Differential Network Analysis Reveals Evolutionary Complexity in Secondary Metabolism of Rauvolfia serpentina over Catharanthus roseus.

PubMed

Pathania, Shivalika; Bagler, Ganesh; Ahuja, Paramvir S

2016-01-01

Comparative co-expression analysis of multiple species using high-throughput data is an integrative approach to determine the uniformity as well as diversification in biological processes. Rauvolfia serpentina and Catharanthus roseus, both members of Apocyanacae family, are reported to have remedial properties against multiple diseases. Despite of sharing upstream of terpenoid indole alkaloid pathway, there is significant diversity in tissue-specific synthesis and accumulation of specialized metabolites in these plants. This led us to implement comparative co-expression network analysis to investigate the modules and genes responsible for differential tissue-specific expression as well as species-specific synthesis of metabolites. Toward these goals differential network analysis was implemented to identify candidate genes responsible for diversification of metabolites profile. Three genes were identified with significant difference in connectivity leading to differential regulatory behavior between these plants. These genes may be responsible for diversification of secondary metabolism, and thereby for species-specific metabolite synthesis. The network robustness of R. serpentina, determined based on topological properties, was also complemented by comparison of gene-metabolite networks of both plants, and may have evolved to have complex metabolic mechanisms as compared to C. roseus under the influence of various stimuli. This study reveals evolution of complexity in secondary metabolism of R. serpentina, and key genes that contribute toward diversification of specific metabolites.

Comparative analysis of taxonomic, functional, and metabolic patterns of microbiomes from 14 full-scale biogas reactors by metagenomic sequencing and radioisotopic analysis.

PubMed

Luo, Gang; Fotidis, Ioannis A; Angelidaki, Irini

2016-01-01

Biogas production is a very complex process due to the high complexity in diversity and interactions of the microorganisms mediating it, and only limited and diffuse knowledge exists about the variation of taxonomic and functional patterns of microbiomes across different biogas reactors, and their relationships with the metabolic patterns. The present study used metagenomic sequencing and radioisotopic analysis to assess the taxonomic, functional, and metabolic patterns of microbiomes from 14 full-scale biogas reactors operated under various conditions treating either sludge or manure. The results from metagenomic analysis showed that the dominant methanogenic pathway revealed by radioisotopic analysis was not always correlated with the taxonomic and functional compositions. It was found by radioisotopic experiments that the aceticlastic methanogenic pathway was dominant, while metagenomics analysis showed higher relative abundance of hydrogenotrophic methanogens. Principal coordinates analysis showed the sludge-based samples were clearly distinct from the manure-based samples for both taxonomic and functional patterns, and canonical correspondence analysis showed that the both temperature and free ammonia were crucial environmental variables shaping the taxonomic and functional patterns. The study further the overall patterns of functional genes were strongly correlated with overall patterns of taxonomic composition across different biogas reactors. The discrepancy between the metabolic patterns determined by metagenomic analysis and metabolic pathways determined by radioisotopic analysis was found. Besides, a clear correlation between taxonomic and functional patterns was demonstrated for biogas reactors, and also the environmental factors that shaping both taxonomic and functional genes patterns were identified.

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.

Metabolic effects of the iodothyronine functional analogue TRC150094 on the liver and skeletal muscle of high-fat diet fed overweight rats: an integrated proteomic study.

PubMed

Silvestri, Elena; Glinni, Daniela; Cioffi, Federica; Moreno, Maria; Lombardi, Assunta; de Lange, Pieter; Senese, Rosalba; Ceccarelli, Michele; Salzano, Anna Maria; Scaloni, Andrea; Lanni, Antonia; Goglia, Fernando

2012-07-06

A novel functional iodothyronine analogue, TRC150094, which has a much lower potency toward thyroid hormone receptor (α1/β1) activation than triiodothyronine, has been shown to be effective at reducing adiposity in rats simultaneously receiving a high-fat diet (HFD). Here, by combining metabolic, functional and proteomic analysis, we studied how the hepatic and skeletal muscle phenotypes might respond to TRC150094 treatment in HFD-fed overweight rats. Drug treatment increased both the liver and skeletal muscle mitochondrial oxidative capacities without altering mitochondrial efficiency. Coherently, in terms of individual respiratory in-gel activity, blue-native analysis revealed an increased activity of complex V in the liver and of complexes II and V in tibialis muscle in TCR150094-treated animals. Subsequently, the identification of differentially expressed proteins and the analysis of their interrelations gave an integrated view of the phenotypic/metabolic adaptations occurring in the liver and muscle proteomes during drug treatment. TRC150094 significantly altered the expression of several proteins involved in key liver metabolic pathways, including amino acid and nitrogen metabolism, and fructose and mannose metabolism. The canonical pathways most strongly influenced by TRC150094 in tibialis muscle included glycolysis and gluconeogenesis, amino acid, fructose and mannose metabolism, and cell signaling. The phenotypic/metabolic influence of TRC150094 on the liver and skeletal muscle of HFD-fed overweight rats suggests the potential clinical application of this iodothyronine analogue in ameliorating metabolic risk parameters altered by diet regimens.

Brain Metabolic Changes in Rats following Acoustic Trauma

PubMed Central

He, Jun; Zhu, Yejin; Aa, Jiye; Smith, Paul F.; De Ridder, Dirk; Wang, Guangji; Zheng, Yiwen

2017-01-01

Acoustic trauma is the most common cause of hearing loss and tinnitus in humans. However, the impact of acoustic trauma on system biology is not fully understood. It has been increasingly recognized that tinnitus caused by acoustic trauma is unlikely to be generated by a single pathological source, but rather a complex network of changes involving not only the auditory system but also systems related to memory, emotion and stress. One obvious and significant gap in tinnitus research is a lack of biomarkers that reflect the consequences of this interactive “tinnitus-causing” network. In this study, we made the first attempt to analyse brain metabolic changes in rats following acoustic trauma using metabolomics, as a pilot study prior to directly linking metabolic changes to tinnitus. Metabolites in 12 different brain regions collected from either sham or acoustic trauma animals were profiled using a gas chromatography mass spectrometry (GC/MS)-based metabolomics platform. After deconvolution of mass spectra and identification of the molecules, the metabolomic data were processed using multivariate statistical analysis. Principal component analysis showed that metabolic patterns varied among different brain regions; however, brain regions with similar functions had a similar metabolite composition. Acoustic trauma did not change the metabolite clusters in these regions. When analyzed within each brain region using the orthogonal projection to latent structures discriminant analysis sub-model, 17 molecules showed distinct separation between control and acoustic trauma groups in the auditory cortex, inferior colliculus, superior colliculus, vestibular nucleus complex (VNC), and cerebellum. Further metabolic pathway impact analysis and the enrichment overview with network analysis suggested the primary involvement of amino acid metabolism, including the alanine, aspartate and glutamate metabolic pathways, the arginine and proline metabolic pathways and the purine metabolic pathway. Our results provide the first metabolomics evidence that acoustic trauma can induce changes in multiple metabolic pathways. This pilot study also suggests that the metabolomic approach has the potential to identify acoustic trauma-specific metabolic shifts in future studies where metabolic changes are correlated with the animal's tinnitus status. PMID:28392756

Parallelization of Nullspace Algorithm for the computation of metabolic pathways

PubMed Central

Jevremović, Dimitrije; Trinh, Cong T.; Srienc, Friedrich; Sosa, Carlos P.; Boley, Daniel

2011-01-01

Elementary mode analysis is a useful metabolic pathway analysis tool in understanding and analyzing cellular metabolism, since elementary modes can represent metabolic pathways with unique and minimal sets of enzyme-catalyzed reactions of a metabolic network under steady state conditions. However, computation of the elementary modes of a genome- scale metabolic network with 100–1000 reactions is very expensive and sometimes not feasible with the commonly used serial Nullspace Algorithm. In this work, we develop a distributed memory parallelization of the Nullspace Algorithm to handle efficiently the computation of the elementary modes of a large metabolic network. We give an implementation in C++ language with the support of MPI library functions for the parallel communication. Our proposed algorithm is accompanied with an analysis of the complexity and identification of major bottlenecks during computation of all possible pathways of a large metabolic network. The algorithm includes methods to achieve load balancing among the compute-nodes and specific communication patterns to reduce the communication overhead and improve efficiency. PMID:22058581

Metatranscriptomic analysis of diverse microbial communities reveals core metabolic pathways and microbiome-specific functionality.

