-structures has emerged as a useful approach to study the design of these complex systems. A biochemical network is characterized by an inhomogeneous connectivity distribution, which gives rise to several organizational features, including modularity. To what extent the connectivity-based modules reflect the functional organization of the network remains to be further explored. In this work, we examine the influence of physiological perturbations on the modular organization of cellular metabolism. Modules were characterized for two model systems, liver and adipocyte primary metabolism, by applying an algorithm for top-down partition of directed graphs with non-uniform edge weights. The weights were set by the engagement of the corresponding reactions as expressed by the flux distribution. For the base case of the fasted rat liver, three modules were found, carrying out the following biochemical transformations: ketone body production, glucose synthesis and transamination. This basic organization was further modified when different flux distributions were applied that describe the liver's metabolic response to whole body inflammation. For the fully mature adipocyte, only a single module was observed, integrating all of the major pathways needed for lipid storage. Weaker levels of integration between the pathways were found for the early stages of adipocyte differentiation. Our results underscore the inhomogeneous distribution of both connectivity and connection strengths, and suggest that global activity data such as the flux distribution can be used to study the organizational flexibility of cellular metabolism. Supplementary data are available at Bioinformatics online.

  10. Exploring the quantitative relationship between metabolism and enzymatic phenotype by physiological modeling of glucose metabolism and lactate oxidation in solid tumors

    NASA Astrophysics Data System (ADS)

    Wang, Qian; Vaupel, Peter; Ziegler, Sibylle I.; Shi, Kuangyu

    2015-03-01

    Molecular imaging using PET or hyperpolarized MRI can characterize tumor phenotypes by assessing the related metabolism of certain substrates. However, the interpretation of the substrate turnover in terms of a pathophysiological understanding is not straightforward and only semiquantitative. The metabolism of imaging probes is influenced by a number of factors, such as the microvascular structure or the expression of key enzymes. This study aims to use computational simulation to investigate the relationship between the metabolism behind molecular imaging and the underlying tumor phenotype. The study focused on the pathways of glucose metabolism and lactate oxidation in order to establish the quantitative relationship between the expression of several transporters (GLUT, MCT1 and MCT4), expression of the enzyme hexokinase (HK), microvasculature and the metabolism of glucose or lactate and the extracellular pH distribution. A computational model for a 2D tumor tissue phantom was constructed and the spatio-temporal evolution of related species (e.g. oxygen, glucose, lactate, protons, bicarbonate ions) was estimated by solving reaction-diffusion equations. The proposed model was tested by the verification of the simulation results using in vivo and in vitro literature data. The influences of different expression levels of GLUT, MCT1, MCT4, HK and microvessel distribution on substrate concentrations were analyzed. The major results are consistent with experimental data (e.g. GLUT is more influential to glycolytic flux than HK; extracellular pH is not correlated with MCT expressions) and provide theoretical interpretation of the co-influence of multiple factors of the tumor microenvironment. This computational simulation may assist the generation of hypotheses to bridge the discrepancy between tumor metabolism and the functions of transporters and enzymes. It has the potential to accelerate the development of multi-modal imaging strategies for assessment of tumor

  11. Metabolic Flux Increases Glycoprotein Sialylation: Implications for Cell Adhesion and Cancer Metastasis*

    PubMed Central

    Almaraz, Ruben T.; Tian, Yuan; Bhattarcharya, Rahul; Tan, Elaine; Chen, Shih-Hsun; Dallas, Matthew R.; Chen, Li; Zhang, Zhen; Zhang, Hui; Konstantopoulos, Konstantinos; Yarema, Kevin J.

    2012-01-01

    This study reports a global glycoproteomic analysis of pancreatic cancer cells that describes how flux through the sialic acid biosynthetic pathway selectively modulates a subset of N-glycosylation sites found within cellular proteins. These results provide evidence that sialoglycoprotein patterns are not determined exclusively by the transcription of biosynthetic enzymes or the availability of N-glycan sequons; instead, bulk metabolic flux through the sialic acid pathway has a remarkable ability to increase the abundance of certain sialoglycoproteins while having a minimal impact on others. Specifically, of 82 glycoproteins identified through a mass spectrometry and bioinformatics approach, ∼31% showed no change in sialylation, ∼29% exhibited a modest increase, whereas ∼40% experienced an increase of greater than twofold. Increased sialylation of specific glycoproteins resulted in changes to the adhesive properties of SW1990 pancreatic cancer cells (e.g. increased CD44-mediated adhesion to selectins under physiological flow and enhanced integrin-mediated cell mobility on collagen and fibronectin). These results indicate that cancer cells can become more aggressively malignant by controlling the sialylation of proteins implicated in metastatic transformation via metabolic flux. PMID:22457533

  12. Quantitative Relationships between Photosynthetic, Nitrogen Fixing, and Fermentative H2 Metabolism in a Photosynthetic Microbial Mat

    NASA Technical Reports Server (NTRS)

    Hoehler, Tori M.; Albert, Daniel B.; Bebout, Brad M.; Turk, Kendra A.; DesMarais, David J.

    2004-01-01

    The ultimate potential of any microbial ecosystem to contribute chemically to its environment - and therefore, to impact planetary biogeochemistry or to generate recognizable biosignatures - depends not only on the individual metabolic capabilities of constituent organisms, but also on how those capabilities are expressed through interactions with neighboring organisms. This is particularly important for microbial mats, which compress an extremely broad range of metabolic potential into a small and dynamic system. H2 participates in many of these metabolic processes, including the major elemental cycling processes of photosynthesis, nitrogen fixation, sulfate reduction, and fermentation, and may therefore serve as a mediator of microbial interactions within the mat system. Collectively, the requirements of energy, electron transfer, and biomass element stoichiometry suggest quantitative relationships among the major element cycling processes, as regards H2 metabolism We determined experimentally the major contributions to 32 cycling in hypersaline microbial mats from Baja California, Mexico, and compared them to predicted relationships. Fermentation under dark, anoxic conditions is quantitatively the most important mechanism of H2 production, consistent with expectations for non-heterocystous mats such as those under study. Up to 16% of reducing equivalents fixed by photosynthesis during the day may be released by this mechanism. The direct contribution of nitrogen fixation to H2 production is small in comparison, but this process may indirectly stimulate substantial H2 generation, by requiring higher rates of fermentation. Sulfate reduction, aerobic consumption, diffusive and ebulitive loss, and possibly H2-based photoreduction of CO2 serve as the principal H2 sinks. Collectively, these processes interact to create an orders-of-magnitude daily variation in H2 concentrations and fluxes, and thereby in the oxidation-reduction potential that is imposed on microbial

  13. Modeling the optimal central carbon metabolic pathways under feedback inhibition using flux balance analysis.

    PubMed

    De, Rajat K; Tomar, Namrata

    2012-12-01

    Metabolism is a complex process for energy production for cellular activity. It consists of a cascade of reactions that form a highly branched network in which the product of one reaction is the reactant of the next reaction. Metabolic pathways efficiently produce maximal amount of biomass while maintaining a steady-state behavior. The steady-state activity of such biochemical pathways necessarily incorporates feedback inhibition of the enzymes. This observation motivates us to incorporate feedback inhibition for modeling the optimal activity of metabolic pathways using flux balance analysis (FBA). We demonstrate the effectiveness of the methodology on a synthetic pathway with and without feedback inhibition. Similarly, for the first time, the Central Carbon Metabolic (CCM) pathways of Saccharomyces cerevisiae and Homo sapiens have been modeled and compared based on the above understanding. The optimal pathway, which maximizes the amount of the target product(s), is selected from all those obtained by the proposed method. For this, we have observed the concentration of the product inhibited enzymes of CCM pathway and its influence on its corresponding metabolite/substrate. We have also studied the concentration of the enzymes which are responsible for the synthesis of target products. We further hypothesize that an optimal pathway would opt for higher flux rate reactions. In light of these observations, we can say that an optimal pathway should have lower enzyme concentration and higher flux rates. Finally, we demonstrate the superiority of the proposed method by comparing it with the extreme pathway analysis.

  14. Central carbon metabolism influences cellulase production in Bacillus licheniformis.

    PubMed

    Wang, J; Liu, S; Li, Y; Wang, H; Xiao, S; Li, C; Liu, B

    2018-01-01

    Bacillus licheniformis that can produce cellulase including endo glucanase and glucosidase is an important industrial microbe for cellulose degradation. The purpose of this research was to assess the effect of endo glucanase gene bglC and glucosidase gene bglH on the central metabolic flux in B. licheniformis. bglC and bglH were knocked out using homologous recombination method, respectively, and the corresponding knockout strains were obtained for 13 C metabolic flux analysis. A significant change was observed in metabolic fluxes after 13 C metabolic flux ratio analysis. In both of the knockout strains, the increased fluxes of the pentose phosphate pathway and malic enzyme reaction enabled an elevated supply of NADPH which provided enough reducing power for the in vivo synthesis reactions. The fluxes through tricarboxylic acid cycle and anaplerotic reactions increased fast in the two knockout strains, which meant more energy generated. The changed fluxes in central carbon metabolism provided a holistic view of the physiological status in B. licheniformis and possible targets for further strain engineering. Cellulase is very important in the field of agriculture and bioenergy because of its degrading effect on cellulosic biomass. This study presented the effect of central carbon metabolism on cellulase production in Bacillus licheniformis. The study also provided a holistic view of the physiological status in B. licheniformis. The shifted metabolism provided a quantitative evaluation of the biosynthesis of cellulase and a priority ranked target list for further strain engineering. © 2017 The Society for Applied Microbiology.

  15. (13)C-metabolic flux analysis in S-adenosyl-L-methionine production by Saccharomyces cerevisiae.

    PubMed

    Hayakawa, Kenshi; Kajihata, Shuichi; Matsuda, Fumio; Shimizu, Hiroshi

    2015-11-01

    S-Adenosyl-L-methionine (SAM) is a major biological methyl group donor, and is used as a nutritional supplement and prescription drug. Yeast is used for the industrial production of SAM owing to its high intracellular SAM concentrations. To determine the regulation mechanisms responsible for such high SAM production, (13)C-metabolic flux analysis ((13)C-MFA) was conducted to compare the flux distributions in the central metabolism between Kyokai no. 6 (high SAM-producing) and S288C (control) strains. (13)C-MFA showed that the levels of tricarboxylic acid (TCA) cycle flux in SAM-overproducing strain were considerably increased compared to those in the S228C strain. Analysis of ATP balance also showed that a larger amount of excess ATP was produced in the Kyokai 6 strain because of increased oxidative phosphorylation. These results suggest that high SAM production in Kyokai 6 strains could be attributed to enhanced ATP regeneration with high TCA cycle fluxes and respiration activity. Thus, maintaining high respiration efficiency during cultivation is important for improving SAM production. Copyright © 2015 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

  16. Exploring metabolic pathways in genome-scale networks via generating flux modes.

    PubMed

    Rezola, A; de Figueiredo, L F; Brock, M; Pey, J; Podhorski, A; Wittmann, C; Schuster, S; Bockmayr, A; Planes, F J

    2011-02-15

    The reconstruction of metabolic networks at the genome scale has allowed the analysis of metabolic pathways at an unprecedented level of complexity. Elementary flux modes (EFMs) are an appropriate concept for such analysis. However, their number grows in a combinatorial fashion as the size of the metabolic network increases, which renders the application of EFMs approach to large metabolic networks difficult. Novel methods are expected to deal with such complexity. In this article, we present a novel optimization-based method for determining a minimal generating set of EFMs, i.e. a convex basis. We show that a subset of elements of this convex basis can be effectively computed even in large metabolic networks. Our method was applied to examine the structure of pathways producing lysine in Escherichia coli. We obtained a more varied and informative set of pathways in comparison with existing methods. In addition, an alternative pathway to produce lysine was identified using a detour via propionyl-CoA, which shows the predictive power of our novel approach. The source code in C++ is available upon request.

  17. Quiescent Fibroblasts Exhibit High Metabolic Activity

    PubMed Central

    Lemons, Johanna M. S.; Feng, Xiao-Jiang; Bennett, Bryson D.; Legesse-Miller, Aster; Johnson, Elizabeth L.; Raitman, Irene; Pollina, Elizabeth A.; Rabitz, Herschel A.; Rabinowitz, Joshua D.; Coller, Hilary A.

    2010-01-01

    Many cells in mammals exist in the state of quiescence, which is characterized by reversible exit from the cell cycle. Quiescent cells are widely reported to exhibit reduced size, nucleotide synthesis, and metabolic activity. Much lower glycolytic rates have been reported in quiescent compared with proliferating lymphocytes. In contrast, we show here that primary human fibroblasts continue to exhibit high metabolic rates when induced into quiescence via contact inhibition. By monitoring isotope labeling through metabolic pathways and quantitatively identifying fluxes from the data, we show that contact-inhibited fibroblasts utilize glucose in all branches of central carbon metabolism at rates similar to those of proliferating cells, with greater overflow flux from the pentose phosphate pathway back to glycolysis. Inhibition of the pentose phosphate pathway resulted in apoptosis preferentially in quiescent fibroblasts. By feeding the cells labeled glutamine, we also detected a “backwards” flux in the tricarboxylic acid cycle from α-ketoglutarate to citrate that was enhanced in contact-inhibited fibroblasts; this flux likely contributes to shuttling of NADPH from the mitochondrion to cytosol for redox defense or fatty acid synthesis. The high metabolic activity of the fibroblasts was directed in part toward breakdown and resynthesis of protein and lipid, and in part toward excretion of extracellular matrix proteins. Thus, reduced metabolic activity is not a hallmark of the quiescent state. Quiescent fibroblasts, relieved of the biosynthetic requirements associated with generating progeny, direct their metabolic activity to preservation of self integrity and alternative functions beneficial to the organism as a whole. PMID:21049082

  18. Strophanthidin-sensitive sodium fluxes in metabolically poisoned frog skeletal muscle

    PubMed Central

    1976-01-01

    Strophanthidin-sensitive and insensitive unidirectional fluxes of Na were measured in fog sartorius muscles whose internal Na levels were elevated by overnight storage in the cold. ATP levels were lowered, and ADP levels raised, by metabolic poisoning with either 2,4- dinitrofluorobenzene or iodoacetamide. Strophanthidin-sensitive Na efflux and influx both increased after poisoning, while strophanthidin- insensitives fluxes did not. The increase in efflux did not require the presence of external K but was greatly attenuated when Li replaced Na as the major external cation. Membrane potential was not markedly altered by 2,4-dinitrofluorobenzene. These observations indicate that the sodium pump of frog skeletal muscle resembles that of squid giant axon and human erythrocyte in its ability to catalyze Na-Na exchange to an extent determined by intracellular ATP/ADP levels. PMID:1086888

  19. DOSIMETRY MODELING OF INHALED FORMALDEHYDE: BINNING NASAL FLUX PREDICTIONS FOR QUANTITATIVE RISK ASSESSMENT

    EPA Science Inventory

    Dosimetry Modeling of Inhaled Formaldehyde: Binning Nasal Flux Predictions for Quantitative Risk Assessment. Kimbell, J.S., Overton, J.H., Subramaniam, R.P., Schlosser, P.M., Morgan, K.T., Conolly, R.B., and Miller, F.J. (2001). Toxicol. Sci. 000, 000:000.

    Interspecies e...

  20. influx_s: increasing numerical stability and precision for metabolic flux analysis in isotope labelling experiments.

    PubMed

    Sokol, Serguei; Millard, Pierre; Portais, Jean-Charles

    2012-03-01

    The problem of stationary metabolic flux analysis based on isotope labelling experiments first appeared in the early 1950s and was basically solved in early 2000s. Several algorithms and software packages are available for this problem. However, the generic stochastic algorithms (simulated annealing or evolution algorithms) currently used in these software require a lot of time to achieve acceptable precision. For deterministic algorithms, a common drawback is the lack of convergence stability for ill-conditioned systems or when started from a random point. In this article, we present a new deterministic algorithm with significantly increased numerical stability and accuracy of flux estimation compared with commonly used algorithms. It requires relatively short CPU time (from several seconds to several minutes with a standard PC architecture) to estimate fluxes in the central carbon metabolism network of Escherichia coli. The software package influx_s implementing this algorithm is distributed under an OpenSource licence at http://metasys.insa-toulouse.fr/software/influx/. Supplementary data are available at Bioinformatics online.

  1. Fast-SNP: a fast matrix pre-processing algorithm for efficient loopless flux optimization of metabolic models

    PubMed Central

    Saa, Pedro A.; Nielsen, Lars K.

    2016-01-01

    Motivation: Computation of steady-state flux solutions in large metabolic models is routinely performed using flux balance analysis based on a simple LP (Linear Programming) formulation. A minimal requirement for thermodynamic feasibility of the flux solution is the absence of internal loops, which are enforced using ‘loopless constraints’. The resulting loopless flux problem is a substantially harder MILP (Mixed Integer Linear Programming) problem, which is computationally expensive for large metabolic models. Results: We developed a pre-processing algorithm that significantly reduces the size of the original loopless problem into an easier and equivalent MILP problem. The pre-processing step employs a fast matrix sparsification algorithm—Fast- sparse null-space pursuit (SNP)—inspired by recent results on SNP. By finding a reduced feasible ‘loop-law’ matrix subject to known directionalities, Fast-SNP considerably improves the computational efficiency in several metabolic models running different loopless optimization problems. Furthermore, analysis of the topology encoded in the reduced loop matrix enabled identification of key directional constraints for the potential permanent elimination of infeasible loops in the underlying model. Overall, Fast-SNP is an effective and simple algorithm for efficient formulation of loop-law constraints, making loopless flux optimization feasible and numerically tractable at large scale. Availability and Implementation: Source code for MATLAB including examples is freely available for download at http://www.aibn.uq.edu.au/cssb-resources under Software. Optimization uses Gurobi, CPLEX or GLPK (the latter is included with the algorithm). Contact: lars.nielsen@uq.edu.au Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27559155

  2. Effects of drugs in subtoxic concentrations on the metabolic fluxes in human hepatoma cell line Hep G2

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Niklas, Jens; Noor, Fozia, E-mail: fozia.noor@mx.uni-saarland.d; Heinzle, Elmar

    2009-11-01

    Commonly used cytotoxicity assays assess the toxicity of a compound by measuring certain parameters which directly or indirectly correlate to the viability of the cells. However, the effects of a given compound at concentrations considerably below EC{sub 50} values are usually not evaluated. These subtoxic effects are difficult to identify but may eventually cause severe and costly long term problems such as idiosyncratic hepatotoxicity. We determined the toxicity of three hepatotoxic compounds, namely amiodarone, diclofenac and tacrine on the human hepatoma cell line Hep G2 using an online kinetic respiration assay and analysed the effects of subtoxic concentrations of thesemore » drugs on the cellular metabolism by using metabolic flux analysis. Several changes in the metabolism could be detected upon exposure to subtoxic concentrations of the test compounds. Upon exposure to diclofenac and tacrine an increase in the TCA-cycle activity was observed which could be a signature of an uncoupling of the oxidative phosphorylation. The results indicate that metabolic flux analysis could serve as an invaluable novel tool for the investigation of the effects of drugs. The described methodology enables tracking the toxicity of compounds dynamically using the respiration assay in a range of concentrations and the metabolic flux analysis permits interesting insights into the changes in the central metabolism of the cell upon exposure to drugs.« less

  3. A method for accounting for maintenance costs in flux balance analysis improves the prediction of plant cell metabolic phenotypes under stress conditions.

    PubMed

    Cheung, C Y Maurice; Williams, Thomas C R; Poolman, Mark G; Fell, David A; Ratcliffe, R George; Sweetlove, Lee J

    2013-09-01

    Flux balance models of metabolism generally utilize synthesis of biomass as the main determinant of intracellular fluxes. However, the biomass constraint alone is not sufficient to predict realistic fluxes in central heterotrophic metabolism of plant cells because of the major demand on the energy budget due to transport costs and cell maintenance. This major limitation can be addressed by incorporating transport steps into the metabolic model and by implementing a procedure that uses Pareto optimality analysis to explore the trade-off between ATP and NADPH production for maintenance. This leads to a method for predicting cell maintenance costs on the basis of the measured flux ratio between the oxidative steps of the oxidative pentose phosphate pathway and glycolysis. We show that accounting for transport and maintenance costs substantially improves the accuracy of fluxes predicted from a flux balance model of heterotrophic Arabidopsis cells in culture, irrespective of the objective function used in the analysis. Moreover, when the new method was applied to cells under control, elevated temperature and hyper-osmotic conditions, only elevated temperature led to a substantial increase in cell maintenance costs. It is concluded that the hyper-osmotic conditions tested did not impose a metabolic stress, in as much as the metabolic network is not forced to devote more resources to cell maintenance. © 2013 The Authors The Plant Journal © 2013 John Wiley & Sons Ltd.

  4. Temporal Expression-based Analysis of Metabolism

    PubMed Central

    Segrè, Daniel

    2012-01-01

    Metabolic flux is frequently rerouted through cellular metabolism in response to dynamic changes in the intra- and extra-cellular environment. Capturing the mechanisms underlying these metabolic transitions in quantitative and predictive models is a prominent challenge in systems biology. Progress in this regard has been made by integrating high-throughput gene expression data into genome-scale stoichiometric models of metabolism. Here, we extend previous approaches to perform a Temporal Expression-based Analysis of Metabolism (TEAM). We apply TEAM to understanding the complex metabolic dynamics of the respiratorily versatile bacterium Shewanella oneidensis grown under aerobic, lactate-limited conditions. TEAM predicts temporal metabolic flux distributions using time-series gene expression data. Increased predictive power is achieved by supplementing these data with a large reference compendium of gene expression, which allows us to take into account the unique character of the distribution of expression of each individual gene. We further propose a straightforward method for studying the sensitivity of TEAM to changes in its fundamental free threshold parameter θ, and reveal that discrete zones of distinct metabolic behavior arise as this parameter is changed. By comparing the qualitative characteristics of these zones to additional experimental data, we are able to constrain the range of θ to a small, well-defined interval. In parallel, the sensitivity analysis reveals the inherently difficult nature of dynamic metabolic flux modeling: small errors early in the simulation propagate to relatively large changes later in the simulation. We expect that handling such “history-dependent” sensitivities will be a major challenge in the future development of dynamic metabolic-modeling techniques. PMID:23209390

  5. Radiopharmaceuticals for Assessment of Altered Metabolism and Biometal Fluxes in Brain Aging and Alzheimer's Disease with Positron Emission Tomography.

    PubMed

    Xie, Fang; Peng, Fangyu

    2017-01-01

    Aging is a risk factor for Alzheimer's disease (AD). There are changes of brain metabolism and biometal fluxes due to brain aging, which may play a role in pathogenesis of AD. Positron emission tomography (PET) is a versatile tool for tracking alteration of metabolism and biometal fluxes due to brain aging and AD. Age-dependent changes in cerebral glucose metabolism can be tracked with PET using 2-deoxy-2-[18F]-fluoro-D-glucose (18F-FDG), a radiolabeled glucose analogue, as a radiotracer. Based on different patterns of altered cerebral glucose metabolism, 18F-FDG PET was clinically used for differential diagnosis of AD and Frontotemporal dementia (FTD). There are continued efforts to develop additional radiopharmaceuticals or radiotracers for assessment of age-dependent changes of various metabolic pathways and biometal fluxes due to brain aging and AD with PET. Elucidation of age-dependent changes of brain metabolism and altered biometal fluxes is not only significant for a better mechanistic understanding of brain aging and the pathophysiology of AD, but also significant for identification of new targets for the prevention, early diagnosis, and treatment of AD.

  6. Publishing 13C metabolic flux analysis studies: A review and future perspectives

    PubMed Central

    Crown, Scott B.; Antoniewicz, Maciek R.

    2018-01-01

    13C-Metabolic flux analysis (13C-MFA) is a powerful model-based analysis technique for determining intracellular metabolic fluxes in living cells. It has become a standard tool in many labs for quantifying cell physiology, e.g. in metabolic engineering, systems biology, biotechnology, and biomedical research. With the increasing number of 13C-MFA studies published each year, it is now ever more important to provide practical guidelines for performing and publishing 13C-MFA studies so that quality is not sacrificed as the number of publications increases. The main purpose of this paper is to provide an overview of good practices in 13C-MFA, which can eventually be used as minimum data standards for publishing 13C-MFA studies. The motivation for this work is two-fold: (1) currently, there is no general consensus among researchers and journal editors as to what minimum data standards should be required for publishing 13C-MFA studies; as a result, there are great discrepancies in terms of quality and consistency; and (2) there is a growing number of studies that cannot be reproduced or verified independently due to incomplete information provided in these publications. This creates confusion, e.g. when trying to reconcile conflicting results, and hinders progress in the field. Here, we review current status in the 13C-MFA field and highlight some of the shortcomings with regards to 13C-MFA publications. We then propose a checklist that encompasses good practices in 13C-MFA. We hope that these guidelines will be a valuable resource for the community and allow 13C-flux studies to be more easily reproduced and accessed by others in the future. PMID:24025367

  7. Amino Acid Flux from Metabolic Network Benefits Protein Translation: the Role of Resource Availability.

    PubMed

    Hu, Xiao-Pan; Yang, Yi; Ma, Bin-Guang

    2015-06-09

    Protein translation is a central step in gene expression and affected by many factors such as codon usage bias, mRNA folding energy and tRNA abundance. Despite intensive previous studies, how metabolic amino acid supply correlates with protein translation efficiency remains unknown. In this work, we estimated the amino acid flux from metabolic network for each protein in Escherichia coli and Saccharomyces cerevisiae by using Flux Balance Analysis. Integrated with the mRNA expression level, protein abundance and ribosome profiling data, we provided a detailed description of the role of amino acid supply in protein translation. Our results showed that amino acid supply positively correlates with translation efficiency and ribosome density. Moreover, with the rank-based regression model, we found that metabolic amino acid supply facilitates ribosome utilization. Based on the fact that the ribosome density change of well-amino-acid-supplied genes is smaller than poorly-amino-acid-supply genes under amino acid starvation, we reached the conclusion that amino acid supply may buffer ribosome density change against amino acid starvation and benefit maintaining a relatively stable translation environment. Our work provided new insights into the connection between metabolic amino acid supply and protein translation process by revealing a new regulation strategy that is dependent on resource availability.

  8. A Diel Flux Balance Model Captures Interactions between Light and Dark Metabolism during Day-Night Cycles in C3 and Crassulacean Acid Metabolism Leaves.

    PubMed

    Cheung, C Y Maurice; Poolman, Mark G; Fell, David A; Ratcliffe, R George; Sweetlove, Lee J

    2014-06-01

    Although leaves have to accommodate markedly different metabolic flux patterns in the light and the dark, models of leaf metabolism based on flux-balance analysis (FBA) have so far been confined to consideration of the network under continuous light. An FBA framework is presented that solves the two phases of the diel cycle as a single optimization problem and, thus, provides a more representative model of leaf metabolism. The requirement to support continued export of sugar and amino acids from the leaf during the night and to meet overnight cellular maintenance costs forces the model to set aside stores of both carbon and nitrogen during the day. With only minimal constraints, the model successfully captures many of the known features of C 3 leaf metabolism, including the recently discovered role of citrate synthesis and accumulation in the night as a precursor for the provision of carbon skeletons for amino acid synthesis during the day. The diel FBA model can be applied to other temporal separations, such as that which occurs in Crassulacean acid metabolism (CAM) photosynthesis, allowing a system-level analysis of the energetics of CAM. The diel model predicts that there is no overall energetic advantage to CAM, despite the potential for suppression of photorespiration through CO 2 concentration. Moreover, any savings in enzyme machinery costs through suppression of photorespiration are likely to be offset by the higher flux demand of the CAM cycle. It is concluded that energetic or nitrogen use considerations are unlikely to be evolutionary drivers for CAM photosynthesis. © 2014 American Society of Plant Biologists. All Rights Reserved.

  9. System-Wide Quantitative Proteomics of the Metabolic Syndrome in Mice: Genotypic and Dietary Effects.

    PubMed

    Terfve, Camille; Sabidó, Eduard; Wu, Yibo; Gonçalves, Emanuel; Choi, Meena; Vaga, Stefania; Vitek, Olga; Saez-Rodriguez, Julio; Aebersold, Ruedi

    2017-02-03

    Advances in mass spectrometry have made the quantitative measurement of proteins across multiple samples a reality, allowing for the study of complex biological systems such as the metabolic syndrome. Although the deregulation of lipid metabolism and increased hepatic storage of triacylglycerides are known to play a part in the onset of the metabolic syndrome, its molecular basis and dependency on dietary and genotypic factors are poorly characterized. Here, we used an experimental design with two different mouse strains and dietary and metabolic perturbations to generate a compendium of quantitative proteome data using three mass spectrometric techniques. The data reproduce known properties of the metabolic system and indicate differential molecular adaptation of the two mouse strains to perturbations, contributing to a better understanding of the metabolic syndrome. We show that high-quality, high-throughput proteomic data sets provide an unbiased broad overview of the behavior of complex systems after perturbation.

  10. Quantitative trait loci and metabolic pathways

    PubMed Central

    McMullen, M. D.; Byrne, P. F.; Snook, M. E.; Wiseman, B. R.; Lee, E. A.; Widstrom, N. W.; Coe, E. H.

    1998-01-01

    The interpretation of quantitative trait locus (QTL) studies is limited by the lack of information on metabolic pathways leading to most economic traits. Inferences about the roles of the underlying genes with a pathway or the nature of their interaction with other loci are generally not possible. An exception is resistance to the corn earworm Helicoverpa zea (Boddie) in maize (Zea mays L.) because of maysin, a C-glycosyl flavone synthesized in silks via a branch of the well characterized flavonoid pathway. Our results using flavone synthesis as a model QTL system indicate: (i) the importance of regulatory loci as QTLs, (ii) the importance of interconnecting biochemical pathways on product levels, (iii) evidence for “channeling” of intermediates, allowing independent synthesis of related compounds, (iv) the utility of QTL analysis in clarifying the role of specific genes in a biochemical pathway, and (v) identification of a previously unknown locus on chromosome 9S affecting flavone level. A greater understanding of the genetic basis of maysin synthesis and associated corn earworm resistance should lead to improved breeding strategies. More broadly, the insights gained in relating a defined genetic and biochemical pathway affecting a quantitative trait should enhance interpretation of the biological basis of variation for other quantitative traits. PMID:9482823

  11. Metabolic fuels: regulating fluxes to select mix.

    PubMed

    Weber, Jean-Michel

    2011-01-15

    Animals must regulate the fluxes of multiple fuels to support changing metabolic rates that result from variation in physiological circumstances. The aim of fuel selection strategies is to exploit the advantages of individual substrates while minimizing the impact of disadvantages. All exercising mammals share a general pattern of fuel selection: at the same %V(O(2,max)) they oxidize the same ratio of lipids to carbohydrates. However, highly aerobic species rely more on intramuscular fuels because energy supply from the circulation is constrained by trans-sarcolemmal transfer. Fuel selection is performed by recruiting different muscles, different fibers within the same muscles or different pathways within the same fibers. Electromyographic analyses show that shivering humans can modulate carbohydrate oxidation either through the selective recruitment of type II fibers within the same muscles or by regulating pathway recruitment within type I fibers. The selection patterns of shivering and exercise are different: at the same %V(O(2,max)), a muscle producing only heat (shivering) or significant movement (exercise) strikes a different balance between lipid and carbohydrate oxidation. Long-distance migrants provide an excellent model to characterize how to increase maximal substrate fluxes. High lipid fluxes are achieved through the coordinated upregulation of mobilization, transport and oxidation by activating enzymes, lipid-solubilizing proteins and membrane transporters. These endurance athletes support record lipolytic rates in adipocytes, use lipoprotein shuttles to accelerate transport and show increased capacity for lipid oxidation in muscle mitochondria. Some migrant birds use dietary omega-3 fatty acids as performance-enhancing agents to boost their ability to process lipids. These dietary fatty acids become incorporated in membrane phospholipids and bind to peroxisome proliferator-activated receptors to activate membrane proteins and modify gene expression.

  12. Easy regulation of metabolic flux in Escherichia coli using an endogenous type I-E CRISPR-Cas system.

    PubMed

    Chang, Yizhao; Su, Tianyuan; Qi, Qingsheng; Liang, Quanfeng

    2016-11-15

    Clustered regularly interspaced short palindromic repeats interference (CRISPRi) is a recently developed powerful tool for gene regulation. In Escherichia coli, the type I CRISPR system expressed endogenously shall be easy for internal regulation without causing metabolic burden in compared with the widely used type II system, which expressed dCas9 as an additional plasmid. By knocking out cas3 and activating the expression of CRISPR-associated complex for antiviral defense (Cascade), we constructed a native CRISPRi system in E. coli. Downregulation of the target gene from 6 to 82% was demonstrated using green fluorescent protein. Regulation of the citrate synthase gene (gltA) in the TCA cycle affected host metabolism. The effect of metabolic flux regulation was demonstrated by the poly-3-hydroxbutyrate (PHB) accumulation in vivo. By regulating native gltA in E. coli using an engineered endogenous type I-E CRISPR system, we redirected metabolic flux from the central metabolic pathway to the PHB synthesis pathway. This study demonstrated that the endogenous type I-E CRISPR-Cas system is an easy and effective method for regulating internal metabolic pathways, which is useful for product synthesis.

  13. Analysis of Metabolic Pathways and Fluxes in a Newly Discovered Thermophilic and Ethanol-Tolerant Geobacillus Strain

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Tang, Yinjie J.; Sapra, Rajat; Joyner, Dominique

    2009-01-20

    A recently discovered thermophilic bacterium, Geobacillus thermoglucosidasius M10EXG, ferments a range of C5 (e.g., xylose) and C6 sugars (e.g., glucose) and istolerant to high ethanol concentrations (10percent, v/v). We have investigated the central metabolism of this bacterium using both in vitro enzyme assays and 13C-based flux analysis to provide insights into the physiological properties of this extremophile and explore its metabolism for bio-ethanol or other bioprocess applications. Our findings show that glucose metabolism in G. thermoglucosidasius M10EXG proceeds via glycolysis, the pentose phosphate pathway, and the TCA cycle; the Entner?Doudoroff pathway and transhydrogenase activity were not detected. Anaplerotic reactions (includingmore » the glyoxylate shunt, pyruvate carboxylase, and phosphoenolpyruvate carboxykinase) were active, but fluxes through those pathways could not be accuratelydetermined using amino acid labeling. When growth conditions were switched from aerobic to micro-aerobic conditions, fluxes (based on a normalized glucose uptake rate of 100 units (g DCW)-1 h-1) through the TCA cycle and oxidative pentose phosphate pathway were reduced from 64+-3 to 25+-2 and from 30+-2 to 19+-2, respectively. The carbon flux under micro-aerobic growth was directed formate. Under fully anerobic conditions, G. thermoglucosidasius M10EXG used a mixed acid fermentation process and exhibited a maximum ethanol yield of 0.38+-0.07 mol mol-1 glucose. In silico flux balance modeling demonstrates that lactate and acetate production from G. thermoglucosidasius M10EXG reduces the maximum ethanol yieldby approximately threefold, thus indicating that both pathways should be modified to maximize ethanol production.« less

  14. Quantitative Analysis of Cellular Metabolic Dissipative, Self-Organized Structures

    PubMed Central

    de la Fuente, Ildefonso Martínez

    2010-01-01

    One of the most important goals of the postgenomic era is understanding the metabolic dynamic processes and the functional structures generated by them. Extensive studies during the last three decades have shown that the dissipative self-organization of the functional enzymatic associations, the catalytic reactions produced during the metabolite channeling, the microcompartmentalization of these metabolic processes and the emergence of dissipative networks are the fundamental elements of the dynamical organization of cell metabolism. Here we present an overview of how mathematical models can be used to address the properties of dissipative metabolic structures at different organizational levels, both for individual enzymatic associations and for enzymatic networks. Recent analyses performed with dissipative metabolic networks have shown that unicellular organisms display a singular global enzymatic structure common to all living cellular organisms, which seems to be an intrinsic property of the functional metabolism as a whole. Mathematical models firmly based on experiments and their corresponding computational approaches are needed to fully grasp the molecular mechanisms of metabolic dynamical processes. They are necessary to enable the quantitative and qualitative analysis of the cellular catalytic reactions and also to help comprehend the conditions under which the structural dynamical phenomena and biological rhythms arise. Understanding the molecular mechanisms responsible for the metabolic dissipative structures is crucial for unraveling the dynamics of cellular life. PMID:20957111

  15. The nutritional status of Methanosarcina acetivorans regulates glycogen metabolism and gluconeogenesis and glycolysis fluxes.

    PubMed

    Santiago-Martínez, Michel Geovanni; Encalada, Rusely; Lira-Silva, Elizabeth; Pineda, Erika; Gallardo-Pérez, Juan Carlos; Reyes-García, Marco Antonio; Saavedra, Emma; Moreno-Sánchez, Rafael; Marín-Hernández, Alvaro; Jasso-Chávez, Ricardo

    2016-05-01

    Gluconeogenesis is an essential pathway in methanogens because they are unable to use exogenous hexoses as carbon source for cell growth. With the aim of understanding the regulatory mechanisms of central carbon metabolism in Methanosarcina acetivorans, the present study investigated gene expression, the activities and metabolic regulation of key enzymes, metabolite contents and fluxes of gluconeogenesis, as well as glycolysis and glycogen synthesis/degradation pathways. Cells were grown with methanol as a carbon source. Key enzymes were kinetically characterized at physiological pH/temperature. Active consumption of methanol during exponential cell growth correlated with significant methanogenesis, gluconeogenic flux and steady glycogen synthesis. After methanol exhaustion, cells reached the stationary growth phase, which correlated with the rise in glycogen consumption and glycolytic flux, decreased methanogenesis, negligible acetate production and an absence of gluconeogenesis. Elevated activities of carbon monoxide dehydrogenase/acetyl-CoA synthetase complex and pyruvate: ferredoxin oxidoreductase suggested the generation of acetyl-CoA and pyruvate for glycogen synthesis. In the early stationary growth phase, the transcript contents and activities of pyruvate phosphate dikinase, fructose 1,6-bisphosphatase and glycogen synthase decreased, whereas those of glycogen phosphorylase, ADP-phosphofructokinase and pyruvate kinase increased. Therefore, glycogen and gluconeogenic metabolites were synthesized when an external carbon source was provided. Once such a carbon source became depleted, glycolysis and methanogenesis fed by glycogen degradation provided the ATP supply. Weak inhibition of key enzymes by metabolites suggested that the pathways evaluated were mainly transcriptionally regulated. Because glycogen metabolism and glycolysis/gluconeogenesis are not present in all methanogens, the overall data suggest that glycogen storage might represent an environmental

  16. IsoDesign: a software for optimizing the design of 13C-metabolic flux analysis experiments.

    PubMed

    Millard, Pierre; Sokol, Serguei; Letisse, Fabien; Portais, Jean-Charles

    2014-01-01

    The growing demand for (13) C-metabolic flux analysis ((13) C-MFA) in the field of metabolic engineering and systems biology is driving the need to rationalize expensive and time-consuming (13) C-labeling experiments. Experimental design is a key step in improving both the number of fluxes that can be calculated from a set of isotopic data and the precision of flux values. We present IsoDesign, a software that enables these parameters to be maximized by optimizing the isotopic composition of the label input. It can be applied to (13) C-MFA investigations using a broad panel of analytical tools (MS, MS/MS, (1) H NMR, (13) C NMR, etc.) individually or in combination. It includes a visualization module to intuitively select the optimal label input depending on the biological question to be addressed. Applications of IsoDesign are described, with an example of the entire (13) C-MFA workflow from the experimental design to the flux map including important practical considerations. IsoDesign makes the experimental design of (13) C-MFA experiments more accessible to a wider biological community. IsoDesign is distributed under an open source license at http://metasys.insa-toulouse.fr/software/isodes/ © 2013 Wiley Periodicals, Inc.

  17. Metabolic modelling and flux analysis of microorganisms from the Atacama Desert used in biotechnological processes.

    PubMed

    Razmilic, Valeria; Castro, Jean Franco; Marchant, Francisca; Asenjo, Juan A; Andrews, Barbara

    2018-02-02

    Metabolic modelling is a useful tool that enables the rational design of metabolic engineering experiments and the study of the unique capabilities of biotechnologically important microorganisms. The extreme abiotic conditions of the Atacama Desert have selected microbial diversity with exceptional characteristics that can be applied in the mining industry for bioleaching processes and for production of specialised metabolites with antimicrobial, antifungal, antiviral, antitumoral, among other activities. In this review we summarise the scientific data available of the use of metabolic modelling and flux analysis to improve the performance of Atacama Desert microorganisms in biotechnological applications.

  18. Maximum entropy modeling of metabolic networks by constraining growth-rate moments predicts coexistence of phenotypes

    NASA Astrophysics Data System (ADS)

    De Martino, Daniele

    2017-12-01

    In this work maximum entropy distributions in the space of steady states of metabolic networks are considered upon constraining the first and second moments of the growth rate. Coexistence of fast and slow phenotypes, with bimodal flux distributions, emerges upon considering control on the average growth (optimization) and its fluctuations (heterogeneity). This is applied to the carbon catabolic core of Escherichia coli where it quantifies the metabolic activity of slow growing phenotypes and it provides a quantitative map with metabolic fluxes, opening the possibility to detect coexistence from flux data. A preliminary analysis on data for E. coli cultures in standard conditions shows degeneracy for the inferred parameters that extend in the coexistence region.

  19. Enzyme clustering accelerates processing of intermediates through metabolic channeling

    PubMed Central

    Castellana, Michele; Wilson, Maxwell Z.; Xu, Yifan; Joshi, Preeti; Cristea, Ileana M.; Rabinowitz, Joshua D.; Gitai, Zemer; Wingreen, Ned S.

    2015-01-01

    We present a quantitative model to demonstrate that coclustering multiple enzymes into compact agglomerates accelerates the processing of intermediates, yielding the same efficiency benefits as direct channeling, a well-known mechanism in which enzymes are funneled between enzyme active sites through a physical tunnel. The model predicts the separation and size of coclusters that maximize metabolic efficiency, and this prediction is in agreement with previously reported spacings between coclusters in mammalian cells. For direct validation, we study a metabolic branch point in Escherichia coli and experimentally confirm the model prediction that enzyme agglomerates can accelerate the processing of a shared intermediate by one branch, and thus regulate steady-state flux division. Our studies establish a quantitative framework to understand coclustering-mediated metabolic channeling and its application to both efficiency improvement and metabolic regulation. PMID:25262299

  20. A genome-scale metabolic flux model of Escherichia coli K–12 derived from the EcoCyc database

    PubMed Central

    2014-01-01

    Background Constraint-based models of Escherichia coli metabolic flux have played a key role in computational studies of cellular metabolism at the genome scale. We sought to develop a next-generation constraint-based E. coli model that achieved improved phenotypic prediction accuracy while being frequently updated and easy to use. We also sought to compare model predictions with experimental data to highlight open questions in E. coli biology. Results We present EcoCyc–18.0–GEM, a genome-scale model of the E. coli K–12 MG1655 metabolic network. The model is automatically generated from the current state of EcoCyc using the MetaFlux software, enabling the release of multiple model updates per year. EcoCyc–18.0–GEM encompasses 1445 genes, 2286 unique metabolic reactions, and 1453 unique metabolites. We demonstrate a three-part validation of the model that breaks new ground in breadth and accuracy: (i) Comparison of simulated growth in aerobic and anaerobic glucose culture with experimental results from chemostat culture and simulation results from the E. coli modeling literature. (ii) Essentiality prediction for the 1445 genes represented in the model, in which EcoCyc–18.0–GEM achieves an improved accuracy of 95.2% in predicting the growth phenotype of experimental gene knockouts. (iii) Nutrient utilization predictions under 431 different media conditions, for which the model achieves an overall accuracy of 80.7%. The model’s derivation from EcoCyc enables query and visualization via the EcoCyc website, facilitating model reuse and validation by inspection. We present an extensive investigation of disagreements between EcoCyc–18.0–GEM predictions and experimental data to highlight areas of interest to E. coli modelers and experimentalists, including 70 incorrect predictions of gene essentiality on glucose, 80 incorrect predictions of gene essentiality on glycerol, and 83 incorrect predictions of nutrient utilization. Conclusion Significant

  1. Assessment of energetic costs of AhR activation by β-naphthoflavone in rainbow trout (Oncorhynchus mykiss) hepatocytes using metabolic flux analysis

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Nault, Rance, E-mail: naultran@msu.edu; Abdul-Fattah, Hiba; Mironov, Gleb G.

    2013-08-15

    Exposure to environmental contaminants such as activators of the aryl hydrocarbon receptor (AhR) leads to the induction of defense and detoxification mechanisms. While these mechanisms allow organisms to metabolize and excrete at least some of these environmental contaminants, it has been proposed that these mechanisms lead to significant energetic challenges. This study tests the hypothesis that activation of the AhR by the model agonist β-naphthoflavone (βNF) results in increased energetic costs in rainbow trout (Oncorhynchus mykiss) hepatocytes. To address this hypothesis, we employed traditional biochemical approaches to examine energy allocation and metabolism including the adenylate energy charge (AEC), protein synthesismore » rates, Na{sup +}/K{sup +}-ATPase activity, and enzyme activities. Moreover, we have used for the first time in a fish cell preparation, metabolic flux analysis (MFA) an in silico approach for the estimation of intracellular metabolic fluxes. Exposure of trout hepatocytes to 1 μM βNF for 48 h did not alter hepatocyte AEC, protein synthesis, or Na{sup +}/K{sup +}-ATPase activity but did lead to sparing of glycogen reserves and changes in activities of alanine aminotransferase and citrate synthase suggesting altered metabolism. Conversely, MFA did not identify altered metabolic fluxes, although we do show that the dynamic metabolism of isolated trout hepatocytes poses a significant challenge for this type of approach which should be considered in future studies. - Highlights: • Energetic costs of AhR activation by βNF was examined in rainbow trout hepatocytes. • Metabolic flux analysis was performed on a fish cell preparation for the first time. • Exposure to βNF led to sparing of glycogen reserves and altered enzyme activities. • Adenylate energy charge was maintained despite temporal changes in metabolism.« less

  2. Metabolic pathway analysis of Scheffersomyces (Pichia) stipitis: effect of oxygen availability on ethanol synthesis and flux distributions.

    PubMed

    Unrean, Pornkamol; Nguyen, Nhung H A

    2012-06-01

    Elementary mode analysis (EMA) identifies all possible metabolic states of the cell metabolic network. Investigation of these states can provide a detailed insight into the underlying metabolism in the cell. In this study, the flux states of Scheffersomyces (Pichia) stipitis metabolism were examined. It was shown that increasing oxygen levels led to a decrease of ethanol synthesis. This trend was confirmed by experimental evaluation of S. stipitis in glucose-xylose fermentation. The oxygen transfer rate for an optimal ethanol production was 1.8 mmol/l/h, which gave the ethanol yield of 0.40 g/g and the ethanol productivity of 0.25 g/l/h. For a better understanding of the cell's regulatory mechanism in response to oxygenation levels, EMA was used to examine metabolic flux patterns under different oxygen levels. Up- and downregulation of enzymes in the network during the change of culturing condition from oxygen limitation to oxygen sufficiency were identified. The results indicated the flexibility of S. stipitis metabolism to cope with oxygen availability. In addition, relevant genetic targets towards improved ethanol-producing strains under all oxygenation levels were identified. These targeted genes limited the metabolic functionality of the cell to function according to the most efficient ethanol synthesis pathways. The presented approach is promising and can contribute to the development of culture optimization and strain engineers for improved lignocellulosic ethanol production by S. stipitis.

  3. A Quantitative Study of Oxygen as a Metabolic Regulator

    NASA Technical Reports Server (NTRS)

    Radhakrishnan, Krishnan; LaManna, Joseph C.; Cabrera, Marco E.

    1999-01-01

    An acute reduction in oxygen (O2) delivery to a tissue is generally associated with a decrease in phosphocreatine, increases in ADP, NADH/NAD, and inorganic phosphate, increased rates of glycolysis and lactate production, and reduced rates of pyruvate and fatty acid oxidation. However, given the complexity of the human bioenergetic system and its components, it is difficult to determine quantitatively how cellular metabolic processes interact to maintain ATP homeostasis during stress (e.g., hypoxia, ischemia, and exercise). Of special interest is the determination of mechanisms relating tissue oxygenation to observed metabolic responses at the tissue, organ, and whole body levels and the quantification of how changes in tissue O2 availability affect the pathways of ATP synthesis and the metabolites that control these pathways. In this study, we extend a previously developed mathematical model of human bioenergetics to provide a physicochemical framework that permits quantitative understanding of O2 as a metabolic regulator. Specifically, the enhancement permits studying the effects of variations in tissue oxygenation and in parameters controlling the rate of cellular respiration on glycolysis, lactate production, and pyruvate oxidation. The whole body is described as a bioenergetic system consisting of metabolically distinct tissue/organ subsystems that exchange materials with the blood. In order to study the dynamic response of each subsystem to stimuli, we solve the ordinary differential equations describing the temporal evolution of metabolite levels, given the initial concentrations. The solver used in the present study is the packaged code LSODE, as implemented in the NASA Lewis kinetics and sensitivity analysis code, LSENS. A major advantage of LSENS is the efficient procedures supporting systematic sensitivity analysis, which provides the basic methods for studying parameter sensitivities (i.e., changes in model behavior due to parameter variation

  4. 13 C Flux Analysis Reveals that Rebalancing Medium Amino Acid Composition can Reduce Ammonia Production while Preserving Central Carbon Metabolism of CHO Cell Cultures.

    PubMed

    McAtee Pereira, Allison G; Walther, Jason L; Hollenbach, Myles; Young, Jamey D

    2018-02-06

    13 C metabolic flux analysis (MFA) provides a rigorous approach to quantify intracellular metabolism of industrial cell lines. In this study, 13 C MFA was used to characterize the metabolic response of Chinese hamster ovary (CHO) cells to a novel medium variant designed to reduce ammonia production. Ammonia inhibits growth and viability of CHO cell cultures, alters glycosylation of recombinant proteins, and enhances product degradation. Ammonia production was reduced by manipulating the amino acid composition of the culture medium; specifically, glutamine, glutamate, asparagine, aspartate, and serine levels were adjusted. Parallel 13 C flux analysis experiments determined that, while ammonia production decreased by roughly 40%, CHO cell metabolic phenotype, growth, viability, and monoclonal antibody (mAb) titer were not significantly altered by the changes in media composition. This study illustrates how 13 C flux analysis can be applied to assess the metabolic effects of media manipulations on mammalian cell cultures. The analysis revealed that adjusting the amino acid composition of CHO cell culture media can effectively reduce ammonia production while preserving fluxes throughout central carbon metabolism. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  5. Quantitative petri net model of gene regulated metabolic networks in the cell.

    PubMed

    Chen, Ming; Hofestädt, Ralf

    2011-01-01

    A method to exploit hybrid Petri nets (HPN) for quantitatively modeling and simulating gene regulated metabolic networks is demonstrated. A global kinetic modeling strategy and Petri net modeling algorithm are applied to perform the bioprocess functioning and model analysis. With the model, the interrelations between pathway analysis and metabolic control mechanism are outlined. Diagrammatical results of the dynamics of metabolites are simulated and observed by implementing a HPN tool, Visual Object Net ++. An explanation of the observed behavior of the urea cycle is proposed to indicate possibilities for metabolic engineering and medical care. Finally, the perspective of Petri nets on modeling and simulation of metabolic networks is discussed.

  6. Metabolic Flux Analysis in Isotope Labeling Experiments Using the Adjoint Approach.

    PubMed

    Mottelet, Stephane; Gaullier, Gil; Sadaka, Georges

    2017-01-01

    Comprehension of metabolic pathways is considerably enhanced by metabolic flux analysis (MFA-ILE) in isotope labeling experiments. The balance equations are given by hundreds of algebraic (stationary MFA) or ordinary differential equations (nonstationary MFA), and reducing the number of operations is therefore a crucial part of reducing the computation cost. The main bottleneck for deterministic algorithms is the computation of derivatives, particularly for nonstationary MFA. In this article, we explain how the overall identification process may be speeded up by using the adjoint approach to compute the gradient of the residual sum of squares. The proposed approach shows significant improvements in terms of complexity and computation time when it is compared with the usual (direct) approach. Numerical results are obtained for the central metabolic pathways of Escherichia coli and are validated against reference software in the stationary case. The methods and algorithms described in this paper are included in the sysmetab software package distributed under an Open Source license at http://forge.scilab.org/index.php/p/sysmetab/.

  7. Untargeted Metabolic Quantitative Trait Loci Analyses Reveal a Relationship between Primary Metabolism and Potato Tuber Quality1[W][OA

    PubMed Central

    Carreno-Quintero, Natalia; Acharjee, Animesh; Maliepaard, Chris; Bachem, Christian W.B.; Mumm, Roland; Bouwmeester, Harro; Visser, Richard G.F.; Keurentjes, Joost J.B.

    2012-01-01

    Recent advances in -omics technologies such as transcriptomics, metabolomics, and proteomics along with genotypic profiling have permitted dissection of the genetics of complex traits represented by molecular phenotypes in nonmodel species. To identify the genetic factors underlying variation in primary metabolism in potato (Solanum tuberosum), we have profiled primary metabolite content in a diploid potato mapping population, derived from crosses between S. tuberosum and wild relatives, using gas chromatography-time of flight-mass spectrometry. In total, 139 polar metabolites were detected, of which we identified metabolite quantitative trait loci for approximately 72% of the detected compounds. In order to obtain an insight into the relationships between metabolic traits and classical phenotypic traits, we also analyzed statistical associations between them. The combined analysis of genetic information through quantitative trait locus coincidence and the application of statistical learning methods provide information on putative indicators associated with the alterations in metabolic networks that affect complex phenotypic traits. PMID:22223596

  8. Updates to a 13C metabolic flux analysis model for evaluating energy metabolism in cultured cerebellar granule neurons from neonatal rats.

    PubMed

    Jekabsons, Mika B; Gebril, Hoda M; Wang, Yan-Hong; Avula, Bharathi; Khan, Ikhlas A

    2017-10-01

    A hexose phosphate recycling model previously developed to infer fluxes through the major glucose consuming pathways in cultured cerebellar granule neurons (CGNs) from neonatal rats metabolizing [1,2- 13 C 2 ]glucose was revised by considering reverse flux through the non-oxidative pentose phosphate pathway (PPP) and symmetrical succinate oxidation within the tricarboxylic acid (TCA) cycle. The model adjusts three flux ratios to effect 13 C distribution in the hexose, pentose, and triose phosphate pools, and in TCA cycle malate to minimize the error between predicted and measured 13 C labeling in exported lactate (i.e., unlabeled, single-, double-, and triple-labeled; M, M1, M2, and M3, respectively). Inclusion of reverse non-oxidative PPP flux substantially increased the number of calculations but ultimately had relatively minor effects on the labeling of glycolytic metabolites. From the error-minimized solution in which the predicted M-M3 lactate differed by 0.49% from that measured by liquid chromatography-triple quadrupole mass spectrometry, the neurons exhibited negligible forward non-oxidative PPP flux. Thus, no glucose was used by the pentose cycle despite explicit consideration of hexose phosphate recycling. Mitochondria consumed only 16% of glucose while 45% was exported as lactate by aerobic glycolysis. The remaining 39% of glucose was shunted to pentose phosphates presumably for de novo nucleotide synthesis, but the proportion metabolized through the oxidative PPP vs. the reverse non-oxidative PPP could not be determined. The lactate exported as M1 (2.5%) and M3 (1.2%) was attributed to malic enzyme, which was responsible for 7.8% of pyruvate production (vs. 92.2% by glycolysis). The updated model is more broadly applicable to different cell types by considering bi-directional flux through the non-oxidative PPP. Its application to cultured neurons utilizing glucose as the sole exogenous substrate has demonstrated substantial oxygen-independent glucose

  9. (13)C-metabolic flux analysis of lipid accumulation in the oleaginous fungus Mucor circinelloides.

    PubMed

    Zhao, Lina; Zhang, Huaiyuan; Wang, Liping; Chen, Haiqin; Chen, Yong Q; Chen, Wei; Song, Yuanda

    2015-12-01

    The oleaginous fungus Mucor circinelloides is of industrial interest because it can produce high levels of polyunsaturated fatty acid γ-linolenic acid. M. circinelloides CBS 277.49 is able to accumulate less than 15% of cell dry weight as lipids, while M. circinelloides WJ11 can accumulate lipid up to 36%. In order to better understand the mechanisms behind the differential lipid accumulation in these two strains, tracer experiments with (13)C-glucose were performed with the growth of M. circinelloides and subsequent gas chromatography-mass spectrometric detection of (13)C-patterns in proteinogenic amino acids was carried out to identify the metabolic network topology and estimate intracellular fluxes. Our results showed that the high oleaginous strain WJ11 had higher flux of pentose phosphate pathway and malic enzyme, lower flux in tricarboxylic acid cycle, higher flux in glyoxylate cycle and ATP: citrate lyase, together, it might provide more NADPH and substrate acetyl-CoA for fatty acid synthesis. Copyright © 2015 Elsevier Ltd. All rights reserved.

  10. In vivo nuclear magnetic resonance studies of hepatic methoxyflurane metabolism. II. A reevaluation of hepatic metabolic pathways.

    PubMed

    Selinsky, B S; Perlman, M E; London, R E

    1988-05-01

    Methoxyflurane (2,2-dichloro-1,1-difluoro-ethyl methyl ether) is believed to be metabolized via two convergent metabolic pathways. The relative flux through these two metabolic pathways has been investigated using a combination of in vivo surface coil NMR techniques and in vitro analyses of urinary metabolites. Analysis of the measured concentrations of inorganic fluoride, oxalate, and methoxydifluoroacetate in the urine of methoxyflurane-treated rats for 4 days after anesthesia indicates that the anesthetic is metabolized primarily via dechlorination to yield methoxydifluoroacetate. The methoxydifluoroacetate is largely excreted without further metabolism, although a small percentage of this metabolite is broken down to yield fluoride and oxalate, as determined by urine analysis of rats dosed with synthetic methoxydifluoroacetate. At early times after methoxyflurane exposure, the relative concentrations of methoxyflurane metabolites indicate that a significant fraction of the metabolic flux occurs via a different pathway, presumably demethylation, to yield dichloroacetate as an intermediate. Direct analysis of dichloroacetate in the urine using water-suppressed proton NMR indicates that the level of this metabolite is below the detection threshold of the method. Measurements made on the urine of rats dosed directly with dichloroacetate indicate that this compound is quickly metabolized, and dichloroacetate levels in urine are again found to be below the detection threshold. These results demonstrate the quantitative importance of the dechlorination pathway in the metabolism of methoxyflurane in rats.

  11. Multi-scale modeling of Arabidopsis thaliana response to different CO2 conditions: From gene expression to metabolic flux.

    PubMed

    Liu, Lin; Shen, Fangzhou; Xin, Changpeng; Wang, Zhuo

    2016-01-01

    Multi-scale investigation from gene transcript level to metabolic activity is important to uncover plant response to environment perturbation. Here we integrated a genome-scale constraint-based metabolic model with transcriptome data to explore Arabidopsis thaliana response to both elevated and low CO2 conditions. The four condition-specific models from low to high CO2 concentrations show differences in active reaction sets, enriched pathways for increased/decreased fluxes, and putative post-transcriptional regulation, which indicates that condition-specific models are necessary to reflect physiological metabolic states. The simulated CO2 fixation flux at different CO2 concentrations is consistent with the measured Assimilation-CO2intercellular curve. Interestingly, we found that reactions in primary metabolism are affected most significantly by CO2 perturbation, whereas secondary metabolic reactions are not influenced a lot. The changes predicted in key pathways are consistent with existing knowledge. Another interesting point is that Arabidopsis is required to make stronger adjustment on metabolism to adapt to the more severe low CO2 stress than elevated CO2 . The challenges of identifying post-transcriptional regulation could also be addressed by the integrative model. In conclusion, this innovative application of multi-scale modeling in plants demonstrates potential to uncover the mechanisms of metabolic response to different conditions. © 2015 Institute of Botany, Chinese Academy of Sciences.

  12. Quantitative rates of brain glucose metabolism distinguish minimally conscious from vegetative state patients.

    PubMed

    Stender, Johan; Kupers, Ron; Rodell, Anders; Thibaut, Aurore; Chatelle, Camille; Bruno, Marie-Aurélie; Gejl, Michael; Bernard, Claire; Hustinx, Roland; Laureys, Steven; Gjedde, Albert

    2015-01-01

    The differentiation of the vegetative or unresponsive wakefulness syndrome (VS/UWS) from the minimally conscious state (MCS) is an important clinical issue. The cerebral metabolic rate of glucose (CMRglc) declines when consciousness is lost, and may reveal the residual cognitive function of these patients. However, no quantitative comparisons of cerebral glucose metabolism in VS/UWS and MCS have yet been reported. We calculated the regional and whole-brain CMRglc of 41 patients in the states of VS/UWS (n=14), MCS (n=21) or emergence from MCS (EMCS, n=6), and healthy volunteers (n=29). Global cortical CMRglc in VS/UWS and MCS averaged 42% and 55% of normal, respectively. Differences between VS/UWS and MCS were most pronounced in the frontoparietal cortex, at 42% and 60% of normal. In brainstem and thalamus, metabolism declined equally in the two conditions. In EMCS, metabolic rates were indistinguishable from those of MCS. Ordinal logistic regression predicted that patients are likely to emerge into MCS at CMRglc above 45% of normal. Receiver-operating characteristics showed that patients in MCS and VS/UWS can be differentiated with 82% accuracy, based on cortical metabolism. Together these results reveal a significant correlation between whole-brain energy metabolism and level of consciousness, suggesting that quantitative values of CMRglc reveal consciousness in severely brain-injured patients.

  13. Capturing the essence of a metabolic network: a flux balance analysis approach.

    PubMed

    Murabito, Ettore; Simeonidis, Evangelos; Smallbone, Kieran; Swinton, Jonathan

    2009-10-07

    As genome-scale metabolic reconstructions emerge, tools to manage their size and complexity will be increasingly important. Flux balance analysis (FBA) is a constraint-based approach widely used to study the metabolic capabilities of cellular or subcellular systems. FBA problems are highly underdetermined and many different phenotypes can satisfy any set of constraints through which the metabolic system is represented. Two of the main concerns in FBA are exploring the space of solutions for a given metabolic network and finding a specific phenotype which is representative for a given task such as maximal growth rate. Here, we introduce a recursive algorithm suitable for overcoming both of these concerns. The method proposed is able to find the alternate optimal patterns of active reactions of an FBA problem and identify the minimal subnetwork able to perform a specific task as optimally as the whole. Our method represents an alternative to and an extension of other approaches conceived for exploring the space of solutions of an FBA problem. It may also be particularly helpful in defining a scaffold of reactions upon which to build up a dynamic model, when the important pathways of the system have not yet been well-defined.

  14. From Position-Specific Labeling to Environmental Fluxomics: Elucidating Biogeochemical Cycles from the Metabolic Perspective (BG Division Outstanding ECS Award Lecture)

    NASA Astrophysics Data System (ADS)

    Dippold, Michaela; Apostel, Carolin; Dijkstra, Paul; Kuzyakov, Yakov

    2017-04-01

    Understanding soil and sedimentary organic matter (SOM) dynamics is one of the most important challenges in biogeoscience. To disentangle the fluxes and transformations of C in soils a detailed knowledge on the biochemical pathways and its controlling factors is required. Biogeochemists' view on the C transformation of microorganisms in soil has rarely exceed a strongly simplified concept assuming that C gets either oxidized to CO2 via the microbial catabolism or incorporated into biomass via the microbial anabolism. Biochemists, however, thoroughly identified in the past decades the individual reactions of glycolysis, pentose-phosphate pathway and citric acid cycle underlying the microbial catabolism. At various points within that metabolic network the anabolic fluxes feeding biomass formation branch off. Recent studies on metabolic flux tracing by position-specific isotope labeling allowed tracing these C transformations in soils in situ, an approach which is qunatitatively complemented by metabolic flux modeling. This approach has reached new impact by the cutting-edge combination of position-specific 13C labeling with compound-specific isotope analysis of microbial biomarkers and metabolites which allows 1) tracing specific anabolic pathways in diverse microbial communities in soils and 2) identification of specific pathways of individual functional microbial groups. Thus, the combination of position-specific labeling, compound-specific isotope incorporation in biomarkers and quantitative metabolic flux modelling provide the toolbox for quantitative soil fluxomics. Our studies combining position-specific labeled glucose with amino sugar 13C analysis showed that up to 55% of glucose, incorporated into the glucose derivative glucosamine, first passed glycolysis before allocated back via gluconeogenesis. Similarly, glutamate-derived C is allocated via anaplerotic pathways towards fatty acid synthesis and in parallel to its oxidation in citric acid cycle. Thus

  15. Random sampling of elementary flux modes in large-scale metabolic networks.

    PubMed

    Machado, Daniel; Soons, Zita; Patil, Kiran Raosaheb; Ferreira, Eugénio C; Rocha, Isabel

    2012-09-15

    The description of a metabolic network in terms of elementary (flux) modes (EMs) provides an important framework for metabolic pathway analysis. However, their application to large networks has been hampered by the combinatorial explosion in the number of modes. In this work, we develop a method for generating random samples of EMs without computing the whole set. Our algorithm is an adaptation of the canonical basis approach, where we add an additional filtering step which, at each iteration, selects a random subset of the new combinations of modes. In order to obtain an unbiased sample, all candidates are assigned the same probability of getting selected. This approach avoids the exponential growth of the number of modes during computation, thus generating a random sample of the complete set of EMs within reasonable time. We generated samples of different sizes for a metabolic network of Escherichia coli, and observed that they preserve several properties of the full EM set. It is also shown that EM sampling can be used for rational strain design. A well distributed sample, that is representative of the complete set of EMs, should be suitable to most EM-based methods for analysis and optimization of metabolic networks. Source code for a cross-platform implementation in Python is freely available at http://code.google.com/p/emsampler. dmachado@deb.uminho.pt Supplementary data are available at Bioinformatics online.

  16. A Diel Flux Balance Model Captures Interactions between Light and Dark Metabolism during Day-Night Cycles in C3 and Crassulacean Acid Metabolism Leaves1[C][W][OPEN

    PubMed Central

    Cheung, C.Y. Maurice; Poolman, Mark G.; Fell, David. A.; Ratcliffe, R. George; Sweetlove, Lee J.

    2014-01-01

    Although leaves have to accommodate markedly different metabolic flux patterns in the light and the dark, models of leaf metabolism based on flux-balance analysis (FBA) have so far been confined to consideration of the network under continuous light. An FBA framework is presented that solves the two phases of the diel cycle as a single optimization problem and, thus, provides a more representative model of leaf metabolism. The requirement to support continued export of sugar and amino acids from the leaf during the night and to meet overnight cellular maintenance costs forces the model to set aside stores of both carbon and nitrogen during the day. With only minimal constraints, the model successfully captures many of the known features of C3 leaf metabolism, including the recently discovered role of citrate synthesis and accumulation in the night as a precursor for the provision of carbon skeletons for amino acid synthesis during the day. The diel FBA model can be applied to other temporal separations, such as that which occurs in Crassulacean acid metabolism (CAM) photosynthesis, allowing a system-level analysis of the energetics of CAM. The diel model predicts that there is no overall energetic advantage to CAM, despite the potential for suppression of photorespiration through CO2 concentration. Moreover, any savings in enzyme machinery costs through suppression of photorespiration are likely to be offset by the higher flux demand of the CAM cycle. It is concluded that energetic or nitrogen use considerations are unlikely to be evolutionary drivers for CAM photosynthesis. PMID:24596328

  17. Genealogy profiling through strain improvement by using metabolic network analysis: metabolic flux genealogy of several generations of lysine-producing corynebacteria.

    PubMed

    Wittmann, Christoph; Heinzle, Elmar

    2002-12-01

    A comprehensive approach of metabolite balancing, (13)C tracer studies, gas chromatography-mass spectrometry, matrix-assisted laser desorption ionization-time of flight mass spectrometry, and isotopomer modeling was applied for comparative metabolic network analysis of a genealogy of five successive generations of lysine-producing Corynebacterium glutamicum. The five strains examined (C. glutamicum ATCC 13032, 13287, 21253, 21526, and 21543) were previously obtained by random mutagenesis and selection. Throughout the genealogy, the lysine yield in batch cultures increased markedly from 1.2 to 24.9% relative to the glucose uptake flux. Strain optimization was accompanied by significant changes in intracellular flux distributions. The relative pentose phosphate pathway (PPP) flux successively increased, clearly corresponding to the product yield. Moreover, the anaplerotic net flux increased almost twofold as a consequence of concerted regulation of C(3) carboxylation and C(4) decarboxylation fluxes to cover the increased demand for lysine formation; thus, the overall increase was a consequence of concerted regulation of C(3) carboxylation and C(4) decarboxylation fluxes. The relative flux through isocitrate dehydrogenase dropped from 82.7% in the wild type to 59.9% in the lysine-producing mutants. In contrast to the NADPH demand, which increased from 109 to 172% due to the increasing lysine yield, the overall NADPH supply remained constant between 185 and 196%, resulting in a decrease in the apparent NADPH excess through strain optimization. Extrapolated to industrial lysine producers, the NADPH supply might become a limiting factor. The relative contributions of PPP and the tricarboxylic acid cycle to NADPH generation changed markedly, indicating that C. glutamicum is able to maintain a constant supply of NADPH under completely different flux conditions. Statistical analysis by a Monte Carlo approach revealed high precision for the estimated fluxes, underlining the

  18. Genealogy Profiling through Strain Improvement by Using Metabolic Network Analysis: Metabolic Flux Genealogy of Several Generations of Lysine-Producing Corynebacteria

    PubMed Central

    Wittmann, Christoph; Heinzle, Elmar

    2002-01-01

    A comprehensive approach of metabolite balancing, 13C tracer studies, gas chromatography-mass spectrometry, matrix-assisted laser desorption ionization-time of flight mass spectrometry, and isotopomer modeling was applied for comparative metabolic network analysis of a genealogy of five successive generations of lysine-producing Corynebacterium glutamicum. The five strains examined (C. glutamicum ATCC 13032, 13287, 21253, 21526, and 21543) were previously obtained by random mutagenesis and selection. Throughout the genealogy, the lysine yield in batch cultures increased markedly from 1.2 to 24.9% relative to the glucose uptake flux. Strain optimization was accompanied by significant changes in intracellular flux distributions. The relative pentose phosphate pathway (PPP) flux successively increased, clearly corresponding to the product yield. Moreover, the anaplerotic net flux increased almost twofold as a consequence of concerted regulation of C3 carboxylation and C4 decarboxylation fluxes to cover the increased demand for lysine formation; thus, the overall increase was a consequence of concerted regulation of C3 carboxylation and C4 decarboxylation fluxes. The relative flux through isocitrate dehydrogenase dropped from 82.7% in the wild type to 59.9% in the lysine-producing mutants. In contrast to the NADPH demand, which increased from 109 to 172% due to the increasing lysine yield, the overall NADPH supply remained constant between 185 and 196%, resulting in a decrease in the apparent NADPH excess through strain optimization. Extrapolated to industrial lysine producers, the NADPH supply might become a limiting factor. The relative contributions of PPP and the tricarboxylic acid cycle to NADPH generation changed markedly, indicating that C. glutamicum is able to maintain a constant supply of NADPH under completely different flux conditions. Statistical analysis by a Monte Carlo approach revealed high precision for the estimated fluxes, underlining the fact that

  19. Redirection of pyruvate flux toward desired metabolic pathways through substrate channeling between pyruvate kinase and pyruvate-converting enzymes in Saccharomyces cerevisiae.

    PubMed

    Kim, Sujin; Bae, Sang-Jeong; Hahn, Ji-Sook

    2016-04-07

    Spatial organization of metabolic enzymes allows substrate channeling, which accelerates processing of intermediates. Here, we investigated the effect of substrate channeling on the flux partitioning at a metabolic branch point, focusing on pyruvate metabolism in Saccharomyces cerevisiae. As a platform strain for the channeling of pyruvate flux, PYK1-Coh-Myc strain was constructed in which PYK1 gene encoding pyruvate kinase is tagged with cohesin domain. By using high-affinity cohesin-dockerin interaction, the pyruvate-forming enzyme Pyk1 was tethered to heterologous pyruvate-converting enzymes, lactate dehydrogenase and α-acetolactate synthase, to produce lactic acid and 2,3-butanediol, respectively. Pyruvate flux was successfully redirected toward desired pathways, with a concomitant decrease in ethanol production even without genetic attenuation of the ethanol-producing pathway. This pyruvate channeling strategy led to an improvement of 2,3-butanediol production by 38%, while showing a limitation in improving lactic acid production due to a reduced activity of lactate dehydrogenase by dockerin tagging.

  20. Understanding alternative fluxes/effluxes through comparative metabolic pathway analysis of phylum actinobacteria using a simplified approach.

    PubMed

    Verma, Mansi; Lal, Devi; Saxena, Anjali; Anand, Shailly; Kaur, Jasvinder; Kaur, Jaspreet; Lal, Rup

    2013-12-01

    Actinobacteria are known for their diverse metabolism and physiology. Some are dreadful human pathogens whereas some constitute the natural flora for human gut. Therefore, the understanding of metabolic pathways is a key feature for targeting the pathogenic bacteria without disturbing the symbiotic ones. A big challenge faced today is multiple drug resistance by Mycobacterium and other pathogens that utilize alternative fluxes/effluxes. With the availability of genome sequence, it is now feasible to conduct the comparative in silico analysis. Here we present a simplified approach to compare metabolic pathways so that the species specific enzyme may be traced and engineered for future therapeutics. The analyses of four key carbohydrate metabolic pathways, i.e., glycolysis, pyruvate metabolism, tri carboxylic acid cycle and pentose phosphate pathway suggest the presence of alternative fluxes. It was found that the upper pathway of glycolysis was highly variable in the actinobacterial genomes whereas lower glycolytic pathway was highly conserved. Likewise, pentose phosphate pathway was well conserved in contradiction to TCA cycle, which was found to be incomplete in majority of actinobacteria. The clustering based on presence and absence of genes of these metabolic pathways clearly revealed that members of different genera shared identical pathways and, therefore, provided an easy method to identify the metabolic similarities/differences between pathogenic and symbiotic organisms. The analyses could identify isoenzymes and some key enzymes that were found to be missing in some pathogenic actinobacteria. The present work defines a simple approach to explore the effluxes in four metabolic pathways within the phylum actinobacteria. The analysis clearly reflects that actinobacteria exhibit diverse routes for metabolizing substrates. The pathway comparison can help in finding the enzymes that can be used as drug targets for pathogens without effecting symbiotic organisms

  1. Metabolic network rewiring of propionate flux compensates vitamin B12 deficiency in C. elegans

    PubMed Central

    Watson, Emma; Olin-Sandoval, Viridiana; Hoy, Michael J; Li, Chi-Hua; Louisse, Timo; Yao, Victoria; Mori, Akihiro; Holdorf, Amy D; Troyanskaya, Olga G; Ralser, Markus; Walhout, Albertha JM

    2016-01-01

    Metabolic network rewiring is the rerouting of metabolism through the use of alternate enzymes to adjust pathway flux and accomplish specific anabolic or catabolic objectives. Here, we report the first characterization of two parallel pathways for the breakdown of the short chain fatty acid propionate in Caenorhabditis elegans. Using genetic interaction mapping, gene co-expression analysis, pathway intermediate quantification and carbon tracing, we uncover a vitamin B12-independent propionate breakdown shunt that is transcriptionally activated on vitamin B12 deficient diets, or under genetic conditions mimicking the human diseases propionic- and methylmalonic acidemia, in which the canonical B12-dependent propionate breakdown pathway is blocked. Our study presents the first example of transcriptional vitamin-directed metabolic network rewiring to promote survival under vitamin deficiency. The ability to reroute propionate breakdown according to B12 availability may provide C. elegans with metabolic plasticity and thus a selective advantage on different diets in the wild. DOI: http://dx.doi.org/10.7554/eLife.17670.001 PMID:27383050

  2. Enhanced uridine 5'-monophosphate production by whole cell of Saccharomyces cerevisiae through rational redistribution of metabolic flux.

    PubMed

    Liu, Dong; Chen, Yong; Li, An; Xie, Jingjing; Xiong, Jian; Bai, Jianxin; Chen, Xiaochun; Niu, Huanqing; Zhou, Tao; Ying, Hanjie

    2012-06-01

    A whole-cell biocatalytic process for uridine 5'-monophosphate (UMP) production from orotic acid by Saccharomyces cerevisiae was developed. To rationally redistribute the metabolic flux between glycolysis and pentose phosphate pathway, statistical methods were employed first to find out the critical factors in the process. NaH(2)PO(4), MgCl(2) and pH were found to be the important factors affecting UMP production significantly. The levels of these three factors required for the maximum production of UMP were determined: NaH(2)PO(4) 22.1 g/L; MgCl(2) 2.55 g/L; pH 8.15. An enhancement of UMP production from 6.12 to 8.13 g/L was achieved. A significant redistribution of metabolic fluxes was observed and the underlying mechanism was discussed.

  3. A genome-scale Escherichia coli kinetic metabolic model k-ecoli457 satisfying flux data for multiple mutant strains

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Khodayari, Ali; Maranas, Costas D.

    Kinetic models of metabolism at a genome scale that faithfully recapitulate the effect of multiple genetic interventions would be transformative in our ability to reliably design novel overproducing microbial strains. Here, we introduce k-ecoli457, a genome-scale kinetic model of Escherichia coli metabolism that satisfies fluxomic data for wild-type and 25 mutant strains under different substrates and growth conditions. The k-ecoli457 model contains 457 model reactions, 337 metabolites and 295 substrate-level regulatory interactions. Parameterization is carried out using a genetic algorithm by simultaneously imposing all available fluxomic data (about 30 measured fluxes per mutant). Furthermore, the Pearson correlation coefficient between experimentalmore » data and predicted product yields for 320 engineered strains spanning 24 product metabolites is 0.84. This is substantially higher than that using flux balance analysis, minimization of metabolic adjustment or maximization of product yield exhibiting systematic errors with correlation coefficients of, respectively, 0.18, 0.37 and 0.47.« less

  4. A genome-scale Escherichia coli kinetic metabolic model k-ecoli457 satisfying flux data for multiple mutant strains

    DOE PAGES

    Khodayari, Ali; Maranas, Costas D.

    2016-12-20

    Kinetic models of metabolism at a genome scale that faithfully recapitulate the effect of multiple genetic interventions would be transformative in our ability to reliably design novel overproducing microbial strains. Here, we introduce k-ecoli457, a genome-scale kinetic model of Escherichia coli metabolism that satisfies fluxomic data for wild-type and 25 mutant strains under different substrates and growth conditions. The k-ecoli457 model contains 457 model reactions, 337 metabolites and 295 substrate-level regulatory interactions. Parameterization is carried out using a genetic algorithm by simultaneously imposing all available fluxomic data (about 30 measured fluxes per mutant). Furthermore, the Pearson correlation coefficient between experimentalmore » data and predicted product yields for 320 engineered strains spanning 24 product metabolites is 0.84. This is substantially higher than that using flux balance analysis, minimization of metabolic adjustment or maximization of product yield exhibiting systematic errors with correlation coefficients of, respectively, 0.18, 0.37 and 0.47.« less

  5. Integrated stoichiometric, thermodynamic and kinetic modelling of steady state metabolism

    PubMed Central

    Fleming, R.M.T.; Thiele, I.; Provan, G.; Nasheuer, H.P.

    2010-01-01

    The quantitative analysis of biochemical reactions and metabolites is at frontier of biological sciences. The recent availability of high-throughput technology data sets in biology has paved the way for new modelling approaches at various levels of complexity including the metabolome of a cell or an organism. Understanding the metabolism of a single cell and multi-cell organism will provide the knowledge for the rational design of growth conditions to produce commercially valuable reagents in biotechnology. Here, we demonstrate how equations representing steady state mass conservation, energy conservation, the second law of thermodynamics, and reversible enzyme kinetics can be formulated as a single system of linear equalities and inequalities, in addition to linear equalities on exponential variables. Even though the feasible set is non-convex, the reformulation is exact and amenable to large-scale numerical analysis, a prerequisite for computationally feasible genome scale modelling. Integrating flux, concentration and kinetic variables in a unified constraint-based formulation is aimed at increasing the quantitative predictive capacity of flux balance analysis. Incorporation of experimental and theoretical bounds on thermodynamic and kinetic variables ensures that the predicted steady state fluxes are both thermodynamically and biochemically feasible. The resulting in silico predictions are tested against fluxomic data for central metabolism in E. coli and compare favourably with in silico prediction by flux balance analysis. PMID:20230840

  6. Metabolic Mapping: Quantitative Enzyme Cytochemistry and Histochemistry to Determine the Activity of Dehydrogenases in Cells and Tissues.

    PubMed

    Molenaar, Remco J; Khurshed, Mohammed; Hira, Vashendriya V V; Van Noorden, Cornelis J F

    2018-05-26

    Altered cellular metabolism is a hallmark of many diseases, including cancer, cardiovascular diseases and infection. The metabolic motor units of cells are enzymes and their activity is heavily regulated at many levels, including the transcriptional, mRNA stability, translational, post-translational and functional level. This complex regulation means that conventional quantitative or imaging assays, such as quantitative mRNA experiments, Western Blots and immunohistochemistry, yield incomplete information regarding the ultimate activity of enzymes, their function and/or their subcellular localization. Quantitative enzyme cytochemistry and histochemistry (i.e., metabolic mapping) show in-depth information on in situ enzymatic activity and its kinetics, function and subcellular localization in an almost true-to-nature situation. We describe a protocol to detect the activity of dehydrogenases, which are enzymes that perform redox reactions to reduce cofactors such as NAD(P) + and FAD. Cells and tissue sections are incubated in a medium that is specific for the enzymatic activity of one dehydrogenase. Subsequently, the dehydrogenase that is the subject of investigation performs its enzymatic activity in its subcellular site. In a chemical reaction with the reaction medium, this ultimately generates blue-colored formazan at the site of the dehydrogenase's activity. The formazan's absorbance is therefore a direct measure of the dehydrogenase's activity and can be quantified using monochromatic light microscopy and image analysis. The quantitative aspect of this protocol enables researchers to draw statistical conclusions from these assays. Besides observational studies, this technique can be used for inhibition studies of specific enzymes. In this context, studies benefit from the true-to-nature advantages of metabolic mapping, giving in situ results that may be physiologically more relevant than in vitro enzyme inhibition studies. In all, metabolic mapping is an

  7. Metabolic flux analysis of the halophilic archaeon Haladaptatus paucihalophilus.

    PubMed

    Liu, Guangxiu; Zhang, Manxiao; Mo, Tianlu; He, Lian; Zhang, Wei; Yu, Yi; Zhang, Qi; Ding, Wei

    2015-11-27

    This work reports the (13)C-assisted metabolic flux analysis of Haladaptatus paucihalophilus, a halophilic archaeon possessing an intriguing osmoadaption mechanism. We showed that the carbon flow is through the oxidative tricarboxylic acid (TCA) cycle whereas the reductive TCA cycle is not operative in H. paucihalophilus. In addition, both threonine and the citramalate pathways contribute to isoleucine biosynthesis, whereas lysine is synthesized through the diaminopimelate pathway and not through the α-aminoadipate pathway. Unexpected, the labeling patterns of glycine from the cells grown on [1-(13)C]pyruvate and [2-(13)C]pyruvate suggest that, unlike all the organisms investigated so far, in which glycine is produced exclusively from the serine hydroxymethyltransferase (SHMT) pathway, glycine biosynthesis in H. paucihalophilus involves different pathways including SHMT, threonine aldolase (TA) and the reverse reaction of glycine cleavage system (GCS), demonstrating for the first time that other pathways instead of SHMT can also make a significant contribution to the cellular glycine pool. Transcriptional analysis confirmed that both TA and GCS genes were transcribed in H. paucihalophilus, and the transcriptional level is independent of salt concentrations in the culture media. This study expands our understanding of amino acid biosynthesis and provides valuable insights into the metabolism of halophilic archaea. Copyright © 2015 Elsevier Inc. All rights reserved.

  8. Multiscale Metabolic Modeling: Dynamic Flux Balance Analysis on a Whole-Plant Scale1[W][OPEN

    PubMed Central

    Grafahrend-Belau, Eva; Junker, Astrid; Eschenröder, André; Müller, Johannes; Schreiber, Falk; Junker, Björn H.

    2013-01-01

    Plant metabolism is characterized by a unique complexity on the cellular, tissue, and organ levels. On a whole-plant scale, changing source and sink relations accompanying plant development add another level of complexity to metabolism. With the aim of achieving a spatiotemporal resolution of source-sink interactions in crop plant metabolism, a multiscale metabolic modeling (MMM) approach was applied that integrates static organ-specific models with a whole-plant dynamic model. Allowing for a dynamic flux balance analysis on a whole-plant scale, the MMM approach was used to decipher the metabolic behavior of source and sink organs during the generative phase of the barley (Hordeum vulgare) plant. It reveals a sink-to-source shift of the barley stem caused by the senescence-related decrease in leaf source capacity, which is not sufficient to meet the nutrient requirements of sink organs such as the growing seed. The MMM platform represents a novel approach for the in silico analysis of metabolism on a whole-plant level, allowing for a systemic, spatiotemporally resolved understanding of metabolic processes involved in carbon partitioning, thus providing a novel tool for studying yield stability and crop improvement. PMID:23926077

  9. Combining Flux Balance and Energy Balance Analysis for Large-Scale Metabolic Network: Biochemical Circuit Theory for Analysis of Large-Scale Metabolic Networks

    NASA Technical Reports Server (NTRS)

    Beard, Daniel A.; Liang, Shou-Dan; Qian, Hong; Biegel, Bryan (Technical Monitor)

    2001-01-01

    Predicting behavior of large-scale biochemical metabolic networks represents one of the greatest challenges of bioinformatics and computational biology. Approaches, such as flux balance analysis (FBA), that account for the known stoichiometry of the reaction network while avoiding implementation of detailed reaction kinetics are perhaps the most promising tools for the analysis of large complex networks. As a step towards building a complete theory of biochemical circuit analysis, we introduce energy balance analysis (EBA), which compliments the FBA approach by introducing fundamental constraints based on the first and second laws of thermodynamics. Fluxes obtained with EBA are thermodynamically feasible and provide valuable insight into the activation and suppression of biochemical pathways.

  10. Understanding Regulation of Metabolism through Feasibility Analysis

    PubMed Central

    Nikerel, Emrah; Berkhout, Jan; Hu, Fengyuan; Teusink, Bas; Reinders, Marcel J. T.; de Ridder, Dick

    2012-01-01

    Understanding cellular regulation of metabolism is a major challenge in systems biology. Thus far, the main assumption was that enzyme levels are key regulators in metabolic networks. However, regulation analysis recently showed that metabolism is rarely controlled via enzyme levels only, but through non-obvious combinations of hierarchical (gene and enzyme levels) and metabolic regulation (mass action and allosteric interaction). Quantitative analyses relating changes in metabolic fluxes to changes in transcript or protein levels have revealed a remarkable lack of understanding of the regulation of these networks. We study metabolic regulation via feasibility analysis (FA). Inspired by the constraint-based approach of Flux Balance Analysis, FA incorporates a model describing kinetic interactions between molecules. We enlarge the portfolio of objectives for the cell by defining three main physiologically relevant objectives for the cell: function, robustness and temporal responsiveness. We postulate that the cell assumes one or a combination of these objectives and search for enzyme levels necessary to achieve this. We call the subspace of feasible enzyme levels the feasible enzyme space. Once this space is constructed, we can study how different objectives may (if possible) be combined, or evaluate the conditions at which the cells are faced with a trade-off among those. We apply FA to the experimental scenario of long-term carbon limited chemostat cultivation of yeast cells, studying how metabolism evolves optimally. Cells employ a mixed strategy composed of increasing enzyme levels for glucose uptake and hexokinase and decreasing levels of the remaining enzymes. This trade-off renders the cells specialized in this low-carbon flux state to compete for the available glucose and get rid of over-overcapacity. Overall, we show that FA is a powerful tool for systems biologists to study regulation of metabolism, interpret experimental data and evaluate hypotheses. PMID

  11. Determination of ¹⁵N-incorporation into plant proteins and their absolute quantitation: a new tool to study nitrogen flux dynamics and protein pool sizes elicited by plant-herbivore interactions.

    PubMed

    Ullmann-Zeunert, Lynn; Muck, Alexander; Wielsch, Natalie; Hufsky, Franziska; Stanton, Mariana A; Bartram, Stefan; Böcker, Sebastian; Baldwin, Ian T; Groten, Karin; Svatoš, Aleš

    2012-10-05

    Herbivory leads to changes in the allocation of nitrogen among different pools and tissues; however, a detailed quantitative analysis of these changes has been lacking. Here, we demonstrate that a mass spectrometric data-independent acquisition approach known as LC-MS(E), combined with a novel algorithm to quantify heavy atom enrichment in peptides, is able to quantify elicited changes in protein amounts and (15)N flux in a high throughput manner. The reliable identification/quantitation of rabbit phosphorylase b protein spiked into leaf protein extract was achieved. The linear dynamic range, reproducibility of technical and biological replicates, and differences between measured and expected (15)N-incorporation into the small (SSU) and large (LSU) subunits of ribulose-1,5-bisphosphate-carboxylase/oxygenase (RuBisCO) and RuBisCO activase 2 (RCA2) of Nicotiana attenuata plants grown in hydroponic culture at different known concentrations of (15)N-labeled nitrate were used to further evaluate the procedure. The utility of the method for whole-plant studies in ecologically realistic contexts was demonstrated by using (15)N-pulse protocols on plants growing in soil under unknown (15)N-incorporation levels. Additionally, we quantified the amounts of lipoxygenase 2 (LOX2) protein, an enzyme important in antiherbivore defense responses, demonstrating that the approach allows for in-depth quantitative proteomics and (15)N flux analyses of the metabolic dynamics elicited during plant-herbivore interactions.

  12. Soil Fluxomics: Disentangling Microbial Group Specific Metabolism by Modeling of 13C-Incorporation into PLFAs

    NASA Astrophysics Data System (ADS)

    Apostel, C.; Kuzyakov, Y.; Dippold, M. A.

    2016-12-01

    Soils are the largest terrestrial C sinks and microorganisms are the most important drivers of organic matter (OM) dynamics in soils: C allocation to ana- or catabolism in microbial cells is the decisive step, whether C gets oxidized to CO2 or whether it is allocated to microbial biomass, which, after cell death can be stabilized in soils. The metabolic parameter describing the ratio between the two fluxes is the carbon use efficiency (CUE), which can be assessed by position-specific labeling followed by metabolic flux modelling. However, to disentangle the single microbial groups' contribution to the bulk soil CUE, a tracing of individual groups metabolism is necessary. We assessed short-term (3 and 10 days) transformations of monosaccharides by adding position-specifically 13C labeled glucose to soil in a field experiment. Incorporation of 13C in the microbial PLFAs enabled us to distinguish individual microbial groups metabolic fluxes and compare their C-utilization efficiency using a quantitative C-flux model. The position-specific pattern in PLFAs revealed two sets of microorganisms: one metabolized glucose mainly by glycolysis and the other mainly by the pentose-phosphate pathway, which results in a higher CUE. Both of those sets included prokaryotic as well as eukaryotic microorganisms. This demonstrates that phylogenetic grouping is not decisive for the metabolic behavior of a microbial group and that the contribution of individual group members to the soil C fluxes cannot be concluded from their phylogeny.

  13. Revealing Differences in Metabolic Flux Distributions between a Mutant Strain and Its Parent Strain Gluconacetobacter xylinus CGMCC 2955

    PubMed Central

    Liu, Miao; Yang, Xiao-Ning; Zhu, Hui-Xia; Jia, Yuan-Yuan; Jia, Shi-Ru; Piergiovanni, Luciano

    2014-01-01

    A better understanding of metabolic fluxes is important for manipulating microbial metabolism toward desired end products, or away from undesirable by-products. A mutant strain, Gluconacetobacter xylinus AX2-16, was obtained by combined chemical mutation of the parent strain (G. xylinus CGMCC 2955) using DEC (diethyl sulfate) and LiCl. The highest bacterial cellulose production for this mutant was obtained at about 11.75 g/L, which was an increase of 62% compared with that by the parent strain. In contrast, gluconic acid (the main byproduct) concentration was only 5.71 g/L for mutant strain, which was 55.7% lower than that of parent strain. Metabolic flux analysis indicated that 40.1% of the carbon source was transformed to bacterial cellulose in mutant strain, compared with 24.2% for parent strain. Only 32.7% and 4.0% of the carbon source were converted into gluconic acid and acetic acid in mutant strain, compared with 58.5% and 9.5% of that in parent strain. In addition, a higher flux of tricarboxylic acid (TCA) cycle was obtained in mutant strain (57.0%) compared with parent strain (17.0%). It was also indicated from the flux analysis that more ATP was produced in mutant strain from pentose phosphate pathway (PPP) and TCA cycle. The enzymatic activity of succinate dehydrogenase (SDH), which is one of the key enzymes in TCA cycle, was 1.65-fold higher in mutant strain than that in parent strain at the end of culture. It was further validated by the measurement of ATPase that 3.53–6.41 fold higher enzymatic activity was obtained from mutant strain compared with parent strain. PMID:24901455

  14. Bidirectional reaction steps in metabolic networks: I. Modeling and simulation of carbon isotope labeling experiments.

    PubMed

    Wiechert, W; de Graaf, A A

    1997-07-05

    The extension of metabolite balancing with carbon labeling experiments, as described by Marx et al. (Biotechnol. Bioeng. 49: 11-29), results in a much more detailed stationary metabolic flux analysis. As opposed to basic metabolite flux balancing alone, this method enables both flux directions of bidirectional reaction steps to be quantitated. However, the mathematical treatment of carbon labeling systems is much more complicated, because it requires the solution of numerous balance equations that are bilinear with respect to fluxes and fractional labeling. In this study, a universal modeling framework is presented for describing the metabolite and carbon atom flux in a metabolic network. Bidirectional reaction steps are extensively treated and their impact on the system's labeling state is investigated. Various kinds of modeling assumptions, as usually made for metabolic fluxes, are expressed by linear constraint equations. A numerical algorithm for the solution of the resulting linear constrained set of nonlinear equations is developed. The numerical stability problems caused by large bidirectional fluxes are solved by a specially developed transformation method. Finally, the simulation of carbon labeling experiments is facilitated by a flexible software tool for network synthesis. An illustrative simulation study on flux identifiability from available flux and labeling measurements in the cyclic pentose phosphate pathway of a recombinant strain of Zymomonas mobilis concludes this contribution.

  15. A simplified method for power-law modelling of metabolic pathways from time-course data and steady-state flux profiles.

    PubMed

    Kitayama, Tomoya; Kinoshita, Ayako; Sugimoto, Masahiro; Nakayama, Yoichi; Tomita, Masaru

    2006-07-17

    In order to improve understanding of metabolic systems there have been attempts to construct S-system models from time courses. Conventionally, non-linear curve-fitting algorithms have been used for modelling, because of the non-linear properties of parameter estimation from time series. However, the huge iterative calculations required have hindered the development of large-scale metabolic pathway models. To solve this problem we propose a novel method involving power-law modelling of metabolic pathways from the Jacobian of the targeted system and the steady-state flux profiles by linearization of S-systems. The results of two case studies modelling a straight and a branched pathway, respectively, showed that our method reduced the number of unknown parameters needing to be estimated. The time-courses simulated by conventional kinetic models and those described by our method behaved similarly under a wide range of perturbations of metabolite concentrations. The proposed method reduces calculation complexity and facilitates the construction of large-scale S-system models of metabolic pathways, realizing a practical application of reverse engineering of dynamic simulation models from the Jacobian of the targeted system and steady-state flux profiles.

  16. Improving the phenotype predictions of a yeast genome-scale metabolic model by incorporating enzymatic constraints

    DOE PAGES

    Sánchez, Benjamín J.; Zhang, Cheng; Nilsson, Avlant; ...

    2017-03-08

    Genome-scale metabolic models (GEMs) are widely used to calculate metabolic phenotypes. They rely on defining a set of constraints, the most common of which is that the production of metabolites and/or growth are limited by the carbon source uptake rate. However, enzyme abundances and kinetics, which act as limitations on metabolic fluxes, are not taken into account. Here, we present GECKO, a method that enhances a GEM to account for enzymes as part of reactions, thereby ensuring that each metabolic flux does not exceed its maximum capacity, equal to the product of the enzyme's abundance and turnover number. We appliedmore » GECKO to a Saccharomyces cerevisiae GEM and demonstrated that the new model could correctly describe phenotypes that the previous model could not, particularly under high enzymatic pressure conditions, such as yeast growing on different carbon sources in excess, coping with stress, or overexpressing a specific pathway. GECKO also allows to directly integrate quantitative proteomics data; by doing so, we significantly reduced flux variability of the model, in over 60% of metabolic reactions. Additionally, the model gives insight into the distribution of enzyme usage between and within metabolic pathways. The developed method and model are expected to increase the use of model-based design in metabolic engineering.« less

  17. Improving the phenotype predictions of a yeast genome-scale metabolic model by incorporating enzymatic constraints

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Sánchez, Benjamín J.; Zhang, Cheng; Nilsson, Avlant

    Genome-scale metabolic models (GEMs) are widely used to calculate metabolic phenotypes. They rely on defining a set of constraints, the most common of which is that the production of metabolites and/or growth are limited by the carbon source uptake rate. However, enzyme abundances and kinetics, which act as limitations on metabolic fluxes, are not taken into account. Here, we present GECKO, a method that enhances a GEM to account for enzymes as part of reactions, thereby ensuring that each metabolic flux does not exceed its maximum capacity, equal to the product of the enzyme's abundance and turnover number. We appliedmore » GECKO to a Saccharomyces cerevisiae GEM and demonstrated that the new model could correctly describe phenotypes that the previous model could not, particularly under high enzymatic pressure conditions, such as yeast growing on different carbon sources in excess, coping with stress, or overexpressing a specific pathway. GECKO also allows to directly integrate quantitative proteomics data; by doing so, we significantly reduced flux variability of the model, in over 60% of metabolic reactions. Additionally, the model gives insight into the distribution of enzyme usage between and within metabolic pathways. The developed method and model are expected to increase the use of model-based design in metabolic engineering.« less

  18. Metabolic flux analysis of recombinant Pichia pastoris growing on different glycerol/methanol mixtures by iterative fitting of NMR-derived (13)C-labelling data from proteinogenic amino acids.

    PubMed

    Jordà, Joel; de Jesus, Sérgio S; Peltier, Solenne; Ferrer, Pau; Albiol, Joan

    2014-01-25

    The yeast Pichia pastoris has emerged as one of the most promising yeast cell factories for the production of heterologous proteins. The readily available genetic tools and the ease of high-cell density cultivations using methanol or glycerol/methanol mixtures are among the key factors for this development. Previous studies have shown that the use of mixed feeds of glycerol and methanol seem to alleviate the metabolic burden derived from protein production, allowing for higher specific and volumetric process productivities. However, initial studies of glycerol/methanol co-metabolism in P. pastoris by classical metabolic flux analyses using (13)C-derived Metabolic Flux Ratio (METAFoR) constraints were hampered by the reduced labelling information obtained when using C3:C1 substrate mixtures in relation to the conventional C6 substrate, that is, glucose. In this study, carbon flux distributions through the central metabolic pathways in glycerol/methanol co-assimilation conditions have been further characterised using biosynthetically directed fractional (13)C labelling. In particular, metabolic flux distributions were obtained under 3 different glycerol/methanol ratios and growth rates by iterative fitting of NMR-derived (13)C-labelling data from proteinogenic amino acids using the software tool (13)CFlux2. Specifically, cells were grown aerobically in chemostat cultures fed with 80:20, 60:40 and 40:60 (w:w) glycerol/methanol mixtures at two dilutions rates (0.05 hour(-1) and 0.16 hour(-1)), allowing to obtain additional data (biomass composition and extracellular fluxes) to complement pre-existing datasets. The performed (13)C-MFA reveals a significant redistribution of carbon fluxes in the central carbon metabolism as a result of the shift in the dilution rate, while the ratio of carbon sources has a lower impact on carbon flux distribution in cells growing at the same dilution rate. At low growth rate, the percentage of methanol directly dissimilated to CO2 ranges

  19. The photospheric magnetic flux budget

    NASA Technical Reports Server (NTRS)

    Schrijver, C. J.; Harvey, K. L.

    1994-01-01

    The ensemble of bipolar regions and the magnetic network both contain a substantial and strongly variable part of the photospheric magnetic flux at any phase in the solar cycle. The time-dependent distribution of the magnetic flux over and within these components reflects the action of the dynamo operating in the solar interior. We perform a quantitative comparison of the flux emerging in the ensemble of magnetic bipoles with the observed flux content of the solar photosphere. We discuss the photospheric flux budget in terms of flux appearance and disappearance, and argue that a nonlinear dependence exists between the flux present in the photosphere and the rate of flux appearance and disappearance. In this context, we discuss the problem of making quantitative statements about dynamos in cool stars other than the Sun.

  20. 13C based proteinogenic amino acid (PAA) and metabolic flux ratio analysis of Lactococcus lactis reveals changes in pentose phosphate (PP) pathway in response to agitation and temperature related stresses.

    PubMed

    Azizan, Kamalrul Azlan; Ressom, Habtom W; Mendoza, Eduardo R; Baharum, Syarul Nataqain

    2017-01-01

    Lactococcus lactis subsp. cremoris MG1363 is an important starter culture for dairy fermentation. During industrial fermentations, L. lactis is constantly exposed to stresses that affect the growth and performance of the bacterium. Although the response of L. lactis to several stresses has been described, the adaptation mechanisms at the level of in vivo fluxes have seldom been described. To gain insights into cellular metabolism, 13 C metabolic flux analysis and gas chromatography mass spectrometry (GC-MS) were used to measure the flux ratios of active pathways in the central metabolism of L. lactis when subjected to three conditions varying in temperature (30°C, 37°C) and agitation (with and without agitation at 150 rpm). Collectively, the concentrations of proteinogenic amino acids (PAAs) and free fatty acids (FAAs) were compared, and Pearson correlation analysis ( r ) was calculated to measure the pairwise relationship between PAAs. Branched chain and aromatic amino acids, threonine, serine, lysine and histidine were correlated strongly, suggesting changes in flux regulation in glycolysis, the pentose phosphate (PP) pathway, malic enzyme and anaplerotic reaction catalysed by pyruvate carboxylase (pycA). Flux ratio analysis revealed that glucose was mainly converted by glycolysis, highlighting the stability of L. lactis' central carbon metabolism despite different conditions. Higher flux ratios through oxaloacetate (OAA) from pyruvate (PYR) reaction in all conditions suggested the activation of pyruvate carboxylate (pycA) in L. lactis , in response to acid stress during exponential phase. Subsequently, more significant flux ratio differences were seen through the oxidative and non-oxidative pentose phosphate (PP) pathways, malic enzyme, and serine and C1 metabolism, suggesting NADPH requirements in response to environmental stimuli. These reactions could play an important role in optimization strategies for metabolic engineering in L. lactis . Overall, the

  1. CardioNet: a human metabolic network suited for the study of cardiomyocyte metabolism.

    PubMed

    Karlstädt, Anja; Fliegner, Daniela; Kararigas, Georgios; Ruderisch, Hugo Sanchez; Regitz-Zagrosek, Vera; Holzhütter, Hermann-Georg

    2012-08-29

    Availability of oxygen and nutrients in the coronary circulation is a crucial determinant of cardiac performance. Nutrient composition of coronary blood may significantly vary in specific physiological and pathological conditions, for example, administration of special diets, long-term starvation, physical exercise or diabetes. Quantitative analysis of cardiac metabolism from a systems biology perspective may help to a better understanding of the relationship between nutrient supply and efficiency of metabolic processes required for an adequate cardiac output. Here we present CardioNet, the first large-scale reconstruction of the metabolic network of the human cardiomyocyte comprising 1793 metabolic reactions, including 560 transport processes in six compartments. We use flux-balance analysis to demonstrate the capability of the network to accomplish a set of 368 metabolic functions required for maintaining the structural and functional integrity of the cell. Taking the maintenance of ATP, biosynthesis of ceramide, cardiolipin and further important phospholipids as examples, we analyse how a changed supply of glucose, lactate, fatty acids and ketone bodies may influence the efficiency of these essential processes. CardioNet is a functionally validated metabolic network of the human cardiomyocyte that enables theorectical studies of cellular metabolic processes crucial for the accomplishment of an adequate cardiac output.

  2. What do magnetic resonance-based measurements of Pi→ATP flux tell us about skeletal muscle metabolism?

    PubMed

    Kemp, Graham J; Brindle, Kevin M

    2012-08-01

    Magnetic resonance spectroscopy (MRS) methods offer a potentially valuable window into cellular metabolism. Measurement of flux between inorganic phosphate (Pi) and ATP using (31)P MRS magnetization transfer has been used in resting muscle to assess what is claimed to be mitochondrial ATP synthesis and has been particularly popular in the study of insulin effects and insulin resistance. However, the measured Pi→ATP flux in resting skeletal muscle is far higher than the true rate of oxidative ATP synthesis, being dominated by a glycolytically mediated Pi↔ATP exchange reaction that is unrelated to mitochondrial function. Furthermore, even if measured accurately, the ATP production rate in resting muscle has no simple relationship to mitochondrial capacity as measured either ex vivo or in vivo. We summarize the published measurements of Pi→ATP flux, concentrating on work relevant to diabetes and insulin, relate it to current understanding of the physiology of mitochondrial ATP synthesis and glycolytic Pi↔ATP exchange, and discuss some possible implications of recently reported correlations between Pi→ATP flux and other physiological measures.

  3. THE EVOLUTION OF SOLAR FLUX FROM 0.1 nm TO 160 {mu}m: QUANTITATIVE ESTIMATES FOR PLANETARY STUDIES

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Claire, Mark W.; Sheets, John; Meadows, Victoria S.

    2012-09-20

    Understanding changes in the solar flux over geologic time is vital for understanding the evolution of planetary atmospheres because it affects atmospheric escape and chemistry, as well as climate. We describe a numerical parameterization for wavelength-dependent changes to the non-attenuated solar flux appropriate for most times and places in the solar system. We combine data from the Sun and solar analogs to estimate enhanced UV and X-ray fluxes for the young Sun and use standard solar models to estimate changing visible and infrared fluxes. The parameterization, a series of multipliers relative to the modern top of the atmosphere flux atmore » Earth, is valid from 0.1 nm through the infrared, and from 0.6 Gyr through 6.7 Gyr, and is extended from the solar zero-age main sequence to 8.0 Gyr subject to additional uncertainties. The parameterization is applied to a representative modern day flux, providing quantitative estimates of the wavelength dependence of solar flux for paleodates relevant to the evolution of atmospheres in the solar system (or around other G-type stars). We validate the code by Monte Carlo analysis of uncertainties in stellar age and flux, and with comparisons to the solar proxies {kappa}{sup 1} Cet and EK Dra. The model is applied to the computation of photolysis rates on the Archean Earth.« less

  4. QUANTITATIVE EVALUATION OF BROMODICHLOROMETHANE METABOLISM BY RECOMBINANT RAT AND HUMAN CYTOCHROME P450S

    EPA Science Inventory

    ABSTRACT
    We report quantitative estimates of the parameters for metabolism of bromodichloromethane (BDCM) by recombinant preparations of hepatic cytochrome P450s (CYPs) from rat and human. BDCM is a drinking water disinfectant byproduct that has been implicated in liver, kidn...

  5. Metabolite recycling and bidirectional C fluxes: Revolutionizing our view on microbial C cycling in soils

    NASA Astrophysics Data System (ADS)

    Dippold, M. A.; Apostel, C.; Kuzyakov, Y.

    2016-12-01

    Biogeochemists' view on microbial C transformation in soil has rarely exceed a strongly simplified concept assuming that C gets either oxidized to CO2 via the microbial catabolism or incorporated into biomass via the anabolism. However, life in a C limited environment as challenging as soil requires microbial adaptation strategies at all levels of metabolism. By coupling of position-specific labeling of core metabolites with compound-specific isotope analysis we demonstrated that catabolic oxidation of these metabolites exists in parallel to reductive, energy consuming pathways, reducing them for anabolic purposes. Up to 55% of glucose, incorporated into the glucose derivative glucosamine, first passed glycolysis before allocated back via gluconeogenesis. Similarly, glutamate-derived C is allocated via anaplerotic pathways towards fatty acid synthesis and in parallel to its oxidation in the citric acid cycle. Furthermore, position-specific labeling of rather `cost-intensive' biomass compounds such as fatty acids revealed that intact recycling of metabolites is a crucial microbial adaptation to C scarcity in soils. Both processes are unlikely to occur in pure cultures, where constant growth conditions under high C supply allow a straight unidirectional regulation of C metabolism. However, unstable environmental conditions, C scarcity and interactions between a still unknown diversity of microorganisms in soils are likely to induce the observed metabolic diversity. To understand how microorganisms catalyze the biogeochemical fluxes in soil, a profound understanding of their metabolic adaptation strategies such as recycling or switching between bidirectional fluxes is crucial. Metabolic flux models adapted to soil microbial communities and their regulatory strategies will not only deepen our understanding on the microorganims' reactions to environmental changes but also create the prerequisits for a quantitative prediction of biogeochemical fluxes based on the

  6. Uncertainty quantification in flux balance analysis of spatially lumped and distributed models of neuron-astrocyte metabolism.

    PubMed

    Calvetti, Daniela; Cheng, Yougan; Somersalo, Erkki

    2016-12-01

    Identifying feasible steady state solutions of a brain energy metabolism model is an inverse problem that allows infinitely many solutions. The characterization of the non-uniqueness, or the uncertainty quantification of the flux balance analysis, is tantamount to identifying the degrees of freedom of the solution. The degrees of freedom of multi-compartment mathematical models for energy metabolism of a neuron-astrocyte complex may offer a key to understand the different ways in which the energetic needs of the brain are met. In this paper we study the uncertainty in the solution, using techniques of linear algebra to identify the degrees of freedom in a lumped model, and Markov chain Monte Carlo methods in its extension to a spatially distributed case. The interpretation of the degrees of freedom in metabolic terms, more specifically, glucose and oxygen partitioning, is then leveraged to derive constraints on the free parameters to guarantee that the model is energetically feasible. We demonstrate how the model can be used to estimate the stoichiometric energy needs of the cells as well as the household energy based on the measured oxidative cerebral metabolic rate of glucose and glutamate cycling. Moreover, our analysis shows that in the lumped model the net direction of lactate dehydrogenase (LDH) in the cells can be deduced from the glucose partitioning between the compartments. The extension of the lumped model to a spatially distributed multi-compartment setting that includes diffusion fluxes from capillary to tissue increases the number of degrees of freedom, requiring the use of statistical sampling techniques. The analysis of the distributed model reveals that some of the conclusions valid for the spatially lumped model, e.g., concerning the LDH activity and glucose partitioning, may no longer hold.

  7. Metabolic Profiling and Flux Analysis of MEL-2 Human Embryonic Stem Cells during Exponential Growth at Physiological and Atmospheric Oxygen Concentrations

    PubMed Central

    Titmarsh, Drew; Krömer, Jens O.; Kao, Li-Pin; Nielsen, Lars; Wolvetang, Ernst; Cooper-White, Justin

    2014-01-01

    As human embryonic stem cells (hESCs) steadily progress towards regenerative medicine applications there is an increasing emphasis on the development of bioreactor platforms that enable expansion of these cells to clinically relevant numbers. Surprisingly little is known about the metabolic requirements of hESCs, precluding the rational design and optimisation of such platforms. In this study, we undertook an in-depth characterisation of MEL-2 hESC metabolic behaviour during the exponential growth phase, combining metabolic profiling and flux analysis tools at physiological (hypoxic) and atmospheric (normoxic) oxygen concentrations. To overcome variability in growth profiles and the problem of closing mass balances in a complex environment, we developed protocols to accurately measure uptake and production rates of metabolites, cell density, growth rate and biomass composition, and designed a metabolic flux analysis model for estimating internal rates. hESCs are commonly considered to be highly glycolytic with inactive or immature mitochondria, however, whilst the results of this study confirmed that glycolysis is indeed highly active, we show that at least in MEL-2 hESC, it is supported by the use of oxidative phosphorylation within the mitochondria utilising carbon sources, such as glutamine to maximise ATP production. Under both conditions, glycolysis was disconnected from the mitochondria with all of the glucose being converted to lactate. No difference in the growth rates of cells cultured under physiological or atmospheric oxygen concentrations was observed nor did this cause differences in fluxes through the majority of the internal metabolic pathways associated with biogenesis. These results suggest that hESCs display the conventional Warburg effect, with high aerobic activity despite high lactate production, challenging the idea of an anaerobic metabolism with low mitochondrial activity. The results of this study provide new insight that can be used in

  8. In vivo imaging and quantitative monitoring of autophagic flux in tobacco BY-2 cells.

    PubMed

    Hanamata, Shigeru; Kurusu, Takamitsu; Okada, Masaaki; Suda, Akiko; Kawamura, Koki; Tsukada, Emi; Kuchitsu, Kazuyuki

    2013-01-01

    Autophagy has been shown to play essential roles in the growth, development and survival of eukaryotic cells. However, simple methods for quantification and visualization of autophagic flux remain to be developed in living plant cells. Here, we analyzed the autophagic flux in transgenic tobacco BY-2 cell lines expressing fluorescence-tagged NtATG8a as a marker for autophagosome formation. Under sucrose-starved conditions, the number of punctate signals of YFP-NtATG8a increased, and the fluorescence intensity of the cytoplasm and nucleoplasm decreased. Conversely, these changes were not observed in BY-2 cells expressing a C-terminal glycine deletion mutant of the NtATG8a protein (NtATG8aΔG). To monitor the autophagic flux more easily, we generated a transgenic BY-2 cell line expressing NtATG8a fused to a pH-sensitive fluorescent tag, a tandem fusion of the acid-insensitive RFP and the acid-sensitive YFP. In sucrose-rich conditions, both fluorescent signals were detected in the cytoplasm and only weakly in the vacuole. In contrast, under sucrose-starved conditions, the fluorescence intensity of the cytoplasm decreased, and the RFP signal clearly increased in the vacuole, corresponding to the fusion of the autophagosome to the vacuole and translocation of ATG8 from the cytoplasm to the vacuole. Moreover, we introduce a novel simple easy way to monitor the autophagic flux non-invasively by only measuring the ratio of fluorescence of RFP and YFP in the cell suspension using a fluorescent image analyzer without microscopy. The present in vivo quantitative monitoring system for the autophagic flux offers a powerful tool for determining the physiological functions and molecular mechanisms of plant autophagy induced by environmental stimuli.

  9. In vivo imaging and quantitative monitoring of autophagic flux in tobacco BY-2 cells

    PubMed Central

    Hanamata, Shigeru; Kurusu, Takamitsu; Okada, Masaaki; Suda, Akiko; Kawamura, Koki; Tsukada, Emi; Kuchitsu, Kazuyuki

    2013-01-01

    Autophagy has been shown to play essential roles in the growth, development and survival of eukaryotic cells. However, simple methods for quantification and visualization of autophagic flux remain to be developed in living plant cells. Here, we analyzed the autophagic flux in transgenic tobacco BY-2 cell lines expressing fluorescence-tagged NtATG8a as a marker for autophagosome formation. Under sucrose-starved conditions, the number of punctate signals of YFP-NtATG8a increased, and the fluorescence intensity of the cytoplasm and nucleoplasm decreased. Conversely, these changes were not observed in BY-2 cells expressing a C-terminal glycine deletion mutant of the NtATG8a protein (NtATG8aΔG). To monitor the autophagic flux more easily, we generated a transgenic BY-2 cell line expressing NtATG8a fused to a pH-sensitive fluorescent tag, a tandem fusion of the acid-insensitive RFP and the acid-sensitive YFP. In sucrose-rich conditions, both fluorescent signals were detected in the cytoplasm and only weakly in the vacuole. In contrast, under sucrose-starved conditions, the fluorescence intensity of the cytoplasm decreased, and the RFP signal clearly increased in the vacuole, corresponding to the fusion of the autophagosome to the vacuole and translocation of ATG8 from the cytoplasm to the vacuole. Moreover, we introduce a novel simple easy way to monitor the autophagic flux non-invasively by only measuring the ratio of fluorescence of RFP and YFP in the cell suspension using a fluorescent image analyzer without microscopy. The present in vivo quantitative monitoring system for the autophagic flux offers a powerful tool for determining the physiological functions and molecular mechanisms of plant autophagy induced by environmental stimuli. PMID:23123450

  10. Differential Substrate Usage and Metabolic Fluxes in Francisella tularensis Subspecies holarctica and Francisella novicida

    PubMed Central

    Chen, Fan; Rydzewski, Kerstin; Kutzner, Erika; Häuslein, Ina; Schunder, Eva; Wang, Xinzhe; Meighen-Berger, Kevin; Grunow, Roland; Eisenreich, Wolfgang; Heuner, Klaus

    2017-01-01

    Francisella tularensis is an intracellular pathogen for many animals causing the infectious disease, tularemia. Whereas F. tularensis subsp. holarctica is highly pathogenic for humans, F. novicida is almost avirulent for humans, but virulent for mice. In order to compare metabolic fluxes between these strains, we performed 13C-labeling experiments with F. tularensis subsp. holarctica wild type (beaver isolate), F. tularensis subsp. holarctica strain LVS, or F. novicida strain U112 in complex media containing either [U-13C6]glucose, [1,2-13C2]glucose, [U-13C3]serine, or [U-13C3]glycerol. GC/MS-based isotopolog profiling of amino acids, polysaccharide-derived glucose, free fructose, amino sugars derived from the cell wall, fatty acids, 3-hydroxybutyrate, lactate, succinate and malate revealed uptake and metabolic usage of all tracers under the experimental conditions with glucose being the major carbon source for all strains under study. The labeling patterns of the F. tularensis subsp. holarctica wild type were highly similar to those of the LVS strain, but showed remarkable differences to the labeling profiles of the metabolites from the F. novicida strain. Glucose was directly used for polysaccharide and cell wall biosynthesis with higher rates in F. tularensis subsp. holarctica or metabolized, with higher rates in F. novicida, via glycolysis and the non-oxidative pentose phosphate pathway (PPP). Catabolic turnover of glucose via gluconeogenesis was also observed. In all strains, Ala was mainly synthesized from pyruvate, although no pathway from pyruvate to Ala is annotated in the genomes of F. tularensis and F. novicida. Glycerol efficiently served as a gluconeogenetic substrate in F. novicida, but only less in the F. tularensis subsp. holarctica strains. In any of the studied strains, serine did not serve as a major substrate and was not significantly used for gluconeogenesis under the experimental conditions. Rather, it was only utilized, at low rates, in

  11. Omics markers of the red cell storage lesion and metabolic linkage

    PubMed Central

    D’Alessandro, Angelo; Nemkov, Travis; Reisz, Julie; Dzieciatkowska, Monika; Wither, Matthew J.; Hansen, Kirk C.

    2017-01-01

    The introduction of omics technologies in the field of Transfusion Medicine has significantly advanced our understanding of the red cell storage lesion. While the clinical relevance of such a lesion is still a matter of debate, quantitative and redox proteomics approaches, as well quantitative metabolic flux analysis and metabolic tracing experiments promise to revolutionise our understanding of the role of blood processing strategies, inform the design and testing of novel additives or technologies (such as pathogen reduction), and evaluate the clinical relevance of donor and recipient biological variability with respect to red cell storability and transfusion outcomes. By reviewing existing literature in this rapidly expanding research endeavour, we highlight for the first time a correlation between metabolic markers of the red cell storage age and protein markers of haemolysis. Finally, we introduce the concept of metabolic linkage, i.e. the appreciation of a network of highly correlated small molecule metabolites which results from biochemical constraints of erythrocyte metabolic enzyme activities. For the foreseeable future, red cell studies will advance Transfusion Medicine and haematology by addressing the alteration of metabolic linkage phenotypes in response to stimuli, including, but not limited to, storage additives, enzymopathies (e.g. glucose 6-phosphate dehydrogenase deficiency), hypoxia, sepsis or haemorrhage. PMID:28263171

  12. Comprehensive metabolic modeling of multiple 13C-isotopomer data sets to study metabolism in perfused working hearts

    PubMed Central

    Kelleher, Joanne K.; Rouf, Rosanne; Muoio, Deborah M.; Antoniewicz, Maciek R.

    2016-01-01

    In many forms of cardiomyopathy, alterations in energy substrate metabolism play a key role in disease pathogenesis. Stable isotope tracing in rodent heart perfusion systems can be used to determine cardiac metabolic fluxes, namely those relative fluxes that contribute to pyruvate, the acetyl-CoA pool, and pyruvate anaplerosis, which are critical to cardiac homeostasis. Methods have previously been developed to interrogate these relative fluxes using isotopomer enrichments of measured metabolites and algebraic equations to determine a predefined metabolic flux model. However, this approach is exquisitely sensitive to measurement error, thus precluding accurate relative flux parameter determination. In this study, we applied a novel mathematical approach to determine relative cardiac metabolic fluxes using 13C-metabolic flux analysis (13C-MFA) aided by multiple tracer experiments and integrated data analysis. Using 13C-MFA, we validated a metabolic network model to explain myocardial energy substrate metabolism. Four different 13C-labeled substrates were queried (i.e., glucose, lactate, pyruvate, and oleate) based on a previously published study. We integrated the analysis of the complete set of isotopomer data gathered from these mouse heart perfusion experiments into a single comprehensive network model that delineates substrate contributions to both pyruvate and acetyl-CoA pools at a greater resolution than that offered by traditional methods using algebraic equations. To our knowledge, this is the first rigorous application of 13C-MFA to interrogate data from multiple tracer experiments in the perfused heart. We anticipate that this approach can be used widely to study energy substrate metabolism in this and other similar biological systems. PMID:27496880

  13. Shigella reroutes host cell central metabolism to obtain high-flux nutrient supply for vigorous intracellular growth.

    PubMed

    Kentner, David; Martano, Giuseppe; Callon, Morgane; Chiquet, Petra; Brodmann, Maj; Burton, Olga; Wahlander, Asa; Nanni, Paolo; Delmotte, Nathanaël; Grossmann, Jonas; Limenitakis, Julien; Schlapbach, Ralph; Kiefer, Patrick; Vorholt, Julia A; Hiller, Sebastian; Bumann, Dirk

    2014-07-08

    Shigella flexneri proliferate in infected human epithelial cells at exceptionally high rates. This vigorous growth has important consequences for rapid progression to life-threatening bloody diarrhea, but the underlying metabolic mechanisms remain poorly understood. Here, we used metabolomics, proteomics, and genetic experiments to determine host and Shigella metabolism during infection in a cell culture model. The data suggest that infected host cells maintain largely normal fluxes through glycolytic pathways, but the entire output of these pathways is captured by Shigella, most likely in the form of pyruvate. This striking strategy provides Shigella with an abundant favorable energy source, while preserving host cell ATP generation, energy charge maintenance, and survival, despite ongoing vigorous exploitation. Shigella uses a simple three-step pathway to metabolize pyruvate at high rates with acetate as an excreted waste product. The crucial role of this pathway for Shigella intracellular growth suggests targets for antimicrobial chemotherapy of this devastating disease.

  14. Shigella reroutes host cell central metabolism to obtain high-flux nutrient supply for vigorous intracellular growth

    PubMed Central

    Kentner, David; Martano, Giuseppe; Callon, Morgane; Chiquet, Petra; Brodmann, Maj; Burton, Olga; Wahlander, Asa; Nanni, Paolo; Delmotte, Nathanaël; Grossmann, Jonas; Limenitakis, Julien; Schlapbach, Ralph; Kiefer, Patrick; Vorholt, Julia A.; Hiller, Sebastian; Bumann, Dirk

    2014-01-01

    Shigella flexneri proliferate in infected human epithelial cells at exceptionally high rates. This vigorous growth has important consequences for rapid progression to life-threatening bloody diarrhea, but the underlying metabolic mechanisms remain poorly understood. Here, we used metabolomics, proteomics, and genetic experiments to determine host and Shigella metabolism during infection in a cell culture model. The data suggest that infected host cells maintain largely normal fluxes through glycolytic pathways, but the entire output of these pathways is captured by Shigella, most likely in the form of pyruvate. This striking strategy provides Shigella with an abundant favorable energy source, while preserving host cell ATP generation, energy charge maintenance, and survival, despite ongoing vigorous exploitation. Shigella uses a simple three-step pathway to metabolize pyruvate at high rates with acetate as an excreted waste product. The crucial role of this pathway for Shigella intracellular growth suggests targets for antimicrobial chemotherapy of this devastating disease. PMID:24958876

  15. Effect of amino acid supplementation on titer and glycosylation distribution in hybridoma cell cultures-Systems biology-based interpretation using genome-scale metabolic flux balance model and multivariate data analysis.

    PubMed

    Reimonn, Thomas M; Park, Seo-Young; Agarabi, Cyrus D; Brorson, Kurt A; Yoon, Seongkyu

    2016-09-01

    Genome-scale flux balance analysis (FBA) is a powerful systems biology tool to characterize intracellular reaction fluxes during cell cultures. FBA estimates intracellular reaction rates by optimizing an objective function, subject to the constraints of a metabolic model and media uptake/excretion rates. A dynamic extension to FBA, dynamic flux balance analysis (DFBA), can calculate intracellular reaction fluxes as they change during cell cultures. In a previous study by Read et al. (2013), a series of informed amino acid supplementation experiments were performed on twelve parallel murine hybridoma cell cultures, and this data was leveraged for further analysis (Read et al., Biotechnol Prog. 2013;29:745-753). In order to understand the effects of media changes on the model murine hybridoma cell line, a systems biology approach is applied in the current study. Dynamic flux balance analysis was performed using a genome-scale mouse metabolic model, and multivariate data analysis was used for interpretation. The calculated reaction fluxes were examined using partial least squares and partial least squares discriminant analysis. The results indicate media supplementation increases product yield because it raises nutrient levels extending the growth phase, and the increased cell density allows for greater culture performance. At the same time, the directed supplementation does not change the overall metabolism of the cells. This supports the conclusion that product quality, as measured by glycoform assays, remains unchanged because the metabolism remains in a similar state. Additionally, the DFBA shows that metabolic state varies more at the beginning of the culture but less by the middle of the growth phase, possibly due to stress on the cells during inoculation. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:1163-1173, 2016. © 2016 American Institute of Chemical Engineers.