PubMed

Jiang, Yue; Xiong, Xuejian; Danska, Jayne; Parkinson, John

2016-01-12

Metatranscriptomics is emerging as a powerful technology for the functional characterization of complex microbial communities (microbiomes). Use of unbiased RNA-sequencing can reveal both the taxonomic composition and active biochemical functions of a complex microbial community. However, the lack of established reference genomes, computational tools and pipelines make analysis and interpretation of these datasets challenging. Systematic studies that compare data across microbiomes are needed to demonstrate the ability of such pipelines to deliver biologically meaningful insights on microbiome function. Here, we apply a standardized analytical pipeline to perform a comparative analysis of metatranscriptomic data from diverse microbial communities derived from mouse large intestine, cow rumen, kimchi culture, deep-sea thermal vent and permafrost. Sequence similarity searches allowed annotation of 19 to 76% of putative messenger RNA (mRNA) reads, with the highest frequency in the kimchi dataset due to its relatively low complexity and availability of closely related reference genomes. Metatranscriptomic datasets exhibited distinct taxonomic and functional signatures. From a metabolic perspective, we identified a common core of enzymes involved in amino acid, energy and nucleotide metabolism and also identified microbiome-specific pathways such as phosphonate metabolism (deep sea) and glycan degradation pathways (cow rumen). Integrating taxonomic and functional annotations within a novel visualization framework revealed the contribution of different taxa to metabolic pathways, allowing the identification of taxa that contribute unique functions. The application of a single, standard pipeline confirms that the rich taxonomic and functional diversity observed across microbiomes is not simply an artefact of different analysis pipelines but instead reflects distinct environmental influences. At the same time, our findings show how microbiome complexity and availability of reference genomes can impact comprehensive annotation of metatranscriptomes. Consequently, beyond the application of standardized pipelines, additional caution must be taken when interpreting their output and performing downstream, microbiome-specific, analyses. The pipeline used in these analyses along with a tutorial has been made freely available for download from our project website: http://www.compsysbio.org/microbiome .

Visualization of Metabolic Interaction Networks in Microbial Communities Using VisANT 5.0

PubMed Central

Wang, Yan; DeLisi, Charles; Segrè, Daniel; Hu, Zhenjun

2016-01-01

The complexity of metabolic networks in microbial communities poses an unresolved visualization and interpretation challenge. We address this challenge in the newly expanded version of a software tool for the analysis of biological networks, VisANT 5.0. We focus in particular on facilitating the visual exploration of metabolic interaction between microbes in a community, e.g. as predicted by COMETS (Computation of Microbial Ecosystems in Time and Space), a dynamic stoichiometric modeling framework. Using VisANT’s unique metagraph implementation, we show how one can use VisANT 5.0 to explore different time-dependent ecosystem-level metabolic networks. In particular, we analyze the metabolic interaction network between two bacteria previously shown to display an obligate cross-feeding interdependency. In addition, we illustrate how a putative minimal gut microbiome community could be represented in our framework, making it possible to highlight interactions across multiple coexisting species. We envisage that the “symbiotic layout” of VisANT can be employed as a general tool for the analysis of metabolism in complex microbial communities as well as heterogeneous human tissues. VisANT is freely available at: http://visant.bu.edu and COMETS at http://comets.bu.edu. PMID:27081850

Visualization of Metabolic Interaction Networks in Microbial Communities Using VisANT 5.0.

PubMed

Granger, Brian R; Chang, Yi-Chien; Wang, Yan; DeLisi, Charles; Segrè, Daniel; Hu, Zhenjun

2016-04-01

The complexity of metabolic networks in microbial communities poses an unresolved visualization and interpretation challenge. We address this challenge in the newly expanded version of a software tool for the analysis of biological networks, VisANT 5.0. We focus in particular on facilitating the visual exploration of metabolic interaction between microbes in a community, e.g. as predicted by COMETS (Computation of Microbial Ecosystems in Time and Space), a dynamic stoichiometric modeling framework. Using VisANT's unique metagraph implementation, we show how one can use VisANT 5.0 to explore different time-dependent ecosystem-level metabolic networks. In particular, we analyze the metabolic interaction network between two bacteria previously shown to display an obligate cross-feeding interdependency. In addition, we illustrate how a putative minimal gut microbiome community could be represented in our framework, making it possible to highlight interactions across multiple coexisting species. We envisage that the "symbiotic layout" of VisANT can be employed as a general tool for the analysis of metabolism in complex microbial communities as well as heterogeneous human tissues. VisANT is freely available at: http://visant.bu.edu and COMETS at http://comets.bu.edu.

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

Granger, Brian R.; Chang, Yi -Chien; Wang, Yan

Here, the complexity of metabolic networks in microbial communities poses an unresolved visualization and interpretation challenge. We address this challenge in the newly expanded version of a software tool for the analysis of biological networks, VisANT 5.0. We focus in particular on facilitating the visual exploration of metabolic interaction between microbes in a community, e.g. as predicted by COMETS (Computation of Microbial Ecosystems in Time and Space), a dynamic stoichiometric modeling framework. Using VisANT's unique meta-graph implementation, we show how one can use VisANT 5.0 to explore different time-dependent ecosystem-level metabolic networks. In particular, we analyze the metabolic interaction networkmore » between two bacteria previously shown to display an obligate cross-feeding interdependency. In addition, we illustrate how a putative minimal gut microbiome community could be represented in our framework, making it possible to highlight interactions across multiple coexisting species. We envisage that the "symbiotic layout" of VisANT can be employed as a general tool for the analysis of metabolism in complex microbial communities as well as heterogeneous human tissues.« less

Segregation of the Anodic Microbial Communities in a Microbial Fuel Cell Cascade

PubMed Central

Hodgson, Douglas M.; Smith, Ann; Dahale, Sonal; Stratford, James P.; Li, Jia V.; Grüning, André; Bushell, Michael E.; Marchesi, Julian R.; Avignone Rossa, C.

2016-01-01

Metabolic interactions within microbial communities are essential for the efficient degradation of complex organic compounds, and underpin natural phenomena driven by microorganisms, such as the recycling of carbon-, nitrogen-, and sulfur-containing molecules. These metabolic interactions ultimately determine the function, activity and stability of the community, and therefore their understanding would be essential to steer processes where microbial communities are involved. This is exploited in the design of microbial fuel cells (MFCs), bioelectrochemical devices that convert the chemical energy present in substrates into electrical energy through the metabolic activity of microorganisms, either single species or communities. In this work, we analyzed the evolution of the microbial community structure in a cascade of MFCs inoculated with an anaerobic microbial community and continuously fed with a complex medium. The analysis of the composition of the anodic communities revealed the establishment of different communities in the anodes of the hydraulically connected MFCs, with a decrease in the abundance of fermentative taxa and a concurrent increase in respiratory taxa along the cascade. The analysis of the metabolites in the anodic suspension showed a metabolic shift between the first and last MFC, confirming the segregation of the anodic communities. Those results suggest a metabolic interaction mechanism between the predominant fermentative bacteria at the first stages of the cascade and the anaerobic respiratory electrogenic population in the latter stages, which is reflected in the observed increase in power output. We show that our experimental system represents an ideal platform for optimization of processes where the degradation of complex substrates is involved, as well as a potential tool for the study of metabolic interactions in complex microbial communities. PMID:27242723

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

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.

Combined transcriptome and metabolome analyses of metformin effects reveal novel links between metabolic networks in steroidogenic systems.