  16. Control of fluxes in metabolic networks

    PubMed Central

    Basler, Georg; Nikoloski, Zoran; Larhlimi, Abdelhalim; Barabási, Albert-László; Liu, Yang-Yu

    2016-01-01

    Understanding the control of large-scale metabolic networks is central to biology and medicine. However, existing approaches either require specifying a cellular objective or can only be used for small networks. We introduce new coupling types describing the relations between reaction activities, and develop an efficient computational framework, which does not require any cellular objective for systematic studies of large-scale metabolism. We identify the driver reactions facilitating control of 23 metabolic networks from all kingdoms of life. We find that unicellular organisms require a smaller degree of control than multicellular organisms. Driver reactions are under complex cellular regulation in Escherichia coli, indicating their preeminent role in facilitating cellular control. In human cancer cells, driver reactions play pivotal roles in malignancy and represent potential therapeutic targets. The developed framework helps us gain insights into regulatory principles of diseases and facilitates design of engineering strategies at the interface of gene regulation, signaling, and metabolism. PMID:27197218

  17. Control of fluxes in metabolic networks.

    PubMed

    Basler, Georg; Nikoloski, Zoran; Larhlimi, Abdelhalim; Barabási, Albert-László; Liu, Yang-Yu

    2016-07-01

    Understanding the control of large-scale metabolic networks is central to biology and medicine. However, existing approaches either require specifying a cellular objective or can only be used for small networks. We introduce new coupling types describing the relations between reaction activities, and develop an efficient computational framework, which does not require any cellular objective for systematic studies of large-scale metabolism. We identify the driver reactions facilitating control of 23 metabolic networks from all kingdoms of life. We find that unicellular organisms require a smaller degree of control than multicellular organisms. Driver reactions are under complex cellular regulation in Escherichia coli, indicating their preeminent role in facilitating cellular control. In human cancer cells, driver reactions play pivotal roles in malignancy and represent potential therapeutic targets. The developed framework helps us gain insights into regulatory principles of diseases and facilitates design of engineering strategies at the interface of gene regulation, signaling, and metabolism. © 2016 Basler et al.; Published by Cold Spring Harbor Laboratory Press.

  18. Systematic inference of functional phosphorylation events in yeast metabolism.

    PubMed

    Chen, Yu; Wang, Yonghong; Nielsen, Jens

    2017-07-01

    Protein phosphorylation is a post-translational modification that affects proteins by changing their structure and conformation in a rapid and reversible way, and it is an important mechanism for metabolic regulation in cells. Phosphoproteomics enables high-throughput identification of phosphorylation events on metabolic enzymes, but identifying functional phosphorylation events still requires more detailed biochemical characterization. Therefore, development of computational methods for investigating unknown functions of a large number of phosphorylation events identified by phosphoproteomics has received increased attention. We developed a mathematical framework that describes the relationship between phosphorylation level of a metabolic enzyme and the corresponding flux through the enzyme. Using this framework, it is possible to quantitatively estimate contribution of phosphorylation events to flux changes. We showed that phosphorylation regulation analysis, combined with a systematic workflow and correlation analysis, can be used for inference of functional phosphorylation events in steady and dynamic conditions, respectively. Using this analysis, we assigned functionality to phosphorylation events of 17 metabolic enzymes in the yeast Saccharomyces cerevisiae , among which 10 are novel. Phosphorylation regulation analysis cannot only be extended for inference of other functional post-translational modifications but also be a promising scaffold for multi-omics data integration in systems biology. Matlab codes for flux balance analysis in this study are available in Supplementary material. yhwang@ecust.edu.cn or nielsenj@chalmers.se. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com

  19. Quantitative optical imaging of paracetamol-induced metabolism changes in the liver

    NASA Astrophysics Data System (ADS)

    Liang, Xiaowen; Wang, Haolu; Liu, Xin; Roberts, Michael

    2016-12-01

    Paracetamol is the most readily available and widely used painkiller. However, its toxicity remains the most common cause of liver injury. The toxicity of paracetamol has been attributing to its toxic metabolite, which depletes cellular glutathione (GSH) stores and reacts within cells to increase oxidative stress, leading to mitochondrial dysfunction and cell necrosis. Multiphoton microscopy (MPM) and fluorescence lifetime imaging (FLIM) can provide quantitative imaging of biological tissues and organs in vivo and allow direct visualization of cellular events, which were used to monitor cellular metabolism in paracetamol-induced toxicity in this study. To better understand mechanisms of paracetamol induced liver injury, the redox ratio of NADH/FAD in liver cells were detected and quantified by MPM imaging to represent the relative rates of glycolysis and oxidative phosphorylation within cells. Compared to normal liver, average fluorescence lifetime of NADH and redox ratio of NADH/FAD in hepatocytes was significantly decreased after paracetamol overdose for 12 and 24 hrs, reflecting impaired metabolic activity. GSH levels of treatment groups were significantly lower than those of normal livers, with gradually decreasing from periportal to centrilobular zonation. This imaging technique has significant implications for investigating metabolic mechanisms of paracetamol toxicity.

  20. Quantitative Method to Investigate the Balance between Metabolism and Proteome Biomass: Starting from Glycine.

    PubMed

    Gu, Haiwei; Carroll, Patrick A; Du, Jianhai; Zhu, Jiangjiang; Neto, Fausto Carnevale; Eisenman, Robert N; Raftery, Daniel

    2016-12-12

    The balance between metabolism and biomass is very important in biological systems; however, to date there has been no quantitative method to characterize the balance. In this methodological study, we propose to use the distribution of amino acids in different domains to investigate this balance. It is well known that endogenous or exogenous amino acids in a biological system are either metabolized or incorporated into free amino acids (FAAs) or proteome amino acids (PAAs). Using glycine (Gly) as an example, we demonstrate a novel method to accurately determine the amounts of amino acids in various domains using serum, urine, and cell samples. As expected, serum and urine had very different distributions of FAA- and PAA-Gly. Using Tet21N human neuroblastoma cells, we also found that Myc(oncogene)-induced metabolic reprogramming included a higher rate of metabolizing Gly, which provides additional evidence that the metabolism of proliferating cells is adapted to facilitate producing new cells. It is therefore anticipated that our method will be very valuable for further studies of the metabolism and biomass balance that will lead to a better understanding of human cancers. © 2016 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

  1. A bottom-up approach to urban metabolism: the perspective of BRIDGE

    NASA Astrophysics Data System (ADS)

    Chrysoulakis, N.; Borrego, C.; San Josè, R.; Grimmond, S. B.; Jones, M. B.; Magliulo, V.; Klostermann, J.; Santamouris, M.

    2011-12-01

    Urban metabolism considers a city as a system and usually distinguishes between energy and material flows as its components. "Metabolic" studies are usually top-down approaches that assess the inputs and outputs of food, water, energy, and pollutants from a city, or that compare the changing metabolic process of several cities. In contrast, bottom-up approaches are based on quantitative estimates of urban metabolism components at local to regional scales. Such approaches consider the urban metabolism as the 3D exchange and transformation of energy and matter between a city and its environment. The city is considered as a system and the physical flows between this system and its environment are quantitatively estimated. The transformation of landscapes from primarily agricultural and forest uses to urbanized landscapes can greatly modify energy and material exchanges and it is, therefore, an important aspect of an urban area. Here we focus on the exchanges and transformation of energy, water, carbon and pollutants. Recent advances in bio-physical sciences have led to new methods and models to estimate local scale energy, water, carbon and pollutant fluxes. However, there is often poor communication of new knowledge and its implications to end-users, such as planners, architects and engineers. The FP7 Project BRIDGE (SustainaBle uRban plannIng Decision support accountinG for urban mEtabolism) aims at bridging this gap and at illustrating the advantages of considering environmental issues in urban planning. BRIDGE does not perform a complete life cycle analysis or calculate whole system urban metabolism, but rather focuses on specific metabolism components (energy, water, carbon and pollutants). Its main goal is the development of a Decision Suport System (DSS) with the potential to select planning actions which better fit the goal of changing the metabolism of urban systems towards sustainability. BRIDGE evaluates how planning alternatives can modify the physical

  2. Quantitative Validation of the Presto Blue Metabolic Assay for Online Monitoring of Cell Proliferation in a 3D Perfusion Bioreactor System.

    PubMed

    Sonnaert, Maarten; Papantoniou, Ioannis; Luyten, Frank P; Schrooten, Jan Ir

    2015-06-01

    As the fields of tissue engineering and regenerative medicine mature toward clinical applications, the need for online monitoring both for quantitative and qualitative use becomes essential. Resazurin-based metabolic assays are frequently applied for determining cytotoxicity and have shown great potential for monitoring 3D bioreactor-facilitated cell culture. However, no quantitative correlation between the metabolic conversion rate of resazurin and cell number has been defined yet. In this work, we determined conversion rates of Presto Blue, a resazurin-based metabolic assay, for human periosteal cells during 2D and 3D static and 3D perfusion cultures. Our results showed that for the evaluated culture systems there is a quantitative correlation between the Presto Blue conversion rate and the cell number during the expansion phase with no influence of the perfusion-related parameters, that is, flow rate and shear stress. The correlation between the cell number and Presto Blue conversion subsequently enabled the definition of operating windows for optimal signal readouts. In conclusion, our data showed that the conversion of the resazurin-based Presto Blue metabolic assay can be used as a quantitative readout for online monitoring of cell proliferation in a 3D perfusion bioreactor system, although a system-specific validation is required.

  3. Quantitative Validation of the Presto Blue™ Metabolic Assay for Online Monitoring of Cell Proliferation in a 3D Perfusion Bioreactor System

    PubMed Central

    Sonnaert, Maarten; Papantoniou, Ioannis; Luyten, Frank P.

    2015-01-01

    As the fields of tissue engineering and regenerative medicine mature toward clinical applications, the need for online monitoring both for quantitative and qualitative use becomes essential. Resazurin-based metabolic assays are frequently applied for determining cytotoxicity and have shown great potential for monitoring 3D bioreactor-facilitated cell culture. However, no quantitative correlation between the metabolic conversion rate of resazurin and cell number has been defined yet. In this work, we determined conversion rates of Presto Blue™, a resazurin-based metabolic assay, for human periosteal cells during 2D and 3D static and 3D perfusion cultures. Our results showed that for the evaluated culture systems there is a quantitative correlation between the Presto Blue conversion rate and the cell number during the expansion phase with no influence of the perfusion-related parameters, that is, flow rate and shear stress. The correlation between the cell number and Presto Blue conversion subsequently enabled the definition of operating windows for optimal signal readouts. In conclusion, our data showed that the conversion of the resazurin-based Presto Blue metabolic assay can be used as a quantitative readout for online monitoring of cell proliferation in a 3D perfusion bioreactor system, although a system-specific validation is required. PMID:25336207

  4. A dynamic metabolic flux analysis of ABE (acetone-butanol-ethanol) fermentation by Clostridium acetobutylicum ATCC 824, with riboflavin as a by-product.

    PubMed

    Zhao, Xinhe; Kasbi, Mayssa; Chen, Jingkui; Peres, Sabine; Jolicoeur, Mario

    2017-12-01

    The present study reveals that supplementing sodium acetate (NaAc) strongly stimulates riboflavin production in acetone-butanol-ethanol (ABE) fermentation by Clostridium acetobutylicum ATCC 824 with xylose as carbon source. Riboflavin production increased from undetectable concentrations to ∼0.2 g L -1 (0.53 mM) when supplementing 60 mM NaAc. Of interest, solvents production and biomass yield were also promoted with fivefold acetone, 2.6-fold butanol, and 2.4-fold biomass adding NaAc. A kinetic metabolic model, developed to simulate ABE biosystem, with riboflavin production, revealed from a dynamic metabolic flux analysis (dMFA) simultaneous increase of riboflavin (ribA) and GTP (precursor of riboflavin) (PurM) synthesis flux rates under NaAc supplementation. The model includes 23 fluxes, 24 metabolites, and 72 kinetic parameters. It also suggested that NaAc condition has first stimulated the accumulation of intracellular metabolite intermediates during the acidogenic phase, which have then fed the solventogenic phase leading to increased ABE production. In addition, NaAc resulted in higher intracellular levels of NADH during the whole culture. Moreover, lower GTP-to-adenosine phosphates (ATP, ADP, AMP) ratio under NaAc supplemented condition suggests that GTP may have a minor role in the cell energetic metabolism compared to its contribution to riboflavin synthesis. © 2017 Wiley Periodicals, Inc.

  5. Comparative 13C Metabolic Flux Analysis of Pyruvate Dehydrogenase Complex-Deficient, l-Valine-Producing Corynebacterium glutamicum▿†

    PubMed Central

    Bartek, Tobias; Blombach, Bastian; Lang, Siegmund; Eikmanns, Bernhard J.; Wiechert, Wolfgang; Oldiges, Marco; Nöh, Katharina; Noack, Stephan

    2011-01-01

    l-Valine can be formed successfully using C. glutamicum strains missing an active pyruvate dehydrogenase enzyme complex (PDHC). Wild-type C. glutamicum and four PDHC-deficient strains were compared by 13C metabolic flux analysis, especially focusing on the split ratio between glycolysis and the pentose phosphate pathway (PPP). Compared to the wild type, showing a carbon flux of 69% ± 14% through the PPP, a strong increase in the PPP flux was observed in PDHC-deficient strains with a maximum of 113% ± 22%. The shift in the split ratio can be explained by an increased demand of NADPH for l-valine formation. In accordance, the introduction of the Escherichia coli transhydrogenase PntAB, catalyzing the reversible conversion of NADH to NADPH, into an l-valine-producing C. glutamicum strain caused the PPP flux to decrease to 57% ± 6%, which is below the wild-type split ratio. Hence, transhydrogenase activity offers an alternative perspective for sufficient NADPH supply, which is relevant for most amino acid production systems. Moreover, as demonstrated for l-valine, this bypass leads to a significant increase of product yield due to a concurrent reduction in carbon dioxide formation via the PPP. PMID:21784914

  6. Comprehensive metabolic modeling of multiple 13C-isotopomer data sets to study metabolism in perfused working hearts.

    PubMed

    Crown, Scott B; Kelleher, Joanne K; Rouf, Rosanne; Muoio, Deborah M; Antoniewicz, Maciek R

    2016-10-01

    In many forms of cardiomyopathy, alterations in energy substrate metabolism play a key role in disease pathogenesis. Stable isotope tracing in rodent heart perfusion systems can be used to determine cardiac metabolic fluxes, namely those relative fluxes that contribute to pyruvate, the acetyl-CoA pool, and pyruvate anaplerosis, which are critical to cardiac homeostasis. Methods have previously been developed to interrogate these relative fluxes using isotopomer enrichments of measured metabolites and algebraic equations to determine a predefined metabolic flux model. However, this approach is exquisitely sensitive to measurement error, thus precluding accurate relative flux parameter determination. In this study, we applied a novel mathematical approach to determine relative cardiac metabolic fluxes using 13 C-metabolic flux analysis ( 13 C-MFA) aided by multiple tracer experiments and integrated data analysis. Using 13 C-MFA, we validated a metabolic network model to explain myocardial energy substrate metabolism. Four different 13 C-labeled substrates were queried (i.e., glucose, lactate, pyruvate, and oleate) based on a previously published study. We integrated the analysis of the complete set of isotopomer data gathered from these mouse heart perfusion experiments into a single comprehensive network model that delineates substrate contributions to both pyruvate and acetyl-CoA pools at a greater resolution than that offered by traditional methods using algebraic equations. To our knowledge, this is the first rigorous application of 13 C-MFA to interrogate data from multiple tracer experiments in the perfused heart. We anticipate that this approach can be used widely to study energy substrate metabolism in this and other similar biological systems. Copyright © 2016 the American Physiological Society.

  7. Reducing Recon 2 for steady-state flux analysis of HEK cell culture.

    PubMed

    Quek, Lake-Ee; Dietmair, Stefanie; Hanscho, Michael; Martínez, Verónica S; Borth, Nicole; Nielsen, Lars K

    2014-08-20

    A representative stoichiometric model is essential to perform metabolic flux analysis (MFA) using experimentally measured consumption (or production) rates as constraints. For Human Embryonic Kidney (HEK) cell culture, there is the opportunity to use an extremely well-curated and annotated human genome-scale model Recon 2 for MFA. Performing MFA using Recon 2 without any modification would have implied that cells have access to all functionality encoded by the genome, which is not realistic. The majority of intracellular fluxes are poorly determined as only extracellular exchange rates are measured. This is compounded by the fact that there is no suitable metabolic objective function to suppress non-specific fluxes. We devised a heuristic to systematically reduce Recon 2 to emphasize flux through core metabolic reactions. This implies that cells would engage these dominant metabolic pathways to grow, and any significant changes in gross metabolic phenotypes would have invoked changes in these pathways. The reduced metabolic model becomes a functionalized version of Recon 2 used for identifying significant metabolic changes in cells by flux analysis. Copyright © 2014 Elsevier B.V. All rights reserved.

  8. Resource constrained flux balance analysis predicts selective pressure on the global structure of metabolic networks.

    PubMed

    Abedpour, Nima; Kollmann, Markus

    2015-11-23

    A universal feature of metabolic networks is their hourglass or bow-tie structure on cellular level. This architecture reflects the conversion of multiple input nutrients into multiple biomass components via a small set of precursor metabolites. However, it is yet unclear to what extent this structural feature is the result of natural selection. We extend flux balance analysis to account for limited cellular resources. Using this model, optimal structure of metabolic networks can be calculated for different environmental conditions. We observe a significant structural reshaping of metabolic networks for a toy-network and E. coli core metabolism if we increase the share of invested resources for switching between different nutrient conditions. Here, hub nodes emerge and the optimal network structure becomes bow-tie-like as a consequence of limited cellular resource constraint. We confirm this theoretical finding by comparing the reconstructed metabolic networks of bacterial species with respect to their lifestyle. We show that bow-tie structure can give a system-level fitness advantage to organisms that live in highly competitive and fluctuating environments. Here, limitation of cellular resources can lead to an efficiency-flexibility tradeoff where it pays off for the organism to shorten catabolic pathways if they are frequently activated and deactivated. As a consequence, generalists that shuttle between diverse environmental conditions should have a more predominant bow-tie structure than specialists that visit just a few isomorphic habitats during their life cycle.

  9. The Short-Chain Fatty Acid Uptake Fluxes by Mice on a Guar Gum Supplemented Diet Associate with Amelioration of Major Biomarkers of the Metabolic Syndrome

    PubMed Central

    den Besten, Gijs; Havinga, Rick; Bleeker, Aycha; Rao, Shodhan; Gerding, Albert; van Eunen, Karen; Groen, Albert K.; Reijngoud, Dirk-Jan; Bakker, Barbara M.

    2014-01-01

    Studies with dietary supplementation of various types of fibers have shown beneficial effects on symptoms of the metabolic syndrome. Short-chain fatty acids (SCFAs), the main products of intestinal bacterial fermentation of dietary fiber, have been suggested to play a key role. Whether the concentration of SCFAs or their metabolism drives these beneficial effects is not yet clear. In this study we investigated the SCFA concentrations and in vivo host uptake fluxes in the absence or presence of the dietary fiber guar gum. C57Bl/6J mice were fed a high-fat diet supplemented with 0%, 5%, 7.5% or 10% of the fiber guar gum. To determine the effect on SCFA metabolism, 13C-labeled acetate, propionate or butyrate were infused into the cecum of mice for 6 h and the isotopic enrichment of cecal SCFAs was measured. The in vivo production, uptake and bacterial interconversion of acetate, propionate and butyrate were calculated by combining the data from the three infusion experiments in a single steady-state isotope model. Guar gum treatment decreased markers of the metabolic syndrome (body weight, adipose weight, triglycerides, glucose and insulin levels and HOMA-IR) in a dose-dependent manner. In addition, hepatic mRNA expression of genes involved in gluconeogenesis and fatty acid synthesis decreased dose-dependently by guar gum treatment. Cecal SCFA concentrations were increased compared to the control group, but no differences were observed between the different guar gum doses. Thus, no significant correlation was found between cecal SCFA concentrations and metabolic markers. In contrast, in vivo SCFA uptake fluxes by the host correlated linearly with metabolic markers. We argue that in vivo SCFA fluxes, and not concentrations, govern the protection from the metabolic syndrome by dietary fibers. PMID:25203112

  10. Staphylococcus aureus Coordinates Leukocidin Expression and Pathogenesis by Sensing Metabolic Fluxes via RpiRc

    PubMed Central

    Balasubramanian, Divya; Ohneck, Elizabeth A.; Chapman, Jessica; Weiss, Andy; Kim, Min Kyung; Reyes-Robles, Tamara; Zhong, Judy; Shaw, Lindsey N.; Lun, Desmond S.; Ueberheide, Beatrix; Shopsin, Bo

    2016-01-01

    ABSTRACT Staphylococcus aureus is a formidable human pathogen that uses secreted cytolytic factors to injure immune cells and promote infection of its host. Of these proteins, the bicomponent family of pore-forming leukocidins play critical roles in S. aureus pathogenesis. The regulatory mechanisms governing the expression of these toxins are incompletely defined. In this work, we performed a screen to identify transcriptional regulators involved in leukocidin expression in S. aureus strain USA300. We discovered that a metabolic sensor-regulator, RpiRc, is a potent and selective repressor of two leukocidins, LukED and LukSF-PV. Whole-genome transcriptomics, S. aureus exoprotein proteomics, and metabolomic analyses revealed that RpiRc influences the expression and production of disparate virulence factors. Additionally, RpiRc altered metabolic fluxes in the trichloroacetic acid cycle, glycolysis, and amino acid metabolism. Using mutational analyses, we confirmed and extended the observation that RpiRc signals through the accessory gene regulatory (Agr) quorum-sensing system in USA300. Specifically, RpiRc represses the rnaIII promoter, resulting in increased repressor of toxins (Rot) levels, which in turn negatively affect leukocidin expression. Inactivation of rpiRc phenocopied rot deletion and increased S. aureus killing of primary human polymorphonuclear leukocytes and the pathogenesis of bloodstream infection in vivo. Collectively, our results suggest that S. aureus senses metabolic shifts by RpiRc to differentially regulate the expression of leukocidins and to promote invasive disease. PMID:27329753

  11. Investigation of metabolic objectives in cultured hepatocytes.

    PubMed

    Uygun, Korkut; Matthew, Howard W T; Huang, Yinlun

    2007-06-15

    Using optimization based methods to predict fluxes in metabolic flux balance models has been a successful approach for some microorganisms, enabling construction of in silico models and even inference of some regulatory motifs. However, this success has not been translated to mammalian cells. The lack of knowledge about metabolic objectives in mammalian cells is a major obstacle that prevents utilization of various metabolic engineering tools and methods for tissue engineering and biomedical purposes. In this work, we investigate and identify possible metabolic objectives for hepatocytes cultured in vitro. To achieve this goal, we present a special data-mining procedure for identifying metabolic objective functions in mammalian cells. This multi-level optimization based algorithm enables identifying the major fluxes in the metabolic objective from MFA data in the absence of information about critical active constraints of the system. Further, once the objective is determined, active flux constraints can also be identified and analyzed. This information can be potentially used in a predictive manner to improve cell culture results or clinical metabolic outcomes. As a result of the application of this method, it was found that in vitro cultured hepatocytes maximize oxygen uptake, coupling of urea and TCA cycles, and synthesis of serine and urea. Selection of these fluxes as the metabolic objective enables accurate prediction of the flux distribution in the system given a limited amount of flux data; thus presenting a workable in silico model for cultured hepatocytes. It is observed that an overall homeostasis picture is also emergent in the findings.

  12. Quantitative metabolic imaging using endogenous fluorescence to detect stem cell differentiation

    NASA Astrophysics Data System (ADS)

    Quinn, Kyle P.; Sridharan, Gautham V.; Hayden, Rebecca S.; Kaplan, David L.; Lee, Kyongbum; Georgakoudi, Irene

    2013-12-01

    The non-invasive high-resolution spatial mapping of cell metabolism within tissues could provide substantial advancements in assessing the efficacy of stem cell therapy and understanding tissue development. Here, using two-photon excited fluorescence microscopy, we elucidate the relationships among endogenous cell fluorescence, cell redox state, and the differentiation of human mesenchymal stem cells into adipogenic and osteoblastic lineages. Using liquid chromatography/mass spectrometry and quantitative PCR, we evaluate the sensitivity of an optical redox ratio of FAD/(NADH + FAD) to metabolic changes associated with stem cell differentiation. Furthermore, we probe the underlying physiological mechanisms, which relate a decrease in the redox ratio to the onset of differentiation. Because traditional assessments of stem cells and engineered tissues are destructive, time consuming, and logistically intensive, the development and validation of a non-invasive, label-free approach to defining the spatiotemporal patterns of cell differentiation can offer a powerful tool for rapid, high-content characterization of cell and tissue cultures.

  13. Quantitative evaluation of high-energy O- ion particle flux in a DC magnetron sputter plasma with an indium-tin-oxide target

    NASA Astrophysics Data System (ADS)

    Suyama, Taku; Bae, Hansin; Setaka, Kenta; Ogawa, Hayato; Fukuoka, Yushi; Suzuki, Haruka; Toyoda, Hirotaka

    2017-11-01

    O- ion flux from the indium tin oxide (ITO) sputter target under Ar ion bombardment is quantitatively evaluated using a calorimetry method. Using a mass spectrometer with an energy analyzer, O- energy distribution is measured with spatial dependence. Directional high-energy O- ion ejected from the target surface is observed. Using a calorimetry method, localized heat flux originated from high-energy O- ion is measured. From absolute evaluation of the heat flux from O- ion, O- particle flux in order of 1018 m-2 s-1 is evaluated at a distance of 10 cm from the target. Production yield of O- ion on the ITO target by one Ar+ ion impingement at a kinetic energy of 244 eV is estimated to be 3.3  ×  10-3 as the minimum value.

  14. Addressing metabolic heterogeneity in clear cell renal cell carcinoma with quantitative Dixon MRI

    PubMed Central

    Zhang, Yue; Udayakumar, Durga; Cai, Ling; Hu, Zeping; Kapur, Payal; Kho, Eun-Young; Pavía-Jiménez, Andrea; Fulkerson, Michael; de Leon, Alberto Diaz; Yuan, Qing; Dimitrov, Ivan E.; Ye, Jin; Mitsche, Matthew A.; Kim, Hyeonwoo; McDonald, Jeffrey G.; Madhuranthakam, Ananth J.; Dwivedi, Durgesh K.; Lenkinski, Robert E.; Cadeddu, Jeffrey A.; Margulis, Vitaly; Brugarolas, James; DeBerardinis, Ralph J.

    2017-01-01

    BACKGROUND. Dysregulated lipid and glucose metabolism in clear cell renal cell carcinoma (ccRCC) has been implicated in disease progression, and whole tumor tissue–based assessment of these changes is challenged by the tumor heterogeneity. We studied a noninvasive quantitative MRI method that predicts metabolic alterations in the whole tumor. METHODS. We applied Dixon-based MRI for in vivo quantification of lipid accumulation (fat fraction [FF]) in targeted regions of interest of 45 primary ccRCCs and correlated these MRI measures to mass spectrometry–based lipidomics and metabolomics of anatomically colocalized tissue samples isolated from the same tumor after surgery. RESULTS. In vivo tumor FF showed statistically significant (P < 0.0001) positive correlation with histologic fat content (Spearman correlation coefficient, ρ = 0.79), spectrometric triglycerides (ρ = 0.56) and cholesterol (ρ = 0.47); it showed negative correlation with free fatty acids (ρ = –0.44) and phospholipids (ρ = –0.65). We observed both inter- and intratumoral heterogeneity in lipid accumulation within the same tumor grade, whereas most aggressive tumors (International Society of Urological Pathology [ISUP] grade 4) exhibited reduced lipid accumulation. Cellular metabolites in tumors were altered compared with adjacent renal parenchyma. CONCLUSION. Our results support the use of noninvasive quantitative Dixon-based MRI as a biomarker of reprogrammed lipid metabolism in ccRCC, which may serve as a predictor of tumor aggressiveness before surgical intervention. FUNDING. NIH R01CA154475 (YZ, MF, PK, IP), NIH P50CA196516 (IP, JB, RJD, JAC, PK), Welch Foundation I-1832 (JY), and NIH P01HL020948 (JGM). PMID:28768909

  15. Leaf day respiration: low CO2 flux but high significance for metabolism and carbon balance.

    PubMed

    Tcherkez, Guillaume; Gauthier, Paul; Buckley, Thomas N; Busch, Florian A; Barbour, Margaret M; Bruhn, Dan; Heskel, Mary A; Gong, Xiao Ying; Crous, Kristine Y; Griffin, Kevin; Way, Danielle; Turnbull, Matthew; Adams, Mark A; Atkin, Owen K; Farquhar, Graham D; Cornic, Gabriel

    2017-12-01

    Contents 986 I. 987 II. 987 III. 988 IV. 991 V. 992 VI. 995 VII. 997 VIII. 998 References 998 SUMMARY: It has been 75 yr since leaf respiratory metabolism in the light (day respiration) was identified as a low-flux metabolic pathway that accompanies photosynthesis. In principle, it provides carbon backbones for nitrogen assimilation and evolves CO 2 and thus impacts on plant carbon and nitrogen balances. However, for a long time, uncertainties have remained as to whether techniques used to measure day respiratory efflux were valid and whether day respiration responded to environmental gaseous conditions. In the past few years, significant advances have been made using carbon isotopes, 'omics' analyses and surveys of respiration rates in mesocosms or ecosystems. There is substantial evidence that day respiration should be viewed as a highly dynamic metabolic pathway that interacts with photosynthesis and photorespiration and responds to atmospheric CO 2 mole fraction. The view of leaf day respiration as a constant and/or negligible parameter of net carbon exchange is now outdated and it should now be regarded as a central actor of plant carbon-use efficiency. © 2017 The Authors. New Phytologist © 2017 New Phytologist Trust.

  16. An objective function exploiting suboptimal solutions in metabolic networks

    PubMed Central

    2013-01-01

    Background Flux Balance Analysis is a theoretically elegant, computationally efficient, genome-scale approach to predicting biochemical reaction fluxes. Yet FBA models exhibit persistent mathematical degeneracy that generally limits their predictive power. Results We propose a novel objective function for cellular metabolism that accounts for and exploits degeneracy in the metabolic network to improve flux predictions. In our model, regulation drives metabolism toward a region of flux space that allows nearly optimal growth. Metabolic mutants deviate minimally from this region, a function represented mathematically as a convex cone. Near-optimal flux configurations within this region are considered equally plausible and not subject to further optimizing regulation. Consistent with relaxed regulation near optimality, we find that the size of the near-optimal region predicts flux variability under experimental perturbation. Conclusion Accounting for suboptimal solutions can improve the predictive power of metabolic FBA models. Because fluctuations of enzyme and metabolite levels are inevitable, tolerance for suboptimality may support a functionally robust metabolic network. PMID:24088221

  17. Cellular metabolic network analysis: discovering important reactions in Treponema pallidum.

    PubMed

    Chen, Xueying; Zhao, Min; Qu, Hong

    2015-01-01

    T. pallidum, the syphilis-causing pathogen, performs very differently in metabolism compared with other bacterial pathogens. The desire for safe and effective vaccine of syphilis requests identification of important steps in T. pallidum's metabolism. Here, we apply Flux Balance Analysis to represent the reactions quantitatively. Thus, it is possible to cluster all reactions in T. pallidum. By calculating minimal cut sets and analyzing topological structure for the metabolic network of T. pallidum, critical reactions are identified. As a comparison, we also apply the analytical approaches to the metabolic network of H. pylori to find coregulated drug targets and unique drug targets for different microorganisms. Based on the clustering results, all reactions are further classified into various roles. Therefore, the general picture of their metabolic network is obtained and two types of reactions, both of which are involved in nucleic acid metabolism, are found to be essential for T. pallidum. It is also discovered that both hubs of reactions and the isolated reactions in purine and pyrimidine metabolisms play important roles in T. pallidum. These reactions could be potential drug targets for treating syphilis.

  18. Estimating the size of the solution space of metabolic networks

    PubMed Central

    Braunstein, Alfredo; Mulet, Roberto; Pagnani, Andrea

    2008-01-01

    Background Cellular metabolism is one of the most investigated system of biological interactions. While the topological nature of individual reactions and pathways in the network is quite well understood there is still a lack of comprehension regarding the global functional behavior of the system. In the last few years flux-balance analysis (FBA) has been the most successful and widely used technique for studying metabolism at system level. This method strongly relies on the hypothesis that the organism maximizes an objective function. However only under very specific biological conditions (e.g. maximization of biomass for E. coli in reach nutrient medium) the cell seems to obey such optimization law. A more refined analysis not assuming extremization remains an elusive task for large metabolic systems due to algorithmic limitations. Results In this work we propose a novel algorithmic strategy that provides an efficient characterization of the whole set of stable fluxes compatible with the metabolic constraints. Using a technique derived from the fields of statistical physics and information theory we designed a message-passing algorithm to estimate the size of the affine space containing all possible steady-state flux distributions of metabolic networks. The algorithm, based on the well known Bethe approximation, can be used to approximately compute the volume of a non full-dimensional convex polytope in high dimensions. We first compare the accuracy of the predictions with an exact algorithm on small random metabolic networks. We also verify that the predictions of the algorithm match closely those of Monte Carlo based methods in the case of the Red Blood Cell metabolic network. Then we test the effect of gene knock-outs on the size of the solution space in the case of E. coli central metabolism. Finally we analyze the statistical properties of the average fluxes of the reactions in the E. coli metabolic network. Conclusion We propose a novel efficient

  19. Dynamic flux balancing elucidates NAD(P)H production as limiting response to furfural inhibition in Saccharomyces cerevisiae.

    PubMed

    Pornkamol, Unrean; Franzen, Carl J

    2015-08-01

    Achieving efficient and economical lignocellulose-based bioprocess requires a robust organism tolerant to furfural, a major inhibitory compound present in lignocellulosic hydrolysate. The aim of this study was to develop a model that could generate quantitative descriptions of cell metabolism for elucidating the cell's adaptive response to furfural. Such a modelling tool could provide strategies for the design of more robust cells. A dynamic flux balance (dFBA) model of Saccharomyces cerevisiae was created by coupling a kinetic fermentation model with a previously published genome-scale stoichiometric model. The dFBA model was used for studying intracellular and extracellular flux responses to furfural perturbations under steady state and dynamic conditions. The predicted effects of furfural on dynamic flux profiles agreed well with previously published experimental results. The model showed that the yeast cell adjusts its metabolism in response to furfural challenge by increasing fluxes through the pentose phosphate pathway, TCA cycle, and proline and serine biosynthesis in order to meet the high demand of NAD(P)H cofactors. The model described here can be used to aid in systematic optimization of the yeast, as well as of the fermentation process, for efficient lignocellulosic ethanol production. Copyright © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  20. Systematic Comparison of Label-Free, Metabolic Labeling, and Isobaric Chemical Labeling for Quantitative Proteomics on LTQ Orbitrap Velos

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Li, Zhou; Adams, Rachel M; Chourey, Karuna

    2012-01-01

    A variety of quantitative proteomics methods have been developed, including label-free, metabolic labeling, and isobaric chemical labeling using iTRAQ or TMT. Here, these methods were compared in terms of the depth of proteome coverage, quantification accuracy, precision, and reproducibility using a high-performance hybrid mass spectrometer, LTQ Orbitrap Velos. Our results show that (1) the spectral counting method provides the deepest proteome coverage for identification, but its quantification performance is worse than labeling-based approaches, especially the quantification reproducibility; (2) metabolic labeling and isobaric chemical labeling are capable of accurate, precise, and reproducible quantification and provide deep proteome coverage for quantification. Isobaricmore » chemical labeling surpasses metabolic labeling in terms of quantification precision and reproducibility; (3) iTRAQ and TMT perform similarly in all aspects compared in the current study using a CID-HCD dual scan configuration. Based on the unique advantages of each method, we provide guidance for selection of the appropriate method for a quantitative proteomics study.« less

  1. Constraint-based strain design using continuous modifications (CosMos) of flux bounds finds new strategies for metabolic engineering.

    PubMed

    Cotten, Cameron; Reed, Jennifer L

    2013-05-01

    In recent years, a growing number of metabolic engineering strain design techniques have employed constraint-based modeling to determine metabolic and regulatory network changes which are needed to improve chemical production. These methods use systems-level analysis of metabolism to help guide experimental efforts by identifying deletions, additions, downregulations, and upregulations of metabolic genes that will increase biological production of a desired metabolic product. In this work, we propose a new strain design method with continuous modifications (CosMos) that provides strategies for deletions, downregulations, and upregulations of fluxes that will lead to the production of the desired products. The method is conceptually simple and easy to implement, and can provide additional strategies over current approaches. We found that the method was able to find strain design strategies that required fewer modifications and had larger predicted yields than strategies from previous methods in example and genome-scale networks. Using CosMos, we identified modification strategies for producing a variety of metabolic products, compared strategies derived from Escherichia coli and Saccharomyces cerevisiae metabolic models, and examined how imperfect implementation may affect experimental outcomes. This study gives a powerful and flexible technique for strain engineering and examines some of the unexpected outcomes that may arise when strategies are implemented experimentally. Copyright © 2013 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim.

  2. Mapping the landscape of metabolic goals of a cell

    DOE PAGES

    Zhao, Qi; Stettner, Arion I.; Reznik, Ed; ...

    2016-05-23

    Here, genome-scale flux balance models of metabolism provide testable predictions of all metabolic rates in an organism, by assuming that the cell is optimizing a metabolic goal known as the objective function. We introduce an efficient inverse flux balance analysis (invFBA) approach, based on linear programming duality, to characterize the space of possible objective functions compatible with measured fluxes. After testing our algorithm on simulated E. coli data and time-dependent S. oneidensis fluxes inferred from gene expression, we apply our inverse approach to flux measurements in long-term evolved E. coli strains, revealing objective functions that provide insight into metabolic adaptationmore » trajectories.« less

  3. Metabolomic and 13C-Metabolic Flux Analysis of a Xylose-Consuming Saccharomyces cerevisiae Strain Expressing Xylose Isomerase

    PubMed Central

    Wasylenko, Thomas M.; Stephanopoulos, Gregory

    2016-01-01

    Over the past two decades significant progress has been made in the engineering of xylose-consuming Saccharomyces cerevisiae strains for production of lignocellulosic biofuels. However, the ethanol productivities achieved on xylose are still significantly lower than those observed on glucose for reasons that are not well understood. We have undertaken an analysis of central carbon metabolite pool sizes and metabolic fluxes on glucose and on xylose under aerobic and anaerobic conditions in a strain capable of rapid xylose assimilation via xylose isomerase in order to investigate factors that may limit the rate of xylose fermentation. We find that during xylose utilization the flux through the non-oxidative PPP is high but the flux through the oxidative PPP is low, highlighting an advantage of the strain employed in this study. Furthermore, xylose fails to elicit the full carbon catabolite repression response that is characteristic of glucose fermentation in S. cerevisiae. We present indirect evidence that the incomplete activation of the fermentation program on xylose results in a bottleneck in lower glycolysis, leading to inefficient re-oxidation of NADH produced in glycolysis. PMID:25311863

  4. Role of Central Metabolism in the Osmoadaptation of the Halophilic Bacterium Chromohalobacter salexigens*

    PubMed Central

    Pastor, José M.; Bernal, Vicente; Salvador, Manuel; Argandoña, Montserrat; Vargas, Carmen; Csonka, Laszlo; Sevilla, Ángel; Iborra, José L.; Nieto, Joaquín J.; Cánovas, Manuel

    2013-01-01

    Bacterial osmoadaptation involves the cytoplasmic accumulation of compatible solutes to counteract extracellular osmolarity. The halophilic and highly halotolerant bacterium Chromohalobacter salexigens is able to grow up to 3 m NaCl in a minimal medium due to the de novo synthesis of ectoines. This is an osmoregulated pathway that burdens central metabolic routes by quantitatively drawing off TCA cycle intermediaries. Consequently, metabolism in C. salexigens has adapted to support this biosynthetic route. Metabolism of C. salexigens is more efficient at high salinity than at low salinity, as reflected by lower glucose consumption, lower metabolite overflow, and higher biomass yield. At low salinity, by-products (mainly gluconate, pyruvate, and acetate) accumulate extracellularly. Using [1-13C]-, [2-13C]-, [6-13C]-, and [U-13C6]glucose as carbon sources, we were able to determine the main central metabolic pathways involved in ectoines biosynthesis from glucose. C. salexigens uses the Entner-Doudoroff pathway rather than the standard glycolytic pathway for glucose catabolism, and anaplerotic activity is high to replenish the TCA cycle with the intermediaries withdrawn for ectoines biosynthesis. Metabolic flux ratios at low and high salinity were similar, revealing a certain metabolic rigidity, probably due to its specialization to support high biosynthetic fluxes and partially explaining why metabolic yields are so highly affected by salinity. This work represents an important contribution to the elucidation of specific metabolic adaptations in compatible solute-accumulating halophilic bacteria. PMID:23615905

  5. Quantitative real-time optical imaging of the tissue metabolic rate of oxygen consumption

    NASA Astrophysics Data System (ADS)

    Ghijsen, Michael; Lentsch, Griffin R.; Gioux, Sylvain; Brenner, Matthew; Durkin, Anthony J.; Choi, Bernard; Tromberg, Bruce J.

    2018-03-01

    The tissue metabolic rate of oxygen consumption (tMRO2) is a clinically relevant marker for a number of pathologies including cancer and arterial occlusive disease. We present and validate a noncontact method for quantitatively mapping tMRO2 over a wide, scalable field of view at 16 frames / s. We achieve this by developing a dual-wavelength, near-infrared coherent spatial frequency-domain imaging (cSFDI) system to calculate tissue optical properties (i.e., absorption, μa, and reduced scattering, μs‧, parameters) as well as the speckle flow index (SFI) at every pixel. Images of tissue oxy- and deoxyhemoglobin concentration ( [ HbO2 ] and [HHb]) are calculated from optical properties and combined with SFI to calculate tMRO2. We validate the system using a series of yeast-hemoglobin tissue-simulating phantoms and conduct in vivo tests in humans using arterial occlusions that demonstrate sensitivity to tissue metabolic oxygen debt and its repayment. Finally, we image the impact of cyanide exposure and toxicity reversal in an in vivo rabbit model showing clear instances of mitochondrial uncoupling and significantly diminished tMRO2. We conclude that dual-wavelength cSFDI provides rapid, quantitative, wide-field mapping of tMRO2 that can reveal unique spatial and temporal dynamics relevant to tissue pathology and viability.

  6. Measuring and modeling C flux rates through the central metabolic pathways in microbial communities using position-specific 13C-labeled tracers

    NASA Astrophysics Data System (ADS)

    Dijkstra, P.; van Groenigen, K.; Hagerty, S.; Salpas, E.; Fairbanks, D. E.; Hungate, B. A.; KOCH, G. W.; Schwartz, E.

    2012-12-01

    The production of energy and metabolic precursors occurs in well-known processes such as glycolysis and Krebs cycle. We use position-specific 13C-labeled metabolic tracers, combined with models of microbial metabolic organization, to analyze the response of microbial community energy production, biosynthesis, and C use efficiency (CUE) in soils, decomposing litter, and aquatic communities. The method consists of adding position-specific 13C -labeled metabolic tracers to parallel soil incubations, in this case 1-13C and 2,3-13C pyruvate and 1-13C and U-13C glucose. The measurement of CO2 released from the labeled tracers is used to calculate the C flux rates through the various metabolic pathways. A simplified metabolic model consisting of 23 reactions is solved using results of the metabolic tracer experiments and assumptions of microbial precursor demand. This new method enables direct estimation of fundamental aspects of microbial energy production, CUE, and soil organic matter formation in relatively undisturbed microbial communities. We will present results showing the range of metabolic patterns observed in these communities and discuss results from testing metabolic models.

  7. Insights from quantitative metaproteomics and protein-stable isotope probing into microbial ecology.

    PubMed

    von Bergen, Martin; Jehmlich, Nico; Taubert, Martin; Vogt, Carsten; Bastida, Felipe; Herbst, Florian-Alexander; Schmidt, Frank; Richnow, Hans-Hermann; Seifert, Jana

    2013-10-01

    The recent development of metaproteomics has enabled the direct identification and quantification of expressed proteins from microbial communities in situ, without the need for microbial enrichment. This became possible by (1) significant increases in quality and quantity of metagenome data and by improvements of (2) accuracy and (3) sensitivity of modern mass spectrometers (MS). The identification of physiologically relevant enzymes can help to understand the role of specific species within a community or an ecological niche. Beside identification, relative and absolute quantitation is also crucial. We will review label-free and label-based methods of quantitation in MS-based proteome analysis and the contribution of quantitative proteome data to microbial ecology. Additionally, approaches of protein-based stable isotope probing (protein-SIP) for deciphering community structures are reviewed. Information on the species-specific metabolic activity can be obtained when substrates or nutrients are labeled with stable isotopes in a protein-SIP approach. The stable isotopes ((13)C, (15)N, (36)S) are incorporated into proteins and the rate of incorporation can be used for assessing the metabolic activity of the corresponding species. We will focus on the relevance of the metabolic and phylogenetic information retrieved with protein-SIP studies and for detecting and quantifying the carbon flux within microbial consortia. Furthermore, the combination of protein-SIP with established tools in microbial ecology such as other stable isotope probing techniques are discussed.

  8. Metabolic Flux Between Unsaturated and Saturated Fatty Acids is Controlled by the FabA:FabB Ratio in the Fully Reconstituted Fatty Acid Biosynthetic Pathway of E. coli#

    PubMed Central

    Xiao, Xirui; Yu, Xingye; Khosla, Chaitan

    2013-01-01

    The entire fatty acid biosynthetic pathway from Escherichia coli, starting from the acetyl-CoA carboxylase, has been reconstituted in vitro from fourteen purified protein components. Radiotracer analysis verified stoichiometric conversion of acetyl-CoA and NAD(P)H into the free fatty acid product, allowing implementation of a facile spectrophotometric assay for kinetic analysis of this multi-enzyme system. At steady state, a maximum turnover rate of 0.5 s−1 was achieved. Under optimal turnover conditions, the predominant products were C16 and C18 saturated as well as monounsaturated fatty acids. The reconstituted system allowed us to quantitatively interrogate the factors that influence metabolic flux toward unsaturated versus saturated fatty acids. In particular, the concentrations of the dehydratase FabA and the β-ketoacyl synthase FabB were found to be crucial for controlling this property. By altering these variables, the percentage of unsaturated fatty acid produced could be adjusted between 10 and 50% without significantly affecting the maximum turnover rate of the pathway. Our reconstituted system provides a powerful tool to understand and engineer rate-limiting and regulatory steps in this complex and practically significant metabolic pathway. PMID:24147979

  9. A Prochlorococcus proving ground for constraint-based metabolic modeling and multi-`omics data integration

    NASA Astrophysics Data System (ADS)

    Casey, J.; Ji, B.; Shaoie, S.; Mardinoglu, A.; Sarathi Sen, P.; Jahn, O.; Reda, K.; Leigh, J.; Follows, M. J.; Nielsen, J.; Karl, D. M.

    2016-02-01

    Representatives of the oligotrophic marine cyanobacterium Prochlorococcus marinus are the smallest free-living photosynthetic organisms, both in terms of physical size and genome size, yet are the most abundant photoautotrophic microbes in the oceans and profoundly influence global biogeochemical cycles. Physiological and regulatory control of nutrient and light stress has been observed in MED4 in culture and in its closely related `ecotype' eMED4 in the field, however its metabolism has not been investigated in detail. We present a genome-scale metabolic network reconstruction of the high-light adapted axenic strain MED4ax ("iJCMED4") for the quantitative analysis of a range of its metabolic phenotypes. The resulting structure is a proving ground for the incorporation of enzyme kinetics, biochemical and elemental compositional data, transcriptomic, proteomic, metabolomic, and fluxomic datasets which can be implemented within a constraint-based metabolic modeling environment. The iJCMED4 stoichiometric model consists of 523 metabolic genes encoding 787 reactions with 673 unique metabolites distributed in 5 sub-cellular compartments and is mass, charge, and thermodynamically balanced. Several variants of flux balance analysis were used to simulate growth and metabolic fluxes over the diel cycle, under various stress conditions (e.g., nitrogen, phosphorus, light), and within the framework of a global biogeochemical model (DARWIN). Model simulations accurately predicted growth rates in culture under a variety of defined medium compositions and there was close agreement of photosynthetic performance, biomass and energy yields and efficiencies, and transporter fluxes for iJCMED4 and culture experiments. In addition to a nearly optimal photosynthetic quotient and central carbon metabolism efficiency, MED4 has made dramatic alterations to redox and phosphorus metabolism across biosynthetic and intermediate pathways. We propose that reductions in phosphate reaction

  10. MCT1 and MCT4 Expression and Lactate Flux Activity Increase During White and Brown Adipogenesis and Impact Adipocyte Metabolism.

    PubMed

    Petersen, Charlotte; Nielsen, Mette D; Andersen, Elise S; Basse, Astrid L; Isidor, Marie S; Markussen, Lasse K; Viuff, Birgitte M; Lambert, Ian H; Hansen, Jacob B; Pedersen, Stine F

    2017-10-12

    Adipose tissue takes up glucose and releases lactate, thereby contributing significantly to systemic glucose and lactate homeostasis. This implies the necessity of upregulation of net acid and lactate flux capacity during adipocyte differentiation and function. However, the regulation of lactate- and acid/base transporters in adipocytes is poorly understood. Here, we tested the hypothesis that adipocyte thermogenesis, browning and differentiation are associated with an upregulation of plasma membrane lactate and acid/base transport capacity that in turn is important for adipocyte metabolism. The mRNA and protein levels of the lactate-H + transporter MCT1 and the Na + ,HCO 3 - cotransporter NBCe1 were upregulated in mouse interscapular brown and inguinal white adipose tissue upon cold induction of thermogenesis and browning. MCT1, MCT4, and NBCe1 were furthermore strongly upregulated at the mRNA and protein level upon differentiation of cultured pre-adipocytes. Adipocyte differentiation was accompanied by increased plasma membrane lactate flux capacity, which was reduced by MCT inhibition and by MCT1 knockdown. Finally, in differentiated brown adipocytes, glycolysis (assessed as ECAR), and after noradrenergic stimulation also oxidative metabolism (OCR), was decreased by MCT inhibition. We suggest that upregulation of MCT1- and MCT4-mediated lactate flux capacity and NBCe1-mediated HCO 3 - /pH homeostasis are important for the physiological function of mature adipocytes.

  11. Fast flux module detection using matroid theory.

    PubMed

    Reimers, Arne C; Bruggeman, Frank J; Olivier, Brett G; Stougie, Leen

    2015-05-01

    Flux balance analysis (FBA) is one of the most often applied methods on genome-scale metabolic networks. Although FBA uniquely determines the optimal yield, the pathway that achieves this is usually not unique. The analysis of the optimal-yield flux space has been an open challenge. Flux variability analysis is only capturing some properties of the flux space, while elementary mode analysis is intractable due to the enormous number of elementary modes. However, it has been found by Kelk et al. (2012) that the space of optimal-yield fluxes decomposes into flux modules. These decompositions allow a much easier but still comprehensive analysis of the optimal-yield flux space. Using the mathematical definition of module introduced by Müller and Bockmayr (2013b), we discovered useful connections to matroid theory, through which efficient algorithms enable us to compute the decomposition into modules in a few seconds for genome-scale networks. Using that every module can be represented by one reaction that represents its function, in this article, we also present a method that uses this decomposition to visualize the interplay of modules. We expect the new method to replace flux variability analysis in the pipelines for metabolic networks.

  12. Quantitative role of splanchnic region in leucine metabolism: L-(1-13C,15N)leucine and substrate balance studies

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Yu, Y.M.; Wagner, D.A.; Tredget, E.E.

    1990-07-01

    The role of the splanchnic region (Sp) in whole body leucine metabolism was assessed in six chronically catheterized fasting mongrel dogs and in eight dogs during constant enteral feeding of a complete amino acid solution (0.24 g.kg-1.h-1). We used primed continuous intravenous infusions of L-(1-13C,15N)leucine and L-(1-14C)leucine and measurements of arteriovenous isotope and leucine balance across the gut, liver, and Sp. In the fasted condition, 3.5% of arterial leucine supply was oxidized in the Sp, accounting for 13% of total body leucine oxidation, with 10% by liver. With amino acid feeding (1) leucine carbon and nitrogen fluxes and oxidation weremore » increased (P less than 0.01) at the whole body level; (2) the percent of whole body leucine oxidation occurring in the Sp and liver increased (P less than 0.01) to 41 and 27%, respectively; (3) fractional metabolic utilization of leucine delivered to the Sp was reduced (P less than 0.01) from 47 to 35%; (4) the deamination rate of leucine in the gut was increased (P less than 0.05), along with an increased reamination rate of alpha-ketoisocaproic acid in the Sp (P less than 0.05). These findings reveal that the Sp accounts for a small fraction of whole body leucine oxidation during the fasting condition, but it plays a quantitatively important role in total body leucine oxidation during amino acid feeding; the gut and liver play cooperative roles in controlling leucine supply to peripheral tissues.« less

  13. An integrated approach to characterize genetic interaction networks in yeast metabolism

    PubMed Central

    Szappanos, Balázs; Kovács, Károly; Szamecz, Béla; Honti, Frantisek; Costanzo, Michael; Baryshnikova, Anastasia; Gelius-Dietrich, Gabriel; Lercher, Martin J.; Jelasity, Márk; Myers, Chad L.; Andrews, Brenda J.; Boone, Charles; Oliver, Stephen G.; Pál, Csaba; Papp, Balázs

    2011-01-01

    Intense experimental and theoretical efforts have been made to globally map genetic interactions, yet we still do not understand how gene-gene interactions arise from the operation of biomolecular networks. To bridge the gap between empirical and computational studies, we: i) quantitatively measure genetic interactions between ~185,000 metabolic gene pairs in Saccharomyces cerevisiae, ii) superpose the data on a detailed systems biology model of metabolism, and iii) introduce a machine-learning method to reconcile empirical interaction data with model predictions. We systematically investigate the relative impacts of functional modularity and metabolic flux coupling on the distribution of negative and positive genetic interactions. We also provide a mechanistic explanation for the link between the degree of genetic interaction, pleiotropy, and gene dispensability. Last, we demonstrate the feasibility of automated metabolic model refinement by correcting misannotations in NAD biosynthesis and confirming them by in vivo experiments. PMID:21623372

  14. Quantitative Assessment of Heterogeneity in Tumor Metabolism Using FDG-PET

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Vriens, Dennis, E-mail: d.vriens@nucmed.umcn.nl; Disselhorst, Jonathan A.; Oyen, Wim J.G.

    2012-04-01

    Purpose: [{sup 18}F]-fluorodeoxyglucose-positron emission tomography (FDG-PET) images are usually quantitatively analyzed in 'whole-tumor' volumes of interest. Also parameters determined with dynamic PET acquisitions, such as the Patlak glucose metabolic rate (MR{sub glc}) and pharmacokinetic rate constants of two-tissue compartment modeling, are most often derived per lesion. We propose segmentation of tumors to determine tumor heterogeneity, potentially useful for dose-painting in radiotherapy and elucidating mechanisms of FDG uptake. Methods and Materials: In 41 patients with 104 lesions, dynamic FDG-PET was performed. On MR{sub glc} images, tumors were segmented in quartiles of background subtracted maximum MR{sub glc} (0%-25%, 25%-50%, 50%-75%, and 75%-100%).more » Pharmacokinetic analysis was performed using an irreversible two-tissue compartment model in the three segments with highest MR{sub glc} to determine the rate constants of FDG metabolism. Results: From the highest to the lowest quartile, significant decreases of uptake (K{sub 1}), washout (k{sub 2}), and phosphorylation (k{sub 3}) rate constants were seen with significant increases in tissue blood volume fraction (V{sub b}). Conclusions: Tumor regions with highest MR{sub glc} are characterized by high cellular uptake and phosphorylation rate constants with relatively low blood volume fractions. In regions with less metabolic activity, the blood volume fraction increases and cellular uptake, washout, and phosphorylation rate constants decrease. These results support the hypothesis that regional tumor glucose phosphorylation rate is not dependent on the transport of nutrients (i.e., FDG) to the tumor.« less

  15. Genome-scale fluxes predicted under the guidance of enzyme abundance using a novel hyper-cube shrink algorithm.

    PubMed

    Xie, Zhengwei; Zhang, Tianyu; Ouyang, Qi

    2018-02-01

    One of the long-expected goals of genome-scale metabolic modelling is to evaluate the influence of the perturbed enzymes on flux distribution. Both ordinary differential equation (ODE) models and constraint-based models, like Flux balance analysis (FBA), lack the capacity to perform metabolic control analysis (MCA) for large-scale networks. In this study, we developed a hyper-cube shrink algorithm (HCSA) to incorporate the enzymatic properties into the FBA model by introducing a pseudo reaction V constrained by enzymatic parameters. Our algorithm uses the enzymatic information quantitatively rather than qualitatively. We first demonstrate the concept by applying HCSA to a simple three-node network, whereby we obtained a good correlation between flux and enzyme abundance. We then validate its prediction by comparison with ODE and with a synthetic network producing voilacein and analogues in Saccharomyces cerevisiae. We show that HCSA can mimic the state-state results of ODE. Finally, we show its capability of predicting the flux distribution in genome-scale networks by applying it to sporulation in yeast. We show the ability of HCSA to operate without biomass flux and perform MCA to determine rate-limiting reactions. Algorithm was implemented by Matlab and C ++. The code is available at https://github.com/kekegg/HCSA. xiezhengwei@hsc.pku.edu.cn or qi@pku.edu.cn. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

  16. Phosphoketolase Pathway for Xylose Catabolism in Clostridium acetobutylicum Revealed by 13C Metabolic Flux Analysis

    PubMed Central

    Liu, Lixia; Zhang, Lei; Tang, Wei; Gu, Yang; Hua, Qiang; Yang, Sheng; Jiang, Weihong

    2012-01-01

    Solvent-producing clostridia are capable of utilizing pentose sugars, including xylose and arabinose; however, little is known about how pentose sugars are catabolized through the metabolic pathways in clostridia. In this study, we identified the xylose catabolic pathways and quantified their fluxes in Clostridium acetobutylicum based on [1-13C]xylose labeling experiments. The phosphoketolase pathway was found to be active, which contributed up to 40% of the xylose catabolic flux in C. acetobutylicum. The split ratio of the phosphoketolase pathway to the pentose phosphate pathway was markedly increased when the xylose concentration in the culture medium was increased from 10 to 20 g liter−1. To our knowledge, this is the first time that the in vivo activity of the phosphoketolase pathway in clostridia has been revealed. A phosphoketolase from C. acetobutylicum was purified and characterized, and its activity with xylulose-5-P was verified. The phosphoketolase was overexpressed in C. acetobutylicum, which resulted in slightly increased xylose consumption rates during the exponential growth phase and a high level of acetate accumulation. PMID:22865845

  17. Metabolism of Citrate and Other Carboxylic Acids in Erythrocytes As a Function of Oxygen Saturation and Refrigerated Storage

    PubMed Central

    Nemkov, Travis; Sun, Kaiqi; Reisz, Julie A.; Yoshida, Tatsuro; Dunham, Andrew; Wen, Edward Y.; Wen, Alexander Q.; Roach, Rob C.; Hansen, Kirk C.; Xia, Yang; D’Alessandro, Angelo

    2017-01-01

    State-of-the-art proteomics technologies have recently helped to elucidate the unanticipated complexity of red blood cell metabolism. One recent example is citrate metabolism, which is catalyzed by cytosolic isoforms of Krebs cycle enzymes that are present and active in mature erythrocytes and was determined using quantitative metabolic flux analysis. In previous studies, we reported significant increases in glycolytic fluxes in red blood cells exposed to hypoxia in vitro or in vivo, an observation relevant to transfusion medicine owing to the potential benefits associated with hypoxic storage of packed red blood cells. Here, using a combination of steady state and quantitative tracing metabolomics experiments with 13C1,2,3-glucose, 13C6-citrate, 13C515N2-glutamine, and 13C1-aspartate via ultra-high performance liquid chromatography coupled on line with mass spectrometry, we observed that hypoxia in vivo and in vitro promotes consumption of citrate and other carboxylates. These metabolic reactions are theoretically explained by the activity of cytosolic malate dehydrogenase 1 and isocitrate dehydrogenase 1 (abundantly represented in the red blood cell proteome), though moonlighting functions of additional enzymes cannot be ruled out. These observations enhance understanding of red blood cell metabolic responses to hypoxia, which could be relevant to understand systemic physiological and pathological responses to high altitude, ischemia, hemorrhage, sepsis, pulmonary hypertension, or hemoglobinopathies. Results from this study will also inform the design and testing of novel additive solutions that optimize red blood cell storage under oxygen-controlled conditions. PMID:29090212

  18. Metabolism of Citrate and Other Carboxylic Acids in Erythrocytes As a Function of Oxygen Saturation and Refrigerated Storage.

    PubMed

    Nemkov, Travis; Sun, Kaiqi; Reisz, Julie A; Yoshida, Tatsuro; Dunham, Andrew; Wen, Edward Y; Wen, Alexander Q; Roach, Rob C; Hansen, Kirk C; Xia, Yang; D'Alessandro, Angelo

    2017-01-01

    State-of-the-art proteomics technologies have recently helped to elucidate the unanticipated complexity of red blood cell metabolism. One recent example is citrate metabolism, which is catalyzed by cytosolic isoforms of Krebs cycle enzymes that are present and active in mature erythrocytes and was determined using quantitative metabolic flux analysis. In previous studies, we reported significant increases in glycolytic fluxes in red blood cells exposed to hypoxia in vitro or in vivo , an observation relevant to transfusion medicine owing to the potential benefits associated with hypoxic storage of packed red blood cells. Here, using a combination of steady state and quantitative tracing metabolomics experiments with 13 C 1,2,3 -glucose, 13 C 6 -citrate, 13 C 5 15 N 2 -glutamine, and 13 C 1 -aspartate via ultra-high performance liquid chromatography coupled on line with mass spectrometry, we observed that hypoxia in vivo and in vitro promotes consumption of citrate and other carboxylates. These metabolic reactions are theoretically explained by the activity of cytosolic malate dehydrogenase 1 and isocitrate dehydrogenase 1 (abundantly represented in the red blood cell proteome), though moonlighting functions of additional enzymes cannot be ruled out. These observations enhance understanding of red blood cell metabolic responses to hypoxia, which could be relevant to understand systemic physiological and pathological responses to high altitude, ischemia, hemorrhage, sepsis, pulmonary hypertension, or hemoglobinopathies. Results from this study will also inform the design and testing of novel additive solutions that optimize red blood cell storage under oxygen-controlled conditions.

  19. Metabolic engineering of Synechocystis sp. PCC 6803 for enhanced ethanol production based on flux balance analysis.

    PubMed

    Yoshikawa, Katsunori; Toya, Yoshihiro; Shimizu, Hiroshi

    2017-05-01

    Synechocystis sp. PCC 6803 is an attractive host for bio-ethanol production due to its ability to directly convert atmospheric carbon dioxide into ethanol using photosystems. To enhance ethanol production in Synechocystis sp. PCC 6803, metabolic engineering was performed based on in silico simulations, using the genome-scale metabolic model. Comprehensive reaction knockout simulations by flux balance analysis predicted that the knockout of NAD(P)H dehydrogenase enhanced ethanol production under photoautotrophic conditions, where ammonium is the nitrogen source. This deletion inhibits the re-oxidation of NAD(P)H, which is generated by ferredoxin-NADP + reductase and imposes re-oxidation in the ethanol synthesis pathway. The effect of deleting the ndhF1 gene, which encodes NADH dehydrogenase subunit 5, on ethanol production was experimentally evaluated using ethanol-producing strains of Synechocystis sp. PCC 6803. The ethanol titer of the ethanol-producing ∆ndhF1 strain increased by 145%, compared with that of the control strain.

  20. Imaging mitochondrial flux in single cells with a FRET sensor for pyruvate.

    PubMed

    San Martín, Alejandro; Ceballo, Sebastián; Baeza-Lehnert, Felipe; Lerchundi, Rodrigo; Valdebenito, Rocío; Contreras-Baeza, Yasna; Alegría, Karin; Barros, L Felipe

    2014-01-01

    Mitochondrial flux is currently accessible at low resolution. Here we introduce a genetically-encoded FRET sensor for pyruvate, and methods for quantitative measurement of pyruvate transport, pyruvate production and mitochondrial pyruvate consumption in intact individual cells at high temporal resolution. In HEK293 cells, neurons and astrocytes, mitochondrial pyruvate uptake was saturated at physiological levels, showing that the metabolic rate is determined by intrinsic properties of the organelle and not by substrate availability. The potential of the sensor was further demonstrated in neurons, where mitochondrial flux was found to rise by 300% within seconds of a calcium transient triggered by a short theta burst, while glucose levels remained unaltered. In contrast, astrocytic mitochondria were insensitive to a similar calcium transient elicited by extracellular ATP. We expect the improved resolution provided by the pyruvate sensor will be of practical interest for basic and applied researchers interested in mitochondrial function.

  1. Imaging Mitochondrial Flux in Single Cells with a FRET Sensor for Pyruvate

    PubMed Central

    Baeza-Lehnert, Felipe; Lerchundi, Rodrigo; Valdebenito, Rocío; Contreras-Baeza, Yasna; Alegría, Karin; Barros, L. Felipe

    2014-01-01

    Mitochondrial flux is currently accessible at low resolution. Here we introduce a genetically-encoded FRET sensor for pyruvate, and methods for quantitative measurement of pyruvate transport, pyruvate production and mitochondrial pyruvate consumption in intact individual cells at high temporal resolution. In HEK293 cells, neurons and astrocytes, mitochondrial pyruvate uptake was saturated at physiological levels, showing that the metabolic rate is determined by intrinsic properties of the organelle and not by substrate availability. The potential of the sensor was further demonstrated in neurons, where mitochondrial flux was found to rise by 300% within seconds of a calcium transient triggered by a short theta burst, while glucose levels remained unaltered. In contrast, astrocytic mitochondria were insensitive to a similar calcium transient elicited by extracellular ATP. We expect the improved resolution provided by the pyruvate sensor will be of practical interest for basic and applied researchers interested in mitochondrial function. PMID:24465702

  2. Metabolic networks evolve towards states of maximum entropy production.

    PubMed

    Unrean, Pornkamol; Srienc, Friedrich

    2011-11-01

    A metabolic network can be described by a set of elementary modes or pathways representing discrete metabolic states that support cell function. We have recently shown that in the most likely metabolic state the usage probability of individual elementary modes is distributed according to the Boltzmann distribution law while complying with the principle of maximum entropy production. To demonstrate that a metabolic network evolves towards such state we have carried out adaptive evolution experiments with Thermoanaerobacterium saccharolyticum operating with a reduced metabolic functionality based on a reduced set of elementary modes. In such reduced metabolic network metabolic fluxes can be conveniently computed from the measured metabolite secretion pattern. Over a time span of 300 generations the specific growth rate of the strain continuously increased together with a continuous increase in the rate of entropy production. We show that the rate of entropy production asymptotically approaches the maximum entropy production rate predicted from the state when the usage probability of individual elementary modes is distributed according to the Boltzmann distribution. Therefore, the outcome of evolution of a complex biological system can be predicted in highly quantitative terms using basic statistical mechanical principles. Copyright © 2011 Elsevier Inc. All rights reserved.

  3. Comprehensive quantitative analysis of central carbon and amino-acid metabolism in Saccharomyces cerevisiae under multiple conditions by targeted proteomics

    PubMed Central

    Costenoble, Roeland; Picotti, Paola; Reiter, Lukas; Stallmach, Robert; Heinemann, Matthias; Sauer, Uwe; Aebersold, Ruedi

    2011-01-01

    Decades of biochemical research have identified most of the enzymes that catalyze metabolic reactions in the yeast Saccharomyces cerevisiae. The adaptation of metabolism to changing nutritional conditions, in contrast, is much less well understood. As an important stepping stone toward such understanding, we exploit the power of proteomics assays based on selected reaction monitoring (SRM) mass spectrometry to quantify abundance changes of the 228 proteins that constitute the central carbon and amino-acid metabolic network in the yeast Saccharomyces cerevisiae, at five different metabolic steady states. Overall, 90% of the targeted proteins, including families of isoenzymes, were consistently detected and quantified in each sample, generating a proteomic data set that represents a nutritionally perturbed biological system at high reproducibility. The data set is near comprehensive because we detect 95–99% of all proteins that are required under a given condition. Interpreted through flux balance modeling, the data indicate that S. cerevisiae retains proteins not necessarily used in a particular environment. Further, the data suggest differential functionality for several metabolic isoenzymes. PMID:21283140

  4. Testicular Metabolic Reprogramming in Neonatal Streptozotocin-Induced Type 2 Diabetic Rats Impairs Glycolytic Flux and Promotes Glycogen Synthesis

    PubMed Central

    Rato, L.; Alves, M. G.; Dias, T. R.; Cavaco, J. E.; Oliveira, Pedro F.

    2015-01-01

    Defects in testicular metabolism are directly implicated with male infertility, but most of the mechanisms associated with type 2 diabetes- (T2DM) induced male infertility remain unknown. We aimed to evaluate the effects of T2DM on testicular glucose metabolism by using a neonatal-streptozotocin- (n-STZ) T2DM animal model. Plasma and testicular hormonal levels were evaluated using specific kits. mRNA and protein expression levels were assessed by real-time PCR and Western Blot, respectively. Testicular metabolic profile was assessed by 1H-NMR spectroscopy. T2DM rats showed increased glycemic levels, impaired glucose tolerance and hyperinsulinemia. Both testicular and serum testosterone levels were decreased, whereas those of 17β-estradiol were not altered. Testicular glycolytic flux was not favored in testicles of T2DM rats, since, despite the increased expression of both glucose transporters 1 and 3 and the enzyme phosphofructokinase 1, lactate dehydrogenase activity was severely decreased contributing to lower testicular lactate content. However, T2DM enhanced testicular glycogen accumulation, by modulating the availability of the precursors for its synthesis. T2DM also affected the reproductive sperm parameters. Taken together these results indicate that T2DM is able to reprogram testicular metabolism by enhancing alternative metabolic pathways, particularly glycogen synthesis, and such alterations are associated with impaired sperm parameters. PMID:26064993

  5. Testicular Metabolic Reprogramming in Neonatal Streptozotocin-Induced Type 2 Diabetic Rats Impairs Glycolytic Flux and Promotes Glycogen Synthesis.

    PubMed

    Rato, L; Alves, M G; Dias, T R; Cavaco, J E; Oliveira, Pedro F

    2015-01-01

    Defects in testicular metabolism are directly implicated with male infertility, but most of the mechanisms associated with type 2 diabetes- (T2DM) induced male infertility remain unknown. We aimed to evaluate the effects of T2DM on testicular glucose metabolism by using a neonatal-streptozotocin- (n-STZ) T2DM animal model. Plasma and testicular hormonal levels were evaluated using specific kits. mRNA and protein expression levels were assessed by real-time PCR and Western Blot, respectively. Testicular metabolic profile was assessed by (1)H-NMR spectroscopy. T2DM rats showed increased glycemic levels, impaired glucose tolerance and hyperinsulinemia. Both testicular and serum testosterone levels were decreased, whereas those of 17β-estradiol were not altered. Testicular glycolytic flux was not favored in testicles of T2DM rats, since, despite the increased expression of both glucose transporters 1 and 3 and the enzyme phosphofructokinase 1, lactate dehydrogenase activity was severely decreased contributing to lower testicular lactate content. However, T2DM enhanced testicular glycogen accumulation, by modulating the availability of the precursors for its synthesis. T2DM also affected the reproductive sperm parameters. Taken together these results indicate that T2DM is able to reprogram testicular metabolism by enhancing alternative metabolic pathways, particularly glycogen synthesis, and such alterations are associated with impaired sperm parameters.

  6. Synthetic metabolic bypass for a metabolic toggle switch enhances acetyl-CoA supply for isopropanol production by Escherichia coli.

    PubMed

    Soma, Yuki; Yamaji, Taiki; Matsuda, Fumio; Hanai, Taizo

    2017-05-01

    Almost all synthetic pathways for biofuel production are designed to require endogenous metabolites in glycolysis, such as phosphoenolpyruvate, pyruvate, and acetyl-CoA. However, such metabolites are also required for bacterial cell growth. To reduce the metabolic imbalance between cell growth and target chemical production, we previously constructed a metabolic toggle switch (MTS) as a conditional flux redirection tool controlling metabolic flux of TCA cycle toward isopropanol production. This approach succeeded to improve the isopropanol production titer and yield while ensuring sufficient cell growth. However, excess accumulation of pyruvate, the precursor for acetyl-CoA synthesis, was also observed. In this study, for efficient conversation of pyruvate to acetyl-CoA (pyruvate oxidation), we designed a synthetic metabolic bypass composed of poxB and acs with the MTS for acetyl-CoA supply from the excess pyruvate. When this designed bypass was expressed at the appropriate expression level associated with the conditional metabolic flux redirection, pyruvate accumulation was prevented, and the isopropanol production titer and yield were improved. Final isopropanol production titer of strain harboring MTS with the synthetic metabolic bypass improved 4.4-fold compared with strain without metabolic flux regulation, and it was 1.3-fold higher than that of strain harboring the conventional MTS alone. Additionally, glucose consumption was also improved 1.7-fold compared with strain without metabolic flux regulation. On the other hand, introduction of the synthetic metabolic bypass alone showed no improvement in isopropanol production and glucose consumption. These results showed that the improvement in bio-production process caused by synergy between the MTS and the synthetic metabolic bypass. Copyright © 2016 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

  7. Metabolic network modeling with model organisms.

    PubMed

    Yilmaz, L Safak; Walhout, Albertha Jm

    2017-02-01

    Flux balance analysis (FBA) with genome-scale metabolic network models (GSMNM) allows systems level predictions of metabolism in a variety of organisms. Different types of predictions with different accuracy levels can be made depending on the applied experimental constraints ranging from measurement of exchange fluxes to the integration of gene expression data. Metabolic network modeling with model organisms has pioneered method development in this field. In addition, model organism GSMNMs are useful for basic understanding of metabolism, and in the case of animal models, for the study of metabolic human diseases. Here, we discuss GSMNMs of most highly used model organisms with the emphasis on recent reconstructions. Published by Elsevier Ltd.

  8. Metabolic network modeling with model organisms

    PubMed Central

    Yilmaz, L. Safak; Walhout, Albertha J.M.

    2017-01-01

    Flux balance analysis (FBA) with genome-scale metabolic network models (GSMNM) allows systems level predictions of metabolism in a variety of organisms. Different types of predictions with different accuracy levels can be made depending on the applied experimental constraints ranging from measurement of exchange fluxes to the integration of gene expression data. Metabolic network modeling with model organisms has pioneered method development in this field. In addition, model organism GSMNMs are useful for basic understanding of metabolism, and in the case of animal models, for the study of metabolic human diseases. Here, we discuss GSMNMs of most highly used model organisms with the emphasis on recent reconstructions. PMID:28088694

  9. Quantitative and qualitative differences in the metabolism of pesticides in biobed substrates and soil.

    PubMed

    Karanasios, Evangelos C; Tsiropoulos, Nikolaos G; Karpouzas, Dimitrios G

    2013-09-01

    Biobed substrates commonly exhibit high degradation capacity. However, degradation does not always lead to detoxification and information on the metabolic pathways of pesticides in biobeds is scarce. We studied the degradation and metabolism of three pesticides in selected biomixtures and soil. Biomixtures stimulated degradation of terbuthylazine and metribuzin, whereas chlorpyrifos degraded faster in soil. The latter was attributed to the lipophilicity of chlorpyrifos which increased adsorption and limited biodegradation in organic-rich biomixtures. Although the same metabolites were detected in all substrates, qualitative and quantitative differences in the metabolic routes of pesticides in the various substrates were observed. Chlorpyrifos was hydrolyzed to 3,5,6-tricholorpyridinol (TCP) which was further degraded only in compost-biomixture CBX1. Metabolism of terbuthylazine in compost biomixtures (BX) and soil resulted in the formation of desethyl-terbuthylazine (DES) which was fully degraded only in the compost-biomixture CBX2, whereas peat-based biomixture (OBX) promoted the hydroxylation of terbuthylazine. Desamino- (DA) (dominant) and diketo- (DK) metribuzin appear as intermediate metabolites in all substrates and were further transformed to desamino-diketo-metribuzin (DADK) which was fully degraded only in compost-biomixture GSBX. Overall, lower amounts of metabolites were accumulated in biomixtures compared to soil stressing the higher depuration efficiency of biobeds. Copyright © 2013 Elsevier Ltd. All rights reserved.

  10. Design principles of autocatalytic cycles constrain enzyme kinetics and force low substrate saturation at flux branch points

    PubMed Central

    Barenholz, Uri; Davidi, Dan; Reznik, Ed; Bar-On, Yinon; Antonovsky, Niv; Noor, Elad; Milo, Ron

    2017-01-01

    A set of chemical reactions that require a metabolite to synthesize more of that metabolite is an autocatalytic cycle. Here, we show that most of the reactions in the core of central carbon metabolism are part of compact autocatalytic cycles. Such metabolic designs must meet specific conditions to support stable fluxes, hence avoiding depletion of intermediate metabolites. As such, they are subjected to constraints that may seem counter-intuitive: the enzymes of branch reactions out of the cycle must be overexpressed and the affinity of these enzymes to their substrates must be relatively weak. We use recent quantitative proteomics and fluxomics measurements to show that the above conditions hold for functioning cycles in central carbon metabolism of E. coli. This work demonstrates that the topology of a metabolic network can shape kinetic parameters of enzymes and lead to seemingly wasteful enzyme usage. DOI: http://dx.doi.org/10.7554/eLife.20667.001 PMID:28169831

  11. Producing Acetic Acid of Acetobacter pasteurianus by Fermentation Characteristics and Metabolic Flux Analysis.

    PubMed

    Wu, Xuefeng; Yao, Hongli; Liu, Qing; Zheng, Zhi; Cao, Lili; Mu, Dongdong; Wang, Hualin; Jiang, Shaotong; Li, Xingjiang

    2018-03-19

    The acetic acid bacterium Acetobacter pasteurianus plays an important role in acetic acid fermentation, which involves oxidation of ethanol to acetic acid through the ethanol respiratory chain under specific conditions. In order to obtain more suitable bacteria for the acetic acid industry, A. pasteurianus JST-S screened in this laboratory was compared with A. pasteurianus CICC 20001, a current industrial strain in China, to determine optimal fermentation parameters under different environmental stresses. The maximum total acid content of A. pasteurianus JST-S was 57.14 ± 1.09 g/L, whereas that of A. pasteurianus CICC 20001 reached 48.24 ± 1.15 g/L in a 15-L stir stank. Metabolic flux analysis was also performed to compare the reaction byproducts. Our findings revealed the potential value of the strain in improvement of industrial vinegar fermentation.

  12. iSCHRUNK--In Silico Approach to Characterization and Reduction of Uncertainty in the Kinetic Models of Genome-scale Metabolic Networks.

    PubMed

    Andreozzi, Stefano; Miskovic, Ljubisa; Hatzimanikatis, Vassily

    2016-01-01

    Accurate determination of physiological states of cellular metabolism requires detailed information about metabolic fluxes, metabolite concentrations and distribution of enzyme states. Integration of fluxomics and metabolomics data, and thermodynamics-based metabolic flux analysis contribute to improved understanding of steady-state properties of metabolism. However, knowledge about kinetics and enzyme activities though essential for quantitative understanding of metabolic dynamics remains scarce and involves uncertainty. Here, we present a computational methodology that allow us to determine and quantify the kinetic parameters that correspond to a certain physiology as it is described by a given metabolic flux profile and a given metabolite concentration vector. Though we initially determine kinetic parameters that involve a high degree of uncertainty, through the use of kinetic modeling and machine learning principles we are able to obtain more accurate ranges of kinetic parameters, and hence we are able to reduce the uncertainty in the model analysis. We computed the distribution of kinetic parameters for glucose-fed E. coli producing 1,4-butanediol and we discovered that the observed physiological state corresponds to a narrow range of kinetic parameters of only a few enzymes, whereas the kinetic parameters of other enzymes can vary widely. Furthermore, this analysis suggests which are the enzymes that should be manipulated in order to engineer the reference state of the cell in a desired way. The proposed approach also sets up the foundations of a novel type of approaches for efficient, non-asymptotic, uniform sampling of solution spaces. Copyright © 2015 International Metabolic Engineering Society. Published by Elsevier Inc. All rights reserved.

  13. Use of chemostat cultures mimicking different phases of wine fermentations as a tool for quantitative physiological analysis

    PubMed Central

    2014-01-01

    Background Saccharomyces cerevisiae is the most relevant yeast species conducting the alcoholic fermentation that takes place during winemaking. Although the physiology of this model organism has been extensively studied, systematic quantitative physiology studies of this yeast under winemaking conditions are still scarce, thus limiting the understanding of fermentative metabolism of wine yeast strains and the systematic description, modelling and prediction of fermentation processes. In this study, we implemented and validated the use of chemostat cultures as a tool to simulate different stages of a standard wine fermentation, thereby allowing to implement metabolic flux analyses describing the sequence of metabolic states of S. cerevisae along the wine fermentation. Results Chemostat cultures mimicking the different stages of standard wine fermentations of S. cerevisiae EC1118 were performed using a synthetic must and strict anaerobic conditions. The simulated stages corresponded to the onset of the exponential growth phase, late exponential growth phase and cells just entering stationary phase, at dilution rates of 0.27, 0.04, 0.007 h−1, respectively. Notably, measured substrate uptake and product formation rates at each steady state condition were generally within the range of corresponding conversion rates estimated during the different batch fermentation stages. Moreover, chemostat data were further used for metabolic flux analysis, where biomass composition data for each condition was considered in the stoichiometric model. Metabolic flux distributions were coherent with previous analyses based on batch cultivations data and the pseudo-steady state assumption. Conclusions Steady state conditions obtained in chemostat cultures reflect the environmental conditions and physiological states of S. cerevisiae corresponding to the different growth stages of a typical batch wine fermentation, thereby showing the potential of this experimental approach to

  14. Quantitative Study on Corrosion of Steel Strands Based on Self-Magnetic Flux Leakage.

    PubMed

    Xia, Runchuan; Zhou, Jianting; Zhang, Hong; Liao, Leng; Zhao, Ruiqiang; Zhang, Zeyu

    2018-05-02

    This paper proposed a new computing method to quantitatively and non-destructively determine the corrosion of steel strands by analyzing the self-magnetic flux leakage (SMFL) signals from them. The magnetic dipole model and three growth models (Logistic model, Exponential model, and Linear model) were proposed to theoretically analyze the characteristic value of SMFL. Then, the experimental study on the corrosion detection by the magnetic sensor was carried out. The setup of the magnetic scanning device and signal collection method were also introduced. The results show that the Logistic Growth model is verified as the optimal model for calculating the magnetic field with good fitting effects. Combined with the experimental data analysis, the amplitudes of the calculated values ( B xL ( x,z ) curves) agree with the measured values in general. This method provides significant application prospects for the evaluation of the corrosion and the residual bearing capacity of steel strand.

  15. Beaver-mediated lateral hydrologic connectivity, fluvial carbon and nutrient flux, and aquatic ecosystem metabolism

    NASA Astrophysics Data System (ADS)

    Wegener, Pam; Covino, Tim; Wohl, Ellen

    2017-06-01

    River networks that drain mountain landscapes alternate between narrow and wide valley segments. Within the wide segments, beaver activity can facilitate the development and maintenance of complex, multithread planform. Because the narrow segments have limited ability to retain water, carbon, and nutrients, the wide, multithread segments are likely important locations of retention. We evaluated hydrologic dynamics, nutrient flux, and aquatic ecosystem metabolism along two adjacent segments of a river network in the Rocky Mountains, Colorado: (1) a wide, multithread segment with beaver activity; and, (2) an adjacent (directly upstream) narrow, single-thread segment without beaver activity. We used a mass balance approach to determine the water, carbon, and nutrient source-sink behavior of each river segment across a range of flows. While the single-thread segment was consistently a source of water, carbon, and nitrogen, the beaver impacted multithread segment exhibited variable source-sink dynamics as a function of flow. Specifically, the multithread segment was a sink for water, carbon, and nutrients during high flows, and subsequently became a source as flows decreased. Shifts in river-floodplain hydrologic connectivity across flows related to higher and more variable aquatic ecosystem metabolism rates along the multithread relative to the single-thread segment. Our data suggest that beaver activity in wide valleys can create a physically complex hydrologic environment that can enhance hydrologic and biogeochemical buffering, and promote high rates of aquatic ecosystem metabolism. Given the widespread removal of beaver, determining the cumulative effects of these changes is a critical next step in restoring function in altered river networks.

  16. Computational Flux Balance Analysis Predicts that Stimulation of Energy Metabolism in Astrocytes and their Metabolic Interactions with Neurons Depend on Uptake of K+ Rather than Glutamate.

    PubMed

    DiNuzzo, Mauro; Giove, Federico; Maraviglia, Bruno; Mangia, Silvia

    2017-01-01

    Brain activity involves essential functional and metabolic interactions between neurons and astrocytes. The importance of astrocytic functions to neuronal signaling is supported by many experiments reporting high rates of energy consumption and oxidative metabolism in these glial cells. In the brain, almost all energy is consumed by the Na + /K + ATPase, which hydrolyzes 1 ATP to move 3 Na + outside and 2 K + inside the cells. Astrocytes are commonly thought to be primarily involved in transmitter glutamate cycling, a mechanism that however only accounts for few % of brain energy utilization. In order to examine the participation of astrocytic energy metabolism in brain ion homeostasis, here we attempted to devise a simple stoichiometric relation linking glutamatergic neurotransmission to Na + and K + ionic currents. To this end, we took into account ion pumps and voltage/ligand-gated channels using the stoichiometry derived from available energy budget for neocortical signaling and incorporated this stoichiometric relation into a computational metabolic model of neuron-astrocyte interactions. We aimed at reproducing the experimental observations about rates of metabolic pathways obtained by 13 C-NMR spectroscopy in rodent brain. When simulated data matched experiments as well as biophysical calculations, the stoichiometry for voltage/ligand-gated Na + and K + fluxes generated by neuronal activity was close to a 1:1 relationship, and specifically 63/58 Na + /K + ions per glutamate released. We found that astrocytes are stimulated by the extracellular K + exiting neurons in excess of the 3/2 Na + /K + ratio underlying Na + /K + ATPase-catalyzed reaction. Analysis of correlations between neuronal and astrocytic processes indicated that astrocytic K + uptake, but not astrocytic Na + -coupled glutamate uptake, is instrumental for the establishment of neuron-astrocytic metabolic partnership. Our results emphasize the importance of K + in stimulating the activation of

  17. Determining and understanding the control of flux. An illustration in submitochondrial particles of how to validate schemes of metabolic control.

    PubMed

    Moreno-Sánchez, R; Bravo, C; Westerhoff, H V

    1999-09-01

    Two complementary methods were used to determine how the rate of respiration and that of ATP hydrolysis were controlled in rat liver submitochondrial particles. In the first, 'direct control analysis' method, respiration was titrated with malonate, antimycin or cyanide at 20, 30 and 37 degrees C, to determine the flux control exerted by succinate dehydrogenase, cytochrome bc1 complex and cytochrome c oxidase, respectively. Together, the three respiratory complexes only controlled the flux by about 50%, leaving the other 50% of flux control to the H+ leak. In the second, 'elasticity based' method, the elasticity coefficients of the respiratory chain or the H+-ATPase and the H+ leak towards the H+ gradient were determined. Then, the flux control coefficients were calculated using the connectivity and summation laws of metabolic control theory. The correspondence between the flux control coefficients determined in the two ways validated the two methods. This allowed us to use the second method to analyse what was the kinetic origin of the observed distribution of control. Control of ATP hydrolysis by the ATPase decreased with increasing ATPase activity; hence, the control exerted by the H+ leak increased with increasing ATPase activity, due to a diminishing elasticity towards the H+ gradient. Reverse electron transport was mainly controlled by the ATPase; the sum of flux control coefficients of succinate dehydrogenase, NADH-CoQ oxidoreductase, and H+-ATPase yielded a value greater than one, indicating that the H+ leak exerted a significant negative control on this pathway.

  18. An MRM-based workflow for absolute quantitation of lysine-acetylated metabolic enzymes in mouse liver.

    PubMed

    Xu, Leilei; Wang, Fang; Xu, Ying; Wang, Yi; Zhang, Cuiping; Qin, Xue; Yu, Hongxiu; Yang, Pengyuan

    2015-12-07

    As a key post-translational modification mechanism, protein acetylation plays critical roles in regulating and/or coordinating cell metabolism. Acetylation is a prevalent modification process in enzymes. Protein acetylation modification occurs in sub-stoichiometric amounts; therefore extracting biologically meaningful information from these acetylation sites requires an adaptable, sensitive, specific, and robust method for their quantification. In this work, we combine immunoassays and multiple reaction monitoring-mass spectrometry (MRM-MS) technology to develop an absolute quantification for acetylation modification. With this hybrid method, we quantified the acetylation level of metabolic enzymes, which could demonstrate the regulatory mechanisms of the studied enzymes. The development of this quantitative workflow is a pivotal step for advancing our knowledge and understanding of the regulatory effects of protein acetylation in physiology and pathophysiology.

  19. Quantitative imaging for discovery and assembly of the metabo-regulome

    PubMed Central

    Okumoto, Sakiko; Takanaga, Hitomi; Frommer, Wolf B.

    2009-01-01

    Summary Little is known about regulatory networks that control metabolic flux in plant cells. Detailed understanding of regulation is crucial for synthetic biology. The difficulty of measuring metabolites with cellular and subcellular precision is a major roadblock. New tools have been developed for monitoring extracellular, cytosolic, organellar and vacuolar ion and metabolite concentrations with a time resolution of milliseconds to hours. Genetically encoded sensors allow quantitative measurement of steady-state concentrations of ions, signaling molecules and metabolites and their respective changes over time. Fluorescence resonance energy transfer (FRET) sensors exploit conformational changes in polypeptides as a proxy for analyte concentrations. Subtle effects of analyte binding on the conformation of the recognition element are translated into a FRET change between two fused green fluorescent protein (GFP) variants, enabling simple monitoring of analyte concentrations using fluorimetry or fluorescence microscopy. Fluorimetry provides information averaged over cell populations, while microscopy detects differences between cells or populations of cells. The genetically encoded sensors can be targeted to subcellular compartments or the cell surface. Confocal microscopy ultimately permits observation of gradients or local differences within a compartment. The FRET assays can be adapted to high-throughput analysis to screen mutant populations in order to systematically identify signaling networks that control individual steps in metabolic flux. PMID:19138219

  20. Regulation of pyruvate metabolism and human disease.

    PubMed

    Gray, Lawrence R; Tompkins, Sean C; Taylor, Eric B

    2014-07-01

    Pyruvate is a keystone molecule critical for numerous aspects of eukaryotic and human metabolism. Pyruvate is the end-product of glycolysis, is derived from additional sources in the cellular cytoplasm, and is ultimately destined for transport into mitochondria as a master fuel input undergirding citric acid cycle carbon flux. In mitochondria, pyruvate drives ATP production by oxidative phosphorylation and multiple biosynthetic pathways intersecting the citric acid cycle. Mitochondrial pyruvate metabolism is regulated by many enzymes, including the recently discovered mitochondria pyruvate carrier, pyruvate dehydrogenase, and pyruvate carboxylase, to modulate overall pyruvate carbon flux. Mutations in any of the genes encoding for proteins regulating pyruvate metabolism may lead to disease. Numerous cases have been described. Aberrant pyruvate metabolism plays an especially prominent role in cancer, heart failure, and neurodegeneration. Because most major diseases involve aberrant metabolism, understanding and exploiting pyruvate carbon flux may yield novel treatments that enhance human health.

  1. An integrative machine learning strategy for improved prediction of essential genes in Escherichia coli metabolism using flux-coupled features.

    PubMed

    Nandi, Sutanu; Subramanian, Abhishek; Sarkar, Ram Rup

    2017-07-25

    Prediction of essential genes helps to identify a minimal set of genes that are absolutely required for the appropriate functioning and survival of a cell. The available machine learning techniques for essential gene prediction have inherent problems, like imbalanced provision of training datasets, biased choice of the best model for a given balanced dataset, choice of a complex machine learning algorithm, and data-based automated selection of biologically relevant features for classification. Here, we propose a simple support vector machine-based learning strategy for the prediction of essential genes in Escherichia coli K-12 MG1655 metabolism that integrates a non-conventional combination of an appropriate sample balanced training set, a unique organism-specific genotype, phenotype attributes that characterize essential genes, and optimal parameters of the learning algorithm to generate the best machine learning model (the model with the highest accuracy among all the models trained for different sample training sets). For the first time, we also introduce flux-coupled metabolic subnetwork-based features for enhancing the classification performance. Our strategy proves to be superior as compared to previous SVM-based strategies in obtaining a biologically relevant classification of genes with high sensitivity and specificity. This methodology was also trained with datasets of other recent supervised classification techniques for essential gene classification and tested using reported test datasets. The testing accuracy was always high as compared to the known techniques, proving that our method outperforms known methods. Observations from our study indicate that essential genes are conserved among homologous bacterial species, demonstrate high codon usage bias, GC content and gene expression, and predominantly possess a tendency to form physiological flux modules in metabolism.

  2. Framework for network modularization and Bayesian network analysis to investigate the perturbed metabolic network

    PubMed Central

    2011-01-01

    Background Genome-scale metabolic network models have contributed to elucidating biological phenomena, and predicting gene targets to engineer for biotechnological applications. With their increasing importance, their precise network characterization has also been crucial for better understanding of the cellular physiology. Results We herein introduce a framework for network modularization and Bayesian network analysis (FMB) to investigate organism’s metabolism under perturbation. FMB reveals direction of influences among metabolic modules, in which reactions with similar or positively correlated flux variation patterns are clustered, in response to specific perturbation using metabolic flux data. With metabolic flux data calculated by constraints-based flux analysis under both control and perturbation conditions, FMB, in essence, reveals the effects of specific perturbations on the biological system through network modularization and Bayesian network analysis at metabolic modular level. As a demonstration, this framework was applied to the genetically perturbed Escherichia coli metabolism, which is a lpdA gene knockout mutant, using its genome-scale metabolic network model. Conclusions After all, it provides alternative scenarios of metabolic flux distributions in response to the perturbation, which are complementary to the data obtained from conventionally available genome-wide high-throughput techniques or metabolic flux analysis. PMID:22784571

  3. Framework for network modularization and Bayesian network analysis to investigate the perturbed metabolic network.

    PubMed

    Kim, Hyun Uk; Kim, Tae Yong; Lee, Sang Yup

    2011-01-01

    Genome-scale metabolic network models have contributed to elucidating biological phenomena, and predicting gene targets to engineer for biotechnological applications. With their increasing importance, their precise network characterization has also been crucial for better understanding of the cellular physiology. We herein introduce a framework for network modularization and Bayesian network analysis (FMB) to investigate organism's metabolism under perturbation. FMB reveals direction of influences among metabolic modules, in which reactions with similar or positively correlated flux variation patterns are clustered, in response to specific perturbation using metabolic flux data. With metabolic flux data calculated by constraints-based flux analysis under both control and perturbation conditions, FMB, in essence, reveals the effects of specific perturbations on the biological system through network modularization and Bayesian network analysis at metabolic modular level. As a demonstration, this framework was applied to the genetically perturbed Escherichia coli metabolism, which is a lpdA gene knockout mutant, using its genome-scale metabolic network model. After all, it provides alternative scenarios of metabolic flux distributions in response to the perturbation, which are complementary to the data obtained from conventionally available genome-wide high-throughput techniques or metabolic flux analysis.

  4. Metabolic reconstruction, constraint-based analysis and game theory to probe genome-scale metabolic networks.

    PubMed

    Ruppin, Eytan; Papin, Jason A; de Figueiredo, Luis F; Schuster, Stefan

    2010-08-01

    With the advent of modern omics technologies, it has become feasible to reconstruct (quasi-) whole-cell metabolic networks and characterize them in more and more detail. Computer simulations of the dynamic behavior of such networks are difficult due to a lack of kinetic data and to computational limitations. In contrast, network analysis based on appropriate constraints such as the steady-state condition (constraint-based analysis) is feasible and allows one to derive conclusions about the system's metabolic capabilities. Here, we review methods for the reconstruction of metabolic networks, modeling techniques such as flux balance analysis and elementary flux modes and current progress in their development and applications. Game-theoretical methods for studying metabolic networks are discussed as well. Copyright © 2010 Elsevier Ltd. All rights reserved.

  5. Metabolic control analysis of integrated energy metabolism in permeabilized cardiomyocytes - experimental study.

    PubMed

    Tepp, Kersti; Timohhina, Natalja; Chekulayev, Vladimir; Shevchuk, Igor; Kaambre, Tuuli; Saks, Valdur

    2010-01-01

    The main focus of this research was to apply Metabolic Control Analysis to quantitative investigation of the regulation of respiration by components of the Mitochondrial Interactosome (MI, a supercomplex consisting of ATP Synthasome, mitochondrial creatine kinase (MtCK), voltage dependent anion channel (VDAC), and tubulin) in permeabilized cardiomyocytes. Flux control coefficients (FCC) were measured using two protocols: 1) with direct ADP activation, and 2) with MtCK activation by creatine (Cr) in the presence of ATP and pyruvate kinase-phosphoenolpyruvate system. The results show that the metabolic control is much stronger in the latter case: the sum of the measured FCC is 2.7 versus 0.74 (ADP activation). This is consistent with previous data showing recycling of ADP and ATP inside the MI due to the functional coupling between MtCK and ANT and limited permeability of VDAC for these compounds, PCr being the major energy carrier between the mitochondria and ATPases. In physiological conditions, when the MI is activated, the key sites of regulation of respiration in mitochondria are MtCK (FCC = 0.93), adenine nucleotide translocase ANT (FCC = 0.95) and CoQ cytochrome c oxidoreductase (FCC = 0.4). These results show clearly that under the physiological conditions the energy transfer from mitochondria to the cytoplasm is regulated by the MI supercomplex and is very sensitive to metabolic signals.

  6. Cyanobacterial carbon metabolism: Fluxome plasticity and oxygen dependence: Cyanobacterial Carbon Metabolism

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Wan, Ni; DeLorenzo, Drew M.; He, Lian

    Synechocystis sp. strain PCC 6803 has been widely used as a photo-biorefinery chassis. Based on its genome annotation, this species contains a complete TCA cycle, an Embden-Meyerhof-Parnas pathway (EMPP), an oxidative pentose phosphate pathway (OPPP), and an Entner–Doudoroff pathway (EDP). To evaluate how Synechocystis 6803 catabolizes glucose under heterotrophic conditions, we performed 13C metabolic flux analysis, metabolite pool size analysis, gene knockouts, and heterologous expressions. The results revealed a cyclic mode of flux through the OPPP. Small, but non-zero, fluxes were observed through the TCA cycle and the malic shunt. Independent knockouts of 6-phosphogluconate dehydrogenase (gnd) and malic enzyme (me)more » corroborated these results, as neither mutant could grow under dark heterotrophic conditions. Our data also indicate that Synechocystis 6803 metabolism relies upon oxidative phosphorylation to generate ATP from NADPH under dark or insufficient light conditions. The pool sizes of intermediates in the TCA cycle, particularly acetyl-CoA, were found to be several fold lower in Synechocystis 6803 (compared to E. coli metabolite pool sizes), while its sugar phosphate intermediates were several-fold higher. Moreover, negligible flux was detected through the native, or heterologous, EDP in the wild type or Δgnd strains under heterotrophic conditions. Comparing photoautotrophic, photomixotrophic, and heterotrophic conditions, the Calvin cycle, OPPP, and EMPP in Synechocystis 6803 possess the ability to regulate their fluxes under various growth conditions (plastic), whereas its TCA cycle always maintains at low levels (rigid). This work also demonstrates how genetic profiles do not always reflect actual metabolic flux through native or heterologous pathways. Biotechnol. Bioeng. 2017;114: 1593–1602. © 2017 Wiley Periodicals, Inc.« less

  7. Quantitative analysis of autophagic flux by confocal pH-imaging of autophagic intermediates

    PubMed Central

    Maulucci, Giuseppe; Chiarpotto, Michela; Papi, Massimiliano; Samengo, Daniela; Pani, Giovambattista; De Spirito, Marco

    2015-01-01

    Although numerous techniques have been developed to monitor autophagy and to probe its cellular functions, these methods cannot evaluate in sufficient detail the autophagy process, and suffer limitations from complex experimental setups and/or systematic errors. Here we developed a method to image, contextually, the number and pH of autophagic intermediates by using the probe mRFP-GFP-LC3B as a ratiometric pH sensor. This information is expressed functionally by AIPD, the pH distribution of the number of autophagic intermediates per cell. AIPD analysis reveals how intermediates are characterized by a continuous pH distribution, in the range 4.5–6.5, and therefore can be described by a more complex set of states rather than the usual biphasic one (autophagosomes and autolysosomes). AIPD shape and amplitude are sensitive to alterations in the autophagy pathway induced by drugs or environmental states, and allow a quantitative estimation of autophagic flux by retrieving the concentrations of autophagic intermediates. PMID:26506895

  8. A holistic view of dietary carbohydrate utilization in lobster: digestion, postprandial nutrient flux, and metabolism.

    PubMed

    Rodríguez-Viera, Leandro; Perera, Erick; Casuso, Antonio; Perdomo-Morales, Rolando; Gutierrez, Odilia; Scull, Idania; Carrillo, Olimpia; Martos-Sitcha, Juan A; García-Galano, Tsai; Mancera, Juan Miguel

    2014-01-01

    Crustaceans exhibit a remarkable variation in their feeding habits and food type, but most knowledge on carbohydrate digestion and utilization in this group has come from research on few species. The aim of this study was to make an integrative analysis of dietary carbohydrate utilization in the spiny lobster Panulirus argus. We used complementary methodologies such as different assessments of digestibility, activity measurements of digestive and metabolic enzymes, and post-feeding flux of nutrients and metabolites. Several carbohydrates were well digested by the lobster, but maize starch was less digestible than all other starches studied, and its inclusion in diet affected protein digestibility. Most intense hydrolysis of carbohydrates in the gastric chamber of lobster occurred between 2-6 h after ingestion and afterwards free glucose increased in hemolymph. The inclusion of wheat in diet produced a slow clearance of glucose from the gastric fluid and a gradual increase in hemolymph glucose. More intense hydrolysis of protein in the gastric chamber occurred 6-12 h after ingestion and then amino acids tended to increase in hemolymph. Triglyceride concentration in hemolymph rose earlier in wheat-fed lobsters than in lobsters fed other carbohydrates, but it decreased the most 24 h later. Analyses of metabolite levels and activities of different metabolic enzymes revealed that intermolt lobsters had a low capacity to store and use glycogen, although it was slightly higher in wheat-fed lobsters. Lobsters fed maize and rice diets increased amino acid catabolism, while wheat-fed lobsters exhibited higher utilization of fatty acids. Multivariate analysis confirmed that the type of carbohydrate ingested had a profound effect on overall metabolism. Although we found no evidence of a protein-sparing effect of dietary carbohydrate, differences in the kinetics of their digestion and absorption impacted lobster metabolism determining the fate of other nutrients.

  9. A Holistic View of Dietary Carbohydrate Utilization in Lobster: Digestion, Postprandial Nutrient Flux, and Metabolism

    PubMed Central

    Casuso, Antonio; Perdomo-Morales, Rolando; Gutierrez, Odilia; Scull, Idania; Carrillo, Olimpia; Martos-Sitcha, Juan A.; García-Galano, Tsai; Mancera, Juan Miguel

    2014-01-01

    Crustaceans exhibit a remarkable variation in their feeding habits and food type, but most knowledge on carbohydrate digestion and utilization in this group has come from research on few species. The aim of this study was to make an integrative analysis of dietary carbohydrate utilization in the spiny lobster Panulirus argus. We used complementary methodologies such as different assessments of digestibility, activity measurements of digestive and metabolic enzymes, and post-feeding flux of nutrients and metabolites. Several carbohydrates were well digested by the lobster, but maize starch was less digestible than all other starches studied, and its inclusion in diet affected protein digestibility. Most intense hydrolysis of carbohydrates in the gastric chamber of lobster occurred between 2–6 h after ingestion and afterwards free glucose increased in hemolymph. The inclusion of wheat in diet produced a slow clearance of glucose from the gastric fluid and a gradual increase in hemolymph glucose. More intense hydrolysis of protein in the gastric chamber occurred 6–12 h after ingestion and then amino acids tended to increase in hemolymph. Triglyceride concentration in hemolymph rose earlier in wheat-fed lobsters than in lobsters fed other carbohydrates, but it decreased the most 24 h later. Analyses of metabolite levels and activities of different metabolic enzymes revealed that intermolt lobsters had a low capacity to store and use glycogen, although it was slightly higher in wheat-fed lobsters. Lobsters fed maize and rice diets increased amino acid catabolism, while wheat-fed lobsters exhibited higher utilization of fatty acids. Multivariate analysis confirmed that the type of carbohydrate ingested had a profound effect on overall metabolism. Although we found no evidence of a protein-sparing effect of dietary carbohydrate, differences in the kinetics of their digestion and absorption impacted lobster metabolism determining the fate of other nutrients. PMID

  10. Use of CellNetAnalyzer in biotechnology and metabolic engineering.

    PubMed

    von Kamp, Axel; Thiele, Sven; Hädicke, Oliver; Klamt, Steffen

    2017-11-10

    Mathematical models of the cellular metabolism have become an essential tool for the optimization of biotechnological processes. They help to obtain a systemic understanding of the metabolic processes in the used microorganisms and to find suitable genetic modifications maximizing the production performance. In particular, methods of stoichiometric and constraint-based modeling are frequently used in the context of metabolic and bioprocess engineering. Since metabolic networks can be complex and comprise hundreds or even thousands of metabolites and reactions, dedicated software tools are required for an efficient analysis. One such software suite is CellNetAnalyzer, a MATLAB package providing, among others, various methods for analyzing stoichiometric and constraint-based metabolic models. CellNetAnalyzer can be used via command-line based operations or via a graphical user interface with embedded network visualizations. Herein we will present key functionalities of CellNetAnalyzer for applications in biotechnology and metabolic engineering and thereby review constraint-based modeling techniques such as metabolic flux analysis, flux balance analysis, flux variability analysis, metabolic pathway analysis (elementary flux modes) and methods for computational strain design. Copyright © 2017 The Author(s). Published by Elsevier B.V. All rights reserved.

  11. Deep Proteomics of Mouse Skeletal Muscle Enables Quantitation of Protein Isoforms, Metabolic Pathways, and Transcription Factors*

    PubMed Central

    Deshmukh, Atul S.; Murgia, Marta; Nagaraj, Nagarjuna; Treebak, Jonas T.; Cox, Jürgen; Mann, Matthias

    2015-01-01

    Skeletal muscle constitutes 40% of individual body mass and plays vital roles in locomotion and whole-body metabolism. Proteomics of skeletal muscle is challenging because of highly abundant contractile proteins that interfere with detection of regulatory proteins. Using a state-of-the art MS workflow and a strategy to map identifications from the C2C12 cell line model to tissues, we identified a total of 10,218 proteins, including skeletal muscle specific transcription factors like myod1 and myogenin and circadian clock proteins. We obtain absolute abundances for proteins expressed in a muscle cell line and skeletal muscle, which should serve as a valuable resource. Quantitation of protein isoforms of glucose uptake signaling pathways and in glucose and lipid metabolic pathways provides a detailed metabolic map of the cell line compared with tissue. This revealed unexpectedly complex regulation of AMP-activated protein kinase and insulin signaling in muscle tissue at the level of enzyme isoforms. PMID:25616865

  12. Prognostic Value of Quantitative Metabolic Metrics on Baseline Pre-Sunitinib FDG PET/CT in Advanced Renal Cell Carcinoma

    PubMed Central

    Minamimoto, Ryogo; Barkhodari, Amir; Harshman, Lauren; Srinivas, Sandy; Quon, Andrew

    2016-01-01

    Purpose The objective of this study was to prospectively evaluate various quantitative metrics on FDG PET/CT for monitoring sunitinib therapy and predicting prognosis in patients with metastatic renal cell cancer (mRCC). Methods Seventeen patients (mean age: 59.0 ± 11.6) prospectively underwent a baseline FDG PET/CT and interim PET/CT after 2 cycles (12 weeks) of sunitinib therapy. We measured the highest maximum standardized uptake value (SUVmax) of all identified lesions (highest SUVmax), sum of SUVmax with maximum six lesions (sum of SUVmax), total lesion glycolysis (TLG) and metabolic tumor volume (MTV) from baseline PET/CT and interim PET/CT, and the % decrease in highest SUVmax of lesion (%Δ highest SUVmax), the % decrease in sum of SUVmax, the % decrease in TLG (%ΔTLG) and the % decrease in MTV (%ΔMTV) between baseline and interim PET/CT, and the imaging results were validated by clinical follow-up at 12 months after completion of therapy for progression free survival (PFS). Results At 12 month follow-up, 6/17 (35.3%) patients achieved PFS, while 11/17 (64.7%) patients were deemed to have progression of disease or recurrence within the previous 12 months. At baseline, PET/CT demonstrated metabolically active cancer in all cases. Using baseline PET/CT alone, all of the quantitative imaging metrics were predictive of PFS. Using interim PET/CT, the %Δ highest SUVmax, %Δ sum of SUVmax, and %ΔTLG were also predictive of PFS. Otherwise, interim PET/CT showed no significant difference between the two survival groups regardless of the quantitative metric utilized including MTV and TLG. Conclusions Quantitative metabolic measurements on baseline PET/CT appears to be predictive of PFS at 12 months post-therapy in patients scheduled to undergo sunitinib therapy for mRCC. Change between baseline and interim PET/CT also appeared to have prognostic value but otherwise interim PET/CT after 12 weeks of sunitinib did not appear to be predictive of PFS. PMID:27123976

  13. Quantitative proteomics reveals the importance of nitrogen source to control glucosinolate metabolism in Arabidopsis thaliana and Brassica oleracea

    PubMed Central

    Marino, Daniel; Ariz, Idoia; Lasa, Berta; Santamaría, Enrique; Fernández-Irigoyen, Joaquín; González-Murua, Carmen; Aparicio Tejo, Pedro M.

    2016-01-01

    Accessing different nitrogen (N) sources involves a profound adaptation of plant metabolism. In this study, a quantitative proteomic approach was used to further understand how the model plant Arabidopsis thaliana adjusts to different N sources when grown exclusively under nitrate or ammonium nutrition. Proteome data evidenced that glucosinolate metabolism was differentially regulated by the N source and that both TGG1 and TGG2 myrosinases were more abundant under ammonium nutrition, which is generally considered to be a stressful situation. Moreover, Arabidopsis plants displayed glucosinolate accumulation and induced myrosinase activity under ammonium nutrition. Interestingly, these results were also confirmed in the economically important crop broccoli (Brassica oleracea var. italica). Moreover, these metabolic changes were correlated in Arabidopsis with the differential expression of genes from the aliphatic glucosinolate metabolic pathway. This study underlines the importance of nitrogen nutrition and the potential of using ammonium as the N source in order to stimulate glucosinolate metabolism, which may have important applications not only in terms of reducing pesticide use, but also for increasing plants’ nutritional value. PMID:27085186

  14. In vivo stationary flux analysis by 13C labeling experiments.

    PubMed

    Wiechert, W; de Graaf, A A

    1996-01-01

    Stationary flux analysis is an invaluable tool for metabolic engineering. In the last years the metabolite balancing technique has become well established in the bioengineering community. On the other hand metabolic tracer experiments using 13C isotopes have long been used for intracellular flux determination. Only recently have both techniques been fully combined to form a considerably more powerful flux analysis method. This paper concentrates on modeling and data analysis for the evaluation of such stationary 13C labeling experiments. After reviewing recent experimental developments, the basic equations for modeling carbon labeling in metabolic systems, i.e. metabolite, carbon label and isotopomer balances, are introduced and discussed in some detail. Then the basics of flux estimation from measured extracellular fluxes combined with carbon labeling data are presented and, finally, this method is illustrated by using an example from C. glutamicum. The main emphasis is on the investigation of the extra information that can be obtained with tracer experiments compared with the metabolite balancing technique alone. As a principal result it is shown that the combined flux analysis method can dispense with some rather doubtful assumptions on energy balancing and that the forward and backward flux rates of bidirectional reaction steps can be simultaneously determined in certain situations. Finally, it is demonstrated that the variant of fractional isotopomer measurement is even more powerful than fractional labeling measurement but requires much higher numerical effort to solve the balance equations.

  15. Quantitative metabolomics by H-NMR and LC-MS/MS confirms altered metabolic pathways in diabetes.

    PubMed

    Lanza, Ian R; Zhang, Shucha; Ward, Lawrence E; Karakelides, Helen; Raftery, Daniel; Nair, K Sreekumaran

    2010-05-10

    Insulin is as a major postprandial hormone with profound effects on carbohydrate, fat, and protein metabolism. In the absence of exogenous insulin, patients with type 1 diabetes exhibit a variety of metabolic abnormalities including hyperglycemia, glycosurea, accelerated ketogenesis, and muscle wasting due to increased proteolysis. We analyzed plasma from type 1 diabetic (T1D) humans during insulin treatment (I+) and acute insulin deprivation (I-) and non-diabetic participants (ND) by (1)H nuclear magnetic resonance spectroscopy and liquid chromatography-tandem mass spectrometry. The aim was to determine if this combination of analytical methods could provide information on metabolic pathways known to be altered by insulin deficiency. Multivariate statistics differentiated proton spectra from I- and I+ based on several derived plasma metabolites that were elevated during insulin deprivation (lactate, acetate, allantoin, ketones). Mass spectrometry revealed significant perturbations in levels of plasma amino acids and amino acid metabolites during insulin deprivation. Further analysis of metabolite levels measured by the two analytical techniques indicates several known metabolic pathways that are perturbed in T1D (I-) (protein synthesis and breakdown, gluconeogenesis, ketogenesis, amino acid oxidation, mitochondrial bioenergetics, and oxidative stress). This work demonstrates the promise of combining multiple analytical methods with advanced statistical methods in quantitative metabolomics research, which we have applied to the clinical situation of acute insulin deprivation in T1D to reflect the numerous metabolic pathways known to be affected by insulin deficiency.

  16. Elucidating Rice Cell Metabolism under Flooding and Drought Stresses Using Flux-Based Modeling and Analysis1[C][W][OPEN

    PubMed Central

    Lakshmanan, Meiyappan; Zhang, Zhaoyang; Mohanty, Bijayalaxmi; Kwon, Jun-Young; Choi, Hong-Yeol; Nam, Hyung-Jin; Kim, Dong-Il; Lee, Dong-Yup

    2013-01-01

    Rice (Oryza sativa) is one of the major food crops in world agriculture, especially in Asia. However, the possibility of subsequent occurrence of flood and drought is a major constraint to its production. Thus, the unique behavior of rice toward flooding and drought stresses has required special attention to understand its metabolic adaptations. However, despite several decades of research investigations, the cellular metabolism of rice remains largely unclear. In this study, in order to elucidate the physiological characteristics in response to such abiotic stresses, we reconstructed what is to our knowledge the first metabolic/regulatory network model of rice, representing two tissue types: germinating seeds and photorespiring leaves. The phenotypic behavior and metabolic states simulated by the model are highly consistent with our suspension culture experiments as well as previous reports. The in silico simulation results of seed-derived rice cells indicated (1) the characteristic metabolic utilization of glycolysis and ethanolic fermentation based on oxygen availability and (2) the efficient sucrose breakdown through sucrose synthase instead of invertase. Similarly, flux analysis on photorespiring leaf cells elucidated the crucial role of plastid-cytosol and mitochondrion-cytosol malate transporters in recycling the ammonia liberated during photorespiration and in exporting the excess redox cofactors, respectively. The model simulations also unraveled the essential role of mitochondrial respiration during drought stress. In the future, the combination of experimental and in silico analyses can serve as a promising approach to understand the complex metabolism of rice and potentially help in identifying engineering targets for improving its productivity as well as enabling stress tolerance. PMID:23753178

  17. Construction and completion of flux balance models from pathway databases.

    PubMed

    Latendresse, Mario; Krummenacker, Markus; Trupp, Miles; Karp, Peter D

    2012-02-01

    Flux balance analysis (FBA) is a well-known technique for genome-scale modeling of metabolic flux. Typically, an FBA formulation requires the accurate specification of four sets: biochemical reactions, biomass metabolites, nutrients and secreted metabolites. The development of FBA models can be time consuming and tedious because of the difficulty in assembling completely accurate descriptions of these sets, and in identifying errors in the composition of these sets. For example, the presence of a single non-producible metabolite in the biomass will make the entire model infeasible. Other difficulties in FBA modeling are that model distributions, and predicted fluxes, can be cryptic and difficult to understand. We present a multiple gap-filling method to accelerate the development of FBA models using a new tool, called MetaFlux, based on mixed integer linear programming (MILP). The method suggests corrections to the sets of reactions, biomass metabolites, nutrients and secretions. The method generates FBA models directly from Pathway/Genome Databases. Thus, FBA models developed in this framework are easily queried and visualized using the Pathway Tools software. Predicted fluxes are more easily comprehended by visualizing them on diagrams of individual metabolic pathways or of metabolic maps. MetaFlux can also remove redundant high-flux loops, solve FBA models once they are generated and model the effects of gene knockouts. MetaFlux has been validated through construction of FBA models for Escherichia coli and Homo sapiens. Pathway Tools with MetaFlux is freely available to academic users, and for a fee to commercial users. Download from: biocyc.org/download.shtml. mario.latendresse@sri.com Supplementary data are available at Bioinformatics online.

  18. Quantitative structure-activity relationship modeling on in vitro endocrine effects and metabolic stability involving 26 selected brominated flame retardants.

    PubMed

    Harju, Mikael; Hamers, Timo; Kamstra, Jorke H; Sonneveld, Edwin; Boon, Jan P; Tysklind, Mats; Andersson, Patrik L

    2007-04-01

    In this work, quantitative structure-activity relationships (QSARs) were developed to aid human and environmental risk assessment processes for brominated flame retardants (BFRs). Brominated flame retardants, such as the high-production-volume chemicals polybrominated diphenyl ethers (PBDEs), tetrabromobisphenol A, and hexabromocyclododecane, have been identified as potential endocrine disruptors. Quantitative structure-activity relationship models were built based on the in vitro potencies of 26 selected BFRs. The in vitro assays included interactions with, for example, androgen, progesterone, estrogen, and dioxin (aryl hydrocarbon) receptor, plus competition with thyroxine for its plasma carrier protein (transthyretin), inhibition of estradiol sulfation via sulfotransferase, and finally, rate of metabolization. The QSAR modeling, a number of physicochemical parameters were calculated describing the electronic, lipophilic, and structural characteristics of the molecules. These include frontier molecular orbitals, molecular charges, polarities, log octanol/water partitioning coefficient, and two- and three-dimensional molecularproperties. Experimental properties were included and measured for PBDEs, such as their individual ultraviolet spectra (200-320 nm) and retention times on three different high-performance liquid chromatography columns and one nonpolar gas chromatography column. Quantitative structure-activity relationship models based on androgen antagonism and metabolic degradation rates generally gave similar results, suggesting that lower-brominated PBDEs with bromine substitutions in ortho positions and bromine-free meta- and para positions had the highest potencies and metabolic degradation rates. Predictions made for the constituents of the technical flame retardant Bromkal 70-5DE found BDE 17 to be a potent androgen antagonist and BDE 66, which is a relevant PBDE in environmental samples, to be only a weak antagonist.

  19. Dynamic elementary mode modelling of non-steady state flux data.

    PubMed

    Folch-Fortuny, Abel; Teusink, Bas; Hoefsloot, Huub C J; Smilde, Age K; Ferrer, Alberto

    2018-06-18

    A novel framework is proposed to analyse metabolic fluxes in non-steady state conditions, based on the new concept of dynamic elementary mode (dynEM): an elementary mode activated partially depending on the time point of the experiment. Two methods are introduced here: dynamic elementary mode analysis (dynEMA) and dynamic elementary mode regression discriminant analysis (dynEMR-DA). The former is an extension of the recently proposed principal elementary mode analysis (PEMA) method from steady state to non-steady state scenarios. The latter is a discriminant model that permits to identify which dynEMs behave strongly different depending on the experimental conditions. Two case studies of Saccharomyces cerevisiae, with fluxes derived from simulated and real concentration data sets, are presented to highlight the benefits of this dynamic modelling. This methodology permits to analyse metabolic fluxes at early stages with the aim of i) creating reduced dynamic models of flux data, ii) combining many experiments in a single biologically meaningful model, and iii) identifying the metabolic pathways that drive the organism from one state to another when changing the environmental conditions.

  20. Anion channel sensitivity to cytosolic organic acids implicates a central role for oxaloacetate in integrating ion flux with metabolism in stomatal guard cells.

    PubMed

    Wang, Yizhou; Blatt, Michael R

    2011-10-01

    Stomatal guard cells play a key role in gas exchange for photosynthesis and in minimizing transpirational water loss from plants by opening and closing the stomatal pore. The bulk of the osmotic content driving stomatal movements depends on ionic fluxes across both the plasma membrane and tonoplast, the metabolism of organic acids, primarily Mal (malate), and its accumulation and loss. Anion channels at the plasma membrane are thought to comprise a major pathway for Mal efflux during stomatal closure, implicating their key role in linking solute flux with metabolism. Nonetheless, little is known of the regulation of anion channel current (I(Cl)) by cytosolic Mal or its immediate metabolite OAA (oxaloacetate). In the present study, we have examined the impact of Mal, OAA and of the monocarboxylic acid anion acetate in guard cells of Vicia faba L. and report that all three organic acids affect I(Cl), but with markedly different characteristics and sidedness to their activities. Most prominent was a suppression of ICl by OAA within the physiological range of concentrations found in vivo. These findings indicate a capacity for OAA to co-ordinate organic acid metabolism with I(Cl) through the direct effect of organic acid pool size. The findings of the present study also add perspective to in vivo recordings using acetate-based electrolytes.

  1. Phalangeal quantitative ultrasound and metabolic control in pre-menopausal women with type 1 diabetes mellitus.

    PubMed

    Catalano, A; Morabito, N; Di Vieste, G; Pintaudi, B; Cucinotta, D; Lasco, A; Di Benedetto, A

    2013-05-01

    Several studies have reported increased fracture risk in Type 1 diabetes mellitus (T1DM). Quantitative Ultrasound (QUS) provides information on the structure and elastic properties of bone, which are important determinants of fracture risk, along with bone mineral density. To study phalangeal sites by QUS, examine bone turnover markers and analyze association between these factors with metabolic control in a population of pre-menopausal women with T1DM. Thirty-five T1DM pre-menopausal women (mean age 34.5 ± 6.8 yr) attending the Diabetic Outpatients Clinic in the Department of Internal Medicine, University of Messina, were consecutively enrolled and divided into two groups, taking into account the mean value of glycated hemoglobin in the last three years. Twenty healthy age-matched women served as controls. Phalangeal ultrasound measurements [Amplitude Dependent Speed of Sound (AD-SoS), Ultrasound Bone Profile Index (UBPI), TScore, Z-Score] were performed using a DBM Sonic Bone Profiler. Osteocalcin and deoxypyridinoline served as markers of bone formation and bone resorption, respectively. T1DM women with poor metabolic control showed lower phalangeal QUS values compared to healthy controls (p<0.01) and T1DM women with good metabolic control (p<0.05). No significant differences in QUS measurements were detected between T1DM women with good metabolic control and healthy controls. Lower bone formation and increased bone resorption, although not statistically significant, were observed in patients with poor metabolic control in comparison to patients with good metabolic control. Poor metabolic control may worsen the quality of bone in T1DM. Phalangeal QUS could be considered as a tool to screen T1DM women for osteoporosis in pre-menopausal age.

  2. Second Law of Thermodynamics Applied to Metabolic Networks

    NASA Technical Reports Server (NTRS)

    Nigam, R.; Liang, S.

    2003-01-01

    We present a simple algorithm based on linear programming, that combines Kirchoff's flux and potential laws and applies them to metabolic networks to predict thermodynamically feasible reaction fluxes. These law's represent mass conservation and energy feasibility that are widely used in electrical circuit analysis. Formulating the Kirchoff's potential law around a reaction loop in terms of the null space of the stoichiometric matrix leads to a simple representation of the law of entropy that can be readily incorporated into the traditional flux balance analysis without resorting to non-linear optimization. Our technique is new as it can easily check the fluxes got by applying flux balance analysis for thermodynamic feasibility and modify them if they are infeasible so that they satisfy the law of entropy. We illustrate our method by applying it to the network dealing with the central metabolism of Escherichia coli. Due to its simplicity this algorithm will be useful in studying large scale complex metabolic networks in the cell of different organisms.

  3. Quantitative comparison of in situ soil CO2 flux measurement methods

    Treesearch

    Jennifer D. Knoepp; James M. Vose

    2002-01-01

    Development of reliable regional or global carbon budgets requires accurate measurement of soil CO2 flux. We conducted laboratory and field studies to determine the accuracy and comparability of methods commonly used to measure in situ soil CO2 fluxes. Methods compared included CO2...

  4. Elevated host lipid metabolism revealed by iTRAQ-based quantitative proteomic analysis of cerebrospinal fluid of tuberculous meningitis patients.

    PubMed

    Mu, Jun; Yang, Yongtao; Chen, Jin; Cheng, Ke; Li, Qi; Wei, Yongdong; Zhu, Dan; Shao, Weihua; Zheng, Peng; Xie, Peng

    2015-10-30

    Tuberculous meningitis (TBM) remains to be one of the most deadly infectious diseases. The pathogen interacts with the host immune system, the process of which is largely unknown. Various cellular processes of Mycobacterium tuberculosis (MTB) centers around lipid metabolism. To determine the lipid metabolism related proteins, a quantitative proteomic study was performed here to identify differential proteins in the cerebrospinal fluid (CSF) obtained from TBM patients (n = 12) and healthy controls (n = 12). CSF samples were desalted, concentrated, labelled with isobaric tags for relative and absolute quantitation (iTRAQ™), and analyzed by multi-dimensional liquid chromatography-tandem mass spectrometry (LC-MS/MS). Gene ontology and proteomic phenotyping analysis of the differential proteins were conducted using Database for Annotation, Visualization, and Integrated Discovery (DAVID) Bioinformatics Resources. ApoE and ApoB were selected for validation by ELISA. Proteomic phenotyping of the 4 differential proteins was invloved in the lipid metabolism. ELISA showed significantly increased ApoB levels in TBM subjects compared to healthy controls. Area under the receiver operating characteristic curve analysis demonstrated ApoB levels could distinguish TBM subjects from healthy controls and viral meningitis subjects with 89.3% sensitivity and 92% specificity. CSF lipid metabolism disregulation, especially elevated expression of ApoB, gives insights into the pathogenesis of TBM. Further evaluation of these findings in larger studies including anti-tuberculosis medicated and unmedicated patient cohorts with other center nervous system infectious diseases is required for successful clinical translation. Copyright © 2015 Elsevier Inc. All rights reserved.

  5. The role of short-chain fatty acids in the interplay between diet, gut microbiota, and host energy metabolism

    PubMed Central

    den Besten, Gijs; van Eunen, Karen; Groen, Albert K.; Venema, Koen; Reijngoud, Dirk-Jan; Bakker, Barbara M.

    2013-01-01

    Short-chain fatty acids (SCFAs), the end products of fermentation of dietary fibers by the anaerobic intestinal microbiota, have been shown to exert multiple beneficial effects on mammalian energy metabolism. The mechanisms underlying these effects are the subject of intensive research and encompass the complex interplay between diet, gut microbiota, and host energy metabolism. This review summarizes the role of SCFAs in host energy metabolism, starting from the production by the gut microbiota to the uptake by the host and ending with the effects on host metabolism. There are interesting leads on the underlying molecular mechanisms, but there are also many apparently contradictory results. A coherent understanding of the multilevel network in which SCFAs exert their effects is hampered by the lack of quantitative data on actual fluxes of SCFAs and metabolic processes regulated by SCFAs. In this review we address questions that, when answered, will bring us a great step forward in elucidating the role of SCFAs in mammalian energy metabolism. PMID:23821742

  6. Analysis of optimality in natural and perturbed metabolic networks

    PubMed Central

    Segrè, Daniel; Vitkup, Dennis; Church, George M.