PubMed

Udhane, Sameer S; Legeza, Balazs; Marti, Nesa; Hertig, Damian; Diserens, Gaëlle; Nuoffer, Jean-Marc; Vermathen, Peter; Flück, Christa E

2017-08-17

Metformin is an antidiabetic drug, which inhibits mitochondrial respiratory-chain-complex I and thereby seems to affect the cellular metabolism in many ways. It is also used for the treatment of the polycystic ovary syndrome (PCOS), the most common endocrine disorder in women. In addition, metformin possesses antineoplastic properties. Although metformin promotes insulin-sensitivity and ameliorates reproductive abnormalities in PCOS, its exact mechanisms of action remain elusive. Therefore, we studied the transcriptome and the metabolome of metformin in human adrenal H295R cells. Microarray analysis revealed changes in 693 genes after metformin treatment. Using high resolution magic angle spinning nuclear magnetic resonance spectroscopy (HR-MAS-NMR), we determined 38 intracellular metabolites. With bioinformatic tools we created an integrated pathway analysis to understand different intracellular processes targeted by metformin. Combined metabolomics and transcriptomics data analysis showed that metformin affects a broad range of cellular processes centered on the mitochondrium. Data confirmed several known effects of metformin on glucose and androgen metabolism, which had been identified in clinical and basic studies previously. But more importantly, novel links between the energy metabolism, sex steroid biosynthesis, the cell cycle and the immune system were identified. These omics studies shed light on a complex interplay between metabolic pathways in steroidogenic systems.

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.

Microbial metabolic networks in a complex electrogenic biofilm recovered from a stimulus-induced metatranscriptomics approach

PubMed Central

Ishii, Shun’ichi; Suzuki, Shino; Tenney, Aaron; Norden-Krichmar, Trina M.; Nealson, Kenneth H.; Bretschger, Orianna

2015-01-01

Microorganisms almost always exist as mixed communities in nature. While the significance of microbial community activities is well appreciated, a thorough understanding about how microbial communities respond to environmental perturbations has not yet been achieved. Here we have used a combination of metagenomic, genome binning, and stimulus-induced metatranscriptomic approaches to estimate the metabolic network and stimuli-induced metabolic switches existing in a complex microbial biofilm that was producing electrical current via extracellular electron transfer (EET) to a solid electrode surface. Two stimuli were employed: to increase EET and to stop EET. An analysis of cell activity marker genes after stimuli exposure revealed that only two strains within eleven binned genomes had strong transcriptional responses to increased EET rates, with one responding positively and the other responding negatively. Potential metabolic switches between eleven dominant members were mainly observed for acetate, hydrogen, and ethanol metabolisms. These results have enabled the estimation of a multi-species metabolic network and the associated short-term responses to EET stimuli that induce changes to metabolic flow and cooperative or competitive microbial interactions. This systematic meta-omics approach represents a next step towards understanding complex microbial roles within a community and how community members respond to specific environmental stimuli. PMID:26443302

Maneuvering in the Complex Path from Genotype to Phenotype

NASA Astrophysics Data System (ADS)

Strohman, Richard

2002-04-01

Human disease phenotypes are controlled not only by genes but by lawful self-organizing networks that display system-wide dynamics. These networks range from metabolic pathways to signaling pathways that regulate hormone action. When perturbed, networks alter their output of matter and energy which, depending on the environmental context, can produce either a pathological or a normal phenotype. Study of the dynamics of these networks by approaches such as metabolic control analysis may provide new insights into the pathogenesis and treatment of complex diseases.

Chewing the fat: lipid metabolism and homeostasis during M. tuberculosis infection.

PubMed

Lovewell, Rustin R; Sassetti, Christopher M; VanderVen, Brian C

2016-02-01

The interplay between Mycobacterium tuberculosis lipid metabolism, the immune response and lipid homeostasis in the host creates a complex and dynamic pathogen-host interaction. Advances in imaging and metabolic analysis techniques indicate that M. tuberculosis preferentially associates with foamy cells and employs multiple physiological systems to utilize exogenously derived fatty-acids and cholesterol. Moreover, novel insights into specific host pathways that control lipid accumulation during infection, such as the PPARγ and LXR transcriptional regulators, have begun to reveal mechanisms by which host immunity alters the bacterial micro-environment. As bacterial lipid metabolism and host lipid regulatory pathways are both important, yet inherently complex, components of active tuberculosis, delineating the heterogeneity in lipid trafficking within disease states remains a major challenge for therapeutic design. Copyright © 2015. Published by Elsevier Ltd.

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...

The origin of modern metabolic networks inferred from phylogenomic analysis of protein architecture.

PubMed

Caetano-Anollés, Gustavo; Kim, Hee Shin; Mittenthal, Jay E

2007-05-29

Metabolism represents a complex collection of enzymatic reactions and transport processes that convert metabolites into molecules capable of supporting cellular life. Here we explore the origins and evolution of modern metabolism. Using phylogenomic information linked to the structure of metabolic enzymes, we sort out recruitment processes and discover that most enzymatic activities were associated with the nine most ancient and widely distributed protein fold architectures. An analysis of newly discovered functions showed enzymatic diversification occurred early, during the onset of the modern protein world. Most importantly, phylogenetic reconstruction exercises and other evidence suggest strongly that metabolism originated in enzymes with the P-loop hydrolase fold in nucleotide metabolism, probably in pathways linked to the purine metabolic subnetwork. Consequently, the first enzymatic takeover of an ancient biochemistry or prebiotic chemistry was related to the synthesis of nucleotides for the RNA world.

Metabolome Integrated Analysis of High-Temperature Response in Pinus radiata.

PubMed

Escandón, Mónica; Meijón, Mónica; Valledor, Luis; Pascual, Jesús; Pinto, Gloria; Cañal, María Jesús

2018-01-01

The integrative omics approach is crucial to identify the molecular mechanisms underlying high-temperature response in non-model species. Based on future scenarios of heat increase, Pinus radiata plants were exposed to a temperature of 40°C for a period of 5 days, including recovered plants (30 days after last exposure to 40°C) in the analysis. The analysis of the metabolome using complementary mass spectrometry techniques (GC-MS and LC-Orbitrap-MS) allowed the reliable quantification of 2,287 metabolites. The analysis of identified metabolites and highlighter metabolic pathways across heat time exposure reveal the dynamism of the metabolome in relation to high-temperature response in P. radiata , identifying the existence of a turning point (on day 3) at which P. radiata plants changed from an initial stress response program (shorter-term response) to an acclimation one (longer-term response). Furthermore, the integration of metabolome and physiological measurements, which cover from the photosynthetic state to hormonal profile, suggests a complex metabolic pathway interaction network related to heat-stress response. Cytokinins (CKs), fatty acid metabolism and flavonoid and terpenoid biosynthesis were revealed as the most important pathways involved in heat-stress response in P. radiata , with zeatin riboside (ZR) and isopentenyl adenosine (iPA) as the key hormones coordinating these multiple and complex interactions. On the other hand, the integrative approach allowed elucidation of crucial metabolic mechanisms involved in heat response in P. radiata , as well as the identification of thermotolerance metabolic biomarkers (L-phenylalanine, hexadecanoic acid, and dihydromyricetin), crucial metabolites which can reschedule the metabolic strategy to adapt to high temperature.

Metabolome Integrated Analysis of High-Temperature Response in Pinus radiata

PubMed Central

Escandón, Mónica; Meijón, Mónica; Valledor, Luis; Pascual, Jesús; Pinto, Gloria; Cañal, María Jesús

2018-01-01

The integrative omics approach is crucial to identify the molecular mechanisms underlying high-temperature response in non-model species. Based on future scenarios of heat increase, Pinus radiata plants were exposed to a temperature of 40°C for a period of 5 days, including recovered plants (30 days after last exposure to 40°C) in the analysis. The analysis of the metabolome using complementary mass spectrometry techniques (GC-MS and LC-Orbitrap-MS) allowed the reliable quantification of 2,287 metabolites. The analysis of identified metabolites and highlighter metabolic pathways across heat time exposure reveal the dynamism of the metabolome in relation to high-temperature response in P. radiata, identifying the existence of a turning point (on day 3) at which P. radiata plants changed from an initial stress response program (shorter-term response) to an acclimation one (longer-term response). Furthermore, the integration of metabolome and physiological measurements, which cover from the photosynthetic state to hormonal profile, suggests a complex metabolic pathway interaction network related to heat-stress response. Cytokinins (CKs), fatty acid metabolism and flavonoid and terpenoid biosynthesis were revealed as the most important pathways involved in heat-stress response in P. radiata, with zeatin riboside (ZR) and isopentenyl adenosine (iPA) as the key hormones coordinating these multiple and complex interactions. On the other hand, the integrative approach allowed elucidation of crucial metabolic mechanisms involved in heat response in P. radiata, as well as the identification of thermotolerance metabolic biomarkers (L-phenylalanine, hexadecanoic acid, and dihydromyricetin), crucial metabolites which can reschedule the metabolic strategy to adapt to high temperature. PMID:29719546

Comprehensive lipid analysis: a powerful metanomic tool for predictive and diagnostic medicine.

PubMed

Watkins, S M

2000-09-01

The power and accuracy of predictive diagnostics stand to improve dramatically as a result of lipid metanomics. The high definition of data obtained with this approach allows multiple rather than single metabolites to be used in markers for a group. Since as many as 40 fatty acids are quantified from each lipid class, and up to 15 lipid classes can be quantified easily, more than 600 individual lipid metabolites can be measured routinely for each sample. Because these analyses are comprehensive, only the most appropriate and unique metabolites are selected for their predictive value. Thus, comprehensive lipid analysis promises to greatly improve predictive diagnostics for phenotypes that directly or peripherally involve lipids. A broader and possibly more exciting aspect of this technology is the generation of metabolic profiles that are not simply markers for disease, but metabolic maps that can be used to identify specific genes or activities that cause or influence the disease state. Metanomics is, in essence, functional genomics from metabolite analysis. By defining the metabolic basis for phenotype, researchers and clinicians will have an extraordinary opportunity to understand and treat disease. Much in the same way that gene chips allow researchers to observe the complex expression response to a stimulus, metanomics will enable researchers to observe the complex metabolic interplay responsible for defining phenotype. By extending this approach beyond the observation of individual dysregulations, medicine will begin to profile not single diseases, but health. As health is the proper balance of all vital metabolic pathways, comprehensive or metanomic analysis lends itself very well to identifying the metabolite distributions necessary for optimum health. Comprehensive and quantitative analysis of lipids would provide this degree of diagnostic power to researchers and clinicians interested in mining metabolic profiles for biological meaning.

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.

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

Hartmann, Anja, E-mail: hartmann@ipk-gatersleben.de; Schreiber, Falk; Martin-Luther-University Halle-Wittenberg, Halle

The characterization of biological systems with respect to their behavior and functionality based on versatile biochemical interactions is a major challenge. To understand these complex mechanisms at systems level modeling approaches are investigated. Different modeling formalisms allow metabolic models to be analyzed depending on the question to be solved, the biochemical knowledge and the availability of experimental data. Here, we describe a method for an integrative analysis of the structure and dynamics represented by qualitative and quantitative metabolic models. Using various formalisms, the metabolic model is analyzed from different perspectives. Determined structural and dynamic properties are visualized in the contextmore » of the metabolic model. Interaction techniques allow the exploration and visual analysis thereby leading to a broader understanding of the behavior and functionality of the underlying biological system. The System Biology Metabolic Model Framework (SBM{sup 2} – Framework) implements the developed method and, as an example, is applied for the integrative analysis of the crop plant potato.« less

Genome-centric resolution of microbial diversity, metabolism and interactions in anaerobic digestion.

PubMed

Vanwonterghem, Inka; Jensen, Paul D; Rabaey, Korneel; Tyson, Gene W

2016-09-01

Our understanding of the complex interconnected processes performed by microbial communities is hindered by our inability to culture the vast majority of microorganisms. Metagenomics provides a way to bypass this cultivation bottleneck and recent advances in this field now allow us to recover a growing number of genomes representing previously uncultured populations from increasingly complex environments. In this study, a temporal genome-centric metagenomic analysis was performed of lab-scale anaerobic digesters that host complex microbial communities fulfilling a series of interlinked metabolic processes to enable the conversion of cellulose to methane. In total, 101 population genomes that were moderate to near-complete were recovered based primarily on differential coverage binning. These populations span 19 phyla, represent mostly novel species and expand the genomic coverage of several rare phyla. Classification into functional guilds based on their metabolic potential revealed metabolic networks with a high level of functional redundancy as well as niche specialization, and allowed us to identify potential roles such as hydrolytic specialists for several rare, uncultured populations. Genome-centric analyses of complex microbial communities across diverse environments provide the key to understanding the phylogenetic and metabolic diversity of these interactive communities. © 2016 Society for Applied Microbiology and John Wiley & Sons Ltd.

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.

Metabolic Compartmentation – A System Level Property of Muscle Cells

PubMed Central

Saks, Valdur; Beraud, Nathalie; Wallimann, Theo

2008-01-01

Problems of quantitative investigation of intracellular diffusion and compartmentation of metabolites are analyzed. Principal controversies in recently published analyses of these problems for the living cells are discussed. It is shown that the formal theoretical analysis of diffusion of metabolites based on Fick's equation and using fixed diffusion coefficients for diluted homogenous aqueous solutions, but applied for biological systems in vivo without any comparison with experimental results, may lead to misleading conclusions, which are contradictory to most biological observations. However, if the same theoretical methods are used for analysis of actual experimental data, the apparent diffusion constants obtained are orders of magnitude lower than those in diluted aqueous solutions. Thus, it can be concluded that local restrictions of diffusion of metabolites in a cell are a system-level properties caused by complex structural organization of the cells, macromolecular crowding, cytoskeletal networks and organization of metabolic pathways into multienzyme complexes and metabolons. This results in microcompartmentation of metabolites, their channeling between enzymes and in modular organization of cellular metabolic networks. The perspectives of further studies of these complex intracellular interactions in the framework of Systems Biology are discussed. PMID:19325782

Bridging the gap between fluxomics and industrial biotechnology.

PubMed

Feng, Xueyang; Page, Lawrence; Rubens, Jacob; Chircus, Lauren; Colletti, Peter; Pakrasi, Himadri B; Tang, Yinjie J

2010-01-01

Metabolic flux analysis is a vital tool used to determine the ultimate output of cellular metabolism and thus detect biotechnologically relevant bottlenecks in productivity. ¹³C-based metabolic flux analysis (¹³C-MFA) and flux balance analysis (FBA) have many potential applications in biotechnology. However, noteworthy hurdles in fluxomics study are still present. First, several technical difficulties in both ¹³C-MFA and FBA severely limit the scope of fluxomics findings and the applicability of obtained metabolic information. Second, the complexity of metabolic regulation poses a great challenge for precise prediction and analysis of metabolic networks, as there are gaps between fluxomics results and other omics studies. Third, despite identified metabolic bottlenecks or sources of host stress from product synthesis, it remains difficult to overcome inherent metabolic robustness or to efficiently import and express nonnative pathways. Fourth, product yields often decrease as the number of enzymatic steps increases. Such decrease in yield may not be caused by rate-limiting enzymes, but rather is accumulated through each enzymatic reaction. Fifth, a high-throughput fluxomics tool hasnot been developed for characterizing nonmodel microorganisms and maximizing their application in industrial biotechnology. Refining fluxomics tools and understanding these obstacles will improve our ability to engineer highly efficient metabolic pathways in microbial hosts.

The balance sheet for transcription: an analysis of nuclear RNA metabolism in mammalian cells.