    2002-01-01

    An important goal of whole-cell computational modeling is to integrate detailed biochemical information with biological intuition to produce testable predictions. Based on the premise that prokaryotes such as Escherichia coli have maximized their growth performance along evolution, flux balance analysis (FBA) predicts metabolic flux distributions at steady state by using linear programming. Corroborating earlier results, we show that recent intracellular flux data for wild-type E. coli JM101 display excellent agreement with FBA predictions. Although the assumption of optimality for a wild-type bacterium is justifiable, the same argument may not be valid for genetically engineered knockouts or other bacterial strains that were not exposed to long-term evolutionary pressure. We address this point by introducing the method of minimization of metabolic adjustment (MOMA), whereby we test the hypothesis that knockout metabolic fluxes undergo a minimal redistribution with respect to the flux configuration of the wild type. MOMA employs quadratic programming to identify a point in flux space, which is closest to the wild-type point, compatibly with the gene deletion constraint. Comparing MOMA and FBA predictions to experimental flux data for E. coli pyruvate kinase mutant PB25, we find that MOMA displays a significantly higher correlation than FBA. Our method is further supported by experimental data for E. coli knockout growth rates. It can therefore be used for predicting the behavior of perturbed metabolic networks, whose growth performance is in general suboptimal. MOMA and its possible future extensions may be useful in understanding the evolutionary optimization of metabolism. PMID:12415116

  7. Characterizing the roles of changing population size and selection on the evolution of flux control in metabolic pathways.

    PubMed

    Orlenko, Alena; Chi, Peter B; Liberles, David A

    2017-05-25

    Understanding the genotype-phenotype map is fundamental to our understanding of genomes. Genes do not function independently, but rather as part of networks or pathways. In the case of metabolic pathways, flux through the pathway is an important next layer of biological organization up from the individual gene or protein. Flux control in metabolic pathways, reflecting the importance of mutation to individual enzyme genes, may be evolutionarily variable due to the role of mutation-selection-drift balance. The evolutionary stability of rate limiting steps and the patterns of inter-molecular co-evolution were evaluated in a simulated pathway with a system out of equilibrium due to fluctuating selection, population size, or positive directional selection, to contrast with those under stabilizing selection. Depending upon the underlying population genetic regime, fluctuating population size was found to increase the evolutionary stability of rate limiting steps in some scenarios. This result was linked to patterns of local adaptation of the population. Further, during positive directional selection, as with more complex mutational scenarios, an increase in the observation of inter-molecular co-evolution was observed. Differences in patterns of evolution when systems are in and out of equilibrium, including during positive directional selection may lead to predictable differences in observed patterns for divergent evolutionary scenarios. In particular, this result might be harnessed to detect differences between compensatory processes and directional processes at the pathway level based upon evolutionary observations in individual proteins. Detecting functional shifts in pathways reflects an important milestone in predicting when changes in genotypes result in changes in phenotypes.

  8. A genome-scale metabolic network reconstruction of tomato (Solanum lycopersicum L.) and its application to photorespiratory metabolism.

    PubMed

    Yuan, Huili; Cheung, C Y Maurice; Poolman, Mark G; Hilbers, Peter A J; van Riel, Natal A W

    2016-01-01

    Tomato (Solanum lycopersicum L.) has been studied extensively due to its high economic value in the market, and high content in health-promoting antioxidant compounds. Tomato is also considered as an excellent model organism for studying the development and metabolism of fleshy fruits. However, the growth, yield and fruit quality of tomatoes can be affected by drought stress, a common abiotic stress for tomato. To investigate the potential metabolic response of tomato plants to drought, we reconstructed iHY3410, a genome-scale metabolic model of tomato leaf, and used this metabolic network to simulate tomato leaf metabolism. The resulting model includes 3410 genes and 2143 biochemical and transport reactions distributed across five intracellular organelles including cytosol, plastid, mitochondrion, peroxisome and vacuole. The model successfully described the known metabolic behaviour of tomato leaf under heterotrophic and phototrophic conditions. The in silico investigation of the metabolic characteristics for photorespiration and other relevant metabolic processes under drought stress suggested that: (i) the flux distributions through the mevalonate (MVA) pathway under drought were distinct from that under normal conditions; and (ii) the changes in fluxes through core metabolic pathways with varying flux ratio of RubisCO carboxylase to oxygenase may contribute to the adaptive stress response of plants. In addition, we improved on previous studies of reaction essentiality analysis for leaf metabolism by including potential alternative routes for compensating reaction knockouts. Altogether, the genome-scale model provides a sound framework for investigating tomato metabolism and gives valuable insights into the functional consequences of abiotic stresses. © 2015 The Authors.The Plant Journal published by Society for Experimental Biology and John Wiley & Sons Ltd.

  9. The Key to Acetate: Metabolic Fluxes of Acetic Acid Bacteria under Cocoa Pulp Fermentation-Simulating Conditions

    PubMed Central

    Adler, Philipp; Frey, Lasse Jannis; Berger, Antje; Bolten, Christoph Josef; Hansen, Carl Erik

    2014-01-01

    Acetic acid bacteria (AAB) play an important role during cocoa fermentation, as their main product, acetate, is a major driver for the development of the desired cocoa flavors. Here, we investigated the specialized metabolism of these bacteria under cocoa pulp fermentation-simulating conditions. A carefully designed combination of parallel 13C isotope labeling experiments allowed the elucidation of intracellular fluxes in the complex environment of cocoa pulp, when lactate and ethanol were included as primary substrates among undefined ingredients. We demonstrate that AAB exhibit a functionally separated metabolism during coconsumption of two-carbon and three-carbon substrates. Acetate is almost exclusively derived from ethanol, while lactate serves for the formation of acetoin and biomass building blocks. Although this is suboptimal for cellular energetics, this allows maximized growth and conversion rates. The functional separation results from a lack of phosphoenolpyruvate carboxykinase and malic enzymes, typically present in bacteria to interconnect metabolism. In fact, gluconeogenesis is driven by pyruvate phosphate dikinase. Consequently, a balanced ratio of lactate and ethanol is important for the optimum performance of AAB. As lactate and ethanol are individually supplied by lactic acid bacteria and yeasts during the initial phase of cocoa fermentation, respectively, this underlines the importance of a well-balanced microbial consortium for a successful fermentation process. Indeed, AAB performed the best and produced the largest amounts of acetate in mixed culture experiments when lactic acid bacteria and yeasts were both present. PMID:24837393

  10. The key to acetate: metabolic fluxes of acetic acid bacteria under cocoa pulp fermentation-simulating conditions.

    PubMed

    Adler, Philipp; Frey, Lasse Jannis; Berger, Antje; Bolten, Christoph Josef; Hansen, Carl Erik; Wittmann, Christoph

    2014-08-01

    Acetic acid bacteria (AAB) play an important role during cocoa fermentation, as their main product, acetate, is a major driver for the development of the desired cocoa flavors. Here, we investigated the specialized metabolism of these bacteria under cocoa pulp fermentation-simulating conditions. A carefully designed combination of parallel 13C isotope labeling experiments allowed the elucidation of intracellular fluxes in the complex environment of cocoa pulp, when lactate and ethanol were included as primary substrates among undefined ingredients. We demonstrate that AAB exhibit a functionally separated metabolism during coconsumption of two-carbon and three-carbon substrates. Acetate is almost exclusively derived from ethanol, while lactate serves for the formation of acetoin and biomass building blocks. Although this is suboptimal for cellular energetics, this allows maximized growth and conversion rates. The functional separation results from a lack of phosphoenolpyruvate carboxykinase and malic enzymes, typically present in bacteria to interconnect metabolism. In fact, gluconeogenesis is driven by pyruvate phosphate dikinase. Consequently, a balanced ratio of lactate and ethanol is important for the optimum performance of AAB. As lactate and ethanol are individually supplied by lactic acid bacteria and yeasts during the initial phase of cocoa fermentation, respectively, this underlines the importance of a well-balanced microbial consortium for a successful fermentation process. Indeed, AAB performed the best and produced the largest amounts of acetate in mixed culture experiments when lactic acid bacteria and yeasts were both present.

  11. Software applications for flux balance analysis.

    PubMed

    Lakshmanan, Meiyappan; Koh, Geoffrey; Chung, Bevan K S; Lee, Dong-Yup

    2014-01-01

    Flux balance analysis (FBA) is a widely used computational method for characterizing and engineering intrinsic cellular metabolism. The increasing number of its successful applications and growing popularity are possibly attributable to the availability of specific software tools for FBA. Each tool has its unique features and limitations with respect to operational environment, user-interface and supported analysis algorithms. Presented herein is an in-depth evaluation of currently available FBA applications, focusing mainly on usability, functionality, graphical representation and inter-operability. Overall, most of the applications are able to perform basic features of model creation and FBA simulation. COBRA toolbox, OptFlux and FASIMU are versatile to support advanced in silico algorithms to identify environmental and genetic targets for strain design. SurreyFBA, WEbcoli, Acorn, FAME, GEMSiRV and MetaFluxNet are the distinct tools which provide the user friendly interfaces in model handling. In terms of software architecture, FBA-SimVis and OptFlux have the flexible environments as they enable the plug-in/add-on feature to aid prospective functional extensions. Notably, an increasing trend towards the implementation of more tailored e-services such as central model repository and assistance to collaborative efforts was observed among the web-based applications with the help of advanced web-technologies. Furthermore, most recent applications such as the Model SEED, FAME, MetaFlux and MicrobesFlux have even included several routines to facilitate the reconstruction of genome-scale metabolic models. Finally, a brief discussion on the future directions of FBA applications was made for the benefit of potential tool developers.

  12. Energetics of glucose metabolism: a phenomenological approach to metabolic network modeling.

    PubMed

    Diederichs, Frank

    2010-08-12

    A new formalism to describe metabolic fluxes as well as membrane transport processes was developed. The new flux equations are comparable to other phenomenological laws. Michaelis-Menten like expressions, as well as flux equations of nonequilibrium thermodynamics, can be regarded as special cases of these new equations. For metabolic network modeling, variable conductances and driving forces are required to enable pathway control and to allow a rapid response to perturbations. When applied to oxidative phosphorylation, results of simulations show that whole oxidative phosphorylation cannot be described as a two-flux-system according to nonequilibrium thermodynamics, although all coupled reactions per se fulfill the equations of this theory. Simulations show that activation of ATP-coupled load reactions plus glucose oxidation is brought about by an increase of only two different conductances: a [Ca(2+)] dependent increase of cytosolic load conductances, and an increase of phosphofructokinase conductance by [AMP], which in turn becomes increased through [ADP] generation by those load reactions. In ventricular myocytes, this feedback mechanism is sufficient to increase cellular power output and O(2) consumption several fold, without any appreciable impairment of energetic parameters. Glucose oxidation proceeds near maximal power output, since transformed input and output conductances are nearly equal, yielding an efficiency of about 0.5. This conductance matching is fulfilled also by glucose oxidation of β-cells. But, as a price for the metabolic mechanism of glucose recognition, β-cells have only a limited capability to increase their power output.

  13. Metabolic flux of the oxidative pentose phosphate pathway under low light conditions in Synechocystis sp. PCC 6803.

    PubMed

    Ueda, Kentaro; Nakajima, Tsubasa; Yoshikawa, Katsunori; Toya, Yoshihiro; Matsuda, Fumio; Shimizu, Hiroshi

    2018-02-27

    The role of the oxidative pentose phosphate pathway (oxPPP) in Synechocystis sp. PCC 6803 under mixotrophic conditions was investigated by 13 C metabolic flux analysis. Cells were cultured under low (10 μmol m -2  s -1 ) and high light intensities (100 μmol m -2  s -1 ) in the presence of glucose. The flux of CO 2 fixation by ribulose bisphosphate carboxylase/oxygenase under the high light condition was approximately 3-fold higher than that under the low light condition. Although no flux of the oxPPP was observed under the high light condition, flux of 0.08-0.19 mmol gDCW -1  h -1 in the oxPPP was observed under the low light condition. The balance between the consumption and production of NADPH suggested that approximately 10% of the total NADPH production was generated by the oxPPP under the low light condition. The growth phenotype of a mutant with deleted zwf, which encodes glucose-6-phosphate dehydrogenase in the oxPPP, was compared to that of the parental strain under low and high light conditions. Growth of the Δzwf mutant nearly stopped during the late growth phase under the low light condition, whereas the growth rates of the two strains were identical under the high light condition. These results indicate that NADPH production in the oxPPP is essential for anabolism under low light conditions. The oxPPP appears to play an important role in producing NADPH from glucose and ATP to compensate for NADPH shortage under low light conditions. Copyright © 2018 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

  14. Deep proteomics of mouse skeletal muscle enables quantitation of protein isoforms, metabolic pathways, and transcription factors.

    PubMed

    Deshmukh, Atul S; Murgia, Marta; Nagaraj, Nagarjuna; Treebak, Jonas T; Cox, Jürgen; Mann, Matthias

    2015-04-01

    Skeletal muscle constitutes 40% of individual body mass and plays vital roles in locomotion and whole-body metabolism. Proteomics of skeletal muscle is challenging because of highly abundant contractile proteins that interfere with detection of regulatory proteins. Using a state-of-the art MS workflow and a strategy to map identifications from the C2C12 cell line model to tissues, we identified a total of 10,218 proteins, including skeletal muscle specific transcription factors like myod1 and myogenin and circadian clock proteins. We obtain absolute abundances for proteins expressed in a muscle cell line and skeletal muscle, which should serve as a valuable resource. Quantitation of protein isoforms of glucose uptake signaling pathways and in glucose and lipid metabolic pathways provides a detailed metabolic map of the cell line compared with tissue. This revealed unexpectedly complex regulation of AMP-activated protein kinase and insulin signaling in muscle tissue at the level of enzyme isoforms. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

  15. Disruption of lactate dehydrogenase and alcohol dehydrogenase for increased hydrogen production and its effect on metabolic flux in Enterobacter aerogenes.

    PubMed

    Zhao, Hongxin; Lu, Yuan; Wang, Liyan; Zhang, Chong; Yang, Cheng; Xing, Xinhui

    2015-10-01

    Hydrogen production by Enterobacter aerogenes from glucose was enhanced by deleting the targeted ldhA and adh genes responsible for two NADH-consuming pathways which consume most NADH generated from glycolysis. Compared with the wild-type, the hydrogen yield of IAM1183-ΔldhA increased 1.5 fold. Metabolic flux analysis showed both IAM1183-ΔldhA and IAM1183-Δadh exhibited significant changes in flux, including enhanced flux towards the hydrogen generation. The lactate production of IAM1183-ΔldhA significantly decreased by 91.42%, while the alcohol yield of IAM1183-Δadh decreased to 30%. The mutant IAM1183-ΔldhA with better hydrogen-producing performance was selected for further investigation in a 5-L fermentor. The hydrogen production of IAM1183-ΔldhA was 2.3 times higher than the wild-type. Further results from the fermentation process showed that the pH decreased to 5.39 levels, then gradually increased to 5.96, indicating that some acidic metabolites might be degraded or uptaken by cells. Copyright © 2015 Elsevier Ltd. All rights reserved.

  16. The plasticity of cyanobacterial carbon metabolism

    DOE PAGES

    Xiong, Wei; Cano, Melissa; Wang, Bo; ...

    2017-09-29

    This opinion article aims to raise awareness of a fundamental issue which governs sustainable production of biofuels and bio-chemicals from photosynthetic cyanobacteria. Discussed is the plasticity of carbon metabolism, by which the cyanobacterial cells flexibly distribute intracellular carbon fluxes towards target products and adapt to environmental/genetic alterations. This intrinsic feature in cyanobacterial metabolism is being understood through recent identification of new biochemical reactions and engineering on low-throughput pathways. We focus our discussion on new insights into the nature of metabolic plasticity in cyanobacteria and its impact on hydrocarbons (e.g. ethylene and isoprene) production. Here, we discuss approaches that need tomore » be developed to rationally rewire photosynthetic carbon fluxes throughout primary metabolism. We also outline open questions about the regulatory mechanisms of the metabolic network that remain to be answered, which might shed light on photosynthetic carbon metabolism and help optimize design principles in order to improve the production of fuels and chemicals in cyanobacteria.« less

  17. The plasticity of cyanobacterial carbon metabolism

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Xiong, Wei; Cano, Melissa; Wang, Bo

    This opinion article aims to raise awareness of a fundamental issue which governs sustainable production of biofuels and bio-chemicals from photosynthetic cyanobacteria. Discussed is the plasticity of carbon metabolism, by which the cyanobacterial cells flexibly distribute intracellular carbon fluxes towards target products and adapt to environmental/genetic alterations. This intrinsic feature in cyanobacterial metabolism is being understood through recent identification of new biochemical reactions and engineering on low-throughput pathways. We focus our discussion on new insights into the nature of metabolic plasticity in cyanobacteria and its impact on hydrocarbons (e.g. ethylene and isoprene) production. Here, we discuss approaches that need tomore » be developed to rationally rewire photosynthetic carbon fluxes throughout primary metabolism. We also outline open questions about the regulatory mechanisms of the metabolic network that remain to be answered, which might shed light on photosynthetic carbon metabolism and help optimize design principles in order to improve the production of fuels and chemicals in cyanobacteria.« less

  18. Thermodynamics-based Metabolite Sensitivity Analysis in metabolic networks.

    PubMed

    Kiparissides, A; Hatzimanikatis, V

    2017-01-01

    The increasing availability of large metabolomics datasets enhances the need for computational methodologies that can organize the data in a way that can lead to the inference of meaningful relationships. Knowledge of the metabolic state of a cell and how it responds to various stimuli and extracellular conditions can offer significant insight in the regulatory functions and how to manipulate them. Constraint based methods, such as Flux Balance Analysis (FBA) and Thermodynamics-based flux analysis (TFA), are commonly used to estimate the flow of metabolites through genome-wide metabolic networks, making it possible to identify the ranges of flux values that are consistent with the studied physiological and thermodynamic conditions. However, unless key intracellular fluxes and metabolite concentrations are known, constraint-based models lead to underdetermined problem formulations. This lack of information propagates as uncertainty in the estimation of fluxes and basic reaction properties such as the determination of reaction directionalities. Therefore, knowledge of which metabolites, if measured, would contribute the most to reducing this uncertainty can significantly improve our ability to define the internal state of the cell. In the present work we combine constraint based modeling, Design of Experiments (DoE) and Global Sensitivity Analysis (GSA) into the Thermodynamics-based Metabolite Sensitivity Analysis (TMSA) method. TMSA ranks metabolites comprising a metabolic network based on their ability to constrain the gamut of possible solutions to a limited, thermodynamically consistent set of internal states. TMSA is modular and can be applied to a single reaction, a metabolic pathway or an entire metabolic network. This is, to our knowledge, the first attempt to use metabolic modeling in order to provide a significance ranking of metabolites to guide experimental measurements. Copyright © 2016 International Metabolic Engineering Society. Published by Elsevier

  19. Elevated host lipid metabolism revealed by iTRAQ-based quantitative proteomic analysis of cerebrospinal fluid of tuberculous meningitis patients

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Mu, Jun; Institute of Neuroscience and the Collaborative Innovation Center for Brain Science, Chongqing Medical University, Chongqing; Chongqing Key Laboratory of Neurobiology, Chongqing

    Purpose: Tuberculous meningitis (TBM) remains to be one of the most deadly infectious diseases. The pathogen interacts with the host immune system, the process of which is largely unknown. Various cellular processes of Mycobacterium tuberculosis (MTB) centers around lipid metabolism. To determine the lipid metabolism related proteins, a quantitative proteomic study was performed here to identify differential proteins in the cerebrospinal fluid (CSF) obtained from TBM patients (n = 12) and healthy controls (n = 12). Methods: CSF samples were desalted, concentrated, labelled with isobaric tags for relative and absolute quantitation (iTRAQ™), and analyzed by multi-dimensional liquid chromatography-tandem mass spectrometry (LC-MS/MS). Gene ontology andmore » proteomic phenotyping analysis of the differential proteins were conducted using Database for Annotation, Visualization, and Integrated Discovery (DAVID) Bioinformatics Resources. ApoE and ApoB were selected for validation by ELISA. Results: Proteomic phenotyping of the 4 differential proteins was invloved in the lipid metabolism. ELISA showed significantly increased ApoB levels in TBM subjects compared to healthy controls. Area under the receiver operating characteristic curve analysis demonstrated ApoB levels could distinguish TBM subjects from healthy controls and viral meningitis subjects with 89.3% sensitivity and 92% specificity. Conclusions: CSF lipid metabolism disregulation, especially elevated expression of ApoB, gives insights into the pathogenesis of TBM. Further evaluation of these findings in larger studies including anti-tuberculosis medicated and unmedicated patient cohorts with other center nervous system infectious diseases is required for successful clinical translation. - Highlights: • The first proteomic study on the cerebrospinal fluid of tuberculous meningitis patients using iTRAQ. • Identify 4 differential proteins invloved in the lipid metabolism. • Elevated expression of Apo

  20. Application of dynamic flux balance analysis to an industrial Escherichia coli fermentation.

    PubMed

    Meadows, Adam L; Karnik, Rahi; Lam, Harry; Forestell, Sean; Snedecor, Brad

    2010-03-01

    We have developed a reactor-scale model of Escherichia coli metabolism and growth in a 1000 L process for the production of a recombinant therapeutic protein. The model consists of two distinct parts: (1) a dynamic, process specific portion that describes the time evolution of 37 process variables of relevance and (2) a flux balance based, 123-reaction metabolic model of E. coli metabolism. This model combines several previously reported modeling approaches including a growth rate-dependent biomass composition, maximum growth rate objective function, and dynamic flux balancing. In addition, we introduce concentration-dependent boundary conditions of transport fluxes, dynamic maintenance demands, and a state-dependent cellular objective. This formulation was able to describe specific runs with high-fidelity over process conditions including rich media, simultaneous acetate and glucose consumption, glucose minimal media, and phosphate depleted media. Furthermore, the model accurately describes the effect of process perturbations--such as glucose overbatching and insufficient aeration--on growth, metabolism, and titer. (c) 2009 Elsevier Inc. All rights reserved.

  1. Obesity, metabolic syndrome and adipocytes

    USDA-ARS?s Scientific Manuscript database

    Obesity and metabolic syndrome are examples whereby excess energy consumption and energy flux disruptions are causative agents of increased fatness. Because other, as yet elucidated, cellular factors may be involved and because potential treatments of these metabolic problems involve systemic agents...

  2. Complete Proteomic-Based Enzyme Reaction and Inhibition Kinetics Reveal How Monolignol Biosynthetic Enzyme Families Affect Metabolic Flux and Lignin in Populus trichocarpa[W

    PubMed Central

    Wang, Jack P.; Naik, Punith P.; Chen, Hsi-Chuan; Shi, Rui; Lin, Chien-Yuan; Liu, Jie; Shuford, Christopher M.; Li, Quanzi; Sun, Ying-Hsuan; Tunlaya-Anukit, Sermsawat; Williams, Cranos M.; Muddiman, David C.; Ducoste, Joel J.; Sederoff, Ronald R.; Chiang, Vincent L.

    2014-01-01

    We established a predictive kinetic metabolic-flux model for the 21 enzymes and 24 metabolites of the monolignol biosynthetic pathway using Populus trichocarpa secondary differentiating xylem. To establish this model, a comprehensive study was performed to obtain the reaction and inhibition kinetic parameters of all 21 enzymes based on functional recombinant proteins. A total of 104 Michaelis-Menten kinetic parameters and 85 inhibition kinetic parameters were derived from these enzymes. Through mass spectrometry, we obtained the absolute quantities of all 21 pathway enzymes in the secondary differentiating xylem. This extensive experimental data set, generated from a single tissue specialized in wood formation, was used to construct the predictive kinetic metabolic-flux model to provide a comprehensive mathematical description of the monolignol biosynthetic pathway. The model was validated using experimental data from transgenic P. trichocarpa plants. The model predicts how pathway enzymes affect lignin content and composition, explains a long-standing paradox regarding the regulation of monolignol subunit ratios in lignin, and reveals novel mechanisms involved in the regulation of lignin biosynthesis. This model provides an explanation of the effects of genetic and transgenic perturbations of the monolignol biosynthetic pathway in flowering plants. PMID:24619611

  3. Attractor Metabolic Networks

    PubMed Central

    De la Fuente, Ildefonso M.; Cortes, Jesus M.; Pelta, David A.; Veguillas, Juan

    2013-01-01

    Background The experimental observations and numerical studies with dissipative metabolic networks have shown that cellular enzymatic activity self-organizes spontaneously leading to the emergence of a Systemic Metabolic Structure in the cell, characterized by a set of different enzymatic reactions always locked into active states (metabolic core) while the rest of the catalytic processes are only intermittently active. This global metabolic structure was verified for Escherichia coli, Helicobacter pylori and Saccharomyces cerevisiae, and it seems to be a common key feature to all cellular organisms. In concordance with these observations, the cell can be considered a complex metabolic network which mainly integrates a large ensemble of self-organized multienzymatic complexes interconnected by substrate fluxes and regulatory signals, where multiple autonomous oscillatory and quasi-stationary catalytic patterns simultaneously emerge. The network adjusts the internal metabolic activities to the external change by means of flux plasticity and structural plasticity. Methodology/Principal Findings In order to research the systemic mechanisms involved in the regulation of the cellular enzymatic activity we have studied different catalytic activities of a dissipative metabolic network under different external stimuli. The emergent biochemical data have been analysed using statistical mechanic tools, studying some macroscopic properties such as the global information and the energy of the system. We have also obtained an equivalent Hopfield network using a Boltzmann machine. Our main result shows that the dissipative metabolic network can behave as an attractor metabolic network. Conclusions/Significance We have found that the systemic enzymatic activities are governed by attractors with capacity to store functional metabolic patterns which can be correctly recovered from specific input stimuli. The network attractors regulate the catalytic patterns, modify the efficiency

  4. Systematic Construction of Kinetic Models from Genome-Scale Metabolic Networks

    PubMed Central

    Smallbone, Kieran; Klipp, Edda; Mendes, Pedro; Liebermeister, Wolfram

    2013-01-01

    The quantitative effects of environmental and genetic perturbations on metabolism can be studied in silico using kinetic models. We present a strategy for large-scale model construction based on a logical layering of data such as reaction fluxes, metabolite concentrations, and kinetic constants. The resulting models contain realistic standard rate laws and plausible parameters, adhere to the laws of thermodynamics, and reproduce a predefined steady state. These features have not been simultaneously achieved by previous workflows. We demonstrate the advantages and limitations of the workflow by translating the yeast consensus metabolic network into a kinetic model. Despite crudely selected data, the model shows realistic control behaviour, a stable dynamic, and realistic response to perturbations in extracellular glucose concentrations. The paper concludes by outlining how new data can continuously be fed into the workflow and how iterative model building can assist in directing experiments. PMID:24324546

  5. On-line metabolic pathway analysis based on metabolic signal flow diagram.

    PubMed

    Shi, H; Shimizu, K

    In this work, an integrated modeling approach based on a metabolic signal flow diagram and cellular energetics was used to model the metabolic pathway analysis for the cultivation of yeast on glucose. This approach enables us to make a clear analysis of the flow direction of the carbon fluxes in the metabolic pathways as well as of the degree of activation of a particular pathway for the synthesis of biomaterials for cell growth. The analyses demonstrate that the main metabolic pathways of Saccharomyces cerevisiae change significantly during batch culture. Carbon flow direction is toward glycolysis to satisfy the increase of requirement for precursors and energy. The enzymatic activation of TCA cycle seems to always be at normal level, which may result in the overflow of ethanol due to its limited capacity. The advantage of this approach is that it adopts both virtues of the metabolic signal flow diagram and the simple network analysis method, focusing on the investigation of the flow directions of carbon fluxes and the degree of activation of a particular pathway or reaction loop. All of the variables used in the model equations were determined on-line; the information obtained from the calculated metabolic coefficients may result in a better understanding of cell physiology and help to evaluate the state of the cell culture process. Copyright 1998 John Wiley & Sons, Inc.

  6. Metabolic regulation and maximal reaction optimization in the central metabolism of a yeast cell

    NASA Astrophysics Data System (ADS)

    Kasbawati, Gunawan, A. Y.; Hertadi, R.; Sidarto, K. A.

    2015-03-01

    Regulation of fluxes in a metabolic system aims to enhance the production rates of biotechnologically important compounds. Regulation is held via modification the cellular activities of a metabolic system. In this study, we present a metabolic analysis of ethanol fermentation process of a yeast cell in terms of continuous culture scheme. The metabolic regulation is based on the kinetic formulation in combination with metabolic control analysis to indicate the key enzymes which can be modified to enhance ethanol production. The model is used to calculate the intracellular fluxes in the central metabolism of the yeast cell. Optimal control is then applied to the kinetic model to find the optimal regulation for the fermentation system. The sensitivity results show that there are external and internal control parameters which are adjusted in enhancing ethanol production. As an external control parameter, glucose supply should be chosen in appropriate way such that the optimal ethanol production can be achieved. For the internal control parameter, we find three enzymes as regulation targets namely acetaldehyde dehydrogenase, pyruvate decarboxylase, and alcohol dehydrogenase which reside in the acetaldehyde branch. Among the three enzymes, however, only acetaldehyde dehydrogenase has a significant effect to obtain optimal ethanol production efficiently.

  7. Pyruvate modifies metabolic flux and nutrient sensing during extracorporeal membrane oxygenation in an immature swine model

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Ledee, Dolena R.; Kajimoto, Masaki; O'Kelly-Priddy, Colleen M.

    Extracorporeal membrane oxygenation (ECMO) provides mechanical circulatory support for infants and children with postoperative cardiopulmonary failure. Nutritional support is mandatory during ECMO, although specific actions for substrates on the heart have not been delineated. Prior work shows that enhancing pyruvate oxidation promotes successful weaning from ECMO. Accordingly, we closely examined the role of prolonged systemic pyruvate supplementation in modifying metabolic parameters during the unique conditions of ventricular unloading provided by ECMO. Twelve male mixed breed Yorkshire piglets (age 30-49 days) received systemic infusion of either normal saline (Group C) or pyruvate (Group P) during ECMO for 8 hours. Over themore » final hour piglets received [2-13C] pyruvate, and [13C6]-L-leucine, as an indicator for oxidation and protein synthesis. A significant increase in lactate and pyruvate concentrations occurred, along with an increase in the absolute concentration of all measured CAC intermediates. Group P showed greater anaplerotic flux through pyruvate carboxylation although pyruvate oxidation relative to citrate synthase flux was similar to Group C. The groups demonstrated similar leucine fractional contributions to acetyl-CoA and fractional protein synthesis rates. Pyruvate also promoted an increase in the phosphorylation state of several nutrient sensitive enzymes, such as AMPK and ACC, and promoted O-GlcNAcylation through the hexosamine biosynthetic pathway (HBP). In conclusion, prolonged pyruvate supplementation during ECMO modified anaplerotic pyruvate flux and elicited changes in important nutrient and energy sensitive pathways, while preserving protein synthesis. Therefore, the observed results support the further study of nutritional supplementation and its downstream effects on cardiac adaptation during ventricular unloading.« less

  8. Metabolic reconstruction and flux analysis of industrial Pichia yeasts.

    PubMed

    Chung, Bevan Kai-Sheng; Lakshmanan, Meiyappan; Klement, Maximilian; Ching, Chi Bun; Lee, Dong-Yup

    2013-03-01

    Pichia yeasts have been recognized as important microbial cell factories in the biotechnological industry. Notably, the Pichia pastoris and Pichia stipitis species have attracted much research interest due to their unique cellular physiology and metabolic capability: P. pastoris has the ability to utilize methanol for cell growth and recombinant protein production, while P. stipitis is capable of assimilating xylose to produce ethanol under oxygen-limited conditions. To harness these characteristics for biotechnological applications, it is highly required to characterize their metabolic behavior. Recently, following the genome sequencing of these two Pichia species, genome-scale metabolic networks have been reconstructed to model the yeasts' metabolism from a systems perspective. To date, there are three genome-scale models available for each of P. pastoris and P. stipitis. In this mini-review, we provide an overview of the models, discuss certain limitations of previous studies, and propose potential future works that can be conducted to better understand and engineer Pichia yeasts for industrial applications.

  9. Translational value of liquid chromatography coupled with tandem mass spectrometry-based quantitative proteomics for in vitro-in vivo extrapolation of drug metabolism and transport and considerations in selecting appropriate techniques.

    PubMed

    Al Feteisi, Hajar; Achour, Brahim; Rostami-Hodjegan, Amin; Barber, Jill

    2015-01-01

    Drug-metabolizing enzymes and transporters play an important role in drug absorption, distribution, metabolism and excretion and, consequently, they influence drug efficacy and toxicity. Quantification of drug-metabolizing enzymes and transporters in various tissues is therefore essential for comprehensive elucidation of drug absorption, distribution, metabolism and excretion. Recent advances in liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) have improved the quantification of pharmacologically relevant proteins. This report presents an overview of mass spectrometry-based methods currently used for the quantification of drug-metabolizing enzymes and drug transporters, mainly focusing on applications and cost associated with various quantitative strategies based on stable isotope-labeled standards (absolute quantification peptide standards, quantification concatemers, protein standards for absolute quantification) and label-free analysis. In mass spectrometry, there is no simple relationship between signal intensity and analyte concentration. Proteomic strategies are therefore complex and several factors need to be considered when selecting the most appropriate method for an intended application, including the number of proteins and samples. Quantitative strategies require appropriate mass spectrometry platforms, yet choice is often limited by the availability of appropriate instrumentation. Quantitative proteomics research requires specialist practical skills and there is a pressing need to dedicate more effort and investment to training personnel in this area. Large-scale multicenter collaborations are also needed to standardize quantitative strategies in order to improve physiologically based pharmacokinetic models.

  10. Computational Platform for Flux Analysis Using 13C-Label Tracing- Phase I SBIR Final Report

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Van Dien, Stephen J.

    Isotopic label tracing is a powerful experimental technique that can be combined with metabolic models to quantify metabolic fluxes in an organism under a particular set of growth conditions. In this work we constructed a genome-scale metabolic model of Methylobacterium extorquens, a facultative methylotroph with potential application in the production of useful chemicals from methanol. A series of labeling experiments were performed using 13C-methanol, and the resulting distribution of labeled carbon in the proteinogenic amino acids was determined by mass spectrometry. Algorithms were developed to analyze this data in context of the metabolic model, yielding flux distributions for wild-type andmore » several engineered strains of M. extorquens. These fluxes were compared to those predicted by model simulation alone, and also integrated with microarray data to give an improved understanding of the metabolic physiology of this organism.« less

  11. Physiologically Based Pharmacokinetic (PBPK) Modeling of Interstrain Variability in Trichloroethylene Metabolism in the Mouse

    PubMed Central

    Campbell, Jerry L.; Clewell, Harvey J.; Zhou, Yi-Hui; Wright, Fred A.; Guyton, Kathryn Z.

    2014-01-01

    Background: Quantitative estimation of toxicokinetic variability in the human population is a persistent challenge in risk assessment of environmental chemicals. Traditionally, interindividual differences in the population are accounted for by default assumptions or, in rare cases, are based on human toxicokinetic data. Objectives: We evaluated the utility of genetically diverse mouse strains for estimating toxicokinetic population variability for risk assessment, using trichloroethylene (TCE) metabolism as a case study. Methods: We used data on oxidative and glutathione conjugation metabolism of TCE in 16 inbred and 1 hybrid mouse strains to calibrate and extend existing physiologically based pharmacokinetic (PBPK) models. We added one-compartment models for glutathione metabolites and a two-compartment model for dichloroacetic acid (DCA). We used a Bayesian population analysis of interstrain variability to quantify variability in TCE metabolism. Results: Concentration–time profiles for TCE metabolism to oxidative and glutathione conjugation metabolites varied across strains. Median predictions for the metabolic flux through oxidation were less variable (5-fold range) than that through glutathione conjugation (10-fold range). For oxidative metabolites, median predictions of trichloroacetic acid production were less variable (2-fold range) than DCA production (5-fold range), although the uncertainty bounds for DCA exceeded the predicted variability. Conclusions: Population PBPK modeling of genetically diverse mouse strains can provide useful quantitative estimates of toxicokinetic population variability. When extrapolated to lower doses more relevant to environmental exposures, mouse population-derived variability estimates for TCE metabolism closely matched population variability estimates previously derived from human toxicokinetic studies with TCE, highlighting the utility of mouse interstrain metabolism studies for addressing toxicokinetic variability

  12. Metabolic dynamics in skeletal muscle during acute reduction in blood flow and oxygen supply to mitochondria: in-silico studies using a multi-scale, top-down integrated model.

    PubMed

    Dash, Ranjan K; Li, Yanjun; Kim, Jaeyeon; Beard, Daniel A; Saidel, Gerald M; Cabrera, Marco E

    2008-09-09

    Control mechanisms of cellular metabolism and energetics in skeletal muscle that may become evident in response to physiological stresses such as reduction in blood flow and oxygen supply to mitochondria can be quantitatively understood using a multi-scale computational model. The analysis of dynamic responses from such a model can provide insights into mechanisms of metabolic regulation that may not be evident from experimental studies. For the purpose, a physiologically-based, multi-scale computational model of skeletal muscle cellular metabolism and energetics was developed to describe dynamic responses of key chemical species and reaction fluxes to muscle ischemia. The model, which incorporates key transport and metabolic processes and subcellular compartmentalization, is based on dynamic mass balances of 30 chemical species in both capillary blood and tissue cells (cytosol and mitochondria) domains. The reaction fluxes in cytosol and mitochondria are expressed in terms of a general phenomenological Michaelis-Menten equation involving the compartmentalized energy controller ratios ATP/ADP and NADH/NAD(+). The unknown transport and reaction parameters in the model are estimated simultaneously by minimizing the differences between available in vivo experimental data on muscle ischemia and corresponding model outputs in coupled with the resting linear flux balance constraints using a robust, nonlinear, constrained-based, reduced gradient optimization algorithm. With the optimal parameter values, the model is able to simulate dynamic responses to reduced blood flow and oxygen supply to mitochondria associated with muscle ischemia of several key metabolite concentrations and metabolic fluxes in the subcellular cytosolic and mitochondrial compartments, some that can be measured and others that can not be measured with the current experimental techniques. The model can be applied to test complex hypotheses involving dynamic regulation of cellular metabolism and

  13. Metabolic profiling of triple-negative breast cancer cells reveals metabolic vulnerabilities.

    PubMed

    Lanning, Nathan J; Castle, Joshua P; Singh, Simar J; Leon, Andre N; Tovar, Elizabeth A; Sanghera, Amandeep; MacKeigan, Jeffrey P; Filipp, Fabian V; Graveel, Carrie R

    2017-01-01

    Among breast cancers, the triple-negative breast cancer (TNBC) subtype has the worst prognosis with no approved targeted therapies and only standard chemotherapy as the backbone of systemic therapy. Unique metabolic changes in cancer progression provide innovative therapeutic opportunities. The receptor tyrosine kinases (RTKs) epidermal growth factor receptor (EGFR), and MET receptor are highly expressed in TNBC, making both promising therapeutic targets. RTK signaling profoundly alters cellular metabolism by increasing glucose consumption and subsequently diverting glucose carbon sources into metabolic pathways necessary to support the tumorigenesis. Therefore, detailed metabolic profiles of TNBC subtypes and their response to tyrosine kinase inhibitors may identify therapeutic sensitivities. We quantified the metabolic profiles of TNBC cell lines representing multiple TNBC subtypes using gas chromatography mass spectrometry. In addition, we subjected MDA-MB-231, MDA-MB-468, Hs578T, and HCC70 cell lines to metabolic flux analysis of basal and maximal glycolytic and mitochondrial oxidative rates. Metabolic pool size and flux measurements were performed in the presence and absence of the MET inhibitor, INC280/capmatinib, and the EGFR inhibitor, erlotinib. Further, the sensitivities of these cells to modulators of core metabolic pathways were determined. In addition, we annotated a rate-limiting metabolic enzymes library and performed a siRNA screen in combination with MET or EGFR inhibitors to validate synergistic effects. TNBC cell line models displayed significant metabolic heterogeneity with respect to basal and maximal metabolic rates and responses to RTK and metabolic pathway inhibitors. Comprehensive systems biology analysis of metabolic perturbations, combined siRNA and tyrosine kinase inhibitor screens identified a core set of TCA cycle and fatty acid pathways whose perturbation sensitizes TNBC cells to small molecule targeting of receptor tyrosine kinases

  14. Comprehensive analysis of a Metabolic Model for lipid production in Rhodosporidium toruloides.

    PubMed

    Castañeda, María Teresita; Nuñez, Sebastián; Garelli, Fabricio; Voget, Claudio; Battista, Hernán De

    2018-05-19

    The yeast Rhodosporidium toruloides has been extensively studied for its application in biolipid production. The knowledge of its metabolism capabilities and the application of constraint-based flux analysis methodology provide useful information for process prediction and optimization. The accuracy of the resulting predictions is highly dependent on metabolic models. A metabolic reconstruction for R. toruloides metabolism has been recently published. On the basis of this model, we developed a curated version that unblocks the central nitrogen metabolism and, in addition, completes charge and mass balances in some reactions neglected in the former model. Then, a comprehensive analysis of network capability was performed with the curated model and compared with the published metabolic reconstruction. The flux distribution obtained by lipid optimization with Flux Balance Analysis was able to replicate the internal biochemical changes that lead to lipogenesis in oleaginous microorganisms. These results motivate the development of a genome-scale model for complete elucidation of R. toruloides metabolism. Copyright © 2018 Elsevier B.V. All rights reserved.

  15. Construction of a Genome-Scale Metabolic Model of Arthrospira platensis NIES-39 and Metabolic Design for Cyanobacterial Bioproduction

    PubMed Central

    Yoshikawa, Katsunori; Aikawa, Shimpei; Kojima, Yuta; Toya, Yoshihiro; Furusawa, Chikara; Kondo, Akihiko; Shimizu, Hiroshi

    2015-01-01

    Arthrospira (Spirulina) platensis is a promising feedstock and host strain for bioproduction because of its high accumulation of glycogen and superior characteristics for industrial production. Metabolic simulation using a genome-scale metabolic model and flux balance analysis is a powerful method that can be used to design metabolic engineering strategies for the improvement of target molecule production. In this study, we constructed a genome-scale metabolic model of A. platensis NIES-39 including 746 metabolic reactions and 673 metabolites, and developed novel strategies to improve the production of valuable metabolites, such as glycogen and ethanol. The simulation results obtained using the metabolic model showed high consistency with experimental results for growth rates under several trophic conditions and growth capabilities on various organic substrates. The metabolic model was further applied to design a metabolic network to improve the autotrophic production of glycogen and ethanol. Decreased flux of reactions related to the TCA cycle and phosphoenolpyruvate reaction were found to improve glycogen production. Furthermore, in silico knockout simulation indicated that deletion of genes related to the respiratory chain, such as NAD(P)H dehydrogenase and cytochrome-c oxidase, could enhance ethanol production by using ammonium as a nitrogen source. PMID:26640947

  16. Flux control exerted by mitochondrial outer membrane carnitine palmitoyltransferase over beta-oxidation, ketogenesis and tricarboxylic acid cycle activity in hepatocytes isolated from rats in different metabolic states.

    PubMed Central

    Drynan, L; Quant, P A; Zammit, V A

    1996-01-01

    The Flux Control Coefficients of mitochondrial outer membrane carnitine palmitoyltransferase (CPT I) with respect to the overall rates of beta-oxidation, ketogenesis and tricarboxylic acid cycle activity were measured in hepatocytes isolated from rats in different metabolic states (fed, 24 h-starved, starved-refed and starved/insulin-treated). These conditions were chosen because there is controversy as to whether, when significant control ceases to be exerted by CPT I over the rate of fatty oxidation [Moir and Zammit (1994) Trends Biochem. Sci. 19, 313-317], this is transferred to one or more steps proximal to acylcarnitine synthesis (e.g. decreased delivery of fatty acids to the liver) or to the reaction catalysed by mitochondrial 3-hydroxy-3-methyl-glutaryl-CoA synthase [Hegardt (1995) Biochem. Soc. Trans. 23, 486-490]. Therefore isolated hepatocytes were used in the present study to exclude the involvement of changes in the rate of delivery of non-esterified fatty acids (NEFA) to the liver, such as occur in vivo, and to ascertain whether, under conditions of constant supply of NEFA, CPT I retains control over the relevant fluxes of fatty acid oxidation to ketones and carbon dioxide, or whether control is transferred to another (intrahepatocytic) site. The results clearly show that the Flux Control Coefficients of CPT I with respect to overall beta-oxidation and ketogenesis are very high under all conditions investigated, indicating that control is not lost to another intrahepatic site during the metabolic transitions studied. The control of CPT I over tricarboxylic acid cycle activity was always very low. The significance of these findings for the integration of fatty acid and carbohydrate metabolism in the liver is discussed. PMID:8760364

  17. Energetic and metabolic transient response of Saccharomyces cerevisiae to benzoic acid.

    PubMed

    Kresnowati, M T A P; van Winden, W A; van Gulik, W M; Heijnen, J J

    2008-11-01

    Saccharomyces cerevisiae is known to be able to adapt to the presence of the commonly used food preservative benzoic acid with a large energy expenditure. Some mechanisms for the adaptation process have been suggested, but its quantitative energetic and metabolic aspects have rarely been discussed. This study discusses use of the stimulus response approach to quantitatively study the energetic and metabolic aspects of the transient adaptation of S. cerevisiae to a shift in benzoic acid concentration, from 0 to 0.8 mM. The information obtained also serves as the basis for further utilization of benzoic acid as a tool for targeted perturbation of the energy system, which is important in studying the kinetics and regulation of central carbon metabolism in S. cerevisiae. Using this experimental set-up, we found significant fast-transient (< 3000 s) increases in O(2) consumption and CO(2) production rates, of approximately 50%, which reflect a high energy requirement for the adaptation process. We also found that with a longer exposure time to benzoic acid, S. cerevisiae decreases the cell membrane permeability for this weak acid by a factor of 10 and decreases the cell size to approximately 80% of the initial value. The intracellular metabolite profile in the new steady-state indicates increases in the glycolytic and tricarboxylic acid cycle fluxes, which are in agreement with the observed increases in specific glucose and O(2) uptake rates.

  18. Combined metabonomic and quantitative real-time PCR analyses reveal systems metabolic changes in Jurkat T-cells treated with HIV-1 Tat protein.

    PubMed

    Liao, Wenting; Tan, Guangguo; Zhu, Zhenyu; Chen, Qiuli; Lou, Ziyang; Dong, Xin; Zhang, Wei; Pan, Wei; Chai, Yifeng

    2012-11-02

    HIV-1 Tat protein is released by infected cells and can affect bystander uninfected T cells and induce numerous biological responses which contribute to its pathogenesis. To elucidate the complex pathogenic mechanism, we conducted a comprehensive investigation on Tat protein-related extracellular and intracellular metabolic changes in Jurkat T-cells using combined gas chromatography-mass spectrometry (GC-MS), reversed-phase liquid chromatography-mass spectrometry (RPLC-MS) and a hydrophilic interaction liquid chromatography-mass spectrometry (HILIC-MS)-based metabonomics approach. Quantitative real-time PCR (qRT-PCR) analyses were further employed to measure expressions of several relevant enzymes together with perturbed metabolic pathways. Combined metabonomic and qRT-PCR analyses revealed that HIV-1 Tat caused significant and comprehensive metabolic changes, as represented by significant changes of 37 metabolites and 10 relevant enzymes in HIV-1 Tat-treated cells. Using MetaboAnalyst 2.0, it was found that 11 pathways (Impact-value >0.10) among the regulated pathways were acutely perturbed, including sphingolipid metabolism, glycine, serine and threonine metabolism, pyruvate metabolism, inositol phosphate metabolism, arginine and proline metabolism, citrate cycle, phenylalanine metabolism, tryptophan metabolism, pentose phosphate pathway, glycerophospholipid metabolism, glycolysis or gluconeogenesis. These results provide metabolic evidence of the complex pathogenic mechanism of HIV-1 Tat protein as a "viral toxin", and would help obligate Tat protein as "an important target" for therapeutic intervention and vaccine development.

  19. Synthetic metabolism: metabolic engineering meets enzyme design.

    PubMed

    Erb, Tobias J; Jones, Patrik R; Bar-Even, Arren

    2017-04-01

    Metabolic engineering aims at modifying the endogenous metabolic network of an organism to harness it for a useful biotechnological task, for example, production of a value-added compound. Several levels of metabolic engineering can be defined and are the topic of this review. Basic 'copy, paste and fine-tuning' approaches are limited to the structure of naturally existing pathways. 'Mix and match' approaches freely recombine the repertoire of existing enzymes to create synthetic metabolic networks that are able to outcompete naturally evolved pathways or redirect flux toward non-natural products. The space of possible metabolic solution can be further increased through approaches including 'new enzyme reactions', which are engineered on the basis of known enzyme mechanisms. Finally, by considering completely 'novel enzyme chemistries' with de novo enzyme design, the limits of nature can be breached to derive the most advanced form of synthetic pathways. We discuss the challenges and promises associated with these different metabolic engineering approaches and illuminate how enzyme engineering is expected to take a prime role in synthetic metabolic engineering for biotechnology, chemical industry and agriculture of the future. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

  20. Metabolic remodeling triggered by salivation and diabetes in major salivary glands.

    PubMed

    Nogueira, Fernando N; Carvalho, Rui A

    2017-02-01

    The metabolic profile of major salivary glands was evaluated by 13 C nuclear magnetic resonance isotopomer analysis ( 13 C NMR-IA) following the infusion of [U- 13 C]glucose in order to define the true metabolic character of submandibular (SM) and parotid (PA) glands at rest and during salivary stimulation, and to determine the metabolic remodeling driven by diabetes. In healthy conditions, the SM gland is characterized at rest by a glycolytic metabolic profile and extensive pyruvate cycling. On the contrary, the PA gland, although also dominated by glycolysis, also possesses significant Krebs' cycle activity and does not sustain extensive pyruvate cycling. Under stimulation, both glands increase their glycolytic and Krebs' cycle fluxes, but the metabolic coupling between the two pathways is further compromised to account for the much increased biosynthetic anaplerotic fluxes. In diabetes, the responsiveness of the PA gland to a salivary stimulus is seriously hindered, mostly as a result of the incapacity to burst glycolytic activity and also an inability to improve the Krebs' cycle flux to compensate. The Krebs' cycle activity in the SM gland is also consistently compromised, but the glycolytic flux in this gland is more resilient. This diabetes-induced metabolic remodeling in SM and PA salivary glands illustrates the metabolic need to sustain adequate saliva production, and identifies glycolytic and oxidative pathways as key players in the metabolic dynamism of salivary glands. Copyright © 2016 John Wiley & Sons, Ltd.

  1. Soil CO2 Flux in the Amargosa Desert, Nevada, during El Nino 1998 and La Nina 1999

    USGS Publications Warehouse

    Riggs, Alan C.; Stannard, David I.; Maestas, Florentino B.; Karlinger, Michael R.; Striegl, Robert G.

    2009-01-01

    Mean annual soil CO2 fluxes from normally bare mineral soil in the Amargosa Desert in southern Nevada, United States, measured with clear and opaque soil CO2-flux chambers (autochambers) were small - <5 millimoles per square meter per day - during both El Nino 1998 and La Nina 1999. The 1998 opaque-chamber flux exceeded 1999 opaque-chamber flux by an order of magnitude, whereas the 1998 clear-chamber flux exceeded 1999 clear-chamber flux by less than a factor of two. These data suggest that above-normal soil moisture stimulated increased metabolic activity, but that much of the extra CO2 produced was recaptured by plants. Fluxes from warm moist soil were the largest sustained fluxes measured, and their hourly pattern is consistent with enhanced soil metabolic activity at some depth in the soil and photosynthetic uptake of a substantial portion of the CO2 released. Flux from cool moist soil was smaller than flux from warm moist soil. Flux from hot dry soil was intermediate between warm-moist and cool-moist fluxes, and clear-chamber flux was more than double the opaque-chamber flux, apparently due to a chamber artifact stemming from a thermally controlled CO2 reservoir near the soil surface. There was no demonstrable metabolic contribution to the very small flux from cool dry soil, which was dominated by diffusive up-flux of CO2 from the water table and temperature-controlled CO2-reservoir up- and down-fluxes. These flux patterns suggest that transfer of CO2 across the land surface is a complex process that is difficult to accurately measure.

  2. Metabolic Flux and Fitness

    PubMed Central

    Dykhuizen, Daniel E.; Dean, Antony M.; Hartl, Daniel L.

    1987-01-01

    Studies of Escherichia coli under competition for lactose in chemostat cultures have been used to determine the selective effects of variation in the level of the β-galactoside permease and the β-galactosidase enzyme. The results determine the adaptive topography of these gene products relative to growth in limiting lactose and enable predictions concerning the selective effects of genetic variants found in natural populations. In the terms of metabolic control theory, the β-galactosidase enzyme at wild-type-induced levels has a small control coefficient with respect to fitness (C = 0.018), and hence genetic variants resulting in minor changes in enzyme activity have disproportionately small effects on fitness. However, the apparent control coefficient of the β-galactoside permease at wild-type-induced levels is large (C = 0.551), and hence even minor changes in activity affect fitness. Therefore, we predict that genetic polymorphisms in the lacZ gene are subject to less effective selection in natural populations than are those in the lacY gene. The β-galactoside permease is also less efficient than might be expected, and possible forces resulting in selection for an intermediate optimum level of permease activity are considered. The selective forces that maintain the lactose operon in a regulated state in natural populations are also discussed. PMID:3104135

  3. Pathway Thermodynamics Highlights Kinetic Obstacles in Central Metabolism

    PubMed Central

    Flamholz, Avi; Reznik, Ed; Liebermeister, Wolfram; Milo, Ron

    2014-01-01

    In metabolism research, thermodynamics is usually used to determine the directionality of a reaction or the feasibility of a pathway. However, the relationship between thermodynamic potentials and fluxes is not limited to questions of directionality: thermodynamics also affects the kinetics of reactions through the flux-force relationship, which states that the logarithm of the ratio between the forward and reverse fluxes is directly proportional to the change in Gibbs energy due to a reaction (ΔrG′). Accordingly, if an enzyme catalyzes a reaction with a ΔrG′ of -5.7 kJ/mol then the forward flux will be roughly ten times the reverse flux. As ΔrG′ approaches equilibrium (ΔrG′ = 0 kJ/mol), exponentially more enzyme counterproductively catalyzes the reverse reaction, reducing the net rate at which the reaction proceeds. Thus, the enzyme level required to achieve a given flux increases dramatically near equilibrium. Here, we develop a framework for quantifying the degree to which pathways suffer these thermodynamic limitations on flux. For each pathway, we calculate a single thermodynamically-derived metric (the Max-min Driving Force, MDF), which enables objective ranking of pathways by the degree to which their flux is constrained by low thermodynamic driving force. Our framework accounts for the effect of pH, ionic strength and metabolite concentration ranges and allows us to quantify how alterations to the pathway structure affect the pathway's thermodynamics. Applying this methodology to pathways of central metabolism sheds light on some of their features, including metabolic bypasses (e.g., fermentation pathways bypassing substrate-level phosphorylation), substrate channeling (e.g., of oxaloacetate from malate dehydrogenase to citrate synthase), and use of alternative cofactors (e.g., quinone as an electron acceptor instead of NAD). The methods presented here place another arrow in metabolic engineers' quiver, providing a simple means of evaluating

  4. Quantitative HRMAS proton total correlation spectroscopy applied to cultured melanoma cells treated by chloroethyl nitrosourea: demonstration of phospholipid metabolism alterations.

    PubMed

    Morvan, Daniel; Demidem, Aicha; Papon, Janine; Madelmont, Jean Claude

    2003-02-01

    Recent NMR spectroscopy developments, such as high-resolution magic angle spinning (HRMAS) probes and correlation-enhanced 2D sequences, now allow improved investigations of phospholipid (Plp) metabolism. Using these modalities we previously demonstrated that a mouse-bearing melanoma tumor responded to chloroethyl nitrosourea (CENU) treatment in vivo by altering its Plp metabolism. The aims of the present study were to investigate whether HRMAS proton total correlation spectroscopy (TOCSY) could be used as a quantitative technique to probe Plp metabolism, and to determine the Plp metabolism response of cultured B16 melanoma cells to CENU treatment in vitro. The exploited TOCSY signals of Plp derivatives arose from scalar coupling among the protons of neighbor methylene groups within base headgroups (choline and ethanolamine). For strongly expressed Plp derivatives, TOCSY signals were compared to saturation recovery signals and demonstrated a linear relationship. HRMAS proton TOCSY was thus used to provide concentrations of Plp derivatives during long-term follow-up of CENU-treated cell cultures. Strong Plp metabolism alteration was observed in treated cultured cells in vitro involving a down-regulation of phosphocholine, and a dramatic and irreversible increase of phosphoethanolamine. These findings are discussed in relation to previous in vivo data, and to Plp metabolism enzymatic involvement. Copyright 2003 Wiley-Liss, Inc.

  5. Modeling Central Carbon Metabolic Processes in Soil Microbial Communities: Comparing Measured With Modeled

    NASA Astrophysics Data System (ADS)

    Dijkstra, P.; Fairbanks, D.; Miller, E.; Salpas, E.; Hagerty, S.

    2013-12-01

    Understanding the mechanisms regulating C cycling is hindered by our inability to directly observe and measure the biochemical processes of glycolysis, pentose phosphate pathway, and TCA cycle in intact and complex microbial communities. Position-specific 13C labeled metabolic tracer probing is proposed as a new way to study microbial community energy production, biosynthesis, C use efficiency (the proportion of substrate incorporated into microbial biomass), and enables the quantification of C fluxes through the central C metabolic network processes (Dijkstra et al 2011a,b). We determined the 13CO2 production from U-13C, 1-13C, 2-13C, 3-13C, 4-13C, 5-13C, and 6-13C labeled glucose and 1-13C and 2,3-13C pyruvate in parallel incubations in three soils along an elevation gradient. Qualitative and quantitative interpretation of the results indicate a high pentose phosphate pathway activity in soils. Agreement between modeled and measured CO2 production rates for the six C-atoms of 13C-labeled glucose indicate that the metabolic model used is appropriate for soil community processes, but that improvements can be made. These labeling and modeling techniques may improve our ability to analyze the biochemistry and (eco)physiology of intact microbial communities. Dijkstra, P., Blankinship, J.C., Selmants, P.C., Hart, S.C., Koch, G.W., Schwartz, E., Hungate, B.A., 2011a. Probing C flux patterns of soil microbial metabolic networks using parallel position-specific tracer labeling. Soil Biology & Biochemistry 43, 126-132. Dijkstra, P., Dalder, J.J., Selmants, P.C., Hart, S.C., Koch, G.W., Schwartz, E., Hungate, B.A., 2011b. Modeling soil metabolic processes using isotopologue pairs of position-specific 13C-labeled glucose and pyruvate. Soil Biology & Biochemistry 43, 1848-1857.

  6. Kruppel-like factor 15 regulates skeletal muscle lipid flux and exercise adaptation

    PubMed Central

    Haldar, Saptarsi M.; Jeyaraj, Darwin; Anand, Priti; Zhu, Han; Lu, Yuan; Prosdocimo, Domenick A.; Eapen, Betty; Kawanami, Daiji; Okutsu, Mitsuharu; Brotto, Leticia; Fujioka, Hisashi; Kerner, Janos; Rosca, Mariana G.; McGuinness, Owen P.; Snow, Rod J.; Russell, Aaron P.; Gerber, Anthony N.; Bai, Xiaodong; Yan, Zhen; Nosek, Thomas M.; Brotto, Marco; Hoppel, Charles L.; Jain, Mukesh K.

    2012-01-01

    The ability of skeletal muscle to enhance lipid utilization during exercise is a form of metabolic plasticity essential for survival. Conversely, metabolic inflexibility in muscle can cause organ dysfunction and disease. Although the transcription factor Kruppel-like factor 15 (KLF15) is an important regulator of glucose and amino acid metabolism, its endogenous role in lipid homeostasis and muscle physiology is unknown. Here we demonstrate that KLF15 is essential for skeletal muscle lipid utilization and physiologic performance. KLF15 directly regulates a broad transcriptional program spanning all major segments of the lipid-flux pathway in muscle. Consequently, Klf15-deficient mice have abnormal lipid and energy flux, excessive reliance on carbohydrate fuels, exaggerated muscle fatigue, and impaired endurance exercise capacity. Elucidation of this heretofore unrecognized role for KLF15 now implicates this factor as a central component of the transcriptional circuitry that coordinates physiologic flux of all three basic cellular nutrients: glucose, amino acids, and lipids. PMID:22493257

  7. Glucose metabolism in different regions of the rat brain under hypokinetic stress influence

    NASA Technical Reports Server (NTRS)

    Konitzer, K.; Voigt, S.

    1980-01-01

    Glucose metabolism in rats kept under long term hypokinetic stress was studied in 7 brain regions. Determination was made of the regional levels of glucose, lactate, glutamate, glutamine, aspartate, gamma-aminobutyrate and the incorporation of C-14 from plasma glucose into these metabolites, in glycogen and protein. From the content and activity data the regional glucose flux was approximated quantitatively. Under normal conditions the activity gradient cortex and frontal pole cerebellum, thalamus and mesencephalon, hypothalamus and pons and medulla is identical with that of the regional blood supply (measured with I131 serum albumin as the blood marker). Within the first days of immobilization a functional hypoxia occurred in all brain regions and the utilization of cycle amino acids for protein synthesis was strongly diminished. After the first week of stress the capillary volumes of all regions increased, aerobic glucose metabolism was enhanced (factors 1.3 - 2.0) and the incorporation of glucose C-14 via cycle amino acids into protein was considerably potentiated. The metabolic parameters normalized between the 7th and 11th week of stress. Blood supply and metabolic rate increased most in the hypothalamus.

  8. Application of isotope labeling experiments and (13)C flux analysis to enable rational pathway engineering.

    PubMed

    McAtee, Allison G; Jazmin, Lara J; Young, Jamey D

    2015-12-01

    Isotope labeling experiments (ILEs) and (13)C flux analysis provide actionable information for metabolic engineers to identify knockout, overexpression, and/or media optimization targets. ILEs have been used in both academic and industrial labs to increase product formation, discover novel metabolic functions in previously uncharacterized organisms, and enhance the metabolic efficiency of host cell factories. This review highlights specific examples of how ILEs have been used in conjunction with enzyme or metabolic engineering to elucidate host cell metabolism and improve product titer, rate, or yield in a directed manner. We discuss recent progress and future opportunities involving the use of ILEs and (13)C flux analysis to characterize non-model host organisms and to identify and subsequently eliminate wasteful byproduct pathways or metabolic bottlenecks. Copyright © 2015 Elsevier Ltd. All rights reserved.