PubMed

Jackson, D A; Pombo, A; Iborra, F

2000-02-01

The control of RNA synthesis from protein-coding genes is fundamental in determining the various cell types of higher eukaryotes. The activation of these genes is driven by promoter complexes, and RNA synthesis is performed by an enzyme mega-complex-the RNA polymerase II holoenzyme. These two complexes are the fundamental components required to initiate gene expression and generate the primary transcripts that, after processing, yield mRNAs that pass to the cytoplasm where protein synthesis occurs. But although this gene expression pathway has been studied intensively, aspects of RNA metabolism remain difficult to comprehend. In particular, it is unclear why >95% of RNA polymerized by polymerase II remains in the nucleus, where it is recycled. To explain this apparent paradox, this review presents a detailed description of nuclear RNA (nRNA) metabolism in mammalian cells. We evaluate the number of active transcription units, discuss the distribution of polymerases on active genes, and assess the efficiency with which the products mature and pass to the cytoplasm. Differences between the behavior of mRNAs on this productive pathway and primary transcripts that never leave the nucleus lead us to propose that these represent distinct populations. We discuss possible roles for nonproductive RNAs and present a model to describe the metabolism of these RNAs in the nuclei of mammalian cells.-Jackson, D. A., Pombo, A., Iborra, F. The balance sheet for transcription: an analysis of nuclear RNA metabolism in mammalian cells.

Solution state nuclear magnetic resonance spectroscopy for biological metabolism and pathway intermediate analysis.

PubMed

Nealon, Gareth L; Howard, Mark J

2016-12-15

Using nuclear magnetic resonance (NMR) spectroscopy in the study of metabolism has been immensely popular in medical- and health-related research but has yet to be widely applied to more fundamental biological problems. This review provides some NMR background relevant to metabolism, describes why 1 H NMR spectra are complex as well as introducing relevant terminology and definitions. The applications and practical considerations of NMR metabolic profiling and 13 C NMR-based flux analyses are discussed together with the elegant 'enzyme trap' approach for identifying novel metabolic pathway intermediates. The importance of sample preparation and data analysis are also described and explained with reference to data precision and multivariate analysis to introduce researchers unfamiliar with NMR and metabolism to consider this technique for their research interests. Finally, a brief glance into the future suggests NMR-based metabolism has room to expand in the 21st century through new isotope labels, and NMR technologies and methodologies. © 2016 The Author(s). published by Portland Press Limited on behalf of the Biochemical Society.

Hemolymph Melanization in the Silkmoth Bombyx mori Involves Formation of a High Molecular Mass Complex That Metabolizes Tyrosine*

PubMed Central

Clark, Kevin D.; Strand, Michael R.

2013-01-01

The phenoloxidase (PO) cascade regulates the melanization of blood (hemolymph) in insects and other arthropods. Most studies indicate that microbial elicitors activate the PO cascade, which results in processing of the zymogen PPO to PO. PO is then thought to oxidize tyrosine and o-diphenols to quinones, which leads to melanin. However, different lines of investigation raise questions as to whether these views are fully correct. Here we report that hemolymph from the silkmoth, Bombyx mori, rapidly melanizes after collection from a wound site. Prior studies indicated that in vitro activated PPO hydroxylates Tyr inefficiently. Measurement of in vivo substrate titers, however, suggested that Tyr was the only PO substrate initially present in B. mori plasma and that it is rapidly metabolized by PO. Fractionation of plasma by gel filtration chromatography followed by bioassays indicated that melanization activity was primarily associated with a high mass complex (∼670 kDa) that contained PO. The prophenoloxidase-activating protease inhibitor Egf1.0 blocked formation of this complex and Tyr metabolism, but the addition of phenylthiourea to plasma before fractionation enhanced complex formation and Tyr metabolism. Mass spectrometry analysis indicated that the complex contained PO plus other proteins. Taken together, our results indicate that wounding alone activates the PO cascade in B. mori. They also suggest that complex formation is required for efficient use of Tyr as a substrate. PMID:23553628

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.

iAB-RBC-283: A proteomically derived knowledge-base of erythrocyte metabolism that can be used to simulate its physiological and patho-physiological states.

PubMed

Bordbar, Aarash; Jamshidi, Neema; Palsson, Bernhard O

2011-07-12

The development of high-throughput technologies capable of whole cell measurements of genes, proteins, and metabolites has led to the emergence of systems biology. Integrated analysis of the resulting omic data sets has proved to be hard to achieve. Metabolic network reconstructions enable complex relationships amongst molecular components to be represented formally in a biologically relevant manner while respecting physical constraints. In silico models derived from such reconstructions can then be queried or interrogated through mathematical simulations. Proteomic profiling studies of the mature human erythrocyte have shown more proteins present related to metabolic function than previously thought; however the significance and the causal consequences of these findings have not been explored. Erythrocyte proteomic data was used to reconstruct the most expansive description of erythrocyte metabolism to date, following extensive manual curation, assessment of the literature, and functional testing. The reconstruction contains 281 enzymes representing functions from glycolysis to cofactor and amino acid metabolism. Such a comprehensive view of erythrocyte metabolism implicates the erythrocyte as a potential biomarker for different diseases as well as a 'cell-based' drug-screening tool. The analysis shows that 94 erythrocyte enzymes are implicated in morbid single nucleotide polymorphisms, representing 142 pathologies. In addition, over 230 FDA-approved and experimental pharmaceuticals have enzymatic targets in the erythrocyte. The advancement of proteomic technologies and increased generation of high-throughput proteomic data have created the need for a means to analyze these data in a coherent manner. Network reconstructions provide a systematic means to integrate and analyze proteomic data in a biologically meaning manner. Analysis of the red cell proteome has revealed an unexpected level of complexity in the functional capabilities of human erythrocyte metabolism.

COBRApy: COnstraints-Based Reconstruction and Analysis for Python.

PubMed

Ebrahim, Ali; Lerman, Joshua A; Palsson, Bernhard O; Hyduke, Daniel R

2013-08-08

COnstraint-Based Reconstruction and Analysis (COBRA) methods are widely used for genome-scale modeling of metabolic networks in both prokaryotes and eukaryotes. Due to the successes with metabolism, there is an increasing effort to apply COBRA methods to reconstruct and analyze integrated models of cellular processes. The COBRA Toolbox for MATLAB is a leading software package for genome-scale analysis of metabolism; however, it was not designed to elegantly capture the complexity inherent in integrated biological networks and lacks an integration framework for the multiomics data used in systems biology. The openCOBRA Project is a community effort to promote constraints-based research through the distribution of freely available software. Here, we describe COBRA for Python (COBRApy), a Python package that provides support for basic COBRA methods. COBRApy is designed in an object-oriented fashion that facilitates the representation of the complex biological processes of metabolism and gene expression. COBRApy does not require MATLAB to function; however, it includes an interface to the COBRA Toolbox for MATLAB to facilitate use of legacy codes. For improved performance, COBRApy includes parallel processing support for computationally intensive processes. COBRApy is an object-oriented framework designed to meet the computational challenges associated with the next generation of stoichiometric constraint-based models and high-density omics data sets. http://opencobra.sourceforge.net/

Genome-scale metabolic network of Cordyceps militaris useful for comparative analysis of entomopathogenic fungi.

PubMed

Vongsangnak, Wanwipa; Raethong, Nachon; Mujchariyakul, Warasinee; Nguyen, Nam Ninh; Leong, Hon Wai; Laoteng, Kobkul

2017-08-30

The first genome-scale metabolic network of Cordyceps militaris (iWV1170) was constructed representing its whole metabolisms, which consisted of 894 metabolites and 1,267 metabolic reactions across five compartments, including the plasma membrane, cytoplasm, mitochondria, peroxisome and extracellular space. The iWV1170 could be exploited to explain its phenotypes of growth ability, cordycepin and other metabolites production on various substrates. A high number of genes encoding extracellular enzymes for degradation of complex carbohydrates, lipids and proteins were existed in C. militaris genome. By comparative genome-scale analysis, the adenine metabolic pathway towards putative cordycepin biosynthesis was reconstructed, indicating their evolutionary relationships across eleven species of entomopathogenic fungi. The overall metabolic routes involved in the putative cordycepin biosynthesis were also identified in C. militaris, including central carbon metabolism, amino acid metabolism (glycine, l-glutamine and l-aspartate) and nucleotide metabolism (adenosine and adenine). Interestingly, a lack of the sequence coding for ribonucleotide reductase inhibitor was observed in C. militaris that might contribute to its over-production of cordycepin. Copyright © 2017. Published by Elsevier B.V.

Metabolic potential of lithifying cyanobacteria-dominated thrombolitic mats.

PubMed

Mobberley, Jennifer M; Khodadad, Christina L M; Foster, Jamie S

2013-11-01

Thrombolites are unlaminated carbonate deposits formed by the metabolic activities of microbial mats and can serve as potential models for understanding the molecular mechanisms underlying the formation of lithifying communities. To assess the metabolic complexity of these ecosystems, high throughput DNA sequencing of a thrombolitic mat metagenome was coupled with phenotypic microarray analysis. Functional protein analysis of the thrombolite community metagenome delineated several of the major metabolic pathways that influence carbonate mineralization including cyanobacterial photosynthesis, sulfate reduction, sulfide oxidation, and aerobic heterotrophy. Spatial profiling of metabolite utilization within the thrombolite-forming microbial mats suggested that the top 5 mm contained a more metabolically diverse and active community than the deeper within the mat. This study provides evidence that despite the lack of mineral layering within the clotted thrombolite structure there is a vertical gradient of metabolic activity within the thrombolitic mat community. This metagenomic profiling also serves as a foundation for examining the active role individual functional groups of microbes play in coordinating metabolisms that lead to mineralization.

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

Understanding Plant Nitrogen Metabolism through Metabolomics and Computational Approaches

PubMed Central

Beatty, Perrin H.; Klein, Matthias S.; Fischer, Jeffrey J.; Lewis, Ian A.; Muench, Douglas G.; Good, Allen G.

2016-01-01

A comprehensive understanding of plant metabolism could provide a direct mechanism for improving nitrogen use efficiency (NUE) in crops. One of the major barriers to achieving this outcome is our poor understanding of the complex metabolic networks, physiological factors, and signaling mechanisms that affect NUE in agricultural settings. However, an exciting collection of computational and experimental approaches has begun to elucidate whole-plant nitrogen usage and provides an avenue for connecting nitrogen-related phenotypes to genes. Herein, we describe how metabolomics, computational models of metabolism, and flux balance analysis have been harnessed to advance our understanding of plant nitrogen metabolism. We introduce a model describing the complex flow of nitrogen through crops in a real-world agricultural setting and describe how experimental metabolomics data, such as isotope labeling rates and analyses of nutrient uptake, can be used to refine these models. In summary, the metabolomics/computational approach offers an exciting mechanism for understanding NUE that may ultimately lead to more effective crop management and engineered plants with higher yields. PMID:27735856

Multi-omics analysis provides insight to the Ignicoccus hospitalis - Nanoarchaeum equitans association

DOE PAGES

Rawle, Rachel A.; Hamerly, Timothy; Tripet, Brian P.; ...

2017-06-04

Studies of interspecies interactions are inherently difficult due to the complex mechanisms which enable these relationships. A model system for studying interspecies interactions is the marine hyperthermophiles Ignicoccus hospitalis and Nanoarchaeum equitans. Recent independently-conducted ‘omics’ analyses have generated insights into the molecular factors modulating this association. However, significant questions remain about the nature of the interactions between these archaea. We jointly analyzed multiple levels of omics datasets obtained from published, independent transcriptomics, proteomics, and metabolomics analyses. DAVID identified functionally-related groups enriched when I. hospitalis is grown alone or in co-culture with N. equitans. Enriched molecular pathways were subsequently visualized usingmore » interaction maps generated using STRING. Key findings of our multi-level omics analysis indicated that I. hospitalis provides precursors to N. equitans for energy metabolism. Analysis indicated an overall reduction in diversity of metabolic precursors in the I. hospitalis–N. equitans co-culture, which has been connected to the differential use of ribosomal subunits and was previously unnoticed. We also identified differences in precursors linked to amino acid metabolism, NADH metabolism, and carbon fixation, providing new insights into the metabolic adaptions of I. hospitalis enabling the growth of N. equitans. In conclusion, this multi-omics analysis builds upon previously identified cellular patterns while offering new insights into mechanisms that enable the I. hospitalis–N. equitans association. This study applies statistical and visualization techniques to a mixed-source omics dataset to yield a more global insight into a complex system, that was not readily discernable from separate omics studies.« less

Multi-omics analysis provides insight to the Ignicoccus hospitalis-Nanoarchaeum equitans association.

PubMed

Rawle, Rachel A; Hamerly, Timothy; Tripet, Brian P; Giannone, Richard J; Wurch, Louie; Hettich, Robert L; Podar, Mircea; Copié, Valerie; Bothner, Brian

2017-09-01

Studies of interspecies interactions are inherently difficult due to the complex mechanisms which enable these relationships. A model system for studying interspecies interactions is the marine hyperthermophiles Ignicoccus hospitalis and Nanoarchaeum equitans. Recent independently-conducted 'omics' analyses have generated insights into the molecular factors modulating this association. However, significant questions remain about the nature of the interactions between these archaea. We jointly analyzed multiple levels of omics datasets obtained from published, independent transcriptomics, proteomics, and metabolomics analyses. DAVID identified functionally-related groups enriched when I. hospitalis is grown alone or in co-culture with N. equitans. Enriched molecular pathways were subsequently visualized using interaction maps generated using STRING. Key findings of our multi-level omics analysis indicated that I. hospitalis provides precursors to N. equitans for energy metabolism. Analysis indicated an overall reduction in diversity of metabolic precursors in the I. hospitalis-N. equitans co-culture, which has been connected to the differential use of ribosomal subunits and was previously unnoticed. We also identified differences in precursors linked to amino acid metabolism, NADH metabolism, and carbon fixation, providing new insights into the metabolic adaptions of I. hospitalis enabling the growth of N. equitans. This multi-omics analysis builds upon previously identified cellular patterns while offering new insights into mechanisms that enable the I. hospitalis-N. equitans association. Our study applies statistical and visualization techniques to a mixed-source omics dataset to yield a more global insight into a complex system, that was not readily discernable from separate omics studies. Copyright © 2017 Elsevier B.V. All rights reserved.

The large-scale organization of metabolic networks

NASA Astrophysics Data System (ADS)

Jeong, H.; Tombor, B.; Albert, R.; Oltvai, Z. N.; Barabási, A.-L.

2000-10-01

In a cell or microorganism, the processes that generate mass, energy, information transfer and cell-fate specification are seamlessly integrated through a complex network of cellular constituents and reactions. However, despite the key role of these networks in sustaining cellular functions, their large-scale structure is essentially unknown. Here we present a systematic comparative mathematical analysis of the metabolic networks of 43 organisms representing all three domains of life. We show that, despite significant variation in their individual constituents and pathways, these metabolic networks have the same topological scaling properties and show striking similarities to the inherent organization of complex non-biological systems. This may indicate that metabolic organization is not only identical for all living organisms, but also complies with the design principles of robust and error-tolerant scale-free networks, and may represent a common blueprint for the large-scale organization of interactions among all cellular constituents.

Hypoxia induces a HIF-1α dependent signaling cascade to make a complex metabolic switch in SGBS-adipocytes☆

PubMed Central

Leiherer, Andreas; Geiger, Kathrin; Muendlein, Axel; Drexel, Heinz

2014-01-01

To elucidate the complex impact of hypoxia on adipose tissue, resulting in biased metabolism, insulin resistance and finally diabetes we used mature adipocytes derived from a Simpson-Golabi-Behmel syndrome patient for microarray analysis. We found a significantly increased transcription rate of genes involved in glycolysis and a striking association between the pattern of upregulated genes and disease biomarkers for diabetes mellitus and insulin resistance. Although their upregulation turned out to be HIF-1α-dependent, we identified further transcription factors mainly AP-1 components to play also an important role in hypoxia response. Analyzing the regulatory network of mentioned transcription factors and glycolysis targets we revealed a clear hint for directing glycolysis to glutathione and glycogen synthesis. This metabolic switch in adipocytes enables the cell to prevent oxidative damage in the short term but might induce lipogenesis and establish systemic metabolic disorders in the long run. PMID:24275182

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

RAPID AND AUTOMATED PROCESSING OF MALDI-FTICR/MS DATA FOR N-METABOLIC LABELING IN A SHOTGUN PROTEOMICS ANALYSIS.