  9. The importance of alcohol dehydrogenase in regulation of ethanol metabolism in rat liver cells.

    PubMed Central

    Page, R A; Kitson, K E; Hardman, M J

    1991-01-01

    We used titration with the inhibitors tetramethylene sulphoxide and isobutyramide to assess quantitatively the importance of alcohol dehydrogenase in regulation of ethanol oxidation in rat hepatocytes. In hepatocytes isolated from starved rats the apparent Flux Control Coefficient (calculated assuming a single-substrate irreversible reaction with non-competitive inhibition) of alcohol dehydrogenase is 0.3-0.5. Adjustment of this coefficient to allow for alcohol dehydrogenase being a two-substrate reversible enzyme increases the value by 1.3-1.4-fold. The final value of the Flux Control Coefficient of 0.5-0.7 indicates that alcohol dehydrogenase is a major rate-determining enzyme, but that other factors also have a regulatory role. In hepatocytes from fed rats the Flux Control Coefficient for alcohol dehydrogenase decreases with increasing acetaldehyde concentration. This suggests that, as acetaldehyde concentrations rise, control of the pathway shifts from alcohol dehydrogenase to other enzymes, particularly aldehyde dehydrogenase. There is not a single rate-determining step for the ethanol metabolism pathway and control is shared among several steps. PMID:1898355

  10. Prospects for Quantitative fMRI: Investigating the Effects of Caffeine on Baseline Oxygen Metabolism and the Response to a Visual Stimulus in Humans

    PubMed Central

    Griffeth, Valerie E.M.; Perthen, Joanna E.; Buxton, Richard B.

    2011-01-01

    Functional magnetic resonance imaging (fMRI) provides an indirect reflection of neural activity change in the working brain through detection of blood oxygenation level dependent (BOLD) signal changes. Although widely used to map patterns of brain activation, fMRI has not yet met its potential for clinical and pharmacological studies due to difficulties in quantitatively interpreting the BOLD signal. This difficulty is due to the BOLD response being strongly modulated by two physiological factors in addition to the level of neural activity: the amount of deoxyhemoglobin present in the baseline state and the coupling ratio, n, of evoked changes in blood flow and oxygen metabolism. In this study, we used a quantitative fMRI approach with dual measurement of blood flow and BOLD responses to overcome these limitations and show that these two sources of modulation work in opposite directions following caffeine administration in healthy human subjects. A strong 27% reduction in baseline blood flow and a 22% increase in baseline oxygen metabolism after caffeine consumption led to a decrease in baseline blood oxygenation and was expected to increase the subsequent BOLD response to the visual stimulus. Opposing this, caffeine reduced n through a strong 61% increase in the evoked oxygen metabolism response to the visual stimulus. The combined effect was that BOLD responses pre- and post-caffeine were similar despite large underlying physiological changes, indicating that the magnitude of the BOLD response alone should not be interpreted as a direct measure of underlying neurophysiological changes. Instead, a quantitative methodology based on dual-echo measurement of blood flow and BOLD responses is a promising tool for applying fMRI to disease and drug studies in which both baseline conditions and the coupling of blood flow and oxygen metabolism responses to a stimulus may be altered. PMID:21586328

  11. Metabolite concentrations, fluxes and free energies imply efficient enzyme usage

    DOE PAGES

    Park, Junyoung O.; Rubin, Sara A.; Xu, Yi -Fan; ...

    2016-05-02

    In metabolism, available free energy is limited and must be divided across pathway steps to maintain a negative Δ G throughout. For each reaction, Δ G is log proportional both to a concentration ratio (reaction quotient to equilibrium constant) and to a flux ratio (backward to forward flux). In this paper, we use isotope labeling to measure absolute metabolite concentrations and fluxes in Escherichia coli, yeast and a mammalian cell line. We then integrate this information to obtain a unified set of concentrations and Δ G for each organism. In glycolysis, we find that free energy is partitioned so asmore » to mitigate unproductive backward fluxes associated with Δ G near zero. Across metabolism, we observe that absolute metabolite concentrations and Δ G are substantially conserved and that most substrate (but not inhibitor) concentrations exceed the associated enzyme binding site dissociation constant ( K m or K i). Finally, the observed conservation of metabolite concentrations is consistent with an evolutionary drive to utilize enzymes efficiently given thermodynamic and osmotic constraints.« less

  12. Flux Imbalance Analysis and the Sensitivity of Cellular Growth to Changes in Metabolite Pools

    PubMed Central

    Reznik, Ed; Mehta, Pankaj; Segrè, Daniel

    2013-01-01

    Stoichiometric models of metabolism, such as flux balance analysis (FBA), are classically applied to predicting steady state rates - or fluxes - of metabolic reactions in genome-scale metabolic networks. Here we revisit the central assumption of FBA, i.e. that intracellular metabolites are at steady state, and show that deviations from flux balance (i.e. flux imbalances) are informative of some features of in vivo metabolite concentrations. Mathematically, the sensitivity of FBA to these flux imbalances is captured by a native feature of linear optimization, the dual problem, and its corresponding variables, known as shadow prices. First, using recently published data on chemostat growth of Saccharomyces cerevisae under different nutrient limitations, we show that shadow prices anticorrelate with experimentally measured degrees of growth limitation of intracellular metabolites. We next hypothesize that metabolites which are limiting for growth (and thus have very negative shadow price) cannot vary dramatically in an uncontrolled way, and must respond rapidly to perturbations. Using a collection of published datasets monitoring the time-dependent metabolomic response of Escherichia coli to carbon and nitrogen perturbations, we test this hypothesis and find that metabolites with negative shadow price indeed show lower temporal variation following a perturbation than metabolites with zero shadow price. Finally, we illustrate the broader applicability of flux imbalance analysis to other constraint-based methods. In particular, we explore the biological significance of shadow prices in a constraint-based method for integrating gene expression data with a stoichiometric model. In this case, shadow prices point to metabolites that should rise or drop in concentration in order to increase consistency between flux predictions and gene expression data. In general, these results suggest that the sensitivity of metabolic optima to violations of the steady state constraints

  13. Principles for circadian orchestration of metabolic pathways.

    PubMed

    Thurley, Kevin; Herbst, Christopher; Wesener, Felix; Koller, Barbara; Wallach, Thomas; Maier, Bert; Kramer, Achim; Westermark, Pål O

    2017-02-14

    Circadian rhythms govern multiple aspects of animal metabolism. Transcriptome-, proteome- and metabolome-wide measurements have revealed widespread circadian rhythms in metabolism governed by a cellular genetic oscillator, the circadian core clock. However, it remains unclear if and under which conditions transcriptional rhythms cause rhythms in particular metabolites and metabolic fluxes. Here, we analyzed the circadian orchestration of metabolic pathways by direct measurement of enzyme activities, analysis of transcriptome data, and developing a theoretical method called circadian response analysis. Contrary to a common assumption, we found that pronounced rhythms in metabolic pathways are often favored by separation rather than alignment in the times of peak activity of key enzymes. This property holds true for a set of metabolic pathway motifs (e.g., linear chains and branching points) and also under the conditions of fast kinetics typical for metabolic reactions. By circadian response analysis of pathway motifs, we determined exact timing separation constraints on rhythmic enzyme activities that allow for substantial rhythms in pathway flux and metabolite concentrations. Direct measurements of circadian enzyme activities in mouse skeletal muscle confirmed that such timing separation occurs in vivo.

  14. Principles for circadian orchestration of metabolic pathways

    PubMed Central

    Thurley, Kevin; Herbst, Christopher; Wesener, Felix; Koller, Barbara; Wallach, Thomas; Maier, Bert; Kramer, Achim

    2017-01-01

    Circadian rhythms govern multiple aspects of animal metabolism. Transcriptome-, proteome- and metabolome-wide measurements have revealed widespread circadian rhythms in metabolism governed by a cellular genetic oscillator, the circadian core clock. However, it remains unclear if and under which conditions transcriptional rhythms cause rhythms in particular metabolites and metabolic fluxes. Here, we analyzed the circadian orchestration of metabolic pathways by direct measurement of enzyme activities, analysis of transcriptome data, and developing a theoretical method called circadian response analysis. Contrary to a common assumption, we found that pronounced rhythms in metabolic pathways are often favored by separation rather than alignment in the times of peak activity of key enzymes. This property holds true for a set of metabolic pathway motifs (e.g., linear chains and branching points) and also under the conditions of fast kinetics typical for metabolic reactions. By circadian response analysis of pathway motifs, we determined exact timing separation constraints on rhythmic enzyme activities that allow for substantial rhythms in pathway flux and metabolite concentrations. Direct measurements of circadian enzyme activities in mouse skeletal muscle confirmed that such timing separation occurs in vivo. PMID:28159888

  15. Engineering of metabolic control

    DOEpatents

    Liao, James C.

    2006-10-17

    The invention features a method of producing heterologous molecules in cells under the regulatory control of a metabolite and metabolic flux. The method can enhance the synthesis of heterologous polypeptides and metabolites.

  16. Engineering of metabolic control

    DOEpatents

    Liao, James C.

    2004-03-16

    The invention features a method of producing heterologous molecules in cells under the regulatory control of a metabolite and metabolic flux. The method can enhance the synthesis of heterologous polypeptides and metabolites.

  17. Signaling Pathways Regulating Redox Balance in Cancer Metabolism

    PubMed Central

    De Santis, Maria Chiara; Porporato, Paolo Ettore; Martini, Miriam; Morandi, Andrea

    2018-01-01

    The interplay between rewiring tumor metabolism and oncogenic driver mutations is only beginning to be appreciated. Metabolic deregulation has been described for decades as a bystander effect of genomic aberrations. However, for the biology of malignant cells, metabolic reprogramming is essential to tackle a harsh environment, including nutrient deprivation, reactive oxygen species production, and oxygen withdrawal. Besides the well-investigated glycolytic metabolism, it is emerging that several other metabolic fluxes are relevant for tumorigenesis in supporting redox balance, most notably pentose phosphate pathway, folate, and mitochondrial metabolism. The relationship between metabolic rewiring and mutant genes is still unclear and, therefore, we will discuss how metabolic needs and oncogene mutations influence each other to satisfy cancer cells’ demands. Mutations in oncogenes, i.e., PI3K/AKT/mTOR, RAS pathway, and MYC, and tumor suppressors, i.e., p53 and liver kinase B1, result in metabolic flexibility and may influence response to therapy. Since metabolic rewiring is shaped by oncogenic driver mutations, understanding how specific alterations in signaling pathways affect different metabolic fluxes will be instrumental for the development of novel targeted therapies. In the era of personalized medicine, the combination of driver mutations, metabolite levels, and tissue of origins will pave the way to innovative therapeutic interventions. PMID:29740540

  18. Signaling Pathways Regulating Redox Balance in Cancer Metabolism.

    PubMed

    De Santis, Maria Chiara; Porporato, Paolo Ettore; Martini, Miriam; Morandi, Andrea

    2018-01-01

    The interplay between rewiring tumor metabolism and oncogenic driver mutations is only beginning to be appreciated. Metabolic deregulation has been described for decades as a bystander effect of genomic aberrations. However, for the biology of malignant cells, metabolic reprogramming is essential to tackle a harsh environment, including nutrient deprivation, reactive oxygen species production, and oxygen withdrawal. Besides the well-investigated glycolytic metabolism, it is emerging that several other metabolic fluxes are relevant for tumorigenesis in supporting redox balance, most notably pentose phosphate pathway, folate, and mitochondrial metabolism. The relationship between metabolic rewiring and mutant genes is still unclear and, therefore, we will discuss how metabolic needs and oncogene mutations influence each other to satisfy cancer cells' demands. Mutations in oncogenes, i.e., PI3K/AKT/mTOR, RAS pathway, and MYC, and tumor suppressors, i.e., p53 and liver kinase B1, result in metabolic flexibility and may influence response to therapy. Since metabolic rewiring is shaped by oncogenic driver mutations, understanding how specific alterations in signaling pathways affect different metabolic fluxes will be instrumental for the development of novel targeted therapies. In the era of personalized medicine, the combination of driver mutations, metabolite levels, and tissue of origins will pave the way to innovative therapeutic interventions.

  19. Characterizability of Metabolic Pathway Systems from Time Series Data

    PubMed Central

    Voit, Eberhard O.

    2013-01-01

    Over the past decade, the biomathematical community has devoted substantial effort to the complicated challenge of estimating parameter values for biological systems models. An even more difficult issue is the characterization of functional forms for the processes that govern these systems. Most parameter estimation approaches tacitly assume that these forms are known or can be assumed with some validity. However, this assumption is not always true. The recently proposed method of Dynamic Flux Estimation (DFE) addresses this problem in a genuinely novel fashion for metabolic pathway systems. Specifically, DFE allows the characterization of fluxes within such systems through an analysis of metabolic time series data. Its main drawback is the fact that DFE can only directly be applied if the pathway system contains as many metabolites as unknown fluxes. This situation is unfortunately rare. To overcome this roadblock, earlier work in this field had proposed strategies for augmenting the set of unknown fluxes with independent kinetic information, which however is not always available. Employing Moore-Penrose pseudo-inverse methods of linear algebra, the present article discusses an approach for characterizing fluxes from metabolic time series data that is applicable even if the pathway system is underdetermined and contains more fluxes than metabolites. Intriguingly, this approach is independent of a specific modeling framework and unaffected by noise in the experimental time series data. The results reveal whether any fluxes may be characterized and, if so, which subset is characterizable. They also help with the identification of fluxes that, if they could be determined independently, would allow the application of DFE. PMID:23391489

  20. The Molecular and Metabolic Influence of Long Term Agmatine Consumption*

    PubMed Central

    Nissim, Itzhak; Horyn, Oksana; Daikhin, Yevgeny; Chen, Pan; Li, Changhong; Wehrli, Suzanne L.; Nissim, Ilana; Yudkoff, Marc

    2014-01-01

    Agmatine (AGM), a product of arginine decarboxylation, influences multiple physiologic and metabolic functions. However, the mechanism(s) of action, the impact on whole body gene expression and metabolic pathways, and the potential benefits and risks of long term AGM consumption are still a mystery. Here, we scrutinized the impact of AGM on whole body metabolic profiling and gene expression and assessed a plausible mechanism(s) of AGM action. Studies were performed in rats fed a high fat diet or standard chow. AGM was added to drinking water for 4 or 8 weeks. We used 13C or 15N tracers to assess metabolic reactions and fluxes and real time quantitative PCR to determine gene expression. The results demonstrate that AGM elevated the synthesis and tissue level of cAMP. Subsequently, AGM had a widespread impact on gene expression and metabolic profiling including (a) activation of peroxisomal proliferator-activated receptor-α and its coactivator, PGC1α, and (b) increased expression of peroxisomal proliferator-activated receptor-γ and genes regulating thermogenesis, gluconeogenesis, and carnitine biosynthesis and transport. The changes in gene expression were coupled with improved tissue and systemic levels of carnitine and short chain acylcarnitine, increased β-oxidation but diminished incomplete fatty acid oxidation, decreased fat but increased protein mass, and increased hepatic ureagenesis and gluconeogenesis but decreased glycolysis. These metabolic changes were coupled with reduced weight gain and a curtailment of the hormonal and metabolic derangements associated with high fat diet-induced obesity. The findings suggest that AGM elevated the synthesis and levels of cAMP, thereby mimicking the effects of caloric restriction with respect to metabolic reprogramming. PMID:24523404

  1. Biosignatures in the Context of Low Energy Flux

    NASA Technical Reports Server (NTRS)

    Hoehler, T. M.

    2017-01-01

    Many of the features that are thought of as biosignatures - including the mediation of chemical and physical processes with speed, specificity, and selectivity - result directly or indirectly from life's unique capability to mediate and direct energy flux. As such, it is important to consider the impact that differences in energy flux may have on the quantity and quality of evidence for life. Earth differs from every other body in our solar system in the magnitude of biologically-usable energy flux into a liquid water environment. On a global basis, the capture of light energy into photosynthesis and the flux of chemical energy represented in the products of that photosynthesis (organic material + O2) are about six and four orders of magnitude larger, respectively, than the flux of energy represented in geochemical sources. Our conception of what an inhabited world "looks like" and our intuition about how to search for life are based in this high-energy context. Energy fluxes on worlds beyond Earth may be better approximated by the million-fold smaller flux provided to Earth's biosphere by geochemical sources. As a result, the nature, abundance, and quality of evidence for life that could be expected on an inhabited extraterrestrial world within our solar system may differ profoundly from that found on Earth. Understanding this potential difference in quantitative terms provides important context for the formulation of life detection strategies. The influence of energy flux on biosignatures can be evaluated through reference to the two basic purposes into which life partitions energy flux: (1) Life expends energy to sustain existing biomass in a metabolic steady state (metabolically functional but non-growing). The formal representation of this relationship in the traditional microbiology literature equates biomass directly with energy flux. The direct implication is that worlds having lower energy flux will have correspondingly lower potential to support biomass

  2. 31P-Magnetization Transfer Magnetic Resonance Spectroscopy Measurements of In Vivo Metabolism

    PubMed Central

    Befroy, Douglas E.; Rothman, Douglas L.; Petersen, Kitt Falk; Shulman, Gerald I.

    2012-01-01

    Magnetic resonance spectroscopy offers a broad range of noninvasive analytical methods for investigating metabolism in vivo. Of these, the magnetization-transfer (MT) techniques permit the estimation of the unidirectional fluxes associated with metabolic exchange reactions. Phosphorus (31P) MT measurements can be used to examine the bioenergetic reactions of the creatine-kinase system and the ATP synthesis/hydrolysis cycle. Observations from our group and others suggest that the inorganic phosphate (Pi) → ATP flux in skeletal muscle may be modulated by certain conditions, including aging, insulin resistance, and diabetes, and may reflect inherent alterations in mitochondrial metabolism. However, such effects on the Pi → ATP flux are not universally observed under conditions in which mitochondrial function, assessed by other techniques, is impaired, and recent articles have raised concerns about the absolute magnitude of the measured reaction rates. As the application of 31P-MT techniques becomes more widespread, this article reviews the methodology and outlines our experience with its implementation in a variety of models in vivo. Also discussed are potential limitations of the technique, complementary methods for assessing oxidative metabolism, and whether the Pi → ATP flux is a viable biomarker of metabolic function in vivo. PMID:23093656

  3. Regulation of yeast central metabolism by enzyme phosphorylation

    PubMed Central

    Oliveira, Ana Paula; Ludwig, Christina; Picotti, Paola; Kogadeeva, Maria; Aebersold, Ruedi; Sauer, Uwe

    2012-01-01

    As a frequent post-translational modification, protein phosphorylation regulates many cellular processes. Although several hundred phosphorylation sites have been mapped to metabolic enzymes in Saccharomyces cerevisiae, functionality was demonstrated for few of them. Here, we describe a novel approach to identify in vivo functionality of enzyme phosphorylation by combining flux analysis with proteomics and phosphoproteomics. Focusing on the network of 204 enzymes that constitute the yeast central carbon and amino-acid metabolism, we combined protein and phosphoprotein levels to identify 35 enzymes that change their degree of phosphorylation during growth under five conditions. Correlations between previously determined intracellular fluxes and phosphoprotein abundances provided first functional evidence for five novel phosphoregulated enzymes in this network, adding to nine known phosphoenzymes. For the pyruvate dehydrogenase complex E1 α subunit Pda1 and the newly identified phosphoregulated glycerol-3-phosphate dehydrogenase Gpd1 and phosphofructose-1-kinase complex β subunit Pfk2, we then validated functionality of specific phosphosites through absolute peptide quantification by targeted mass spectrometry, metabolomics and physiological flux analysis in mutants with genetically removed phosphosites. These results demonstrate the role of phosphorylation in controlling the metabolic flux realised by these three enzymes. PMID:23149688

  4. YANA – a software tool for analyzing flux modes, gene-expression and enzyme activities

    PubMed Central

    Schwarz, Roland; Musch, Patrick; von Kamp, Axel; Engels, Bernd; Schirmer, Heiner; Schuster, Stefan; Dandekar, Thomas

    2005-01-01

    Background A number of algorithms for steady state analysis of metabolic networks have been developed over the years. Of these, Elementary Mode Analysis (EMA) has proven especially useful. Despite its low user-friendliness, METATOOL as a reliable high-performance implementation of the algorithm has been the instrument of choice up to now. As reported here, the analysis of metabolic networks has been improved by an editor and analyzer of metabolic flux modes. Analysis routines for expression levels and the most central, well connected metabolites and their metabolic connections are of particular interest. Results YANA features a platform-independent, dedicated toolbox for metabolic networks with a graphical user interface to calculate (integrating METATOOL), edit (including support for the SBML format), visualize, centralize, and compare elementary flux modes. Further, YANA calculates expected flux distributions for a given Elementary Mode (EM) activity pattern and vice versa. Moreover, a dissection algorithm, a centralization algorithm, and an average diameter routine can be used to simplify and analyze complex networks. Proteomics or gene expression data give a rough indication of some individual enzyme activities, whereas the complete flux distribution in the network is often not known. As such data are noisy, YANA features a fast evolutionary algorithm (EA) for the prediction of EM activities with minimum error, including alerts for inconsistent experimental data. We offer the possibility to include further known constraints (e.g. growth constraints) in the EA calculation process. The redox metabolism around glutathione reductase serves as an illustration example. All software and documentation are available for download at . Conclusion A graphical toolbox and an editor for METATOOL as well as a series of additional routines for metabolic network analyses constitute a new user-friendly software for such efforts. PMID:15929789

  5. Cerebral Metabolic Rate of Oxygen (CMRO2 ) Mapping by Combining Quantitative Susceptibility Mapping (QSM) and Quantitative Blood Oxygenation Level-Dependent Imaging (qBOLD).

    PubMed

    Cho, Junghun; Kee, Youngwook; Spincemaille, Pascal; Nguyen, Thanh D; Zhang, Jingwei; Gupta, Ajay; Zhang, Shun; Wang, Yi

    2018-03-07

    To map the cerebral metabolic rate of oxygen (CMRO 2 ) by estimating the oxygen extraction fraction (OEF) from gradient echo imaging (GRE) using phase and magnitude of the GRE data. 3D multi-echo gradient echo imaging and perfusion imaging with arterial spin labeling were performed in 11 healthy subjects. CMRO 2 and OEF maps were reconstructed by joint quantitative susceptibility mapping (QSM) to process GRE phases and quantitative blood oxygen level-dependent (qBOLD) modeling to process GRE magnitudes. Comparisons with QSM and qBOLD alone were performed using ROI analysis, paired t-tests, and Bland-Altman plot. The average CMRO 2 value in cortical gray matter across subjects were 140.4 ± 14.9, 134.1 ± 12.5, and 184.6 ± 17.9 μmol/100 g/min, with corresponding OEFs of 30.9 ± 3.4%, 30.0 ± 1.8%, and 40.9 ± 2.4% for methods based on QSM, qBOLD, and QSM+qBOLD, respectively. QSM+qBOLD provided the highest CMRO 2 contrast between gray and white matter, more uniform OEF than QSM, and less noisy OEF than qBOLD. Quantitative CMRO 2 mapping that fits the entire complex GRE data is feasible by combining QSM analysis of phase and qBOLD analysis of magnitude. © 2018 International Society for Magnetic Resonance in Medicine.

  6. Perspectives for a better understanding of the metabolic integration of photorespiration within a complex plant primary metabolism network

    USDA-ARS?s Scientific Manuscript database

    Photorespiration is an important high flux metabolic pathway that is found in all oxygen-producing photosynthetic organisms. It is often viewed as a closed loop that recycles carbon to fuel the Calvin cycle. However, the photorespiratory cycle is known to interact with several primary metabolic path...

  7. Lipid Metabolic Versatility in Malassezia spp. Yeasts Studied through Metabolic Modeling

    PubMed Central

    Triana, Sergio; de Cock, Hans; Ohm, Robin A.; Danies, Giovanna; Wösten, Han A. B.; Restrepo, Silvia; González Barrios, Andrés F.; Celis, Adriana

    2017-01-01

    Malassezia species are lipophilic and lipid-dependent yeasts belonging to the human and animal microbiota. Typically, they are isolated from regions rich in sebaceous glands. They have been associated with dermatological diseases such as seborrheic dermatitis, pityriasis versicolor, atopic dermatitis, and folliculitis. The genomes of Malassezia globosa, Malassezia sympodialis, and Malassezia pachydermatis lack the genes related to fatty acid synthesis. Here, the lipid-synthesis pathways of these species, as well as of Malassezia furfur, and of an atypical M. furfur variant were reconstructed using genome data and Constraints Based Reconstruction and Analysis. To this end, the genomes of M. furfur CBS 1878 and the atypical M. furfur 4DS were sequenced and annotated. The resulting Enzyme Commission numbers and predicted reactions were similar to the other Malassezia strains despite the differences in their genome size. Proteomic profiling was utilized to validate flux distributions. Flux differences were observed in the production of steroids in M. furfur and in the metabolism of butanoate in M. pachydermatis. The predictions obtained via these metabolic reconstructions also suggested defects in the assimilation of palmitic acid in M. globosa, M. sympodialis, M. pachydermatis, and the atypical variant of M. furfur, but not in M. furfur. These predictions were validated via physiological characterization, showing the predictive power of metabolic network reconstructions to provide new clues about the metabolic versatility of Malassezia. PMID:28959251

  8. Lipid Metabolic Versatility in Malassezia spp. Yeasts Studied through Metabolic Modeling.

    PubMed

    Triana, Sergio; de Cock, Hans; Ohm, Robin A; Danies, Giovanna; Wösten, Han A B; Restrepo, Silvia; González Barrios, Andrés F; Celis, Adriana

    2017-01-01

    Malassezia species are lipophilic and lipid-dependent yeasts belonging to the human and animal microbiota. Typically, they are isolated from regions rich in sebaceous glands. They have been associated with dermatological diseases such as seborrheic dermatitis, pityriasis versicolor, atopic dermatitis, and folliculitis. The genomes of Malassezia globosa , Malassezia sympodialis , and Malassezia pachydermatis lack the genes related to fatty acid synthesis. Here, the lipid-synthesis pathways of these species, as well as of Malassezia furfur , and of an atypical M. furfur variant were reconstructed using genome data and Constraints Based Reconstruction and Analysis. To this end, the genomes of M. furfur CBS 1878 and the atypical M. furfur 4DS were sequenced and annotated. The resulting Enzyme Commission numbers and predicted reactions were similar to the other Malassezia strains despite the differences in their genome size. Proteomic profiling was utilized to validate flux distributions. Flux differences were observed in the production of steroids in M. furfur and in the metabolism of butanoate in M. pachydermatis . The predictions obtained via these metabolic reconstructions also suggested defects in the assimilation of palmitic acid in M. globosa , M. sympodialis , M. pachydermatis , and the atypical variant of M. furfur , but not in M. furfur. These predictions were validated via physiological characterization, showing the predictive power of metabolic network reconstructions to provide new clues about the metabolic versatility of Malassezia .

  9. Quantitative estimation of cholinesterase-specific drug metabolism of carbamate inhibitors provided by the analysis of the area under the inhibition-time curve.

    PubMed

    Zhou, Huimin; Xiao, Qiaoling; Tan, Wen; Zhan, Yiyi; Pistolozzi, Marco

    2017-09-10

    Several molecules containing carbamate groups are metabolized by cholinesterases. This metabolism includes a time-dependent catalytic step which temporary inhibits the enzymes. In this paper we demonstrate that the analysis of the area under the inhibition versus time curve (AUIC) can be used to obtain a quantitative estimation of the amount of carbamate metabolized by the enzyme. (R)-bambuterol monocarbamate and plasma butyrylcholinesterase were used as model carbamate-cholinesterase system. The inhibition of different concentrations of the enzyme was monitored for 5h upon incubation with different concentrations of carbamate and the resulting AUICs were analyzed. The amount of carbamate metabolized could be estimated with <15% accuracy (RE%) and ≤23% precision (RSD%). Since the knowledge of the inhibition kinetics is not required for the analysis, this approach could be used to determine the amount of drug metabolized by cholinesterases in a selected compartment in which the cholinesterase is confined (e.g. in vitro solutions, tissues or body fluids), either in vitro or in vivo. Copyright © 2017 Elsevier B.V. All rights reserved.

  10. Identification and Quantitation of Malonic Acid Biomarkers of In-Born Error Metabolism by Targeted Metabolomics

    NASA Astrophysics Data System (ADS)

    Ambati, Chandra Shekar R.; Yuan, Furong; Abu-Elheiga, Lutfi A.; Zhang, Yiqing; Shetty, Vivekananda

    2017-05-01

    Malonic acid (MA), methylmalonic acid (MMA), and ethylmalonic acid (EMA) metabolites are implicated in various non-cancer disorders that are associated with inborn-error metabolism. In this study, we have slightly modified the published 3-nitrophenylhydrazine (3NPH) derivatization method and applied it to derivatize MA, MMA, and EMA to their hydrazone derivatives, which were amenable for liquid chromatography- mass spectrometry (LC-MS) quantitation. 3NPH was used to derivatize MA, MMA, and EMA, and multiple reaction monitoring (MRM) transitions of the corresponding derivatives were determined by product-ion experiments. Data normalization and absolute quantitation were achieved by using 3NPH derivatized isotopic labeled compounds 13C2-MA, MMA-D3, and EMA-D3. The detection limits were found to be at nanomolar concentrations and a good linearity was achieved from nanomolar to millimolar concentrations. As a proof of concept study, we have investigated the levels of malonic acids in mouse plasma with malonyl-CoA decarboxylase deficiency (MCD-D), and we have successfully applied 3NPH method to identify and quantitate all three malonic acids in wild type (WT) and MCD-D plasma with high accuracy. The results of this method were compared with that of underivatized malonic acid standards experiments that were performed using hydrophilic interaction liquid chromatography (HILIC)-MRM. Compared with HILIC method, 3NPH derivatization strategy was found to be very efficient to identify these molecules as it greatly improved the sensitivity, quantitation accuracy, as well as peak shape and resolution. Furthermore, there was no matrix effect in LC-MS analysis and the derivatized metabolites were found to be very stable for longer time.

  11. Hydrologic flow paths control dissolved organic carbon fluxes and metabolism in an Alpine stream hyporheic zone

    NASA Astrophysics Data System (ADS)

    Battin, Tom J.

    1999-10-01

    The objective of the present paper was to link reach-scale streambed reactive uptake of dissolved organic carbon (DOC) and dissolved oxygen (DO) to subsurface flow paths in an alpine stream (Oberer Seebach (OSB)). The topography adjacent to the stream channel largely determined flow paths, with shallow hillslope groundwater flowing beneath the stream and entering the alluvial groundwater at the opposite bank. As computed from hydrometric data, OSB consistently lost stream water to groundwater with fluxes out of the stream averaging 943 ± 47 and 664 ± 45 L m-2 h-1 at low (Q < 600 L s-1) and high (Q > 600 L s-1) flow, respectively. Hydrometric segregation of streambed fluxes and physicochemical mixing analysis indicated that stream water was the major input component to the streambed with average contributions of 70-80% to the hyporheic zone (i.e., the subsurface zone where shallow groundwater and stream water mix). Surface water was also the major source of DOC with 0.512 ± 0.043 mg C m-2 h-1 to the streambed. The DOC flux from shallow riparian groundwater was lower (0.309 ± 0.071 mg C m-2 h-1) and peaked in autumn with 1.011 mg C m-2 h-1. I computed the relative proportion of downstream discharge through the streambed as the ratio of the downstream length (Ssw) a stream water parcel travels before entering the streambed to the downstream length (Shyp) a streambed water parcel travels before returning to the stream water. The relative streambed DOC retention efficiency, calculated as (input-output)/input of interstitial DOC, correlated with the proportion (Ssw/Shyp) of downstream discharge (r2 = 0.76, p = 0.006). Also, did the streambed metabolism (calculated as DO uptake from mass balance) decrease with low subsurface downstream routing, whereas elevated downstream discharge through the streambed stimulated DO uptake (r2 = 0.69, p = 0.019)? Despite the very short DOC turnover times (˜0.05 days, calculated as mean standing stock/annual input) within the

  12. Dynamic optimization of metabolic networks coupled with gene expression.

    PubMed

    Waldherr, Steffen; Oyarzún, Diego A; Bockmayr, Alexander

    2015-01-21

    The regulation of metabolic activity by tuning enzyme expression levels is crucial to sustain cellular growth in changing environments. Metabolic networks are often studied at steady state using constraint-based models and optimization techniques. However, metabolic adaptations driven by changes in gene expression cannot be analyzed by steady state models, as these do not account for temporal changes in biomass composition. Here we present a dynamic optimization framework that integrates the metabolic network with the dynamics of biomass production and composition. An approximation by a timescale separation leads to a coupled model of quasi-steady state constraints on the metabolic reactions, and differential equations for the substrate concentrations and biomass composition. We propose a dynamic optimization approach to determine reaction fluxes for this model, explicitly taking into account enzyme production costs and enzymatic capacity. In contrast to the established dynamic flux balance analysis, our approach allows predicting dynamic changes in both the metabolic fluxes and the biomass composition during metabolic adaptations. Discretization of the optimization problems leads to a linear program that can be efficiently solved. We applied our algorithm in two case studies: a minimal nutrient uptake network, and an abstraction of core metabolic processes in bacteria. In the minimal model, we show that the optimized uptake rates reproduce the empirical Monod growth for bacterial cultures. For the network of core metabolic processes, the dynamic optimization algorithm predicted commonly observed metabolic adaptations, such as a diauxic switch with a preference ranking for different nutrients, re-utilization of waste products after depletion of the original substrate, and metabolic adaptation to an impending nutrient depletion. These examples illustrate how dynamic adaptations of enzyme expression can be predicted solely from an optimization principle. Copyright

  13. Probing de novo sphingolipid metabolism in mammalian cells utilizing mass spectrometry.

    PubMed

    Snider, Justin M; Snider, Ashley J; Obeid, Lina M; Luberto, Chiara; Hannun, Yusuf A

    2018-06-01

    Sphingolipids constitute a dynamic metabolic network that interconnects several bioactive molecules, including ceramide (Cer), sphingosine (Sph), Sph 1-phosphate, and Cer 1-phosphate. The interconversion of these metabolites is controlled by a cohort of at least 40 enzymes, many of which respond to endogenous or exogenous stimuli. Typical probing of the sphingolipid pathway relies on sphingolipid mass levels or determination of the activity of individual enzymes. Either approach is unable to provide a complete analysis of flux through sphingolipid metabolism, which, given the interconnectivity of the sphingolipid pathway, is critical information to identify nodes of regulation. Here, we present a one-step in situ assay that comprehensively probes the flux through de novo sphingolipid synthesis, post serine palmitoyltransferase, by monitoring the incorporation and metabolism of the 17 carbon dihydrosphingosine precursor with LC/MS. Pulse labeling and analysis of precursor metabolism identified sequential well-defined phases of sphingolipid synthesis, corresponding to the activity of different enzymes in the pathway, further confirmed by the use of specific inhibitors and modulators of sphingolipid metabolism. This work establishes precursor pulse labeling as a practical tool for comprehensively studying metabolic flux through de novo sphingolipid synthesis and complex sphingolipid generation.

  14. Regional Scaling of Airborne Eddy Covariance Flux Observation

    NASA Astrophysics Data System (ADS)

    Sachs, T.; Serafimovich, A.; Metzger, S.; Kohnert, K.; Hartmann, J.

    2014-12-01

    The earth's surface is tightly coupled to the global climate system by the vertical exchange of energy and matter. Thus, to better understand and potentially predict changes to our climate system, it is critical to quantify the surface-atmosphere exchange of heat, water vapor, and greenhouse gases on climate-relevant spatial and temporal scales. Currently, most flux observations consist of ground-based, continuous but local measurements. These provide a good basis for temporal integration, but may not be representative of the larger regional context. This is particularly true for the Arctic, where site selection is additionally bound by logistical constraints, among others. Airborne measurements can overcome this limitation by covering distances of hundreds of kilometers over time periods of a few hours. The Airborne Measurements of Methane Fluxes (AIRMETH) campaigns are designed to quantitatively and spatially explicitly address this issue: The research aircraft POLAR 5 is used to acquire thousands of kilometers of eddy-covariance flux data. During the AIRMETH-2012 and AIRMETH-2013 campaigns we measured the turbulent exchange of energy, methane, and (in 2013) carbon dioxide over the North Slope of Alaska, USA, and the Mackenzie Delta, Canada. Here, we present the potential of environmental response functions (ERFs) for quantitatively linking flux observations to meteorological and biophysical drivers in the flux footprints. We use wavelet transforms of the original high-frequency data to improve spatial discretization of the flux observations. This also enables the quantification of continuous and biophysically relevant land cover properties in the flux footprint of each observation. A machine learning technique is then employed to extract and quantify the functional relationships between flux observations and the meteorological and biophysical drivers. The resulting ERFs are used to extrapolate fluxes over spatio-temporally explicit grids of the study area. The

  15. Characterizability of metabolic pathway systems from time series data.

    PubMed

    Voit, Eberhard O

    2013-12-01

    Over the past decade, the biomathematical community has devoted substantial effort to the complicated challenge of estimating parameter values for biological systems models. An even more difficult issue is the characterization of functional forms for the processes that govern these systems. Most parameter estimation approaches tacitly assume that these forms are known or can be assumed with some validity. However, this assumption is not always true. The recently proposed method of Dynamic Flux Estimation (DFE) addresses this problem in a genuinely novel fashion for metabolic pathway systems. Specifically, DFE allows the characterization of fluxes within such systems through an analysis of metabolic time series data. Its main drawback is the fact that DFE can only directly be applied if the pathway system contains as many metabolites as unknown fluxes. This situation is unfortunately rare. To overcome this roadblock, earlier work in this field had proposed strategies for augmenting the set of unknown fluxes with independent kinetic information, which however is not always available. Employing Moore-Penrose pseudo-inverse methods of linear algebra, the present article discusses an approach for characterizing fluxes from metabolic time series data that is applicable even if the pathway system is underdetermined and contains more fluxes than metabolites. Intriguingly, this approach is independent of a specific modeling framework and unaffected by noise in the experimental time series data. The results reveal whether any fluxes may be characterized and, if so, which subset is characterizable. They also help with the identification of fluxes that, if they could be determined independently, would allow the application of DFE. Copyright © 2013 Elsevier Inc. All rights reserved.

  16. Dynamic modeling of lactic acid fermentation metabolism with Lactococcus lactis.

    PubMed

    Oh, Euhlim; Lu, Mingshou; Park, Changhun; Park, Changhun; Oh, Han Bin; Lee, Sang Yup; Lee, Jinwon

    2011-02-01

    A dynamic model of lactic acid fermentation using Lactococcus lactis was constructed, and a metabolic flux analysis (MFA) and metabolic control analysis (MCA) were performed to reveal an intensive metabolic understanding of lactic acid bacteria (LAB). The parameter estimation was conducted with COPASI software to construct a more accurate metabolic model. The experimental data used in the parameter estimation were obtained from an LC-MS/ MS analysis and time-course simulation study. The MFA results were a reasonable explanation of the experimental data. Through the parameter estimation, the metabolic system of lactic acid bacteria can be thoroughly understood through comparisons with the original parameters. The coefficients derived from the MCA indicated that the reaction rate of L-lactate dehydrogenase was activated by fructose 1,6-bisphosphate and pyruvate, and pyruvate appeared to be a stronger activator of L-lactate dehydrogenase than fructose 1,6-bisphosphate. Additionally, pyruvate acted as an inhibitor to pyruvate kinase and the phosphotransferase system. Glucose 6-phosphate and phosphoenolpyruvate showed activation effects on pyruvate kinase. Hexose transporter was the strongest effector on the flux through L-lactate dehydrogenase. The concentration control coefficient (CCC) showed similar results to the flux control coefficient (FCC).

  17. Quantitative comparisons of type 3 radio burst intensity and fast electron flux at 1 AU

    NASA Technical Reports Server (NTRS)

    Fitzenreiter, R. J.; Evans, L. G.; Lin, R. P.

    1975-01-01

    The flux of fast solar electrons and the intensity of the type 111 radio emission generated by these particles were compared at one AU. Two regimes were found in the generation of type 111 radiation: one where the radio intensity is linearly proportional to the electron flux, and another, which occurs above a threshold electron flux, where the radio intensity is approximately proportional to the 2.4 power of the electron flux. This threshold appears to reflect a transition to a different emission mechanism.

  18. Conventional liquid chromatography/triple quadrupole mass spectrometer-based metabolite identification and semi-quantitative estimation approach in the investigation of dabigatran etexilate in vitro metabolism

    PubMed Central

    Hu, Zhe-Yi; Parker, Robert B.; Herring, Vanessa L.; Laizure, S. Casey

    2012-01-01

    Dabigatran etexilate (DABE) is an oral prodrug that is rapidly converted by esterases to dabigatran (DAB), a direct inhibitor of thrombin. To elucidate the esterase-mediated metabolic pathway of DABE, a high-performance liquid chromatography/mass spectrometer (LC-MS/MS)-based metabolite identification and semi-quantitative estimation approach was developed. To overcome the poor full-scan sensitivity of conventional triple quadrupole mass spectrometry, precursor-product ion pairs were predicted, to search for the potential in vitro metabolites. The detected metabolites were confirmed by the product ion scan. A dilution method was introduced to evaluate the matrix effects of tentatively identified metabolites without chemical standards. Quantitative information on detected metabolites was obtained using ‘metabolite standards’ generated from incubation samples that contain a high concentration of metabolite in combination with a correction factor for mass spectrometry response. Two in vitro metabolites of DABE (M1 and M2) were identified, and quantified by the semi-quantitative estimation approach. It is noteworthy that CES1 convert DABE to M1 while CES2 mediates the conversion of DABE to M2. M1 (or M2) was further metabolized to DAB by CES2 (or CES1). The approach presented here provides a solution to a bioanalytical need for fast identification and semi-quantitative estimation of CES metabolites in preclinical samples. PMID:23239178

  19. Fast growth phenotype of E. coli K-12 from adaptive laboratory evolution does not require intracellular flux rewiring.

    PubMed

    Long, Christopher P; Gonzalez, Jacqueline E; Feist, Adam M; Palsson, Bernhard O; Antoniewicz, Maciek R

    2017-11-01

    Adaptive laboratory evolution (ALE) is a widely-used method for improving the fitness of microorganisms in selected environmental conditions. It has been applied previously to Escherichia coli K-12 MG1655 during aerobic exponential growth on glucose minimal media, a frequently used model organism and growth condition, to probe the limits of E. coli growth rate and gain insights into fast growth phenotypes. Previous studies have described up to 1.6-fold increases in growth rate following ALE, and have identified key causal genetic mutations and changes in transcriptional patterns. Here, we report for the first time intracellular metabolic fluxes for six such adaptively evolved strains, as determined by high-resolution 13 C-metabolic flux analysis. Interestingly, we found that intracellular metabolic pathway usage changed very little following adaptive evolution. Instead, at the level of central carbon metabolism the faster growth was facilitated by proportional increases in glucose uptake and all intracellular rates. Of the six evolved strains studied here, only one strain showed a small degree of flux rewiring, and this was also the strain with unique genetic mutations. A comparison of fluxes with two other wild-type (unevolved) E. coli strains, BW25113 and BL21, showed that inter-strain differences are greater than differences between the parental and evolved strains. Principal component analysis highlighted that nearly all flux differences (95%) between the nine strains were captured by only two principal components. The distance between measured and flux balance analysis predicted fluxes was also investigated. It suggested a relatively wide range of similar stoichiometric optima, which opens new questions about the path-dependency of adaptive evolution. Copyright © 2017 International Metabolic Engineering Society. Published by Elsevier Inc. All rights reserved.

  20. Quantitative comparisons of type III radio burst intensity and fast electron flux at 1 AU

    NASA Technical Reports Server (NTRS)

    Fitzenreiter, R. J.; Evans, L. G.; Lin, R. P.

    1976-01-01

    We compare the flux of fast solar electrons and the intensity of the type III radio emission generated by these particles at 1 AU. We find that there are two regimes in the generation of type III radiation: one where the radio intensity is linearly proportional to the electron flux, and the second regime, which occurs above a threshold electron flux, where the radio intensity is proportional to the approximately 2.4 power of the electron flux. This threshold appears to reflect a transition to a different emission mechanism.

  1. High rates of energy expenditure and water flux in free-ranging Point Reyes mountain beavers Aplodontia rufa phaea

    USGS Publications Warehouse

    Crocker, D.E.; Kofahl, N.; Fellers, G.D.; Gates, N.B.; Houser, D.S.

    2007-01-01

    We measured water flux and energy expenditure in free-ranging Point Reyes mountain beavers Aplodontia rufa phaea by using the doubly labeled water method. Previous laboratory investigations have suggested weak urinary concentrating ability, high rates of water flux, and low basal metabolic rates in this species. However, free-ranging measurements from hygric mammals are rare, and it is not known how these features interact in the environment. Rates of water flux (210 ?? 32 mL d-1) and field metabolic rates (1,488 ?? 486 kJ d-1) were 159% and 265%, respectively, of values predicted by allometric equations for similar-sized herbivores. Mountain beavers can likely meet their water needs through metabolic water production and preformed water in food and thus remain in water balance without access to free water. Arginine-vasopressin levels were strongly correlated with rates of water flux and plasma urea : creatinine ratios, suggesting an important role for this hormone in regulating urinary water loss in mountain beavers. High field metabolic rates may result from cool burrow temperatures that are well below lower critical temperatures measured in previous laboratory studies and suggest that thermoregulation costs may strongly influence field energetics and water flux in semifossorial mammals. ?? 2007 by The University of Chicago. All rights reserved.

  2. Quantitative Trait Loci (QTL)-Guided Metabolic Engineering of a Complex Trait.

    PubMed

    Maurer, Matthew J; Sutardja, Lawrence; Pinel, Dominic; Bauer, Stefan; Muehlbauer, Amanda L; Ames, Tyler D; Skerker, Jeffrey M; Arkin, Adam P

    2017-03-17

    Engineering complex phenotypes for industrial and synthetic biology applications is difficult and often confounds rational design. Bioethanol production from lignocellulosic feedstocks is a complex trait that requires multiple host systems to utilize, detoxify, and metabolize a mixture of sugars and inhibitors present in plant hydrolysates. Here, we demonstrate an integrated approach to discovering and optimizing host factors that impact fitness of Saccharomyces cerevisiae during fermentation of a Miscanthus x giganteus plant hydrolysate. We first used high-resolution Quantitative Trait Loci (QTL) mapping and systematic bulk Reciprocal Hemizygosity Analysis (bRHA) to discover 17 loci that differentiate hydrolysate tolerance between an industrially related (JAY291) and a laboratory (S288C) strain. We then used this data to identify a subset of favorable allelic loci that were most amenable for strain engineering. Guided by this "genetic blueprint", and using a dual-guide Cas9-based method to efficiently perform multikilobase locus replacements, we engineered an S288C-derived strain with superior hydrolysate tolerance than JAY291. Our methods should be generalizable to engineering any complex trait in S. cerevisiae, as well as other organisms.

  3. The Glyoxylate Cycle in an Arbuscular Mycorrhizal Fungus. Carbon Flux and Gene Expression

    PubMed Central

    Lammers, Peter J.; Jun, Jeongwon; Abubaker, Jehad; Arreola, Raul; Gopalan, Anjali; Bago, Berta; Hernandez-Sebastia, Cinta; Allen, James W.; Douds, David D.; Pfeffer, Philip E.; Shachar-Hill, Yair

    2001-01-01

    The arbuscular mycorrhizal (AM) symbiosis is responsible for huge fluxes of photosynthetically fixed carbon from plants to the soil. Lipid, which is the dominant form of stored carbon in the fungal partner and which fuels spore germination, is made by the fungus within the root and is exported to the extraradical mycelium. We tested the hypothesis that the glyoxylate cycle is central to the flow of carbon in the AM symbiosis. The results of 13C labeling of germinating spores and extraradical mycelium with 13C2-acetate and 13C2-glycerol and analysis by nuclear magnetic resonance spectroscopy indicate that there are very substantial fluxes through the glyoxylate cycle in the fungal partner. Full-length sequences obtained by polymerase chain reaction from a cDNA library from germinating spores of the AM fungus Glomus intraradices showed strong homology to gene sequences for isocitrate lyase and malate synthase from plants and other fungal species. Quantitative real-time polymerase chain reaction measurements show that these genes are expressed at significant levels during the symbiosis. Glyoxysome-like bodies were observed by electron microscopy in fungal structures where the glyoxylate cycle is expected to be active, which is consistent with the presence in both enzyme sequences of motifs associated with glyoxysomal targeting. We also identified among several hundred expressed sequence tags several enzymes of primary metabolism whose expression during spore germination is consistent with previous labeling studies and with fluxes into and out of the glyoxylate cycle. PMID:11706207

  4. Pseudomonas putida KT2440 Strain Metabolizes Glucose through a Cycle Formed by Enzymes of the Entner-Doudoroff, Embden-Meyerhof-Parnas, and Pentose Phosphate Pathways.

    PubMed

    Nikel, Pablo I; Chavarría, Max; Fuhrer, Tobias; Sauer, Uwe; de Lorenzo, Víctor

    2015-10-23

    The soil bacterium Pseudomonas putida KT2440 lacks a functional Embden-Meyerhof-Parnas (EMP) pathway, and glycolysis is known to proceed almost exclusively through the Entner-Doudoroff (ED) route. To investigate the raison d'être of this metabolic arrangement, the distribution of periplasmic and cytoplasmic carbon fluxes was studied in glucose cultures of this bacterium by using (13)C-labeled substrates, combined with quantitative physiology experiments, metabolite quantification, and in vitro enzymatic assays under both saturating and non-saturating, quasi in vivo conditions. Metabolic flux analysis demonstrated that 90% of the consumed sugar was converted into gluconate, entering central carbon metabolism as 6-phosphogluconate and further channeled into the ED pathway. Remarkably, about 10% of the triose phosphates were found to be recycled back to form hexose phosphates. This set of reactions merges activities belonging to the ED, the EMP (operating in a gluconeogenic fashion), and the pentose phosphate pathways to form an unforeseen metabolic architecture (EDEMP cycle). Determination of the NADPH balance revealed that the default metabolic state of P. putida KT2440 is characterized by a slight catabolic overproduction of reducing power. Cells growing on glucose thus run a biochemical cycle that favors NADPH formation. Because NADPH is required not only for anabolic functions but also for counteracting different types of environmental stress, such a cyclic operation may contribute to the physiological heftiness of this bacterium in its natural habitats. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

  5. An ancient Chinese wisdom for metabolic engineering: Yin-Yang

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Wu, Stephen G.; He, Lian; Wang, Qingzhao

    In ancient Chinese philosophy, Yin-Yang describes two contrary forces that are interconnected and interdependent. This concept also holds true in microbial cell factories, where Yin represents energy metabolism in the form of ATP, and Yang represents carbon metabolism. Current biotechnology can effectively edit the microbial genome or introduce novel enzymes to redirect carbon fluxes. On the other hand, microbial metabolism loses significant free energy as heat when converting sugar into ATP; while maintenance energy expenditures further aggravate ATP shortage. The limitation of cell “powerhouse” prevents hosts from achieving high carbon yields and rates. Via an Escherichia coli flux balance analysismore » model, we further demonstrate the penalty of ATP cost on biofuel synthesis. To ensure cell powerhouse being sufficient in microbial cell factories, we propose five principles: 1. Take advantage of native pathways for product synthesis. 2. Pursue biosynthesis relying only on pathways or genetic parts without significant ATP burden. 3. Combine microbial production with chemical conversions (semi-biosynthesis) to reduce biosynthesis steps. 4. Create “minimal cells” or use non-model microbial hosts with higher energy fitness. 5. Develop a photosynthesis chassis that can utilize light energy and cheap carbon feedstocks. Meanwhile, metabolic flux analysis can be used to quantify both carbon and energy metabolisms. The fluxomics results are essential to evaluate the industrial potential of laboratory strains, avoiding false starts and dead ends during metabolic engineering« less

  6. An ancient Chinese wisdom for metabolic engineering: Yin-Yang

    DOE PAGES

    Wu, Stephen G.; He, Lian; Wang, Qingzhao; ...

    2015-03-20

    In ancient Chinese philosophy, Yin-Yang describes two contrary forces that are interconnected and interdependent. This concept also holds true in microbial cell factories, where Yin represents energy metabolism in the form of ATP, and Yang represents carbon metabolism. Current biotechnology can effectively edit the microbial genome or introduce novel enzymes to redirect carbon fluxes. On the other hand, microbial metabolism loses significant free energy as heat when converting sugar into ATP; while maintenance energy expenditures further aggravate ATP shortage. The limitation of cell “powerhouse” prevents hosts from achieving high carbon yields and rates. Via an Escherichia coli flux balance analysismore » model, we further demonstrate the penalty of ATP cost on biofuel synthesis. To ensure cell powerhouse being sufficient in microbial cell factories, we propose five principles: 1. Take advantage of native pathways for product synthesis. 2. Pursue biosynthesis relying only on pathways or genetic parts without significant ATP burden. 3. Combine microbial production with chemical conversions (semi-biosynthesis) to reduce biosynthesis steps. 4. Create “minimal cells” or use non-model microbial hosts with higher energy fitness. 5. Develop a photosynthesis chassis that can utilize light energy and cheap carbon feedstocks. Meanwhile, metabolic flux analysis can be used to quantify both carbon and energy metabolisms. The fluxomics results are essential to evaluate the industrial potential of laboratory strains, avoiding false starts and dead ends during metabolic engineering« less

  7. Influence of the late winter bloom on migrant zooplankton metabolism and its implications on export fluxes

    NASA Astrophysics Data System (ADS)

    Putzeys, S.; Yebra, L.; Almeida, C.; Bécognée, P.; Hernández-León, S.

    2011-12-01

    Studies on carbon active fluxes due to diel migrants are scarce and critical for carbon flux models and biogeochemical estimates. We studied the temporal variability and vertical distribution of biomass, indices of feeding and respiration of the zooplanktonic community north off the Canary Islands during the end of the late winter bloom, in order to assess vertical carbon fluxes in this area. Biomass distribution during the day presented two dense layers of organisms at 0-200 m and around 500 m, whereas at night, most of the biomass concentrated in the epipelagic layer. The gut pigment flux (0.05-0.18 mgC·m - 2 ·d - 1 ) represented 0.22% of the estimated passive export flux (POC flux) while potential ingestion represented 3.91% of the POC (1.24-3.40 mgC·m - 2 ·d - 1 ). The active respiratory flux (0.50-1.36 mgC·m - 2 ·d - 1 ) was only 1.57% of the POC flux. The total carbon flux mediated by diel migrants (respiration plus potential ingestion) ranged between 3.37 and 9.22% of the POC flux; which is three-fold higher than calculating ingestion fluxes from gut pigments. Our results suggest that the fluxes by diel migrants play a small role in the downward flux of carbon in the open ocean during the post-bloom period.

  8. Precision metabolic engineering: The design of responsive, selective, and controllable metabolic systems.

    PubMed

    McNerney, Monica P; Watstein, Daniel M; Styczynski, Mark P

    2015-09-01

    Metabolic engineering is generally focused on static optimization of cells to maximize production of a desired product, though recently dynamic metabolic engineering has explored how metabolic programs can be varied over time to improve titer. However, these are not the only types of applications where metabolic engineering could make a significant impact. Here, we discuss a new conceptual framework, termed "precision metabolic engineering," involving the design and engineering of systems that make different products in response to different signals. Rather than focusing on maximizing titer, these types of applications typically have three hallmarks: sensing signals that determine the desired metabolic target, completely directing metabolic flux in response to those signals, and producing sharp responses at specific signal thresholds. In this review, we will first discuss and provide examples of precision metabolic engineering. We will then discuss each of these hallmarks and identify which existing metabolic engineering methods can be applied to accomplish those tasks, as well as some of their shortcomings. Ultimately, precise control of metabolic systems has the potential to enable a host of new metabolic engineering and synthetic biology applications for any problem where flexibility of response to an external signal could be useful. Copyright © 2015 International Metabolic Engineering Society. Published by Elsevier Inc. All rights reserved.

  9. Quantitative mapping of zinc fluxes in the mammalian egg reveals the origin of fertilization-induced zinc sparks

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Que, Emily L.; Bleher, Reiner; Duncan, Francesca E.

    2014-12-15

    Fertilization of a mammalian egg initiates a series of 'zinc sparks' that are necessary to induce the egg-to-embryo transition. Despite the importance of these zinc-efflux events little is known about their origin. To understand the molecular mechanism of the zinc spark we combined four physical approaches that resolve zinc distributions in single cells: a chemical probe for dynamic live-cell fluorescence imaging and a combination of scanning transmission electron microscopy with energy-dispersive spectroscopy, X-ray fluorescence microscopy and three-dimensional elemental tomography for high-resolution elemental mapping. We show that the zinc spark arises from a system of thousands of zinc-loaded vesicles, each ofmore » which contains, on average, 10(6) zinc atoms. These vesicles undergo dynamic movement during oocyte maturation and exocytosis at the time of fertilization. The discovery of these vesicles and the demonstration that zinc sparks originate from them provides a quantitative framework for understanding how zinc fluxes regulate cellular processes« less

  10. Quantitative mapping of zinc fluxes in the mammalian egg reveals the origin of fertilization-induced zinc sparks.

    PubMed

    Que, Emily L; Bleher, Reiner; Duncan, Francesca E; Kong, Betty Y; Gleber, Sophie C; Vogt, Stefan; Chen, Si; Garwin, Seth A; Bayer, Amanda R; Dravid, Vinayak P; Woodruff, Teresa K; O'Halloran, Thomas V

    2015-02-01

    Fertilization of a mammalian egg initiates a series of 'zinc sparks' that are necessary to induce the egg-to-embryo transition. Despite the importance of these zinc-efflux events little is known about their origin. To understand the molecular mechanism of the zinc spark we combined four physical approaches that resolve zinc distributions in single cells: a chemical probe for dynamic live-cell fluorescence imaging and a combination of scanning transmission electron microscopy with energy-dispersive spectroscopy, X-ray fluorescence microscopy and three-dimensional elemental tomography for high-resolution elemental mapping. We show that the zinc spark arises from a system of thousands of zinc-loaded vesicles, each of which contains, on average, 10(6) zinc atoms. These vesicles undergo dynamic movement during oocyte maturation and exocytosis at the time of fertilization. The discovery of these vesicles and the demonstration that zinc sparks originate from them provides a quantitative framework for understanding how zinc fluxes regulate cellular processes.

  11. Quantitative mapping of zinc fluxes in the mammalian egg reveals the origin of fertilization-induced zinc sparks

    DOE PAGES

    Que, Emily L.; Bleher, Reiner; Duncan, Francesca E.; ...

    2014-12-15

    Fertilization of a mammalian egg induces a series of ‘zinc sparks’ that are necessary for inducing the egg-to-embryo transition. Despite the importance of these zinc efflux events little is known about their origin. To understand the molecular mechanism of the zinc spark we combined four physical approaches to resolve zinc distributions in single cells: a chemical probe for dynamic live-cell fluorescence imaging and a combination of scanning transmission electron microscopy with energy dispersive spectroscopy, X-ray fluorescence microscopy, and 3D elemental tomography for high resolution elemental mapping. Here we show that the zinc spark arises from a system of thousands ofmore » zinc-loaded vesicles, each of which contains, on average, 106 zinc atoms. These vesicles undergo dynamic movement during oocyte maturation and exocytosis at the time of fertilization. We conclude that the discovery of these vesicles and the demonstration that zinc sparks originate from them provides a quantitative framework for understanding how zinc fluxes regulate cellular processes.« less

  12. Quantitative mapping of zinc fluxes in the mammalian egg reveals the origin of fertilization-induced zinc sparks

    PubMed Central

    Que, Emily L.; Bleher, Reiner; Duncan, Francesca E.; Kong, Betty Y.; Gleber, Sophie C.; Vogt, Stefan; Chen, Si; Garwin, Seth A.; Bayer, Amanda R.; Dravid, Vinayak; Woodruff, Teresa K.; O’Halloran, Thomas V.

    2015-01-01

    Fertilization of a mammalian egg induces a series of ‘zinc sparks’ that are necessary for inducing the egg-to-embryo transition. Despite the importance of these zinc efflux events little is known about their origin. To understand the molecular mechanism of the zinc spark we combined four physical approaches to resolve zinc distributions in single cells: a chemical probe for dynamic live-cell fluorescence imaging and a combination of scanning transmission electron microscopy with energy dispersive spectroscopy, X-ray fluorescence microscopy, and 3D elemental tomography for high resolution elemental mapping. We show that the zinc spark arises from a system of thousands of zinc-loaded vesicles, each of which contains, on average, 106 zinc atoms. These vesicles undergo dynamic movement during oocyte maturation and exocytosis at the time of fertilization. The discovery of these vesicles and the demonstration that zinc sparks originate from them provides a quantitative framework for understanding how zinc fluxes regulate cellular processes. PMID:25615666

  13. Metabolic analysis of the synthesis of high levels of intracellular human SOD in Saccharomyces cerevisiae rhSOD 2060 411 SGA122.

    PubMed

    Gonzalez, Ramon; Andrews, Barbara A; Molitor, Julia; Asenjo, Juan A

    2003-04-20

    The synthesis of human superoxide dismutase (SOD) in batch cultures of a Saccharomyces cerevisiae strain using a glucose-limited minimal medium was studied through metabolic flux analysis. A stoichiometric model was built, which included 78 reactions, according to metabolic pathways operative in these strains during respirofermentative and oxidative metabolism. It allowed calculation of the distribution of metabolic fluxes during diauxic growth on glucose and ethanol. Fermentation profiles and metabolic fluxes were analyzed at different phases of diauxic growth for the recombinant strain (P+) and for its wild type (P-). The synthesis of SOD by the strain P+ resulted in a decrease in specific growth rate of 34 and 54% (growth on glucose and ethanol respectively) in comparison to the wild type. Both strains exhibited similar flux of glucose consumption and ethanol synthesis but important differences in carbon distribution with biomass/substrate yields and ATP production 50% higher in P-. A higher contribution of fermentative metabolism, with 64% of the energy produced at the phosphorylation level, was observed during SOD production. The flux of precursors to amino acids and nucleotides was higher in the recombinant strain, in agreement with the higher total RNA and protein levels. Lower specific growth rates in strain P+ appear to be related to the decrease in the rate of synthesis of nonrecombinant protein, as well as a decrease in the activities of the pentose phosphate (PP) pathway and TCA cycle. A very different way of entry into the stationary phase was observed for each strain: in the wild-type strain most metabolic fluxes decreased and fluxes related to energy reserve synthesis increased, while in the P+ strain the flux of 22 reactions (including PP pathway and amino acids biosynthesis) related to SOD production increased their fluxes. Changes in SOD production rates at different physiological states appear to be related to the differences in building blocks

  14. Metabolic analysis of adaptive evolution for in silico-designed lactate-producing strains.

    PubMed

    Hua, Qiang; Joyce, Andrew R; Fong, Stephen S; Palsson, Bernhard Ø

    2006-12-05

    Experimental evolution is now frequently applied to many biological systems to achieve desired objectives. To obtain optimized performance for metabolite production, a successful strategy has been recently developed that couples metabolic engineering techniques with laboratory evolution of microorganisms. Previously, we reported the growth characteristics of three lactate-producing, adaptively evolved Escherichia coli mutant strains designed by the OptKnock computational algorithm. Here, we describe the use of (13)C-labeled experiments and mass distribution measurements to study the evolutionary effects on the fluxome of these differently designed strains. Metabolic flux ratios and intracellular flux distributions as well as physiological data were used to elucidate metabolic responses over the course of adaptive evolution and metabolic differences among strains. The study of 3 unevolved and 12 evolved engineered strains as well as a wild-type strain suggests that evolution resulted in remarkable improvements in both substrate utilization rate and the proportion of glycolytic flux to total glucose utilization flux. Among three strain designs, the most significant increases in the fraction of glucose catabolized through glycolysis (>50%) and the glycolytic fluxes (>twofold) were observed in phosphotransacetylase and phosphofructokinase 1 (PFK1) double deletion (pta- pfkA) strains, which were likely attributed to the dramatic evolutionary increase in gene expression and catalytic activity of the minor PFK encoded by pfkB. These fluxomic studies also revealed the important role of acetate synthetic pathway in anaerobic lactate production. Moreover, flux analysis suggested that independent of genetic background, optimal relative flux distributions in cells could be achieved faster than physiological parameters such as nutrient utilization rate. (c) 2006 Wiley Periodicals, Inc.

  15. Network reconstruction of platelet metabolism identifies metabolic signature for aspirin resistance

    NASA Astrophysics Data System (ADS)

    Thomas, Alex; Rahmanian, Sorena; Bordbar, Aarash; Palsson, Bernhard Ø.; Jamshidi, Neema

    2014-01-01

    Recently there has not been a systematic, objective assessment of the metabolic capabilities of the human platelet. A manually curated, functionally tested, and validated biochemical reaction network of platelet metabolism, iAT-PLT-636, was reconstructed using 33 proteomic datasets and 354 literature references. The network contains enzymes mapping to 403 diseases and 231 FDA approved drugs, alluding to an expansive scope of biochemical transformations that may affect or be affected by disease processes in multiple organ systems. The effect of aspirin (ASA) resistance on platelet metabolism was evaluated using constraint-based modeling, which revealed a redirection of glycolytic, fatty acid, and nucleotide metabolism reaction fluxes in order to accommodate eicosanoid synthesis and reactive oxygen species stress. These results were confirmed with independent proteomic data. The construction and availability of iAT-PLT-636 should stimulate further data-driven, systems analysis of platelet metabolism towards the understanding of pathophysiological conditions including, but not strictly limited to, coagulopathies.

  16. Metabolism of 7-ethyoxycoumarin by Isolated Perfused Rainbow Trout Livers

    EPA Science Inventory

    Isolated trout livers were perfused using methods designed to preserve tissue viability and function. Liver performance was evaluated by measuring O2 consumption, vascular resistance, K+ leakage, glucose flux, lactate flux, alanine aminotransferase leakage, and metabolic clearanc...

  17. Advanced Stoichiometric Analysis of Metabolic Networks of Mammalian Systems

    PubMed Central

    Orman, Mehmet A.; Berthiaume, Francois; Androulakis, Ioannis P.; Ierapetritou, Marianthi G.

    2013-01-01

    Metabolic engineering tools have been widely applied to living organisms to gain a comprehensive understanding about cellular networks and to improve cellular properties. Metabolic flux analysis (MFA), flux balance analysis (FBA), and metabolic pathway analysis (MPA) are among the most popular tools in stoichiometric network analysis. Although application of these tools into well-known microbial systems is extensive in the literature, various barriers prevent them from being utilized in mammalian cells. Limited experimental data, complex regulatory mechanisms, and the requirement of more complex nutrient media are some major obstacles in mammalian cell systems. However, mammalian cells have been used to produce therapeutic proteins, to characterize disease states or related abnormal metabolic conditions, and to analyze the toxicological effects of some medicinally important drugs. Therefore, there is a growing need for extending metabolic engineering principles to mammalian cells in order to understand their underlying metabolic functions. In this review article, advanced metabolic engineering tools developed for stoichiometric analysis including MFA, FBA, and MPA are described. Applications of these tools in mammalian cells are discussed in detail, and the challenges and opportunities are highlighted. PMID:22196224

  18. Continuous and batch cultures of Escherichia coli KJ134 for succinic acid fermentation: metabolic flux distributions and production characteristics.

    PubMed

    van Heerden, Carel D; Nicol, Willie

    2013-09-17

    Succinic acid (SA) has become a prominent biobased platform chemical with global production quantities increasing annually. Numerous genetically modified E. coli strains have been developed with the main aim of increasing the SA yield of the organic carbon source. In this study, a promising SA-producing strain, E. coli KJ134 [Biotechnol. Bioeng. 101:881-893, 2008], from the Department of Microbiology and Cell Science of the University of Florida was evaluated under continuous and batch conditions using D-glucose and CO2 in a mineral salt medium. Production characteristics entailing growth and maintenance rates, growth termination points and metabolic flux distributions under growth and non-growth conditions were determined. The culture remained stable for weeks under continuous conditions. Under growth conditions the redox requirements of the reductive tricarboxylic acid (TCA) cycle was solely balanced by acetic acid (AcA) production via the pyruvate dehydrogenase route resulting in a molar ratio of SA:AcA of two. A maximum growth rate of 0.22 h(-1) was obtained, while complete growth inhibition occurred at a SA concentration of 18 g L(-1). Batch culture revealed that high-yield succinate production (via oxidative TCA or glyoxylate redox balancing) occurred under non-growth conditions where a SA:AcA molar ratio of up to five was attained, with a final SA yield of 0.94 g g(-1). Growth termination of the batch culture was in agreement with that of the continuous culture. The maximum maintenance production rate of SA under batch conditions was found to be 0.6 g g(-1) h(-1). This is twice the maintenance rate observed in the continuous runs. The study revealed that the metabolic flux of E. coli KJ134 differs significantly for growth and non-growth conditions, with non-growth conditions resulting in higher SA:AcA ratios and SA yields. Bioreaction characteristics entailing growth and maintenance rates, as well as growth termination markers will guide future fermentor

  19. Precision Metabolic Engineering: the Design of Responsive, Selective, and Controllable Metabolic Systems

    PubMed Central

    McNerney, Monica P.; Watstein, Daniel M.; Styczynski, Mark P.

    2015-01-01

    Metabolic engineering is generally focused on static optimization of cells to maximize production of a desired product, though recently dynamic metabolic engineering has explored how metabolic programs can be varied over time to improve titer. However, these are not the only types of applications where metabolic engineering could make a significant impact. Here, we discuss a new conceptual framework, termed “precision metabolic engineering,” involving the design and engineering of systems that make different products in response to different signals. Rather than focusing on maximizing titer, these types of applications typically have three hallmarks: sensing signals that determine the desired metabolic target, completely directing metabolic flux in response to those signals, and producing sharp responses at specific signal thresholds. In this review, we will first discuss and provide examples of precision metabolic engineering. We will then discuss each of these hallmarks and identify which existing metabolic engineering methods can be applied to accomplish those tasks, as well as some of their shortcomings. Ultimately, precise control of metabolic systems has the potential to enable a host of new metabolic engineering and synthetic biology applications for any problem where flexibility of response to an external signal could be useful. PMID:26189665

  20. Avoiding the Enumeration of Infeasible Elementary Flux Modes by Including Transcriptional Regulatory Rules in the Enumeration Process Saves Computational Costs

    PubMed Central

    Jungreuthmayer, Christian; Ruckerbauer, David E.; Gerstl, Matthias P.; Hanscho, Michael; Zanghellini, Jürgen

    2015-01-01

    Despite the significant progress made in recent years, the computation of the complete set of elementary flux modes of large or even genome-scale metabolic networks is still impossible. We introduce a novel approach to speed up the calculation of elementary flux modes by including transcriptional regulatory information into the analysis of metabolic networks. Taking into account gene regulation dramatically reduces the solution space and allows the presented algorithm to constantly eliminate biologically infeasible modes at an early stage of the computation procedure. Thereby, computational costs, such as runtime, memory usage, and disk space, are extremely reduced. Moreover, we show that the application of transcriptional rules identifies non-trivial system-wide effects on metabolism. Using the presented algorithm pushes the size of metabolic networks that can be studied by elementary flux modes to new and much higher limits without the loss of predictive quality. This makes unbiased, system-wide predictions in large scale metabolic networks possible without resorting to any optimization principle. PMID:26091045

  1. Multiscale Metabolic Modeling of C4 Plants: Connecting Nonlinear Genome-Scale Models to Leaf-Scale Metabolism in Developing Maize Leaves

    PubMed Central

    Bogart, Eli; Myers, Christopher R.

    2016-01-01

    C4 plants, such as maize, concentrate carbon dioxide in a specialized compartment surrounding the veins of their leaves to improve the efficiency of carbon dioxide assimilation. Nonlinear relationships between carbon dioxide and oxygen levels and reaction rates are key to their physiology but cannot be handled with standard techniques of constraint-based metabolic modeling. We demonstrate that incorporating these relationships as constraints on reaction rates and solving the resulting nonlinear optimization problem yields realistic predictions of the response of C4 systems to environmental and biochemical perturbations. Using a new genome-scale reconstruction of maize metabolism, we build an 18000-reaction, nonlinearly constrained model describing mesophyll and bundle sheath cells in 15 segments of the developing maize leaf, interacting via metabolite exchange, and use RNA-seq and enzyme activity measurements to predict spatial variation in metabolic state by a novel method that optimizes correlation between fluxes and expression data. Though such correlations are known to be weak in general, we suggest that developmental gradients may be particularly suited to the inference of metabolic fluxes from expression data, and we demonstrate that our method predicts fluxes that achieve high correlation with the data, successfully capture the experimentally observed base-to-tip transition between carbon-importing tissue and carbon-exporting tissue, and include a nonzero growth rate, in contrast to prior results from similar methods in other systems. PMID:26990967

  2. Fast growth phenotype of E. coli K-12 from adaptive laboratory evolution does not require intracellular flux rewiring

    PubMed Central

    Long, Christopher P.; Gonzalez, Jacqueline E.; Feist, Adam M.; Palsson, Bernhard O.; Antoniewicz, Maciek R.

    2018-01-01

    Adaptive laboratory evolution (ALE) is a widely-used method for improving the fitness of microorganisms in selected environmental conditions. It has been applied previously to Escherichia coli K-12 MG1655 during aerobic exponential growth on glucose minimal media, a frequently used model organism and growth condition, to probe the limits of E. coli growth rate and gain insights into fast growth phenotypes. Previous studies have described up to 1.6-fold increases in growth rate following ALE, and have identified key causal genetic mutations and changes in transcriptional patterns. Here, we report for the first time intracellular metabolic fluxes for six such adaptively evolved strains, as determined by high-resolution 13C-metabolic flux analysis. Interestingly, we found that intracellular metabolic pathway usage changed very little following adaptive evolution. Instead, at the level of central carbon metabolism the faster growth was facilitated by proportional increases in glucose uptake and all intracellular rates. Of the six evolved strains studied here, only one strain showed a small degree of flux rewiring, and this was also the strain with unique genetic mutations. A comparison of fluxes with two other wild-type (unevolved) E. coli strains, BW25113 and BL21, showed that inter-strain differences are greater than differences between the parental and evolved strains. Principal component analysis highlighted that nearly all flux differences (95%) between the nine strains were captured by only two principal components. The distance between measured and flux balance analysis predicted fluxes was also investigated. It suggested a relatively wide range of similar stoichiometric optima, which opens new questions about the path-dependency of adaptive evolution. PMID:28951266

  3. Nitrate addition to groundwater impacted by ethanol-blended fuel accelerates ethanol removal and mitigates the associated metabolic flux dilution and inhibition of BTEX biodegradation

    NASA Astrophysics Data System (ADS)

    Corseuil, Henry Xavier; Gomez, Diego E.; Schambeck, Cássio Moraes; Ramos, Débora Toledo; Alvarez, Pedro J. J.

    2015-03-01

    A comparison of two controlled ethanol-blended fuel releases under monitored natural attenuation (MNA) versus nitrate biostimulation (NB) illustrates the potential benefits of augmenting the electron acceptor pool with nitrate to accelerate ethanol removal and thus mitigate its inhibitory effects on BTEX biodegradation. Groundwater concentrations of ethanol and BTEX were measured 2 m downgradient of the source zones. In both field experiments, initial source-zone BTEX concentrations represented less than 5% of the dissolved total organic carbon (TOC) associated with the release, and measurable BTEX degradation occurred only after the ethanol fraction in the multicomponent substrate mixture decreased sharply. However, ethanol removal was faster in the nitrate amended plot (1.4 years) than under natural attenuation conditions (3.0 years), which led to faster BTEX degradation. This reflects, in part, that an abundant substrate (ethanol) can dilute the metabolic flux of target pollutants (BTEX) whose biodegradation rate eventually increases with its relative abundance after ethanol is preferentially consumed. The fate and transport of ethanol and benzene were accurately simulated in both releases using RT3D with our general substrate interaction module (GSIM) that considers metabolic flux dilution. Since source zone benzene concentrations are relatively low compared to those of ethanol (or its degradation byproduct, acetate), our simulations imply that the initial focus of cleanup efforts (after free-product recovery) should be to stimulate the degradation of ethanol (e.g., by nitrate addition) to decrease its fraction in the mixture and speed up BTEX biodegradation.

  4. Computational Tools for Metabolic Engineering

    PubMed Central

    Copeland, Wilbert B.; Bartley, Bryan A.; Chandran, Deepak; Galdzicki, Michal; Kim, Kyung H.; Sleight, Sean C.; Maranas, Costas D.; Sauro, Herbert M.

    2012-01-01

    A great variety of software applications are now employed in the metabolic engineering field. These applications have been created to support a wide range of experimental and analysis techniques. Computational tools are utilized throughout the metabolic engineering workflow to extract and interpret relevant information from large data sets, to present complex models in a more manageable form, and to propose efficient network design strategies. In this review, we present a number of tools that can assist in modifying and understanding cellular metabolic networks. The review covers seven areas of relevance to metabolic engineers. These include metabolic reconstruction efforts, network visualization, nucleic acid and protein engineering, metabolic flux analysis, pathway prospecting, post-structural network analysis and culture optimization. The list of available tools is extensive and we can only highlight a small, representative portion of the tools from each area. PMID:22629572

  5. Differential retention of metabolic genes following whole-genome duplication.

    PubMed

    Gout, Jean-François; Duret, Laurent; Kahn, Daniel

    2009-05-01

    Classical studies in Metabolic Control Theory have shown that metabolic fluxes usually exhibit little sensitivity to changes in individual enzyme activity, yet remain sensitive to global changes of all enzymes in a pathway. Therefore, little selective pressure is expected on the dosage or expression of individual metabolic genes, yet entire pathways should still be constrained. However, a direct estimate of this selective pressure had not been evaluated. Whole-genome duplications (WGDs) offer a good opportunity to address this question by analyzing the fates of metabolic genes during the massive gene losses that follow. Here, we take advantage of the successive rounds of WGD that occurred in the Paramecium lineage. We show that metabolic genes exhibit different gene retention patterns than nonmetabolic genes. Contrary to what was expected for individual genes, metabolic genes appeared more retained than other genes after the recent WGD, which was best explained by selection for gene expression operating on entire pathways. Metabolic genes also tend to be less retained when present at high copy number before WGD, contrary to other genes that show a positive correlation between gene retention and preduplication copy number. This is rationalized on the basis of the classical concave relationship relating metabolic fluxes with enzyme expression.

  6. Physiologically Shrinking the Solution Space of a Saccharomyces cerevisiae Genome-Scale Model Suggests the Role of the Metabolic Network in Shaping Gene Expression Noise.

    PubMed

    Chi, Baofang; Tao, Shiheng; Liu, Yanlin

    2015-01-01

    Sampling the solution space of genome-scale models is generally conducted to determine the feasible region for metabolic flux distribution. Because the region for actual metabolic states resides only in a small fraction of the entire space, it is necessary to shrink the solution space to improve the predictive power of a model. A common strategy is to constrain models by integrating extra datasets such as high-throughput datasets and C13-labeled flux datasets. However, studies refining these approaches by performing a meta-analysis of massive experimental metabolic flux measurements, which are closely linked to cellular phenotypes, are limited. In the present study, experimentally identified metabolic flux data from 96 published reports were systematically reviewed. Several strong associations among metabolic flux phenotypes were observed. These phenotype-phenotype associations at the flux level were quantified and integrated into a Saccharomyces cerevisiae genome-scale model as extra physiological constraints. By sampling the shrunken solution space of the model, the metabolic flux fluctuation level, which is an intrinsic trait of metabolic reactions determined by the network, was estimated and utilized to explore its relationship to gene expression noise. Although no correlation was observed in all enzyme-coding genes, a relationship between metabolic flux fluctuation and expression noise of genes associated with enzyme-dosage sensitive reactions was detected, suggesting that the metabolic network plays a role in shaping gene expression noise. Such correlation was mainly attributed to the genes corresponding to non-essential reactions, rather than essential ones. This was at least partially, due to regulations underlying the flux phenotype-phenotype associations. Altogether, this study proposes a new approach in shrinking the solution space of a genome-scale model, of which sampling provides new insights into gene expression noise.

  7. TNA4OptFlux – a software tool for the analysis of strain optimization strategies

    PubMed Central

    2013-01-01

    Background Rational approaches for Metabolic Engineering (ME) deal with the identification of modifications that improve the microbes’ production capabilities of target compounds. One of the major challenges created by strain optimization algorithms used in these ME problems is the interpretation of the changes that lead to a given overproduction. Often, a single gene knockout induces changes in the fluxes of several reactions, as compared with the wild-type, and it is therefore difficult to evaluate the physiological differences of the in silico mutant. This is aggravated by the fact that genome-scale models per se are difficult to visualize, given the high number of reactions and metabolites involved. Findings We introduce a software tool, the Topological Network Analysis for OptFlux (TNA4OptFlux), a plug-in which adds to the open-source ME platform OptFlux the capability of creating and performing topological analysis over metabolic networks. One of the tool’s major advantages is the possibility of using these tools in the analysis and comparison of simulated phenotypes, namely those coming from the results of strain optimization algorithms. We illustrate the capabilities of the tool by using it to aid the interpretation of two E. coli strains designed in OptFlux for the overproduction of succinate and glycine. Conclusions Besides adding new functionalities to the OptFlux software tool regarding topological analysis, TNA4OptFlux methods greatly facilitate the interpretation of non-intuitive ME strategies by automating the comparison between perturbed and non-perturbed metabolic networks. The plug-in is available on the web site http://www.optflux.org, together with extensive documentation. PMID:23641878

  8. Substituted 2-benzothiazolamines as sodium flux inhibitors: quantitative structure-activity relationships and anticonvulsant activity.

    PubMed

    Hays, S J; Rice, M J; Ortwine, D F; Johnson, G; Schwarz, R D; Boyd, D K; Copeland, L F; Vartanian, M G; Boxer, P A

    1994-10-01

    Thirty-two aryl-substituted 2-benzothiazolamines have been tested for their ability to modulate sodium flux in rat cortical slices. A QSAR analysis, applied to these derivatives, showed a trend toward increasing potency as sodium flux inhibitors with increasing lipophilicity, decreasing size, and increasing electron withdrawal of the benzo ring substituents. Additionally, 4- or 5-substitution of the benzo ring was found to decrease potency. The combination of increased lipophilicity, small size, and electron withdrawal severely limited which groups were tolerated on the benzo ring, thus suggesting that the optimal substitution patterns have been prepared within this series. Nine of these compounds were potent inhibitors of veratridine-induced sodium flux (NaFl). These nine compounds also proved to be anticonvulsant in the maximal electroshock (MES) assay. Fourteen additional 2-benzothiazolamines demonstrated activity in the MES screen, yet exhibited no activity in the NaFl assay. These derivatives may be interacting at the sodium channel in a manner not discernible by the flux paradigm, or they may be acting by an alternative mechanism in vivo.

  9. Sequential Metabolic Phases as a Means to Optimize Cellular Output in a Constant Environment

    PubMed Central

    Bockmayr, Alexander; Holzhütter, Hermann-Georg

    2015-01-01

    Temporal changes of gene expression are a well-known regulatory feature of all cells, which is commonly perceived as a strategy to adapt the proteome to varying external conditions. However, temporal (rhythmic and non-rhythmic) changes of gene expression are also observed under virtually constant external conditions. Here we hypothesize that such changes are a means to render the synthesis of the metabolic output more efficient than under conditions of constant gene activities. In order to substantiate this hypothesis, we used a flux-balance model of the cellular metabolism. The total time span spent on the production of a given set of target metabolites was split into a series of shorter time intervals (metabolic phases) during which only selected groups of metabolic genes are active. The related flux distributions were calculated under the constraint that genes can be either active or inactive whereby the amount of protein related to an active gene is only controlled by the number of active genes: the lower the number of active genes the more protein can be allocated to the enzymes carrying non-zero fluxes. This concept of a predominantly protein-limited efficiency of gene expression clearly differs from other concepts resting on the assumption of an optimal gene regulation capable of allocating to all enzymes and transporters just that fraction of protein necessary to prevent rate limitation. Applying this concept to a simplified metabolic network of the central carbon metabolism with glucose or lactate as alternative substrates, we demonstrate that switching between optimally chosen stationary flux modes comprising different sets of active genes allows producing a demanded amount of target metabolites in a significantly shorter time than by a single optimal flux mode at fixed gene activities. Our model-based findings suggest that temporal expression of metabolic genes can be advantageous even under conditions of constant external substrate supply. PMID:25786979

  10. [Quantitative mineralogical analyzes of kidney stones and diagnosing metabolic disorders in female patients with calcium oxalate urolithiasis].

    PubMed

    Kustov, A V; Moryganov, M A; Strel'nikov, A I; Zhuravleva, N I; Airapetyan, A O

    2016-02-01

    To conduct a complex examination of female patients with calcium oxalate urolithiasis to detect metabolic disorders, leading to stone formation. The study was carried out using complex physical and chemical methods, including quantitative X-ray phase analysis of urinary stones, pH measurement, volumetry, urine and blood spectrophotometry. Quantitative mineralogical composition of stones, daily urine pH profile, daily urinary excretion of ions of calcium, magnesium, oxalate, phosphate, citrate and uric acid were determined in 20 female patients with calcium oxalate stones. We have shown that most of the stones comprised calcium oxalate monohydrate or mixtures of calcium oxalate dihydrate and hydroxyapatite. Among the identified abnormalities, the most frequent were hypocitraturia and hypercalciuria - 90 and 45%, respectively. Our findings revealed that the daily secretion of citrate and oxalate in patients older than 50 years was significantly lower than in younger patients. In conclusion, daily urinary citrate excretion should be measured in female patients with calcium oxalate stones. This is necessary both to determine the causes of stone formation, and to monitor the effectiveness of citrate therapy.

  11. Comparative iTRAQ-Based Quantitative Proteomic Analysis of Pelteobagrus vachelli Liver under Acute Hypoxia: Implications in Metabolic Responses.

    PubMed

    Zhang, Guosong; Zhang, Jiajia; Wen, Xin; Zhao, Cheng; Zhang, Hongye; Li, Xinru; Yin, Shaowu

    2017-09-01

    More and more frequently these days, aquatic ecosystems are being stressed by nutrient enrichment, pollutants, and global warming, leading to a serious depletion in oxygen concentrations. Although a sudden, significant lack of oxygen will result in mortality, fishes can have an acute behavior (e.g., an increase in breathing rate, reduction in swimming frequency) and physiology responses (e.g., increase in oxygen delivery, and reduction in oxygen consumption) to hypoxia, which allows them to maintain normal physical activity. Therefore, in order to shed further light on the molecular mechanisms of hypoxia adaptation in fishes, the authors conduct comparative quantitative proteomics on Pelteobagrus vachelli livers using iTRAQ. The research identifies 511 acute hypoxia-responsive proteins in P. vachelli. Furthermore, comparison of several of the diverse key pathways studied (e.g., peroxisome pathway, PPAR signaling pathway, lipid metabolism, glycolysis/gluco-neogenesis, and amino acid metabolism) help to articulate the different mechanisms involved in the hypoxia response of P. vachelli. Data from proteome analysis shows that P. vachelli can have an acute reaction to hypoxia, including detoxification of metabolic by-products and oxidative stress in light of continued metabolic activity (e.g., peroxisomes), an activation in the capacity of catabolism to get more energy (e.g., lipolysis and amino acid catabolism), a depression in the capacity of biosynthesis to reduce energy consumption (e.g., biosynthesis of amino acids and lipids), and a shift in the aerobic and anaerobic contributions to total metabolism. The observed hypoxia-related changes in the liver proteome of the fish can help to understand or can be related to the hypoxia-related response that takes place in similar conditions in the liver or other proteomes of mammals. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  12. A Method of Accounting for Enzyme Costs in Flux Balance Analysis Reveals Alternative Pathways and Metabolite Stores in an Illuminated Arabidopsis Leaf.

    PubMed

    Cheung, C Y Maurice; Ratcliffe, R George; Sweetlove, Lee J

    2015-11-01

    Flux balance analysis of plant metabolism is an established method for predicting metabolic flux phenotypes and for exploring the way in which the plant metabolic network delivers specific outcomes in different cell types, tissues, and temporal phases. A recurring theme is the need to explore the flexibility of the network in meeting its objectives and, in particular, to establish the extent to which alternative pathways can contribute to achieving specific outcomes. Unfortunately, predictions from conventional flux balance analysis minimize the simultaneous operation of alternative pathways, but by introducing flux-weighting factors to allow for the variable intrinsic cost of supporting each flux, it is possible to activate different pathways in individual simulations and, thus, to explore alternative pathways by averaging thousands of simulations. This new method has been applied to a diel genome-scale model of Arabidopsis (Arabidopsis thaliana) leaf metabolism to explore the flexibility of the network in meeting the metabolic requirements of the leaf in the light. This identified alternative flux modes in the Calvin-Benson cycle revealed the potential for alternative transitory carbon stores in leaves and led to predictions about the light-dependent contribution of alternative electron flow pathways and futile cycles in energy rebalancing. Notable features of the analysis include the light-dependent tradeoff between the use of carbohydrates and four-carbon organic acids as transitory storage forms and the way in which multiple pathways for the consumption of ATP and NADPH can contribute to the balancing of the requirements of photosynthetic metabolism with the energy available from photon capture. © 2015 American Society of Plant Biologists. All Rights Reserved.

  13. Fermentation of Xylose Causes Inefficient Metabolic State Due to Carbon/Energy Starvation and Reduced Glycolytic Flux in Recombinant Industrial Saccharomyces cerevisiae

    PubMed Central

    Matsushika, Akinori; Nagashima, Atsushi; Goshima, Tetsuya; Hoshino, Tamotsu

    2013-01-01

    In the present study, comprehensive, quantitative metabolome analysis was carried out on the recombinant glucose/xylose-cofermenting S. cerevisiae strain MA-R4 during fermentation with different carbon sources, including glucose, xylose, or glucose/xylose mixtures. Capillary electrophoresis time-of-flight mass spectrometry was used to determine the intracellular pools of metabolites from the central carbon pathways, energy metabolism pathways, and the levels of twenty amino acids. When xylose instead of glucose was metabolized by MA-R4, glycolytic metabolites including 3- phosphoglycerate, 2- phosphoglycerate, phosphoenolpyruvate, and pyruvate were dramatically reduced, while conversely, most pentose phosphate pathway metabolites such as sedoheptulose 7- phosphate and ribulose 5-phosphate were greatly increased. These results suggest that the low metabolic activity of glycolysis and the pool of pentose phosphate pathway intermediates are potential limiting factors in xylose utilization. It was further demonstrated that during xylose fermentation, about half of the twenty amino acids declined, and the adenylate/guanylate energy charge was impacted due to markedly decreased adenosine triphosphate/adenosine monophosphate and guanosine triphosphate/guanosine monophosphate ratios, implying that the fermentation of xylose leads to an inefficient metabolic state where the biosynthetic capabilities and energy balance are severely impaired. In addition, fermentation with xylose alone drastically increased the level of citrate in the tricarboxylic acid cycle and increased the aromatic amino acids tryptophan and tyrosine, strongly supporting the view that carbon starvation was induced. Interestingly, fermentation with xylose alone also increased the synthesis of the polyamine spermidine and its precursor S-adenosylmethionine. Thus, differences in carbon substrates, including glucose and xylose in the fermentation medium, strongly influenced the dynamic metabolism of MA-R4

  14. Fundamental Escherichia coli biochemical pathways for biomass and energy production: creation of overall flux states.

    PubMed

    Carlson, Ross; Srienc, Friedrich

    2004-04-20

    We have previously shown that the metabolism for most efficient cell growth can be realized by a combination of two types of elementary modes. One mode produces biomass while the second mode generates only energy. The identity of the four most efficient biomass and energy pathway pairs changes, depending on the degree of oxygen limitation. The identification of such pathway pairs for different growth conditions offers a pathway-based explanation of maintenance energy generation. For a given growth rate, experimental aerobic glucose consumption rates can be used to estimate the contribution of each pathway type to the overall metabolic flux pattern. All metabolic fluxes are then completely determined by the stoichiometries of involved pathways defining all nutrient consumption and metabolite secretion rates. We present here equations that permit computation of network fluxes on the basis of unique pathways for the case of optimal, glucose-limited Escherichia coli growth under varying levels of oxygen stress. Predicted glucose and oxygen uptake rates and some metabolite secretion rates are in remarkable agreement with experimental observations supporting the validity of the presented approach. The entire most efficient, steady-state, metabolic rate structure is explicitly defined by the developed equations without need for additional computer simulations. The approach should be generally useful for analyzing and interpreting genomic data by predicting concise, pathway-based metabolic rate structures. Copyright 2004 Wiley Periodicals, Inc.

  15. A quantitative study of methanol/sorbitol co-feeding process of a Pichia pastoris Mut+/pAOX1-lacZ strain

    PubMed Central

    2013-01-01

    Background One of the main challenges for heterologous protein production by the methylotrophic yeast Pichia pastoris at large-scale is related to its high oxygen demand. A promising solution is a co-feeding strategy based on a methanol/sorbitol mixture during the induction phase. Nonetheless, a deep understanding of the cellular physiology and the regulation of the AOX1 promoter, used to govern heterologous protein production, during this co-feeding strategy is still scarce. Results Transient continuous cultures with a dilution rate of 0.023 h-1 at 25°C were performed to quantitatively assess the benefits of a methanol/sorbitol co-feeding process with a Mut+ strain in which the pAOX1-lacZ construct served as a reporter gene. Cell growth and metabolism, including O2 consumption together with CO2 and heat production were analyzed with regard to a linear change of methanol fraction in the mixed feeding media. In addition, the regulation of the promoter AOX1 was investigated by means of β-galactosidase measurements. Our results demonstrated that the cell-specific oxygen consumption (qO2) could be reduced by decreasing the methanol fraction in the feeding media. More interestingly, maximal β-galactosidase cell-specific activity (>7500 Miller unit) and thus, optimal pAOX1 induction, was achieved and maintained in the range of 0.45 ~ 0.75 C-mol/C-mol of methanol fraction. In addition, the qO2 was reduced by 30% at most in those conditions. Based on a simplified metabolic network, metabolic flux analysis (MFA) was performed to quantify intracellular metabolic flux distributions during the transient continuous cultures, which further shed light on the advantages of methanol/sorbitol co-feeding process. Finally, our observations were further validated in fed-batch cultures. Conclusion This study brings quantitative insight into the co-feeding process, which provides valuable data for the control of methanol/sorbitol co-feeding, aiming at enhancing biomass and

  16. Lake Metabolism: Comparison of Lake Metabolic Rates Estimated from a Diel CO2- and the Common Diel O2-Technique.

    PubMed

    Peeters, Frank; Atamanchuk, Dariia; Tengberg, Anders; Encinas-Fernández, Jorge; Hofmann, Hilmar

    2016-01-01

    Lake metabolism is a key factor for the understanding of turnover of energy and of organic and inorganic matter in lake ecosystems. Long-term time series on metabolic rates are commonly estimated from diel changes in dissolved oxygen. Here we present long-term data on metabolic rates based on diel changes in total dissolved inorganic carbon (DIC) utilizing an open-water diel CO2-technique. Metabolic rates estimated with this technique and the traditional diel O2-technique agree well in alkaline Lake Illmensee (pH of ~8.5), although the diel changes in molar CO2 concentrations are much smaller than those of the molar O2 concentrations. The open-water diel CO2- and diel O2-techniques provide independent measures of lake metabolic rates that differ in their sensitivity to transport processes. Hence, the combination of both techniques can help to constrain uncertainties arising from assumptions on vertical fluxes due to gas exchange and turbulent diffusion. This is particularly important for estimates of lake respiration rates because these are much more sensitive to assumptions on gradients in vertical fluxes of O2 or DIC than estimates of lake gross primary production. Our data suggest that it can be advantageous to estimate respiration rates assuming negligible gradients in vertical fluxes rather than including gas exchange with the atmosphere but neglecting vertical mixing in the water column. During two months in summer the average lake net production was close to zero suggesting at most slightly autotrophic conditions. However, the lake emitted O2 and CO2 during the entire time period suggesting that O2 and CO2 emissions from lakes can be decoupled from the metabolism in the near surface layer.

  17. Lake Metabolism: Comparison of Lake Metabolic Rates Estimated from a Diel CO2- and the Common Diel O2-Technique

    PubMed Central

    Peeters, Frank; Atamanchuk, Dariia; Tengberg, Anders; Encinas-Fernández, Jorge; Hofmann, Hilmar

    2016-01-01

    Lake metabolism is a key factor for the understanding of turnover of energy and of organic and inorganic matter in lake ecosystems. Long-term time series on metabolic rates are commonly estimated from diel changes in dissolved oxygen. Here we present long-term data on metabolic rates based on diel changes in total dissolved inorganic carbon (DIC) utilizing an open-water diel CO2-technique. Metabolic rates estimated with this technique and the traditional diel O2-technique agree well in alkaline Lake Illmensee (pH of ~8.5), although the diel changes in molar CO2 concentrations are much smaller than those of the molar O2 concentrations. The open-water diel CO2- and diel O2-techniques provide independent measures of lake metabolic rates that differ in their sensitivity to transport processes. Hence, the combination of both techniques can help to constrain uncertainties arising from assumptions on vertical fluxes due to gas exchange and turbulent diffusion. This is particularly important for estimates of lake respiration rates because these are much more sensitive to assumptions on gradients in vertical fluxes of O2 or DIC than estimates of lake gross primary production. Our data suggest that it can be advantageous to estimate respiration rates assuming negligible gradients in vertical fluxes rather than including gas exchange with the atmosphere but neglecting vertical mixing in the water column. During two months in summer the average lake net production was close to zero suggesting at most slightly autotrophic conditions. However, the lake emitted O2 and CO2 during the entire time period suggesting that O2 and CO2 emissions from lakes can be decoupled from the metabolism in the near surface layer. PMID:28002477

  18. A mathematical model of liver metabolism: from steady state to dynamic

    NASA Astrophysics Data System (ADS)

    Calvetti, D.; Kuceyeski, A.; Somersalo, E.

    2008-07-01

    The increase in Type 2 diabetes and other metabolic disorders has led to an intense focus on the areas of research related to metabolism. Because the liver is essential in regulating metabolite concentrations that maintain life, it is especially important to have good knowledge of the functions within this organ. In silico mathematical models that can adequately describe metabolite concentrations, flux and transport rates in the liver in vivo can be a useful predictive tool. Fully dynamic models, which contain expressions for Michaelis-Menten reaction kinetics can be utilized to investigate different metabolic states, for example exercise, fed or starved state. In this paper we describe a two compartment (blood and tissue) spatially lumped liver metabolism model. First, we use Bayesian Flux Balance Analysis (BFBA) to estimate the values of flux and transport rates at steady state, which agree closely with values from the literature. These values are then used to find a set of Michaelis-Menten parameters and initial concentrations which identify a dynamic model that can be used for exploring different metabolic states. In particular, we investigate the effect of doubling the concentration of lactate entering the system via the hepatic artery and portal vein. This change in lactate concentration forces the system to a new steady state, where glucose production is increased.

  19. Redistribution of carbon flux in Torulopsis glabrata by altering vitamin and calcium level.

    PubMed

    Liu, Liming; Li, Yin; Zhu, Yang; Du, Guocheng; Chen, Jian

    2007-01-01

    Manipulation of cofactor (thiamine, biotin and Ca(2+)) levels as a potential tool to redistribute carbon flux was studied in Torulopsis glabrata. With sub-optimization of vitamin in fermentation medium, the carbon flux was blocked at the key node of pyruvate, and 69 g/L pyruvate was accumulated. Increasing the concentrations of thiamine and biotin could selectively open the valve of carbon flux from pyruvate to pyruvate dehydrogenase complex, the pyruvate carboxylase (PC) pathway and the channel into the TCA cycle, leading to the over-production of alpha-ketoglutarate. In addition, the activity of PC was enhanced with Ca(2+) present in fermentation medium. By combining high concentration's vitamins and CaCO(3) as the pH buffer, a batch culture was conducted in a 7-L fermentor, with the pyruvate concentration decreased to 21.8 g/L while alpha-ketoglutarate concentration increased to 43.7 g/L. Our study indicated that the metabolic flux could be redistributed to overproduce desired metabolites with manipulating the cofactor levels. Furthermore, the manipulation of vitamin level provided an alternative tool to realize metabolic engineering goals.

  20. Prediction of Metabolic Flux Distribution from Gene Expression Data Based on the Flux Minimization Principle

    DTIC Science & Technology

    2014-11-14

    problem. Modification of the PLOS ONE | www.plosone.org 1 November 2014 | Volume 9 | Issue 11 | e112524 Report Documentation Page Form ApprovedOMB No. 0704... Form 298 (Rev. 8-98) Prescribed by ANSI Std Z39-18 FBA algorithm to incorporate additional biological information from gene expression profiles is...We set the maximization of biomass production as the objective of FBA and implemented it in two different forms : without flux minimization (or

  1. Quantitative Proteomic Analysis Reveals That Anti-Cancer Effects of Selenium-Binding Protein 1 In Vivo Are Associated with Metabolic Pathways

    PubMed Central

    Ying, Qi; Ansong, Emmanuel; Diamond, Alan M.; Lu, Zhaoxin; Yang, Wancai; Bie, Xiaomei

    2015-01-01

    Previous studies have shown the tumor-suppressive role of selenium-binding protein 1 (SBP1), but the underlying mechanisms are unclear. In this study, we found that induction of SBP1 showed significant inhibition of colorectal cancer cell growth and metastasis in mice. We further employed isobaric tags for relative and absolute quantitation (iTRAQ) to identify proteins that were involved in SBP1-mediated anti-cancer effects in tumor tissues. We identified 132 differentially expressed proteins, among them, 53 proteins were upregulated and 79 proteins were downregulated. Importantly, many of the differentially altered proteins were associated with lipid/glucose metabolism, which were also linked to Glycolysis, MAPK, Wnt, NF-kB, NOTCH and epithelial-mesenchymal transition (EMT) signaling pathways. These results have revealed a novel mechanism that SBP1-mediated cancer inhibition is through altering lipid/glucose metabolic signaling pathways. PMID:25974208

  2. Quantitative imaging of brain energy metabolisms and neuroenergetics using in vivo X-nuclear 2H, 17O and 31P MRS at ultra-high field.

    PubMed

    Zhu, Xiao-Hong; Lu, Ming; Chen, Wei

    2018-07-01

    Brain energy metabolism relies predominantly on glucose and oxygen utilization to generate biochemical energy in the form of adenosine triphosphate (ATP). ATP is essential for maintaining basal electrophysiological activities in a resting brain and supporting evoked neuronal activity under an activated state. Studying complex neuroenergetic processes in the brain requires sophisticated neuroimaging techniques enabling noninvasive and quantitative assessment of cerebral energy metabolisms and quantification of metabolic rates. Recent state-of-the-art in vivo X-nuclear MRS techniques, including 2 H, 17 O and 31 P MRS have shown promise, especially at ultra-high fields, in the quest for understanding neuroenergetics and brain function using preclinical models and in human subjects under healthy and diseased conditions. Copyright © 2018 Elsevier Inc. All rights reserved.

  3. iTRAQ-Based Quantitative Proteomics Analysis of Black Rice Grain Development Reveals Metabolic Pathways Associated with Anthocyanin Biosynthesis

    PubMed Central

    Chen, Linghua; Huang, Yining; Xu, Ming; Cheng, Zuxin; Zhang, Dasheng; Zheng, Jingui

    2016-01-01

    Background Black rice (Oryza sativa L.), whose pericarp is rich in anthocyanins (ACNs), is considered as a healthier alternative to white rice. Molecular species of ACNs in black rice have been well documented in previous studies; however, information about the metabolic mechanisms underlying ACN biosynthesis during black rice grain development is unclear. Results The aim of the present study was to determine changes in the metabolic pathways that are involved in the dynamic grain proteome during the development of black rice indica cultivar, (Oryza sativa L. indica var. SSP). Isobaric tags for relative and absolute quantification (iTRAQ) MS/MS were employed to identify statistically significant alterations in the grain proteome. Approximately 928 proteins were detected, of which 230 were differentially expressed throughout 5 successive developmental stages, starting from 3 to 20 days after flowering (DAF). The greatest number of differentially expressed proteins was observed on 7 and 10 DAF, including 76 proteins that were upregulated and 39 that were downregulated. The biological process analysis of gene ontology revealed that the 230 differentially expressed proteins could be sorted into 14 functional groups. Proteins in the largest group were related to metabolic process, which could be integrated into multiple biochemical pathways. Specifically, proteins with a role in ACN biosynthesis, sugar synthesis, and the regulation of gene expression were upregulated, particularly from the onset of black rice grain development and during development. In contrast, the expression of proteins related to signal transduction, redox homeostasis, photosynthesis and N-metabolism decreased during grain maturation. Finally, 8 representative genes encoding different metabolic proteins were verified via quantitative real-time polymerase chain reaction (qRT-PCR) analysis, these genes had differed in transcriptional and translational expression during grain development. Conclusions

  4. iTRAQ-Based Quantitative Proteomics Analysis of Black Rice Grain Development Reveals Metabolic Pathways Associated with Anthocyanin Biosynthesis.

    PubMed

    Chen, Linghua; Huang, Yining; Xu, Ming; Cheng, Zuxin; Zhang, Dasheng; Zheng, Jingui

    2016-01-01

    Black rice (Oryza sativa L.), whose pericarp is rich in anthocyanins (ACNs), is considered as a healthier alternative to white rice. Molecular species of ACNs in black rice have been well documented in previous studies; however, information about the metabolic mechanisms underlying ACN biosynthesis during black rice grain development is unclear. The aim of the present study was to determine changes in the metabolic pathways that are involved in the dynamic grain proteome during the development of black rice indica cultivar, (Oryza sativa L. indica var. SSP). Isobaric tags for relative and absolute quantification (iTRAQ) MS/MS were employed to identify statistically significant alterations in the grain proteome. Approximately 928 proteins were detected, of which 230 were differentially expressed throughout 5 successive developmental stages, starting from 3 to 20 days after flowering (DAF). The greatest number of differentially expressed proteins was observed on 7 and 10 DAF, including 76 proteins that were upregulated and 39 that were downregulated. The biological process analysis of gene ontology revealed that the 230 differentially expressed proteins could be sorted into 14 functional groups. Proteins in the largest group were related to metabolic process, which could be integrated into multiple biochemical pathways. Specifically, proteins with a role in ACN biosynthesis, sugar synthesis, and the regulation of gene expression were upregulated, particularly from the onset of black rice grain development and during development. In contrast, the expression of proteins related to signal transduction, redox homeostasis, photosynthesis and N-metabolism decreased during grain maturation. Finally, 8 representative genes encoding different metabolic proteins were verified via quantitative real-time polymerase chain reaction (qRT-PCR) analysis, these genes had differed in transcriptional and translational expression during grain development. Expression analyses of

  5. Elucidating central metabolic redox obstacles hindering ethanol production in Clostridium thermocellum.

    PubMed

    Thompson, R Adam; Layton, Donovan S; Guss, Adam M; Olson, Daniel G; Lynd, Lee R; Trinh, Cong T

    2015-11-01

    Clostridium thermocellum is an anaerobic, Gram-positive, thermophilic bacterium that has generated great interest due to its ability to ferment lignocellulosic biomass to ethanol. However, ethanol production is low due to the complex and poorly understood branched metabolism of C. thermocellum, and in some cases overflow metabolism as well. In this work, we developed a predictive stoichiometric metabolic model for C. thermocellum which incorporates the current state of understanding, with particular attention to cofactor specificity in the atypical glycolytic enzymes and the complex energy, redox, and fermentative pathways with the goal of aiding metabolic engineering efforts. We validated the model's capability to encompass experimentally observed phenotypes for the parent strain and derived mutants designed for significant perturbation of redox and energy pathways. Metabolic flux distributions revealed significant alterations in key metabolic branch points (e.g., phosphoenol pyruvate, pyruvate, acetyl-CoA, and cofactor nodes) in engineered strains for channeling electron and carbon fluxes for enhanced ethanol synthesis, with the best performing strain doubling ethanol yield and titer compared to the parent strain. In silico predictions of a redox-imbalanced genotype incapable of growth were confirmed in vivo, and a mutant strain was used as a platform to probe redox bottlenecks in the central metabolism that hinder efficient ethanol production. The results highlight the robustness of the redox metabolism of C. thermocellum and the necessity of streamlined electron flux from reduced ferredoxin to NAD(P)H for high ethanol production. The model was further used to design a metabolic engineering strategy to phenotypically constrain C. thermocellum to achieve high ethanol yields while requiring minimal genetic manipulations. The model can be applied to design C. thermocellum as a platform microbe for consolidated bioprocessing to produce ethanol and other reduced

  6. Engineering Plant One-Carbon Metabolism

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    David Rhodes

    2005-02-09

    Primary and secondary metabolism intersect in the one-carbon (C1) area. Primary metabolism supplies most of the C1 units and competes with secondary metabolism for their use. This competition is potentially severe because secondary products such as lignin, alkaloids, and glycine betaine (GlyBet) require massive amounts of C1 units. Towards the goal of understanding how C1 metabolism is regulated at the metabolic and gene levels so as to successfully engineer C1 supply to match demand, we have: (1) cloned complete suites of C1 genes from maize and tobacco, and incorporated them into DNA arrays; (2) prepared antisense constructs and mutants engineeredmore » with alterations in C1 unit supply and demand; and (3) have quantified the impacts of these alterations on gene expression (using DNA arrays), and on metabolic fluxes (by combining isotope labeling, MS, NMR and computer modeling). Metabolic flux analysis and modeling in tobacco engineered for GlyBet synthesis by expressing choline oxidizing enzymes in either the chloroplast or cytosol, has shown that the choline biosynthesis network is rigid, and tends to resist large changes in C1 demand. A major constraint on engineering enhanced flux to GlyBet in tobacco is a low capacity of choline transport across the chloroplast envelope. Maize and sorghum mutants defective in GlyBet synthesis show greatly reduced flux of C1 units into choline in comparison to GlyBet-accumulating wildtypes, but this is not associated with altered expression of any of the C1 genes. Control of C1 flux to choline in tobacco, maize and sorghum appears to reside primarily at the level of N-methylation of phosphoethanolamine. A candidate signal for the control of this flux is the pool size of phosphocholine which down-regulates and feedback inhibits phosphoethanolamine N-methyltransferase. Methionine S-methyltransferase (MMT) catalyzes the synthesis of S-methylmethionine (SMM) from methionine (Met) and S-adenosylmethionine (AdoMet). SMM can be

  7. Quantitative habitability.

    PubMed

    Shock, Everett L; Holland, Melanie E

    2007-12-01

    A framework is proposed for a quantitative approach to studying habitability. Considerations of environmental supply and organismal demand of energy lead to the conclusions that power units are most appropriate and that the units for habitability become watts per organism. Extreme and plush environments are revealed to be on a habitability continuum, and extreme environments can be quantified as those where power supply only barely exceeds demand. Strategies for laboratory and field experiments are outlined that would quantify power supplies, power demands, and habitability. An example involving a comparison of various metabolisms pursued by halophiles is shown to be well on the way to a quantitative habitability analysis.

  8. Pore-scale simulation of microbial growth using a genome-scale metabolic model: Implications for Darcy-scale reactive transport

    NASA Astrophysics Data System (ADS)

    Tartakovsky, G. D.; Tartakovsky, A. M.; Scheibe, T. D.; Fang, Y.; Mahadevan, R.; Lovley, D. R.

    2013-09-01

    Recent advances in microbiology have enabled the quantitative simulation of microbial metabolism and growth based on genome-scale characterization of metabolic pathways and fluxes. We have incorporated a genome-scale metabolic model of the iron-reducing bacteria Geobacter sulfurreducens into a pore-scale simulation of microbial growth based on coupling of iron reduction to oxidation of a soluble electron donor (acetate). In our model, fluid flow and solute transport is governed by a combination of the Navier-Stokes and advection-diffusion-reaction equations. Microbial growth occurs only on the surface of soil grains where solid-phase mineral iron oxides are available. Mass fluxes of chemical species associated with microbial growth are described by the genome-scale microbial model, implemented using a constraint-based metabolic model, and provide the Robin-type boundary condition for the advection-diffusion equation at soil grain surfaces. Conventional models of microbially-mediated subsurface reactions use a lumped reaction model that does not consider individual microbial reaction pathways, and describe reactions rates using empirically-derived rate formulations such as the Monod-type kinetics. We have used our pore-scale model to explore the relationship between genome-scale metabolic models and Monod-type formulations, and to assess the manifestation of pore-scale variability (microenvironments) in terms of apparent Darcy-scale microbial reaction rates. The genome-scale model predicted lower biomass yield, and different stoichiometry for iron consumption, in comparison to prior Monod formulations based on energetics considerations. We were able to fit an equivalent Monod model, by modifying the reaction stoichiometry and biomass yield coefficient, that could effectively match results of the genome-scale simulation of microbial behaviors under excess nutrient conditions, but predictions of the fitted Monod model deviated from those of the genome-scale model

  9. Pore-scale simulation of microbial growth using a genome-scale metabolic model: Implications for Darcy-scale reactive transport

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Tartakovsky, Guzel D.; Tartakovsky, Alexandre M.; Scheibe, Timothy D.

    2013-09-07

    Recent advances in microbiology have enabled the quantitative simulation of microbial metabolism and growth based on genome-scale characterization of metabolic pathways and fluxes. We have incorporated a genome-scale metabolic model of the iron-reducing bacteria Geobacter sulfurreducens into a pore-scale simulation of microbial growth based on coupling of iron reduction to oxidation of a soluble electron donor (acetate). In our model, fluid flow and solute transport is governed by a combination of the Navier-Stokes and advection-diffusion-reaction equations. Microbial growth occurs only on the surface of soil grains where solid-phase mineral iron oxides are available. Mass fluxes of chemical species associated withmore » microbial growth are described by the genome-scale microbial model, implemented using a constraint-based metabolic model, and provide the Robin-type boundary condition for the advection-diffusion equation at soil grain surfaces. Conventional models of microbially-mediated subsurface reactions use a lumped reaction model that does not consider individual microbial reaction pathways, and describe reactions rates using empirically-derived rate formulations such as the Monod-type kinetics. We have used our pore-scale model to explore the relationship between genome-scale metabolic models and Monod-type formulations, and to assess the manifestation of pore-scale variability (microenvironments) in terms of apparent Darcy-scale microbial reaction rates. The genome-scale model predicted lower biomass yield, and different stoichiometry for iron consumption, in comparisonto prior Monod formulations based on energetics considerations. We were able to fit an equivalent Monod model, by modifying the reaction stoichiometry and biomass yield coefficient, that could effectively match results of the genome-scale simulation of microbial behaviors under excess nutrient conditions, but predictions of the fitted Monod model deviated from those of the genome

  10. Pore-scale simulation of microbial growth using a genome-scale metabolic model: Implications for Darcy-scale reactive transport

    NASA Astrophysics Data System (ADS)

    Scheibe, T. D.; Tartakovsky, G.; Tartakovsky, A. M.; Fang, Y.; Mahadevan, R.; Lovley, D. R.

    2012-12-01

    Recent advances in microbiology have enabled the quantitative simulation of microbial metabolism and growth based on genome-scale characterization of metabolic pathways and fluxes. We have incorporated a genome-scale metabolic model of the iron-reducing bacteria Geobacter sulfurreducens into a pore-scale simulation of microbial growth based on coupling of iron reduction to oxidation of a soluble electron donor (acetate). In our model, fluid flow and solute transport is governed by a combination of the Navier-Stokes and advection-diffusion-reaction equations. Microbial growth occurs only on the surface of soil grains where solid-phase mineral iron oxides are available. Mass fluxes of chemical species associated with microbial growth are described by the genome-scale microbial model, implemented using a constraint-based metabolic model, and provide the Robin-type boundary condition for the advection-diffusion equation at soil grain surfaces. Conventional models of microbially-mediated subsurface reactions use a lumped reaction model that does not consider individual microbial reaction pathways, and describe reactions rates using empirically-derived rate formulations such as the Monod-type kinetics. We have used our pore-scale model to explore the relationship between genome-scale metabolic models and Monod-type formulations, and to assess the manifestation of pore-scale variability (microenvironments) in terms of apparent Darcy-scale microbial reaction rates. The genome-scale model predicted lower biomass yield, and different stoichiometry for iron consumption, in comparison to prior Monod formulations based on energetics considerations. We were able to fit an equivalent Monod model, by modifying the reaction stoichiometry and biomass yield coefficient, that could effectively match results of the genome-scale simulation of microbial behaviors under excess nutrient conditions, but predictions of the fitted Monod model deviated from those of the genome-scale model

  11. Perspectives in metabolic engineering: understanding cellular regulation towards the control of metabolic routes.

    PubMed

    Zadran, Sohila; Levine, Raphael D

    2013-01-01

    Metabolic engineering seeks to redirect metabolic pathways through the modification of specific biochemical reactions or the introduction of new ones with the use of recombinant technology. Many of the chemicals synthesized via introduction of product-specific enzymes or the reconstruction of entire metabolic pathways into engineered hosts that can sustain production and can synthesize high yields of the desired product as yields of natural product-derived compounds are frequently low, and chemical processes can be both energy and material expensive; current endeavors have focused on using biologically derived processes as alternatives to chemical synthesis. Such economically favorable manufacturing processes pursue goals related to sustainable development and "green chemistry". Metabolic engineering is a multidisciplinary approach, involving chemical engineering, molecular biology, biochemistry, and analytical chemistry. Recent advances in molecular biology, genome-scale models, theoretical understanding, and kinetic modeling has increased interest in using metabolic engineering to redirect metabolic fluxes for industrial and therapeutic purposes. The use of metabolic engineering has increased the productivity of industrially pertinent small molecules, alcohol-based biofuels, and biodiesel. Here, we highlight developments in the practical and theoretical strategies and technologies available for the metabolic engineering of simple systems and address current limitations.

  12. Systems biology analysis of drivers underlying hallmarks of cancer cell metabolism

    NASA Astrophysics Data System (ADS)

    Zielinski, Daniel C.; Jamshidi, Neema; Corbett, Austin J.; Bordbar, Aarash; Thomas, Alex; Palsson, Bernhard O.

    2017-01-01

    Malignant transformation is often accompanied by significant metabolic changes. To identify drivers underlying these changes, we calculated metabolic flux states for the NCI60 cell line collection and correlated the variance between metabolic states of these lines with their other properties. The analysis revealed a remarkably consistent structure underlying high flux metabolism. The three primary uptake pathways, glucose, glutamine and serine, are each characterized by three features: (1) metabolite uptake sufficient for the stoichiometric requirement to sustain observed growth, (2) overflow metabolism, which scales with excess nutrient uptake over the basal growth requirement, and (3) redox production, which also scales with nutrient uptake but greatly exceeds the requirement for growth. We discovered that resistance to chemotherapeutic drugs in these lines broadly correlates with the amount of glucose uptake. These results support an interpretation of the Warburg effect and glutamine addiction as features of a growth state that provides resistance to metabolic stress through excess redox and energy production. Furthermore, overflow metabolism observed may indicate that mitochondrial catabolic capacity is a key constraint setting an upper limit on the rate of cofactor production possible. These results provide a greater context within which the metabolic alterations in cancer can be understood.

  13. DRUM: A New Framework for Metabolic Modeling under Non-Balanced Growth. Application to the Carbon Metabolism of Unicellular Microalgae

    PubMed Central

    Baroukh, Caroline; Muñoz-Tamayo, Rafael; Steyer, Jean-Philippe; Bernard, Olivier

    2014-01-01

    Metabolic modeling is a powerful tool to understand, predict and optimize bioprocesses, particularly when they imply intracellular molecules of interest. Unfortunately, the use of metabolic models for time varying metabolic fluxes is hampered by the lack of experimental data required to define and calibrate the kinetic reaction rates of the metabolic pathways. For this reason, metabolic models are often used under the balanced growth hypothesis. However, for some processes such as the photoautotrophic metabolism of microalgae, the balanced-growth assumption appears to be unreasonable because of the synchronization of their circadian cycle on the daily light. Yet, understanding microalgae metabolism is necessary to optimize the production yield of bioprocesses based on this microorganism, as for example production of third-generation biofuels. In this paper, we propose DRUM, a new dynamic metabolic modeling framework that handles the non-balanced growth condition and hence accumulation of intracellular metabolites. The first stage of the approach consists in splitting the metabolic network into sub-networks describing reactions which are spatially close, and which are assumed to satisfy balanced growth condition. The left metabolites interconnecting the sub-networks behave dynamically. Then, thanks to Elementary Flux Mode analysis, each sub-network is reduced to macroscopic reactions, for which simple kinetics are assumed. Finally, an Ordinary Differential Equation system is obtained to describe substrate consumption, biomass production, products excretion and accumulation of some internal metabolites. DRUM was applied to the accumulation of lipids and carbohydrates of the microalgae Tisochrysis lutea under day/night cycles. The resulting model describes accurately experimental data obtained in day/night conditions. It efficiently predicts the accumulation and consumption of lipids and carbohydrates. PMID:25105494

  14. Inverse modeling of the terrestrial carbon flux in China with flux covariance among inverted regions

    NASA Astrophysics Data System (ADS)

    Wang, H.; Jiang, F.; Chen, J. M.; Ju, W.; Wang, H.

    2011-12-01

    Quantitative understanding of the role of ocean and terrestrial biosphere in the global carbon cycle, their response and feedback to climate change is required for the future projection of the global climate. China has the largest amount of anthropogenic CO2 emission, diverse terrestrial ecosystems and an unprecedented rate of urbanization. Thus information on spatial and temporal distributions of the terrestrial carbon flux in China is of great importance in understanding the global carbon cycle. We developed a nested inversion with focus in China. Based on Transcom 22 regions for the globe, we divide China and its neighboring countries into 17 regions, making 39 regions in total for the globe. A Bayesian synthesis inversion is made to estimate the terrestrial carbon flux based on GlobalView CO2 data. In the inversion, GEOS-Chem is used as the transport model to develop the transport matrix. A terrestrial ecosystem model named BEPS is used to produce the prior surface flux to constrain the inversion. However, the sparseness of available observation stations in Asia poses a challenge to the inversion for the 17 small regions. To obtain additional constraint on the inversion, a prior flux covariance matrix is constructed using the BEPS model through analyzing the correlation in the net carbon flux among regions under variable climate conditions. The use of the covariance among different regions in the inversion effectively extends the information content of CO2 observations to more regions. The carbon flux over the 39 land and ocean regions are inverted for the period from 2004 to 2009. In order to investigate the impact of introducing the covariance matrix with non-zero off-diagonal values to the inversion, the inverted terrestrial carbon flux over China is evaluated against ChinaFlux eddy-covariance observations after applying an upscaling methodology.

  15. A quantitative study of methanol/sorbitol co-feeding process of a Pichia pastoris Mut⁺/pAOX1-lacZ strain.

    PubMed

    Niu, Hongxing; Jost, Laurent; Pirlot, Nathalie; Sassi, Hosni; Daukandt, Marc; Rodriguez, Christian; Fickers, Patrick

    2013-04-08

    One of the main challenges for heterologous protein production by the methylotrophic yeast Pichia pastoris at large-scale is related to its high oxygen demand. A promising solution is a co-feeding strategy based on a methanol/sorbitol mixture during the induction phase. Nonetheless, a deep understanding of the cellular physiology and the regulation of the AOX1 promoter, used to govern heterologous protein production, during this co-feeding strategy is still scarce. Transient continuous cultures with a dilution rate of 0.023 h(-1) at 25°C were performed to quantitatively assess the benefits of a methanol/sorbitol co-feeding process with a Mut+ strain in which the pAOX1-lacZ construct served as a reporter gene. Cell growth and metabolism, including O2 consumption together with CO2 and heat production were analyzed with regard to a linear change of methanol fraction in the mixed feeding media. In addition, the regulation of the promoter AOX1 was investigated by means of β-galactosidase measurements. Our results demonstrated that the cell-specific oxygen consumption (qO2) could be reduced by decreasing the methanol fraction in the feeding media. More interestingly, maximal β-galactosidase cell-specific activity (>7500 Miller unit) and thus, optimal pAOX1 induction, was achieved and maintained in the range of 0.45 ~ 0.75 C-mol/C-mol of methanol fraction. In addition, the qO2 was reduced by 30% at most in those conditions. Based on a simplified metabolic network, metabolic flux analysis (MFA) was performed to quantify intracellular metabolic flux distributions during the transient continuous cultures, which further shed light on the advantages of methanol/sorbitol co-feeding process. Finally, our observations were further validated in fed-batch cultures. This study brings quantitative insight into the co-feeding process, which provides valuable data for the control of methanol/sorbitol co-feeding, aiming at enhancing biomass and heterologous protein productivities

  16. Nitrate addition to groundwater impacted by ethanol-blended fuel accelerates ethanol removal and mitigates the associated metabolic flux dilution and inhibition of BTEX biodegradation.

    PubMed

    Corseuil, Henry Xavier; Gomez, Diego E; Schambeck, Cássio Moraes; Ramos, Débora Toledo; Alvarez, Pedro J J

    2015-03-01

    A comparison of two controlled ethanol-blended fuel releases under monitored natural attenuation (MNA) versus nitrate biostimulation (NB) illustrates the potential benefits of augmenting the electron acceptor pool with nitrate to accelerate ethanol removal and thus mitigate its inhibitory effects on BTEX biodegradation. Groundwater concentrations of ethanol and BTEX were measured 2 m downgradient of the source zones. In both field experiments, initial source-zone BTEX concentrations represented less than 5% of the dissolved total organic carbon (TOC) associated with the release, and measurable BTEX degradation occurred only after the ethanol fraction in the multicomponent substrate mixture decreased sharply. However, ethanol removal was faster in the nitrate amended plot (1.4 years) than under natural attenuation conditions (3.0 years), which led to faster BTEX degradation. This reflects, in part, that an abundant substrate (ethanol) can dilute the metabolic flux of target pollutants (BTEX) whose biodegradation rate eventually increases with its relative abundance after ethanol is preferentially consumed. The fate and transport of ethanol and benzene were accurately simulated in both releases using RT3D with our general substrate interaction module (GSIM) that considers metabolic flux dilution. Since source zone benzene concentrations are relatively low compared to those of ethanol (or its degradation byproduct, acetate), our simulations imply that the initial focus of cleanup efforts (after free-product recovery) should be to stimulate the degradation of ethanol (e.g., by nitrate addition) to decrease its fraction in the mixture and speed up BTEX biodegradation. Copyright © 2014 Elsevier B.V. All rights reserved.

  17. Quantitative EEG correlations with brain glucose metabolic rate during anesthesia in volunteers.

    PubMed

    Alkire, M T

    1998-08-01

    To help elucidate the relationship between anesthetic-induced changes in the electroencephalogram (EEG) and the concurrent cerebral metabolic changes caused by anesthesia, positron emission tomography data of cerebral metabolism obtained in volunteers during anesthesia were correlated retrospectively with various concurrently measured EEG descriptors. Volunteers underwent functional brain imaging using the 18fluorodeoxyglucose technique; one scan always assessed awake-baseline cerebral metabolism (n = 7), and the other scans assessed metabolism during propofol sedation (n = 4), propofol anesthesia (n = 4), or isoflurane anesthesia (n = 5). The EEG was recorded continuously during metabolism assessment using a frontal-mastoid montage. Power spectrum variables, median frequency, 95% spectral edge, and bispectral index (BIS) values subsequently were correlated with the percentage of absolute cerebral metabolic reduction (PACMR) of glucose utilization caused by anesthesia. The percentage of absolute cerebral metabolic reduction, evident during anesthesia, trended median frequency (r = -0.46, P = 0.11), and the spectral edge (r = -0.52, P = 0.07), and correlated with anesthetic type (r = -0.70, P < 0.05), relative beta power (r = -0.60, P < 0.05), total power (r = 0.71,P < 0.01), and bispectral index (r = -0.81,P < 0.001). After controlling for anesthetic type, only bispectral index (r = 0.40, P = 0.08) and alpha power (r = 0.37, P = 0.10) approached significance for explaining residual percentage of absolute cerebral metabolic reduction prediction error. Some EEG descriptors correlated linearly with the magnitude of the cerebral metabolic reduction caused by propofol and isoflurane anesthesia. These data suggest that a physiologic link exists between the EEG and cerebral metabolism during anesthesia that is mathematically quantifiable.