PubMed

Jing, Li; Amster, I Jonathan

2009-10-15

Offline high performance liquid chromatography combined with matrix assisted laser desorption and Fourier transform ion cyclotron resonance mass spectrometry (HPLC-MALDI-FTICR/MS) provides the means to rapidly analyze complex mixtures of peptides, such as those produced by proteolytic digestion of a proteome. This method is particularly useful for making quantitative measurements of changes in protein expression by using (15)N-metabolic labeling. Proteolytic digestion of combined labeled and unlabeled proteomes produces complex mixtures that with many mass overlaps when analyzed by HPLC-MALDI-FTICR/MS. A significant challenge to data analysis is the matching of pairs of peaks which represent an unlabeled peptide and its labeled counterpart. We have developed an algorithm and incorporated it into a compute program which significantly accelerates the interpretation of (15)N metabolic labeling data by automating the process of identifying unlabeled/labeled peak pairs. The algorithm takes advantage of the high resolution and mass accuracy of FTICR mass spectrometry. The algorithm is shown to be able to successfully identify the (15)N/(14)N peptide pairs and calculate peptide relative abundance ratios in highly complex mixtures from the proteolytic digest of a whole organism protein extract.

Analysis of Microbial Functions in the Rhizosphere Using a Metabolic-Network Based Framework for Metagenomics Interpretation

PubMed Central

Ofaim, Shany; Ofek-Lalzar, Maya; Sela, Noa; Jinag, Jiandong; Kashi, Yechezkel; Minz, Dror; Freilich, Shiri

2017-01-01

Advances in metagenomics enable high resolution description of complex bacterial communities in their natural environments. Consequently, conceptual approaches for community level functional analysis are in high need. Here, we introduce a framework for a metagenomics-based analysis of community functions. Environment-specific gene catalogs, derived from metagenomes, are processed into metabolic-network representation. By applying established ecological conventions, network-edges (metabolic functions) are assigned with taxonomic annotations according to the dominance level of specific groups. Once a function-taxonomy link is established, prediction of the impact of dominant taxa on the overall community performances is assessed by simulating removal or addition of edges (taxa associated functions). This approach is demonstrated on metagenomic data describing the microbial communities from the root environment of two crop plants – wheat and cucumber. Predictions for environment-dependent effects revealed differences between treatments (root vs. soil), corresponding to documented observations. Metabolism of specific plant exudates (e.g., organic acids, flavonoids) was linked with distinct taxonomic groups in simulated root, but not soil, environments. These dependencies point to the impact of these metabolite families as determinants of community structure. Simulations of the activity of pairwise combinations of taxonomic groups (order level) predicted the possible production of complementary metabolites. Complementation profiles allow formulating a possible metabolic role for observed co-occurrence patterns. For example, production of tryptophan-associated metabolites through complementary interactions is unique to the tryptophan-deficient cucumber root environment. Our approach enables formulation of testable predictions for species contribution to community activity and exploration of the functional outcome of structural shifts in complex bacterial communities. Understanding community-level metabolism is an essential step toward the manipulation and optimization of microbial function. Here, we introduce an analysis framework addressing three key challenges of such data: producing quantified links between taxonomy and function; contextualizing discrete functions into communal networks; and simulating environmental impact on community performances. New technologies will soon provide a high-coverage description of biotic and a-biotic aspects of complex microbial communities such as these found in gut and soil. This framework was designed to allow the integration of high-throughput metabolomic and metagenomic data toward tackling the intricate associations between community structure, community function, and metabolic inputs. PMID:28878756

Imaging Complex Protein Metabolism in Live Organisms by Stimulated Raman Scattering Microscopy with Isotope Labeling

PubMed Central

2016-01-01

Protein metabolism, consisting of both synthesis and degradation, is highly complex, playing an indispensable regulatory role throughout physiological and pathological processes. Over recent decades, extensive efforts, using approaches such as autoradiography, mass spectrometry, and fluorescence microscopy, have been devoted to the study of protein metabolism. However, noninvasive and global visualization of protein metabolism has proven to be highly challenging, especially in live systems. Recently, stimulated Raman scattering (SRS) microscopy coupled with metabolic labeling of deuterated amino acids (D-AAs) was demonstrated for use in imaging newly synthesized proteins in cultured cell lines. Herein, we significantly generalize this notion to develop a comprehensive labeling and imaging platform for live visualization of complex protein metabolism, including synthesis, degradation, and pulse–chase analysis of two temporally defined populations. First, the deuterium labeling efficiency was optimized, allowing time-lapse imaging of protein synthesis dynamics within individual live cells with high spatial–temporal resolution. Second, by tracking the methyl group (CH3) distribution attributed to pre-existing proteins, this platform also enables us to map protein degradation inside live cells. Third, using two subsets of structurally and spectroscopically distinct D-AAs, we achieved two-color pulse–chase imaging, as demonstrated by observing aggregate formation of mutant hungtingtin proteins. Finally, going beyond simple cell lines, we demonstrated the imaging ability of protein synthesis in brain tissues, zebrafish, and mice in vivo. Hence, the presented labeling and imaging platform would be a valuable tool to study complex protein metabolism with high sensitivity, resolution, and biocompatibility for a broad spectrum of systems ranging from cells to model animals and possibly to humans. PMID:25560305

Machine Learning Methods for Analysis of Metabolic Data and Metabolic Pathway Modeling

PubMed Central

Cuperlovic-Culf, Miroslava

2018-01-01

Machine learning uses experimental data to optimize clustering or classification of samples or features, or to develop, augment or verify models that can be used to predict behavior or properties of systems. It is expected that machine learning will help provide actionable knowledge from a variety of big data including metabolomics data, as well as results of metabolism models. A variety of machine learning methods has been applied in bioinformatics and metabolism analyses including self-organizing maps, support vector machines, the kernel machine, Bayesian networks or fuzzy logic. To a lesser extent, machine learning has also been utilized to take advantage of the increasing availability of genomics and metabolomics data for the optimization of metabolic network models and their analysis. In this context, machine learning has aided the development of metabolic networks, the calculation of parameters for stoichiometric and kinetic models, as well as the analysis of major features in the model for the optimal application of bioreactors. Examples of this very interesting, albeit highly complex, application of machine learning for metabolism modeling will be the primary focus of this review presenting several different types of applications for model optimization, parameter determination or system analysis using models, as well as the utilization of several different types of machine learning technologies. PMID:29324649

Machine Learning Methods for Analysis of Metabolic Data and Metabolic Pathway Modeling.

PubMed

Cuperlovic-Culf, Miroslava

2018-01-11

Machine learning uses experimental data to optimize clustering or classification of samples or features, or to develop, augment or verify models that can be used to predict behavior or properties of systems. It is expected that machine learning will help provide actionable knowledge from a variety of big data including metabolomics data, as well as results of metabolism models. A variety of machine learning methods has been applied in bioinformatics and metabolism analyses including self-organizing maps, support vector machines, the kernel machine, Bayesian networks or fuzzy logic. To a lesser extent, machine learning has also been utilized to take advantage of the increasing availability of genomics and metabolomics data for the optimization of metabolic network models and their analysis. In this context, machine learning has aided the development of metabolic networks, the calculation of parameters for stoichiometric and kinetic models, as well as the analysis of major features in the model for the optimal application of bioreactors. Examples of this very interesting, albeit highly complex, application of machine learning for metabolism modeling will be the primary focus of this review presenting several different types of applications for model optimization, parameter determination or system analysis using models, as well as the utilization of several different types of machine learning technologies.

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

Rawle, Rachel A.; Hamerly, Timothy; Tripet, Brian P.