  18. Fructose, insulin resistance, and metabolic dyslipidemia

    PubMed Central

    Basciano, Heather; Federico, Lisa; Adeli, Khosrow

    2005-01-01

    Obesity and type 2 diabetes are occurring at epidemic rates in the United States and many parts of the world. The "obesity epidemic" appears to have emerged largely from changes in our diet and reduced physical activity. An important but not well-appreciated dietary change has been the substantial increase in the amount of dietary fructose consumption from high intake of sucrose and high fructose corn syrup, a common sweetener used in the food industry. A high flux of fructose to the liver, the main organ capable of metabolizing this simple carbohydrate, perturbs glucose metabolism and glucose uptake pathways, and leads to a significantly enhanced rate of de novo lipogenesis and triglyceride (TG) synthesis, driven by the high flux of glycerol and acyl portions of TG molecules from fructose catabolism. These metabolic disturbances appear to underlie the induction of insulin resistance commonly observed with high fructose feeding in both humans and animal models. Fructose-induced insulin resistant states are commonly characterized by a profound metabolic dyslipidemia, which appears to result from hepatic and intestinal overproduction of atherogenic lipoprotein particles. Thus, emerging evidence from recent epidemiological and biochemical studies clearly suggests that the high dietary intake of fructose has rapidly become an important causative factor in the development of the metabolic syndrome. There is an urgent need for increased public awareness of the risks associated with high fructose consumption and greater efforts should be made to curb the supplementation of packaged foods with high fructose additives. The present review will discuss the trends in fructose consumption, the metabolic consequences of increased fructose intake, and the molecular mechanisms leading to fructose-induced lipogenesis, insulin resistance and metabolic dyslipidemia. PMID:15723702

  19. Elucidating central metabolic redox obstacles hindering ethanol production in Clostridium thermocellum

    DOE PAGES

    Thompson, R. Adam; Layton, Donovan S.; Guss, Adam M.; ...

    2015-10-21

    Clostridium thermocellum is an anaerobic, Gram-positive, thermophilic bacterium that has generated great interest due to its ability to ferment lignocellulosic biomass to ethanol. However, ethanol production is low due to the complex and poorly understood branched metabolism of C. thermocellum, and in some cases overflow metabolism as well. In this work, we developed a predictive stoichiometric metabolic model for C. thermocellum which incorporates the current state of understanding, with particular attention to cofactor specificity in the atypical glycolytic enzymes and the complex energy, redox, and fermentative pathways with the goal of aiding metabolic engineering efforts. We validated the model smore » capability to encompass experimentally observed phenotypes for the parent strain and derived mutants designed for significant perturbation of redox and energy pathways. Metabolic flux distributions revealed significant alterations in key metabolic branch points (e.g., phosphoenol pyruvate, pyruvate, acetyl-CoA, and cofactor nodes) in engineered strains for channeling electron and carbon fluxes for enhanced ethanol synthesis, with the best performing strain doubling ethanol yield and titer compared to the parent strain. In silico predictions of a redox-imbalanced genotype incapable of growth were confirmed in vivo, and a mutant strain was used as a platform to probe redox bottlenecks in the central metabolism that hinder efficient ethanol production. The results highlight the robustness of the redox metabolism of C. thermocellum and the necessity of streamlined electron flux from reduced ferredoxin to NAD(P)H for high ethanol production. The model was further used to design a metabolic engineering strategy to phenotypically constrain C. thermocellum to achieve high ethanol yields while requiring minimal genetic manipulations. Furthermore, the model can be applied to design C. thermocellum as a platform microbe for consolidated bioprocessing to produce ethanol

  20. How important is thermodynamics for identifying elementary flux modes?

    PubMed Central

    Peres, Sabine; Jolicœur, Mario; Moulin, Cécile

    2017-01-01

    We present a method for computing thermodynamically feasible elementary flux modes (tEFMs) using equilibrium constants without need of internal metabolite concentrations. The method is compared with the method based on a binary distinction between reversible and irreversible reactions. When all reactions are reversible, adding the constraints based on equilibrium constants reduces the number of elementary flux modes (EFMs) by a factor of two. Declaring in advance some reactions as irreversible, based on reliable biochemical expertise, can in general reduce the number of EFMs by a greater factor. But, even in this case, computing tEFMs can rule out some EFMs which are biochemically irrelevant. We applied our method to two published models described with binary distinction: the monosaccharide metabolism and the central carbon metabolism of Chinese hamster ovary cells. The results show that the binary distinction is in good agreement with biochemical observations. Moreover, the suppression of the EFMs that are not consistent with the equilibrium constants appears to be biologically relevant. PMID:28222104

  1. Genome-scale estimate of the metabolic turnover of E. Coli from the energy balance analysis

    NASA Astrophysics Data System (ADS)

    De Martino, D.

    2016-02-01

    In this article the notion of metabolic turnover is revisited in the light of recent results of out-of-equilibrium thermodynamics. By means of Monte Carlo methods we perform an exact sampling of the enzymatic fluxes in a genome scale metabolic network of E. Coli in stationary growth conditions from which we infer the metabolites turnover times. However the latter are inferred from net fluxes, and we argue that this approximation is not valid for enzymes working nearby thermodynamic equilibrium. We recalculate turnover times from total fluxes by performing an energy balance analysis of the network and recurring to the fluctuation theorem. We find in many cases values one of order of magnitude lower, implying a faster picture of intermediate metabolism.

  2. Engineering microorganisms to increase ethanol production by metabolic redirection

    DOEpatents

    Deng, Yu; Olson, Daniel G.; van Dijken, Johannes Pieter; Shaw, IV, Arthur J.; Argyros, Aaron; Barrett, Trisha; Caiazza, Nicky; Herring, Christopher D.; Rogers, Stephen R.; Agbogbo, Frank

    2017-10-31

    The present invention provides for the manipulation of carbon flux in a recombinant host cell to increase the formation of desirable products. The invention relates to cellulose-digesting organisms that have been genetically modified to allow the production of ethanol at a high yield by redirecting carbon flux at key steps of central metabolism.

  3. Distinct Mechanisms of the ORANGE Protein in Controlling Carotenoid Flux1[OPEN

    PubMed Central

    Ohali, Shachar; Meir, Ayala; Sa’ar, Uzi; Mazourek, Michael; Lewinsohn, Efraim; Schaffer, Arthur A.; Burger, Joseph

    2017-01-01

    β-Carotene adds nutritious value and determines the color of many fruits, including melon (Cucumis melo). In melon mesocarp, β-carotene accumulation is governed by the Orange gene (CmOr) golden single-nucleotide polymorphism (SNP) through a yet to be discovered mechanism. In Arabidopsis (Arabidopsis thaliana), OR increases carotenoid levels by posttranscriptionally regulating phytoene synthase (PSY). Here, we identified a CmOr nonsense mutation (Cmor-lowβ) that lowered fruit β-carotene levels with impaired chromoplast biogenesis. Cmor-lowβ exerted a minimal effect on PSY transcripts but dramatically decreased PSY protein levels and enzymatic activity, leading to reduced carotenoid metabolic flux and accumulation. However, the golden SNP was discovered to not affect PSY protein levels and carotenoid metabolic flux in melon fruit, as shown by carotenoid and immunoblot analyses of selected melon genotypes and by using chemical pathway inhibitors. The high β-carotene accumulation in golden SNP melons was found to be due to a reduced further metabolism of β-carotene. This was revealed by genetic studies with double mutants including carotenoid isomerase (yofi), a carotenoid-isomerase nonsense mutant, which arrests the turnover of prolycopene. The yofi F2 segregants accumulated prolycopene independently of the golden SNP. Moreover, Cmor-lowβ was found to inhibit chromoplast formation and chloroplast disintegration in fruits from 30 d after anthesis until ripening, suggesting that CmOr regulates the chloroplast-to-chromoplast transition. Taken together, our results demonstrate that CmOr is required to achieve PSY protein levels to maintain carotenoid biosynthesis metabolic flux but that the mechanism of the CmOr golden SNP involves an inhibited metabolism downstream of β-carotene to dramatically affect both carotenoid content and plastid fate. PMID:27837090

  4. Carbon Metabolism of Prochlorococcus sp. Under Nitrogen Limitation

    NASA Astrophysics Data System (ADS)

    Szul, M.

    2016-02-01

    Phytoplankton growth rates are limited by nutrient availability in the world's euphotic oligotrophic oceans. In these vast biomes, convergent evolutions of the dominant planktonic populations suggest traits such as small genome and cell size provide selective advantages. While these traits have been shown to improve both thrift and competition for scarce nutrients, how fitness is manifest through reductive evolution on metabolisms remains poorly understood. To develop a better understanding of carbon fate and flux under nutrient limitation, we grew axenic Prochlorococcus under nitrogen-limited and nitrogen-replete conditions and measured metabolite pools, the flux of carbon through these pools as well as photosynthesis, photosystem health and efficiency. Our data show cells under nitrogen limitation reduce rates of both metabolite flux and total carbon fixation while maintaining elevated metabolite pool levels and releasing a larger proportion of total fixed carbon to the environment. Accounting for these observations, potential metabolic mechanisms that contribute to the fitness of Prochlorococcus in the nutrient limited oceans will be discussed.

  5. Quantitative proteomics links metabolic pathways to specific developmental stages of the plant-pathogenic oomycete Phytophthora capsici.

    PubMed

    Pang, Zhili; Srivastava, Vaibhav; Liu, Xili; Bulone, Vincent

    2017-04-01

    The oomycete Phytophthora capsici is a plant pathogen responsible for important losses to vegetable production worldwide. Its asexual reproduction plays an important role in the rapid propagation and spread of the disease in the field. A global proteomics study was conducted to compare two key asexual life stages of P. capsici, i.e. the mycelium and cysts, to identify stage-specific biochemical processes. A total of 1200 proteins was identified using qualitative and quantitative proteomics. The transcript abundance of some of the enriched proteins was also analysed by quantitative real-time polymerase chain reaction. Seventy-three proteins exhibited different levels of abundance between the mycelium and cysts. The proteins enriched in the mycelium are mainly associated with glycolysis, the tricarboxylic acid (or citric acid) cycle and the pentose phosphate pathway, providing the energy required for the biosynthesis of cellular building blocks and hyphal growth. In contrast, the proteins that are predominant in cysts are essentially involved in fatty acid degradation, suggesting that the early infection stage of the pathogen relies primarily on fatty acid degradation for energy production. The data provide a better understanding of P. capsici biology and suggest potential metabolic targets at the two different developmental stages for disease control. © 2016 BSPP AND JOHN WILEY & SONS LTD.

  6. Flux response of glycolysis and storage metabolism during rapid feast/famine conditions in Penicillium chrysogenum using dynamic (13)C labeling.

    PubMed

    de Jonge, Lodewijk; Buijs, Nicolaas A A; Heijnen, Joseph J; van Gulik, Walter M; Abate, Alessandro; Wahl, S Aljoscha

    2014-03-01

    The scale-up of fermentation processes frequently leads to a reduced productivity compared to small-scale screening experiments. Large-scale mixing limitations that lead to gradients in substrate and oxygen availability could influence the microorganism performance. Here, the impact of substrate gradients on a penicillin G producing Penicillium chrysogenum cultivation was analyzed using an intermittent glucose feeding regime. The intermittent feeding led to fluctuations in the extracellular glucose concentration between 400 μM down to 6.5 μM at the end of the cycle. The intracellular metabolite concentrations responded strongly and showed up to 100-fold changes. The intracellular flux changes were estimated on the basis of dynamic (13) C mass isotopomer measurements during three cycles of feast and famine using a novel hybrid modeling approach. The flux estimations indicated a high turnover of internal and external storage metabolites in P. chrysogenum under feast/famine conditions. The synthesis and degradation of storage requires cellular energy (ATP and UTP) in competition with other cellular functions including product formation. Especially, 38% of the incoming glucose was recycled once in storage metabolism. This result indicated that storage turnover is increased under dynamic cultivation conditions and contributes to the observed decrease in productivity compared to reference steady-state conditions. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  7. Metabolite damage and repair in metabolic engineering design.

    PubMed

    Sun, Jiayi; Jeffryes, James G; Henry, Christopher S; Bruner, Steven D; Hanson, Andrew D

    2017-11-01

    The necessarily sharp focus of metabolic engineering and metabolic synthetic biology on pathways and their fluxes has tended to divert attention from the damaging enzymatic and chemical side-reactions that pathway metabolites can undergo. Although historically overlooked and underappreciated, such metabolite damage reactions are now known to occur throughout metabolism and to generate (formerly enigmatic) peaks detected in metabolomics datasets. It is also now known that metabolite damage is often countered by dedicated repair enzymes that undo or prevent it. Metabolite damage and repair are highly relevant to engineered pathway design: metabolite damage reactions can reduce flux rates and product yields, and repair enzymes can provide robust, host-independent solutions. Herein, after introducing the core principles of metabolite damage and repair, we use case histories to document how damage and repair processes affect efficient operation of engineered pathways - particularly those that are heterologous, non-natural, or cell-free. We then review how metabolite damage reactions can be predicted, how repair reactions can be prospected, and how metabolite damage and repair can be built into genome-scale metabolic models. Lastly, we propose a versatile 'plug and play' set of well-characterized metabolite repair enzymes to solve metabolite damage problems known or likely to occur in metabolic engineering and synthetic biology projects. Copyright © 2017 International Metabolic Engineering Society. All rights reserved.

  8. Drug metabolism in birds

    USGS Publications Warehouse

    Pan, Huo Ping; Fouts, James R.

    1979-01-01

    Papers published over 100 years since the beginning of the scientific study of drug metabolism in birds were reviewed. Birds were found to be able to accomplish more than 20 general biotransformation reactions in both functionalization and conjugation. Chickens were the primary subject of study but over 30 species of birds were used. Large species differences in drug metabolism exist between birds and mammals as well as between various birds, these differences were mostly quantitative. Qualitative differences were rare. On the whole, drug metabolism studies in birds have been neglected as compared with similar studies on insects and mammals. The uniqueness of birds and the advantages of using birds in drug metabolism studies are discussed. Possible future studies of drug metabolism in birds are recommended.

  9. A hybrid approach identifies metabolic signatures of high-producers for chinese hamster ovary clone selection and process optimization.

    PubMed

    Popp, Oliver; Müller, Dirk; Didzus, Katharina; Paul, Wolfgang; Lipsmeier, Florian; Kirchner, Florian; Niklas, Jens; Mauch, Klaus; Beaucamp, Nicola

    2016-09-01

    In-depth characterization of high-producer cell lines and bioprocesses is vital to ensure robust and consistent production of recombinant therapeutic proteins in high quantity and quality for clinical applications. This requires applying appropriate methods during bioprocess development to enable meaningful characterization of CHO clones and processes. Here, we present a novel hybrid approach for supporting comprehensive characterization of metabolic clone performance. The approach combines metabolite profiling with multivariate data analysis and fluxomics to enable a data-driven mechanistic analysis of key metabolic traits associated with desired cell phenotypes. We applied the methodology to quantify and compare metabolic performance in a set of 10 recombinant CHO-K1 producer clones and a host cell line. The comprehensive characterization enabled us to derive an extended set of clone performance criteria that not only captured growth and product formation, but also incorporated information on intracellular clone physiology and on metabolic changes during the process. These criteria served to establish a quantitative clone ranking and allowed us to identify metabolic differences between high-producing CHO-K1 clones yielding comparably high product titers. Through multivariate data analysis of the combined metabolite and flux data we uncovered common metabolic traits characteristic of high-producer clones in the screening setup. This included high intracellular rates of glutamine synthesis, low cysteine uptake, reduced excretion of aspartate and glutamate, and low intracellular degradation rates of branched-chain amino acids and of histidine. Finally, the above approach was integrated into a workflow that enables standardized high-content selection of CHO producer clones in a high-throughput fashion. In conclusion, the combination of quantitative metabolite profiling, multivariate data analysis, and mechanistic network model simulations can identify metabolic

  10. Measurement of air and VOC vapor fluxes during gas-driven soil remediation: bench-scale experiments.

    PubMed

    Kim, Heonki; Kim, Taeyun; Shin, Seungyeop; Annable, Michael D

    2012-09-04

    In this laboratory study, an experimental method was developed for the quantitative analyses of gas fluxes in soil during advective air flow. One-dimensional column and two- and three-dimensional flow chamber models were used in this study. For the air flux measurement, n-octane vapor was used as a tracer, and it was introduced in the air flow entering the physical models. The tracer (n-octane) in the gas effluent from the models was captured for a finite period of time using a pack of activated carbon, which then was analyzed for the mass of n-octane. The air flux was calculated based on the mass of n-octane captured by the activated carbon and the inflow concentration. The measured air fluxes are in good agreement with the actual values for one- and two-dimensional model experiments. Using both the two- and three-dimensional models, the distribution of the air flux at the soil surface was measured. The distribution of the air flux was found to be affected by the depth of the saturated zone. The flux and flux distribution of a volatile contaminant (perchloroethene) was also measured by using the two-dimensional model. Quantitative information of both air and contaminant flux may be very beneficial for analyzing the performance of gas-driven subsurface remediation processes including soil vapor extraction and air sparging.

  11. Metabolic Surgery Profoundly Influences Gut Microbial-Host Metabolic Crosstalk

    PubMed Central

    Li, Jia V.; Ashrafian, Hutan; Bueter, Marco; Kinross, James; Sands, Caroline; le Roux, Carel W; Bloom, Stephen R.; Darzi, Ara; Athanasiou, Thanos; Marchesi, Julian R.; Nicholson, Jeremy K.; Holmes, Elaine

    2013-01-01

    Background and Aims Bariatric surgery is increasingly performed worldwide to treat morbid obesity and is also known as metabolic surgery to reflect its beneficial metabolic effects especially with respect to improvement in type 2 diabetes. Understanding surgical weight loss mechanisms and metabolic modulation is required to enhance patient benefits and operative outcomes. Methods We apply a parallel and statistically integrated metagenomic and metabonomic approach to characterize Roux-en-Y gastric bypass (RYGB) effects in a rat model. Results We show substantial shifts of the main gut phyla towards higher levels of Proteobacteria (52-fold) specifically Enterobacter hormaechei. We also find low levels of Firmicutes (4.5-fold) and Bacteroidetes (2-fold) in comparison to sham-operated rats. Faecal extraction studies reveal a decrease in faecal bile acids and a shift from protein degradation to putrefaction through decreased faecal tyrosine with concomitant increases in faecal putrescine and diamnoethane. We find decreased urinary amines and cresols and demonstrate indices of modulated energy metabolism post-RYGB including decreased urinary succinate, 2-oxoglutarate, citrate and fumarate. These changes could also indicate renal tubular acidosis, which associates with increased flux of mitochondrial tricarboxylic acid cycle intermediates. A surgically-induced effect on the gut-brain-liver metabolic axis is inferred by increased neurotropic compounds; faecal γ-aminobutyric acid (GABA) and glutamate. Conclusion This profound co-dependence of mammalian and microbial metabolism, which is systematically altered following RYGB surgery, suggests that RYGB exerts local and global metabolic activities. The effect of RYGB surgery on the host metabolic-microbial crosstalk augments our understanding of the metabolic phenotype of bariatric procedures and can facilitate enhanced treatments for obesity-related diseases. PMID:21572120

  12. Siphon flows in isolated magnetic flux tubes. II - Adiabatic flows

    NASA Technical Reports Server (NTRS)

    Montesinos, Benjamin; Thomas, John H.

    1989-01-01

    This paper extends the study of steady siphon flows in isolated magnetic flux tubes surrounded by field-free gas to the case of adiabatic flows. The basic equations governing steady adiabatic siphon flows in a thin, isolated magnetic flux tube are summarized, and qualitative features of adiabatic flows in elevated, arched flux tubes are discussed. The equations are then cast in nondimensional form and the results of numerical computations of adiabatic siphon flows in arched flux tubes are presented along with comparisons between isothermal and adiabatic flows. The effects of making the interior of the flux tube hotter or colder than the surrounding atmosphere at the upstream footpoint of the arch is considered. In this case, is it found that the adiabatic flows are qualitatively similar to the isothermal flows, with adiabatic cooling producing quantitative differences. Critical flows can produce a bulge point in the rising part of the arch and a concentration of magnetic flux above the bulge point.

  13. Metabolic Analysis of Adaptation to Short-Term Changes in Culture Conditions of the Marine Diatom Thalassiosira pseudonana

    PubMed Central

    Bromke, Mariusz A.; Giavalisco, Patrick; Willmitzer, Lothar; Hesse, Holger

    2013-01-01

    This report describes the metabolic and lipidomic profiling of 97 low-molecular weight compounds from the primary metabolism and 124 lipid compounds of the diatom Thalassiosira pseudonana. The metabolic profiles were created for diatoms perturbed for 24 hours with four different treatments: (I) removal of nitrogen, (II) lower iron concentration, (III) addition of sea salt, (IV) addition of carbonate to their growth media. Our results show that as early as 24 hours after nitrogen depletion significant qualitative and quantitative change in lipid composition as well as in the primary metabolism of Thalassiosira pseudonana occurs. So we can observe the accumulation of several storage lipids, namely triacylglycerides, and TCA cycle intermediates, of which citric acid increases more than 10-fold. These changes are positively correlated with expression of TCA enzymes genes. Next to the TCA cycle intermediates and storage lipid changes, we have observed decrease in N-containing lipids and primary metabolites such as amino acids. As a measure of counteracting nitrogen starvation, we have observed elevated expression levels of nitrogen uptake and amino acid biosynthetic genes. This indicates that diatoms can fast and efficiently adapt to changing environment by altering the metabolic fluxes and metabolite abundances. Especially, the accumulation of proline and the decrease of dimethylsulfoniopropionate suggest that the proline is the main osmoprotectant for the diatom in nitrogen rich conditions. PMID:23799147

  14. Difference in C3-C4 metabolism underlies tradeoff between growth rate and biomass yield in Methylobacterium extorquens AM1.

    PubMed

    Fu, Yanfen; Beck, David A C; Lidstrom, Mary E

    2016-07-19

    Two variants of Methylobacterium extorquens AM1 demonstrated a trade-off between growth rate and biomass yield. In addition, growth rate and biomass yield were also affected by supplementation of growth medium with different amounts of cobalt. The metabolism changes relating to these growth phenomena as well as the trade-off were investigated in this study. (13)C metabolic flux analysis was used to generate a detailed central carbon metabolic flux map with both absolute and normalized flux values. The major differences between the two variants occurred at the formate node as well as within C3-C4 inter-conversion pathways. Higher relative fluxes through formyltetrahydrofolate ligase, phosphoenolpyruvate carboxylase, and malic enzyme led to higher biomass yield, while higher relative fluxes through pyruvate kinase and pyruvate dehydrogenase led to higher growth rate. These results were then tested by phenotypic studies on three mutants (null pyk, null pck mutant and null dme mutant) in both variants, which agreed with the model prediction. In this study, (13)C metabolic flux analysis for two strain variants of M. extorquens AM1 successfully identified metabolic pathways contributing to the trade-off between cell growth and biomass yield. Phenotypic analysis of mutants deficient in corresponding genes supported the conclusion that C3-C4 inter-conversion strategies were the major response to the trade-off.

  15. Metabolism and evolution: A comparative study of reconstructed genome-level metabolic networks

    NASA Astrophysics Data System (ADS)

    Almaas, Eivind

    2008-03-01

    The availability of high-quality annotations of sequenced genomes has made it possible to generate organism-specific comprehensive maps of cellular metabolism. Currently, more than twenty such metabolic reconstructions are publicly available, with the majority focused on bacteria. A typical metabolic reconstruction for a bacterium results in a complex network containing hundreds of metabolites (nodes) and reactions (links), while some even contain more than a thousand. The constrain-based optimization approach of flux-balance analysis (FBA) is used to investigate the functional characteristics of such large-scale metabolic networks, making it possible to estimate an organism's growth behavior in a wide variety of nutrient environments, as well as its robustness to gene loss. We have recently completed the genome-level metabolic reconstruction of Yersinia pseudotuberculosis, as well as the three Yersinia pestis biovars Antiqua, Mediaevalis, and Orientalis. While Y. pseudotuberculosis typically only causes fever and abdominal pain that can mimic appendicitis, the evolutionary closely related Y. pestis strains are the aetiological agents of the bubonic plague. In this presentation, I will discuss our results and conclusions from a comparative study on the evolution of metabolic function in the four Yersiniae networks using FBA and related techniques, and I will give particular focus to the interplay between metabolic network topology and evolutionary flexibility.

  16. High Upward Fluxes of Formic Acid from a Boreal Forest Canopy

    NASA Technical Reports Server (NTRS)

    Schobesberger, Siegfried; Lopez-Hilifiker, Felipe D.; Taipale, Ditte; Millet, Dylan B.; D'Ambro, Emma L.; Rantala, Pekka; Mammarella, Ivan; Zhou, Putian; Wolfe, Glenn M.; Lee, Ben H.; hide

    2016-01-01

    Eddy covariance fluxes of formic acid, HCOOH, were measured over a boreal forest canopy in spring/summer 2014. The HCOOH fluxes were bidirectional but mostly upward during daytime, in contrast to studies elsewhere that reported mostly downward fluxes. Downward flux episodes were explained well by modeled dry deposition rates. The sum of net observed flux and modeled dry deposition yields an upward gross flux of HCOOH, which could not be quantitatively explained by literature estimates of direct vegetative soil emissions nor by efficient chemical production from other volatile organic compounds, suggesting missing or greatly underestimated HCOOH sources in the boreal ecosystem. We implemented a vegetative HCOOH source into the GEOS-Chem chemical transport model to match our derived gross flux and evaluated the updated model against airborne and spaceborne observations. Model biases in the boundary layer were substantially reduced based on this revised treatment, but biases in the free troposphere remain unexplained.

  17. A model of blood-ammonia homeostasis based on a quantitative analysis of nitrogen metabolism in the multiple organs involved in the production, catabolism, and excretion of ammonia in humans.

    PubMed

    Levitt, David G; Levitt, Michael D

    2018-01-01

    Increased blood ammonia (NH 3 ) is an important causative factor in hepatic encephalopathy, and clinical treatment of hepatic encephalopathy is focused on lowering NH 3 . Ammonia is a central element in intraorgan nitrogen (N) transport, and modeling the factors that determine blood-NH 3 concentration is complicated by the need to account for a variety of reactions carried out in multiple organs. This review presents a detailed quantitative analysis of the major factors determining blood-NH 3 homeostasis - the N metabolism of urea, NH 3 , and amino acids by the liver, gastrointestinal system, muscle, kidney, and brain - with the ultimate goal of creating a model that allows for prediction of blood-NH 3 concentration. Although enormous amounts of NH 3 are produced during normal liver amino-acid metabolism, this NH 3 is completely captured by the urea cycle and does not contribute to blood NH 3 . While some systemic NH 3 derives from renal and muscle metabolism, the primary site of blood-NH 3 production is the gastrointestinal tract, as evidenced by portal vein-NH 3 concentrations that are about three times that of systemic blood. Three mechanisms, in order of quantitative importance, release NH 3 in the gut: 1) hydrolysis of urea by bacterial urease, 2) bacterial protein deamination, and 3) intestinal mucosal glutamine metabolism. Although the colon is conventionally assumed to be the major site of gut-NH 3 production, evidence is reviewed that indicates that the stomach (via Helicobacter pylori metabolism) and small intestine and may be of greater importance. In healthy subjects, most of this gut NH 3 is removed by the liver before reaching the systemic circulation. Using a quantitative model, loss of this "first-pass metabolism" due to portal collateral circulation can account for the hyperammonemia observed in chronic liver disease, and there is usually no need to implicate hepatocyte malfunction. In contrast, in acute hepatic necrosis, hyperammonemia results

  18. Integration of C₁ and C₂ Metabolism in Trees.

    PubMed

    Jardine, Kolby J; Fernandes de Souza, Vinicius; Oikawa, Patty; Higuchi, Niro; Bill, Markus; Porras, Rachel; Niinemets, Ülo; Chambers, Jeffrey Q

    2017-09-23

    C₁ metabolism in plants is known to be involved in photorespiration, nitrogen and amino acid metabolism, as well as methylation and biosynthesis of metabolites and biopolymers. Although the flux of carbon through the C₁ pathway is thought to be large, its intermediates are difficult to measure and relatively little is known about this potentially ubiquitous pathway. In this study, we evaluated the C₁ pathway and its integration with the central metabolism using aqueous solutions of 13 C-labeled C₁ and C₂ intermediates delivered to branches of the tropical species Inga edulis via the transpiration stream. Delivery of [ 13 C]methanol and [ 13 C]formaldehyde rapidly stimulated leaf emissions of [ 13 C]methanol, [ 13 C]formaldehyde, [ 13 C]formic acid, and 13 CO₂, confirming the existence of the C1 pathway and rapid interconversion between methanol and formaldehyde. However, while [ 13 C]formate solutions stimulated emissions of 13 CO₂, emissions of [ 13 C]methanol or [ 13 C]formaldehyde were not detected, suggesting that once oxidation to formate occurs it is rapidly oxidized to CO₂ within chloroplasts. 13 C-labeling of isoprene, a known photosynthetic product, was linearly related to 13 CO₂ across C₁ and C₂ ([ 13 C₂]acetate and [2- 13 C]glycine) substrates, consistent with reassimilation of C₁, respiratory, and photorespiratory CO₂. Moreover, [ 13 C]methanol and [ 13 C]formaldehyde induced a quantitative labeling of both carbon atoms of acetic acid emissions, possibly through the rapid turnover of the chloroplastic acetyl-CoA pool via glycolate oxidation. The results support a role of the C₁ pathway to provide an alternative carbon source for glycine methylation in photorespiration, enhance CO₂ concentrations within chloroplasts, and produce key C₂ intermediates (e.g., acetyl-CoA) central to anabolic and catabolic metabolism.

  19. Bonded Cumomer Analysis of Human Melanoma Metabolism Monitored by 13C NMR Spectroscopy of Perfused Tumor Cells*

    PubMed Central

    Shestov, Alexander A.; Mancuso, Anthony; Lee, Seung-Cheol; Guo, Lili; Nelson, David S.; Roman, Jeffrey C.; Henry, Pierre-Gilles; Leeper, Dennis B.; Blair, Ian A.; Glickson, Jerry D.

    2016-01-01

    A network model for the determination of tumor metabolic fluxes from 13C NMR kinetic isotopomer data has been developed and validated with perfused human DB-1 melanoma cells carrying the BRAF V600E mutation, which promotes oxidative metabolism. The model generated in the bonded cumomer formalism describes key pathways of tumor intermediary metabolism and yields dynamic curves for positional isotopic enrichment and spin-spin multiplets. Cells attached to microcarrier beads were perfused with 26 mm [1,6-13C2]glucose under normoxic conditions at 37 °C and monitored by 13C NMR spectroscopy. Excellent agreement between model-predicted and experimentally measured values of the rates of oxygen and glucose consumption, lactate production, and glutamate pool size validated the model. ATP production by glycolytic and oxidative metabolism were compared under hyperglycemic normoxic conditions; 51% of the energy came from oxidative phosphorylation and 49% came from glycolysis. Even though the rate of glutamine uptake was ∼50% of the tricarboxylic acid cycle flux, the rate of ATP production from glutamine was essentially zero (no glutaminolysis). De novo fatty acid production was ∼6% of the tricarboxylic acid cycle flux. The oxidative pentose phosphate pathway flux was 3.6% of glycolysis, and three non-oxidative pentose phosphate pathway exchange fluxes were calculated. Mass spectrometry was then used to compare fluxes through various pathways under hyperglycemic (26 mm) and euglycemic (5 mm) conditions. Under euglycemic conditions glutamine uptake doubled, but ATP production from glutamine did not significantly change. A new parameter measuring the Warburg effect (the ratio of lactate production flux to pyruvate influx through the mitochondrial pyruvate carrier) was calculated to be 21, close to upper limit of oxidative metabolism. PMID:26703469

  20. Probing soil C metabolism in response to temperature: results from experiments and modeling

    NASA Astrophysics Data System (ADS)

    Dijkstra, P.; Dalder, J.; Blankinship, J.; Selmants, P. C.; Schwartz, E.; Koch, G. W.; Hart, S.; Hungate, B. A.

    2010-12-01

    C use efficiency (CUE) is one of the least understood aspects of soil C cycling, has a very large effect on soil respiration and C sequestration, and decreases with elevated temperature. CUE is directly related to substrate partitioning over energy production and biosynthesis. The production of energy and metabolic precursors occurs in well-known processes such as glycolysis and Krebs cycle. We have developed a new stable isotope approach using position-specific 13C-labeled metabolic tracers to measure these fundamental metabolic processes in intact soil communities (1). We use this new approach, combined with models of soil metabolic flux patterns, to analyze the response of microbial energy production, biosynthesis, and CUE to temperature. The method consists of adding small but precise amounts of position-specific 13C -labeled metabolic tracers to parallel soil incubations, in this case 1-13C and 2,3-13C pyruvate and 1-13C and U-13C glucose. The measurement of CO2 released from the labeled tracers is used to calculate the C flux rates through various metabolic pathways. A simplified metabolic model consisting of 23 reactions is iteratively solved using results of the metabolic tracer experiments and information on microbial precursor demand under different temperatures. This new method enables direct study of fundamental aspects of microbial energy production, C use efficiency, and soil organic matter formation in response to temperature. (1) Dijkstra P, Blankinship JC, Selmants PC, Hart SC, Koch GW, Schwarz E and Hungate BA. Probing metabolic flux patterns of soil microbial communities using parallel position-specific tracer labeling. Soil Biology and Biochemistry (accepted)

  1. Metabolic Flux Redirection and Transcriptomic Reprogramming in the Albino Tea Cultivar ‘Yu-Jin-Xiang’ with an Emphasis on Catechin Production

    PubMed Central

    Liu, Guo-Feng; Han, Zhuo-Xiao; Feng, Lin; Gao, Li-Ping; Gao, Ming-Jun; Gruber, Margaret Y.; Zhang, Zhao-Liang; Xia, Tao; Wan, Xiao-Chun; Wei, Shu

    2017-01-01

    In this study, shade-induced conversion from a young pale/yellow leaf phenotype to a green leaf phenotype was studied using metabolic and transcriptomic profiling and the albino cultivar ‘Yu-Jin-Xiang’ (‘YJX’) of Camellia sinensis for a better understanding of mechanisms underlying the phenotype shift and the altered catechin and theanine production. Shaded leaf greening resulted from an increase in leaf chlorophyll and carotenoid abundance and chloroplast development. A total of 1,196 differentially expressed genes (DEGs) were identified between the ‘YJX’ pale and shaded green leaves, and these DEGs affected ‘chloroplast organization’ and ‘response to high light’ besides many other biological processes and pathways. Metabolic flux redirection and transcriptomic reprogramming were found in flavonoid and carotenoid pathways of the ‘YJX’ pale leaves and shaded green leaves to different extents compared to the green cultivar ‘Shu-Cha-Zao’. Enhanced production of the antioxidant quercetin rather than catechin biosynthesis was correlated positively with the enhanced transcription of FLAVONOL SYNTHASE and FLAVANONE/FLAVONOL HYDROXYLASES leading to quercetin accumulation and negatively correlated to suppressed LEUCOANTHOCYANIDIN REDUCTASE, ANTHOCYANIDIN REDUCTASE and SYNTHASE leading to catechin biosynthesis. The altered levels of quercetin and catechins in ‘YJX’ will impact on its tea flavor and health benefits. PMID:28332598

  2. Washout of water-soluble vitamins and of homocysteine during haemodialysis: effect of high-flux and low-flux dialyser membranes.

    PubMed

    Heinz, Judith; Domröse, Ute; Westphal, Sabine; Luley, Claus; Neumann, Klaus H; Dierkes, Jutta

    2008-10-01

    Vitamin deficiencies are common in patients with end-stage renal disease (ESRD) owing to dietary restrictions, drug-nutrient interactions, changes in metabolism, and vitamin losses during dialysis. The present study investigated the levels of serum and red blood cell (RBC) folate, plasma pyridoxal-5'-phosphate (PLP), serum cobalamin, blood thiamine, blood riboflavin, and plasma homocysteine (tHcy) before and after haemodialysis treatment. Vitamin and tHcy blood concentrations were measured in 30 patients with ESRD before and after dialysis session either with low-flux (n = 15) or high-flux (n = 15) dialysers. After the dialysis procedure, significantly lower concentrations of serum folate (37%), plasma PLP (35%), blood thiamine (6%) and blood riboflavin (7%) were observed. No significant changes were found for serum cobalamin or for RBC folate. There were no differences in the washout of water-soluble vitamins between treatments with low-flux and high-flux membranes. Furthermore, a 41% lower concentration in tHcy was observed. The percentage decrease in tHcy was significantly greater in the patients treated with high-flux dialysers (48% vs 37%; P < 0.01). The percentage change during dialysis was significantly inversely related to the molecular weight of the vitamins measured (r =-0.867, P < 0.01). This study showed significantly lower blood or serum levels of various water-soluble vitamins after dialysis, independently of the dialyser membrane. The monitoring of the vitamin status is essential in patients treated with high-flux dialysers as well as in patients treated with low-flux dialysers.

  3. Combinatorial complexity of pathway analysis in metabolic networks.

    PubMed

    Klamt, Steffen; Stelling, Jörg

    2002-01-01

    Elementary flux mode analysis is a promising approach for a pathway-oriented perspective of metabolic networks. However, in larger networks it is hampered by the combinatorial explosion of possible routes. In this work we give some estimations on the combinatorial complexity including theoretical upper bounds for the number of elementary flux modes in a network of a given size. In a case study, we computed the elementary modes in the central metabolism of Escherichia coli while utilizing four different substrates. Interestingly, although the number of modes occurring in this complex network can exceed half a million, it is still far below the upper bound. Hence, to a certain extent, pathway analysis of central catabolism is feasible to assess network properties such as flexibility and functionality.

  4. SU-G-TeP3-10: Radiation Induces Prompt Live-Cell Metabolic Fluxes

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Campos, D; Peeters, W; Bussink, J

    2016-06-15

    Purpose: To compare metabolic dynamics and HIF-1α expression following radiation between a cancerous cell line (UM-SCC-22B) and a normal, immortalized cell line, NOK (Normal Oral Keratinocyte). HIF-1 is a key factor in metabolism and radiosensitivity. A better understanding of how radiation affects the interplay of metabolism and HIF-1 might give a better understanding of the mechanisms responsible for radiosensitivity. Methods: Changes in cellular metabolism in response to radiation are tracked by fluorescence lifetime of NADH. Expression of HIF-1α was measured by immunofluorescence for both cell lines with and without irradiation. Radiation response is also monitored with additional treatment of amore » HIF-1α inhibitor (chrysin) as well as a radical scavenger (glutathione). Changes in oxygen consumption and respiratory capacity are also monitored using the Seahorse XF analyzer. Results: An increase in HIF-1α was found to be in response to radiation for the cancer cell line, but not the normal cell line. Radiation was found to shift metabolism toward glycolytic pathways in cancer cells as measured by oxygen consumption and respiratory capacity. Radiation response was found to be muted by addition of glutathione to cell media. HIF-1α inhibition similarly muted radiation response in cancer. Conclusion: The HIF-1 protein complex is a key regulator cellular metabolism through the regulation of glycolysis and glucose transport enzymes. Moreover, HIF-1 has shown radio-protective effects in tumor vascular endothelia, and has been implicated in metastatic aggression. Monitoring interplay between metabolism and the HIF-1 protein complex can give a more fundamental understanding of radiotherapy response.« less

  5. Carboxylesterase-mediated insecticide resistance: Quantitative increase induces broader metabolic resistance than qualitative change.

    PubMed

    Cui, Feng; Li, Mei-Xia; Chang, Hai-Jing; Mao, Yun; Zhang, Han-Ying; Lu, Li-Xia; Yan, Shuai-Guo; Lang, Ming-Lin; Liu, Li; Qiao, Chuan-Ling

    2015-06-01

    Carboxylesterases are mainly involved in the mediation of metabolic resistance of many insects to organophosphate (OP) insecticides. Carboxylesterases underwent two divergent evolutionary events: (1) quantitative mechanism characterized by the overproduction of carboxylesterase protein; and (2) qualitative mechanism caused by changes in enzymatic properties because of mutation from glycine/alanine to aspartate at the 151 site (G/A151D) or from tryptophan to leucine at the 271 site (W271L), following the numbering of Drosophila melanogaster AChE. Qualitative mechanism has been observed in few species. However, whether this carboxylesterase mutation mechanism is prevalent in insects remains unclear. In this study, wild-type, G/A151D and W271L mutant carboxylesterases from Culex pipiens and Aphis gossypii were subjected to germline transformation and then transferred to D. melanogaster. These germlines were ubiquitously expressed as induced by tub-Gal4. In carboxylesterase activity assay, the introduced mutant carboxylesterase did not enhance the overall carboxylesterase activity of flies. This result indicated that G/A151D or W271L mutation disrupted the original activities of the enzyme. Less than 1.5-fold OP resistance was only observed in flies expressing A. gossypii mutant carboxylesterases compared with those expressing A. gossypii wild-type carboxylesterase. However, transgenic flies universally showed low resistance to OP insecticides compared with non-transgenic flies. The flies expressing A. gossypii W271L mutant esterase exhibited 1.5-fold resistance to deltamethrin, a pyrethroid insecticide compared with non-transgenic flies. The present transgenic Drosophila system potentially showed that a quantitative increase in carboxylesterases induced broader resistance of insects to insecticides than a qualitative change. Copyright © 2014 Elsevier Inc. All rights reserved.

  6. Mitochondrial metabolism mediates oxidative stress and inflammation in fatty liver

    PubMed Central

    Satapati, Santhosh; Kucejova, Blanka; Duarte, Joao A.G.; Fletcher, Justin A.; Reynolds, Lacy; Sunny, Nishanth E.; He, Tianteng; Nair, L. Arya; Livingston, Kenneth; Fu, Xiaorong; Merritt, Matthew E.; Sherry, A. Dean; Malloy, Craig R.; Shelton, John M.; Lambert, Jennifer; Parks, Elizabeth J.; Corbin, Ian; Magnuson, Mark A.; Browning, Jeffrey D.; Burgess, Shawn C.

    2015-01-01

    Mitochondria are critical for respiration in all tissues; however, in liver, these organelles also accommodate high-capacity anaplerotic/cataplerotic pathways that are essential to gluconeogenesis and other biosynthetic activities. During nonalcoholic fatty liver disease (NAFLD), mitochondria also produce ROS that damage hepatocytes, trigger inflammation, and contribute to insulin resistance. Here, we provide several lines of evidence indicating that induction of biosynthesis through hepatic anaplerotic/cataplerotic pathways is energetically backed by elevated oxidative metabolism and hence contributes to oxidative stress and inflammation during NAFLD. First, in murine livers, elevation of fatty acid delivery not only induced oxidative metabolism, but also amplified anaplerosis/cataplerosis and caused a proportional rise in oxidative stress and inflammation. Second, loss of anaplerosis/cataplerosis via genetic knockdown of phosphoenolpyruvate carboxykinase 1 (Pck1) prevented fatty acid–induced rise in oxidative flux, oxidative stress, and inflammation. Flux appeared to be regulated by redox state, energy charge, and metabolite concentration, which may also amplify antioxidant pathways. Third, preventing elevated oxidative metabolism with metformin also normalized hepatic anaplerosis/cataplerosis and reduced markers of inflammation. Finally, independent histological grades in human NAFLD biopsies were proportional to oxidative flux. Thus, hepatic oxidative stress and inflammation are associated with elevated oxidative metabolism during an obesogenic diet, and this link may be provoked by increased work through anabolic pathways. PMID:26571396

  7. Genome-Scale Metabolic Model for the Green Alga Chlorella vulgaris UTEX 395 Accurately Predicts Phenotypes under Autotrophic, Heterotrophic, and Mixotrophic Growth Conditions1

    PubMed Central

    Zuñiga, Cristal; Li, Chien-Ting; Zielinski, Daniel C.; Guarnieri, Michael T.; Antoniewicz, Maciek R.; Zengler, Karsten

    2016-01-01

    The green microalga Chlorella vulgaris has been widely recognized as a promising candidate for biofuel production due to its ability to store high lipid content and its natural metabolic versatility. Compartmentalized genome-scale metabolic models constructed from genome sequences enable quantitative insight into the transport and metabolism of compounds within a target organism. These metabolic models have long been utilized to generate optimized design strategies for an improved production process. Here, we describe the reconstruction, validation, and application of a genome-scale metabolic model for C. vulgaris UTEX 395, iCZ843. The reconstruction represents the most comprehensive model for any eukaryotic photosynthetic organism to date, based on the genome size and number of genes in the reconstruction. The highly curated model accurately predicts phenotypes under photoautotrophic, heterotrophic, and mixotrophic conditions. The model was validated against experimental data and lays the foundation for model-driven strain design and medium alteration to improve yield. Calculated flux distributions under different trophic conditions show that a number of key pathways are affected by nitrogen starvation conditions, including central carbon metabolism and amino acid, nucleotide, and pigment biosynthetic pathways. Furthermore, model prediction of growth rates under various medium compositions and subsequent experimental validation showed an increased growth rate with the addition of tryptophan and methionine. PMID:27372244

  8. Functional Alignment of Metabolic Networks.

    PubMed

    Mazza, Arnon; Wagner, Allon; Ruppin, Eytan; Sharan, Roded

    2016-05-01

    Network alignment has become a standard tool in comparative biology, allowing the inference of protein function, interaction, and orthology. However, current alignment techniques are based on topological properties of networks and do not take into account their functional implications. Here we propose, for the first time, an algorithm to align two metabolic networks by taking advantage of their coupled metabolic models. These models allow us to assess the functional implications of genes or reactions, captured by the metabolic fluxes that are altered following their deletion from the network. Such implications may spread far beyond the region of the network where the gene or reaction lies. We apply our algorithm to align metabolic networks from various organisms, ranging from bacteria to humans, showing that our alignment can reveal functional orthology relations that are missed by conventional topological alignments.

  9. Computational modelling of cellular level metabolism

    NASA Astrophysics Data System (ADS)

    Calvetti, D.; Heino, J.; Somersalo, E.

    2008-07-01

    The steady and stationary state inverse problems consist of estimating the reaction and transport fluxes, blood concentrations and possibly the rates of change of some of the concentrations based on data which are often scarce noisy and sampled over a population. The Bayesian framework provides a natural setting for the solution of this inverse problem, because a priori knowledge about the system itself and the unknown reaction fluxes and transport rates can compensate for the insufficiency of measured data, provided that the computational costs do not become prohibitive. This article identifies the computational challenges which have to be met when analyzing the steady and stationary states of multicompartment model for cellular metabolism and suggest stable and efficient ways to handle the computations. The outline of a computational tool based on the Bayesian paradigm for the simulation and analysis of complex cellular metabolic systems is also presented.

  10. IDAWG: Metabolic incorporation of stable isotope labels for quantitative glycomics of cultured cells

    PubMed Central

    Orlando, Ron; Lim, Jae-Min; Atwood, James A.; Angel, Peggi M.; Fang, Meng; Aoki, Kazuhiro; Alvarez-Manilla, Gerardo; Moremen, Kelley W.; York, William S.; Tiemeyer, Michael; Pierce, Michael; Dalton, Stephen; Wells, Lance

    2012-01-01

    Robust quantification is an essential component of comparative –omic strategies. In this regard, glycomics lags behind proteomics. Although various isotope-tagging and direct quantification methods have recently enhanced comparative glycan analysis, a cell culture labeling strategy, that could provide for glycomics the advantages that SILAC provides for proteomics, has not been described. Here we report the development of IDAWG, Isotopic Detection of Aminosugars With Glutamine, for the incorporation of differential mass tags into the glycans of cultured cells. In this method, culture media containing amide-15N-Gln is used to metabolically label cellular aminosugars with heavy nitrogen. Because the amide side chain of Gln is the sole source of nitrogen for the biosynthesis of GlcNAc, GalNAc, and sialic acid, we demonstrate that culturing mouse embryonic stems cells for 72 hours in the presence of amide-15N-Gln media results in nearly complete incorporation of 15N into N-linked and O-linked glycans. The isotopically heavy monosaccharide residues provide additional information for interpreting glycan fragmentation and also allow quantification in both full MS and MS/MS modes. Thus, IDAWG is a simple to implement, yet powerful quantitative tool for the glycomics toolbox. PMID:19449840

  11. Metal impurity fluxes and plasma-surface interactions in EXTRAP T2R

    NASA Astrophysics Data System (ADS)

    Bergsåker, H.; Menmuir, S.; Rachlew, E.; Brunsell, P. R.; Frassinetti, L.; Drake, J. R.

    2008-03-01

    The EXTRAP T2R is a large aspect ratio Reversed Field Pinch device. The main focus of interest for the experiments is the active feedback control of resistive wall modes [1]. With feedback it has been possible to prolong plasma discharges in T2R from about 20 ms to nearly 100 ms. In a series of experiments in T2R, in H- and D- plasmas with and without feedback, quantitative spectroscopy and passive collector probes have been used to study the flux of metal impurities. Time resolved spectroscopic measurements of Cr and Mo lines showed large metal release towards discharge termination without feedback. Discharge integrated fluxes of Cr, Fe, Ni and Mo were also measured with collector probes at wall position. Reasonable quantitative agreement was found between the spectroscopic and collector probe measurements. The roles of sputtering, thermal evaporation and arcing in impurity production are evaluated based on the composition of the measured impurity flux.

  12. Lipid-induced metabolic dysfunction in skeletal muscle.

    PubMed

    Muoio, Deborah M; Koves, Timothy R

    2007-01-01

    Insulin resistance is a hallmark of type 2 diabetes and commonly observed in other energy-stressed settings such as obesity, starvation, inactivity and ageing. Dyslipidaemia and 'lipotoxicity'--tissue accumulation of lipid metabolites-are increasingly recognized as important drivers of insulin resistant states. Mounting evidence suggests that lipid-induced metabolic dysfunction in skeletal muscle is mediated in large part by stress-activated serine kinases that interfere with insulin signal transduction. However, the metabolic and molecular events that connect lipid oversupply to stress kinase activation and glucose intolerance are as yet unclear. Application of transcriptomics and targeted mass spectrometry-based metabolomics tools has led to our finding that insulin resistance is a condition in which muscle mitochondria are persistently burdened with a heavy lipid load. As a result, high rates of beta-oxidation outpace metabolic flux through the TCA cycle, leading to accumulation of incompletely oxidized acyl-carnitine intermediates. In contrast, exercise training enhances mitochondrial performance, favouring tighter coupling between beta-oxidation and the TCA cycle, and concomitantly restores insulin sensitivity in animals fed a chronic high fat diet. The exercise-activated transcriptional co-activator, PGC1alpha, plays a key role in co-ordinating metabolic flux through these two intersecting metabolic pathways, and its suppression by overfeeding may contribute to obesity-associated mitochondrial dysfunction. Our emerging model predicts that muscle insulin resistance arises from mitochondrial lipid stress and a resultant disconnect between beta-oxidation and TCA cycle activity. Understanding this 'disconnect' and its molecular basis may lead to new therapeutic targets for combating metabolic disease.

  13. FLUXNET to MODIS: Connecting the dots to capture heterogenious biosphere metabolism

    NASA Astrophysics Data System (ADS)

    Woods, K. D.; Schwalm, C.; Huntzinger, D. N.; Massey, R.; Poulter, B.; Kolb, T.

    2015-12-01

    Eddy co-variance flux towers provide our most widely distributed network of direct observations for land-atmosphere carbon exchange. Carbon flux sensitivity analysis is a method that uses in situ networks to understand how ecosystems respond to changes in climatic variables. Flux towers concurrently observe key ecosystem metabolic processes (e..g. gross primary productivity) and micrometeorological variation, but only over small footprints. Remotely sensed vegetation indices from MODIS offer continuous observations of the vegetated land surface, but are less direct, as they are based on light use efficiency algorithms, and not on the ground observations. The marriage of these two data products offers an opportunity to validate remotely sensed indices with in situ observations and translate information derived from tower sites to globally gridded products. Here we provide correlations between Enhanced Vegetation Index (EVI), Leaf Area Index (LAI) and MODIS gross primary production with FLUXNET derived estimates of gross primary production, respiration and net ecosystem exchange. We demonstrate remotely sensed vegetation products which have been transformed to gridded estimates of terrestrial biosphere metabolism on a regional-to-global scale. We demonstrate anomalies in gross primary production, respiration, and net ecosystem exchange as predicted by both MODIS-carbon flux sensitivities and meteorological driver-carbon flux sensitivities. We apply these sensitivities to recent extreme climatic events and demonstrate both our ability to capture changes in biosphere metabolism, and differences in the calculation of carbon flux anomalies based on method. The quantification of co-variation in these two methods of observation is important as it informs both how remotely sensed vegetation indices are correlated with on the ground tower observations, and with what certainty we can expand these observations and relationships.

  14. A review of standardized metabolic phenotyping of animal models.

    PubMed

    Rozman, Jan; Klingenspor, Martin; Hrabě de Angelis, Martin

    2014-10-01

    Metabolic phenotyping of genetically modified animals aims to detect new candidate genes and related metabolic pathways that result in dysfunctional energy balance regulation and predispose for diseases such as obesity or type 2 diabetes mellitus. In this review, we provide a comprehensive overview on the technologies available to monitor energy flux (food uptake, bomb calorimetry of feces and food, and indirect calorimetry) and body composition (qNMR, DXA, and MRI) in animal models for human diseases with a special focus on phenotyping methods established in genetically engineered mice. We use an energy flux model to illustrate the principles of energy allocation, describe methodological aspects how to monitor energy balance, and introduce strategies for data analysis and presentation.

  15. Fusarium oxysporum mediates systems metabolic reprogramming of chickpea roots as revealed by a combination of proteomics and metabolomics.

    PubMed

    Kumar, Yashwant; Zhang, Limin; Panigrahi, Priyabrata; Dholakia, Bhushan B; Dewangan, Veena; Chavan, Sachin G; Kunjir, Shrikant M; Wu, Xiangyu; Li, Ning; Rajmohanan, Pattuparambil R; Kadoo, Narendra Y; Giri, Ashok P; Tang, Huiru; Gupta, Vidya S

    2016-07-01

    Molecular changes elicited by plants in response to fungal attack and how this affects plant-pathogen interaction, including susceptibility or resistance, remain elusive. We studied the dynamics in root metabolism during compatible and incompatible interactions between chickpea and Fusarium oxysporum f. sp. ciceri (Foc), using quantitative label-free proteomics and NMR-based metabolomics. Results demonstrated differential expression of proteins and metabolites upon Foc inoculations in the resistant plants compared with the susceptible ones. Additionally, expression analysis of candidate genes supported the proteomic and metabolic variations in the chickpea roots upon Foc inoculation. In particular, we found that the resistant plants revealed significant increase in the carbon and nitrogen metabolism; generation of reactive oxygen species (ROS), lignification and phytoalexins. The levels of some of the pathogenesis-related proteins were significantly higher upon Foc inoculation in the resistant plant. Interestingly, results also exhibited the crucial role of altered Yang cycle, which contributed in different methylation reactions and unfolded protein response in the chickpea roots against Foc. Overall, the observed modulations in the metabolic flux as outcome of several orchestrated molecular events are determinant of plant's role in chickpea-Foc interactions. © 2016 The Authors. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd.

  16. DOE Office of Scientific and Technical Information (OSTI.GOV)

    Schwender, Jorg; Konig, Christina; Klapperstuck, Matthias

    An attempt has been made to define the extent to which metabolic flux in central plant metabolism is reflected by changes in the transcriptome and metabolome, based on an analysis of in vitro cultured immature embryos of two oilseed rape (Brassica napus) accessions which contrast for seed lipid accumulation. Metabolic flux analysis (MFA) was used to constrain a flux balance metabolic model which included 671 biochemical and transport reactions within the central metabolism. This highly confident flux information was eventually used for comparative analysis of flux vs. transcript (metabolite). Metabolite profiling succeeded in identifying 79 intermediates within the central metabolism,more » some of which differed quantitatively between the two accessions and displayed a significant shift corresponding to flux. An RNA-Seq based transcriptome analysis revealed a large number of genes which were differentially transcribed in the two accessions, including some enzymes/proteins active in major metabolic pathways. With a few exceptions, differential activity in the major pathways (glycolysis, TCA cycle, amino acid, and fatty acid synthesis) was not reflected in contrasting abundances of the relevant transcripts. The conclusion was that transcript abundance on its own cannot be used to infer metabolic activity/fluxes in central plant metabolism. Lastly, this limitation needs to be borne in mind in evaluating transcriptome data and designing metabolic engineering experiments.« less

  17. Metabolic profiling of PPARalpha-/- mice reveals defects in carnitine and amino acid homeostasis that are partially reversed by oral carnitine supplementation.

    PubMed

    Makowski, Liza; Noland, Robert C; Koves, Timothy R; Xing, Weibing; Ilkayeva, Olga R; Muehlbauer, Michael J; Stevens, Robert D; Muoio, Deborah M

    2009-02-01

    Peroxisome proliferator-activated receptor-alpha (PPARalpha) is a master transcriptional regulator of beta-oxidation and a prominent target of hypolipidemic drugs. To gain deeper insights into the systemic consequences of impaired fat catabolism, we used quantitative, mass spectrometry-based metabolic profiling to investigate the fed-to-fasted transition in PPARalpha(+/+) and PPARalpha(-/-) mice. Compared to PPARalpha(+/+) animals, acylcarnitine profiles of PPARalpha(-/-) mice revealed 2- to 4-fold accumulation of long-chain species in the plasma, whereas short-chain species were reduced by as much as 69% in plasma, liver, and skeletal muscle. These results reflect a metabolic bottleneck downstream of carnitine palmitoyltransferase-1, a mitochondrial enzyme that catalyzes the first step in beta-oxidation. Organic and amino acid profiles of starved PPARalpha(-/-) mice suggested compromised citric acid cycle flux, enhanced urea cycle activity, and increased amino acid catabolism. PPARalpha(-/-) mice had 40-50% lower plasma and tissue levels of free carnitine, corresponding with diminished hepatic expression of genes involved in carnitine biosynthesis and transport. One week of oral carnitine supplementation conferred partial metabolic recovery in the PPARalpha(-/-) mice. In summary, comprehensive metabolic profiling revealed novel biomarkers of defective fat oxidation, while also highlighting the potential value of supplemental carnitine as a therapy and diagnostic tool for metabolic disorders.

  18. Mechanistic analysis of multi-omics datasets to generate kinetic parameters for constraint-based metabolic models.

    PubMed

    Cotten, Cameron; Reed, Jennifer L

    2013-01-30

    Constraint-based modeling uses mass balances, flux capacity, and reaction directionality constraints to predict fluxes through metabolism. Although transcriptional regulation and thermodynamic constraints have been integrated into constraint-based modeling, kinetic rate laws have not been extensively used. In this study, an in vivo kinetic parameter estimation problem was formulated and solved using multi-omic data sets for Escherichia coli. To narrow the confidence intervals for kinetic parameters, a series of kinetic model simplifications were made, resulting in fewer kinetic parameters than the full kinetic model. These new parameter values are able to account for flux and concentration data from 20 different experimental conditions used in our training dataset. Concentration estimates from the simplified kinetic model were within one standard deviation for 92.7% of the 790 experimental measurements in the training set. Gibbs free energy changes of reaction were calculated to identify reactions that were often operating close to or far from equilibrium. In addition, enzymes whose activities were positively or negatively influenced by metabolite concentrations were also identified. The kinetic model was then used to calculate the maximum and minimum possible flux values for individual reactions from independent metabolite and enzyme concentration data that were not used to estimate parameter values. Incorporating these kinetically-derived flux limits into the constraint-based metabolic model improved predictions for uptake and secretion rates and intracellular fluxes in constraint-based models of central metabolism. This study has produced a method for in vivo kinetic parameter estimation and identified strategies and outcomes of kinetic model simplification. We also have illustrated how kinetic constraints can be used to improve constraint-based model predictions for intracellular fluxes and biomass yield and identify potential metabolic limitations through the

  19. Mechanistic analysis of multi-omics datasets to generate kinetic parameters for constraint-based metabolic models

    PubMed Central

    2013-01-01

    Background Constraint-based modeling uses mass balances, flux capacity, and reaction directionality constraints to predict fluxes through metabolism. Although transcriptional regulation and thermodynamic constraints have been integrated into constraint-based modeling, kinetic rate laws have not been extensively used. Results In this study, an in vivo kinetic parameter estimation problem was formulated and solved using multi-omic data sets for Escherichia coli. To narrow the confidence intervals for kinetic parameters, a series of kinetic model simplifications were made, resulting in fewer kinetic parameters than the full kinetic model. These new parameter values are able to account for flux and concentration data from 20 different experimental conditions used in our training dataset. Concentration estimates from the simplified kinetic model were within one standard deviation for 92.7% of the 790 experimental measurements in the training set. Gibbs free energy changes of reaction were calculated to identify reactions that were often operating close to or far from equilibrium. In addition, enzymes whose activities were positively or negatively influenced by metabolite concentrations were also identified. The kinetic model was then used to calculate the maximum and minimum possible flux values for individual reactions from independent metabolite and enzyme concentration data that were not used to estimate parameter values. Incorporating these kinetically-derived flux limits into the constraint-based metabolic model improved predictions for uptake and secretion rates and intracellular fluxes in constraint-based models of central metabolism. Conclusions This study has produced a method for in vivo kinetic parameter estimation and identified strategies and outcomes of kinetic model simplification. We also have illustrated how kinetic constraints can be used to improve constraint-based model predictions for intracellular fluxes and biomass yield and identify potential

  20. Phosphoketolase pathway contributes to carbon metabolism in cyanobacteria.

    PubMed

    Xiong, Wei; Lee, Tai-Chi; Rommelfanger, Sarah; Gjersing, Erica; Cano, Melissa; Maness, Pin-Ching; Ghirardi, Maria; Yu, Jianping

    2015-12-07

    Central carbon metabolism in cyanobacteria comprises the Calvin-Benson-Bassham (CBB) cycle, glycolysis, the pentose phosphate (PP) pathway and the tricarboxylic acid (TCA) cycle. Redundancy in this complex metabolic network renders the rational engineering of cyanobacterial metabolism for the generation of biomass, biofuels and chemicals a challenge. Here we report the presence of a functional phosphoketolase pathway, which splits xylulose-5-phosphate (or fructose-6-phosphate) to acetate precursor acetyl phosphate, in an engineered strain of the model cyanobacterium Synechocystis (ΔglgC/xylAB), in which glycogen synthesis is blocked, and xylose catabolism enabled through the introduction of xylose isomerase and xylulokinase. We show that this mutant strain is able to metabolise xylose to acetate on nitrogen starvation. To see whether acetate production in the mutant is linked to the activity of phosphoketolase, we disrupted a putative phosphoketolase gene (slr0453) in the ΔglgC/xylAB strain, and monitored metabolic flux using (13)C labelling; acetate and 2-oxoglutarate production was reduced in the light. A metabolic flux analysis, based on isotopic data, suggests that the phosphoketolase pathway metabolises over 30% of the carbon consumed by ΔglgC/xylAB during photomixotrophic growth on xylose and CO2. Disruption of the putative phosphoketolase gene in wild-type Synechocystis also led to a deficiency in acetate production in the dark, indicative of a contribution of the phosphoketolase pathway to heterotrophic metabolism. We suggest that the phosphoketolase pathway, previously uncharacterized in photosynthetic organisms, confers flexibility in energy and carbon metabolism in cyanobacteria, and could be exploited to increase the efficiency of cyanobacterial carbon metabolism and photosynthetic productivity.