Studies of interspecies interactions are inherently difficult due to the complex mechanisms which enable these relationships. A model system for studying interspecies interactions is the marine hyperthermophiles Ignicoccus hospitalis and Nanoarchaeum equitans. Recent independently-conducted ‘omics’ analyses have generated insights into the molecular factors modulating this association. However, significant questions remain about the nature of the interactions between these archaea. We jointly analyzed multiple levels of omics datasets obtained from published, independent transcriptomics, proteomics, and metabolomics analyses. DAVID identified functionally-related groups enriched when I. hospitalis is grown alone or in co-culture with N. equitans. Enriched molecular pathways were subsequently visualized usingmore » interaction maps generated using STRING. Key findings of our multi-level omics analysis indicated that I. hospitalis provides precursors to N. equitans for energy metabolism. Analysis indicated an overall reduction in diversity of metabolic precursors in the I. hospitalis–N. equitans co-culture, which has been connected to the differential use of ribosomal subunits and was previously unnoticed. We also identified differences in precursors linked to amino acid metabolism, NADH metabolism, and carbon fixation, providing new insights into the metabolic adaptions of I. hospitalis enabling the growth of N. equitans. In conclusion, this multi-omics analysis builds upon previously identified cellular patterns while offering new insights into mechanisms that enable the I. hospitalis–N. equitans association. This study applies statistical and visualization techniques to a mixed-source omics dataset to yield a more global insight into a complex system, that was not readily discernable from separate omics studies.« less

Metabolic pathway profiling of mitochondrial respiratory chain mutants in C. elegans

PubMed Central

MJ, Falk; Z, Zhang; Rosenjack; Nissim; E, Daikhin; Nissim; MM, Sedensky; M, Yudkoff; PG, Morgan

2008-01-01

C. elegans affords a model of primary mitochondrial dysfunction that provides insight into cellular adaptations which accompany mutations in nuclear gene that encode mitochondrial proteins. To this end, we characterized genome-wide expression profiles of C. elegans strains with mutations in nuclear-encoded subunits of respiratory chain complexes. Our goal was to detect concordant changes among clusters of genes that comprise defined metabolic pathways. Results indicate that respiratory chain mutants significantly upregulate a variety of basic cellular metabolic pathways involved in carbohydrate, amino acid, and fatty acid metabolism, as well as cellular defense pathways such as the metabolism of P450 and glutathione. To further confirm and extend expression analysis findings, quantitation of whole worm free amino acid levels was performed in C. elegans mitochondrial mutants for subunits of complexes I, II, and III. Significant differences were seen for 13 of 16 amino acid levels in complex I mutants compared with controls, as well as overarching similarities among profiles of complex I, II, and III mutants compared with controls. The specific pattern of amino acid alterations observed provides novel evidence to suggest that an increase in glutamate-linked transamination reactions caused by the failure of NAD+ dependent oxidation of ketoacids occurs in primary mitochondrial respiratory chain mutants. Recognition of consistent alterations among patterns of nuclear gene expression for multiple biochemical pathways and in quantitative amino acid profiles in a translational genetic model of mitochondrial dysfunction allows insight into the complex pathogenesis underlying primary mitochondrial disease. Such knowledge may enable the development of a metabolomic profiling diagnostic tool applicable to human mitochondrial disease. PMID:18178500

Transcriptional profiling by DDRT-PCR analysis reveals gene expression during seed development in Carya cathayensis Sarg.

PubMed

Huang, You-Jun; Zhou, Qin; Huang, Jian-Qin; Zeng, Yan-Ru; Wang, Zheng-Jia; Zhang, Qi-Xiang; Zhu, Yi-Hang; Shen, Chen; Zheng, Bing-Song

2015-06-01

Hickory (Carya cathayensis Sarg.) seed has one of the highest oil content and is rich in polyunsaturated fatty acids (PUFAs), which kernel is helpful to human health, particularly to human brain function. A better elucidation of lipid accumulation mechanism would help to improve hickory production and seed quality. DDRT-PCR analysis was used to examine gene expression in hickory at thirteen time points during seed development process. A total of 67 unique genes involved in seed development were obtained, and those expression patterns were further confirmed by semi-quantitative RT-PCR and real time RT-PCR analysis. Of them, the genes with known functions were involved in signal transduction, amino acid metabolism, nuclear metabolism, fatty acid metabolism, protein metabolism, carbon metabolism, secondary metabolism, oxidation of fatty acids and stress response, suggesting that hickory underwent a complex metabolism process in seed development. Furthermore, 6 genes related to fatty acid synthesis were explored, and their functions in seed development process were further discussed. The data obtained here would provide the first clues for guiding further functional studies of fatty acid synthesis in hickory. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

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

Respiromics - An integrative analysis linking mitochondrial bioenergetics to molecular signatures.

PubMed

Walheim, Ellen; Wiśniewski, Jacek R; Jastroch, Martin

2018-03-01

Energy metabolism is challenged upon nutrient stress, eventually leading to a variety of metabolic diseases that represent a major global health burden. Here, we combine quantitative mitochondrial respirometry (Seahorse technology) and proteomics (LC-MS/MS-based total protein approach) to understand how molecular changes translate to changes in mitochondrial energy transduction during diet-induced obesity (DIO) in the liver. The integrative analysis reveals that significantly increased palmitoyl-carnitine respiration is supported by an array of proteins enriching lipid metabolism pathways. Upstream of the respiratory chain, the increased capacity for ATP synthesis during DIO associates strongest to mitochondrial uptake of pyruvate, which is routed towards carboxylation. At the respiratory chain, robust increases of complex I are uncovered by cumulative analysis of single subunit concentrations. Specifically, nuclear-encoded accessory subunits, but not mitochondrial-encoded or core units, appear to be permissive for enhanced lipid oxidation. Our integrative analysis, that we dubbed "respiromics", represents an effective tool to link molecular changes to functional mechanisms in liver energy metabolism, and, more generally, can be applied for mitochondrial analysis in a variety of metabolic and mitochondrial disease models. Copyright © 2018 The Authors. Published by Elsevier GmbH.. All rights reserved.

Engineering electron metabolism to increase ethanol production in Clostridium thermocellum.

PubMed

Lo, Jonathan; Olson, Daniel G; Murphy, Sean Jean-Loup; Tian, Liang; Hon, Shuen; Lanahan, Anthony; Guss, Adam M; Lynd, Lee R

2017-01-01

The NfnAB (NADH-dependent reduced ferredoxin: NADP + oxidoreductase) and Rnf (ion-translocating reduced ferredoxin: NAD + oxidoreductase) complexes are thought to catalyze electron transfer between reduced ferredoxin and NAD(P) + . Efficient electron flux is critical for engineering fuel production pathways, but little is known about the relative importance of these enzymes in vivo. In this study we investigate the importance of the NfnAB and Rnf complexes in Clostridium thermocellum for growth on cellobiose and Avicel using gene deletion, enzyme assays, and fermentation product analysis. The NfnAB complex does not seem to play a major role in metabolism, since deletion of nfnAB genes had little effect on the distribution of fermentation products. By contrast, the Rnf complex appears to play an important role in ethanol formation. Deletion of rnf genes resulted in a decrease in ethanol formation. Overexpression of rnf genes resulted in an increase in ethanol production of about 30%, but only in strains where the hydG hydrogenase maturation gene was also deleted. Copyright © 2016 International Metabolic Engineering Society. All rights reserved.

Mutants of Saccharomyces Cerevisiae with Defects in Acetate Metabolism: Isolation and Characterization of Acn(-) Mutants

PubMed Central

McCammon, M. T.

1996-01-01

The two carbon compounds, ethanol and acetate, can be oxidatively metabolized as well as assimilated into carbohydrate in the yeast Saccharomyces cerevisiae. The distribution of acetate metabolic enzymes among several cellular compartments, mitochondria, peroxisomes, and cytoplasm makes it an intriguing system to study complex metabolic interactions. To investigate the complex process of carbon catabolism and assimilation, mutants unable to grow on acetate were isolated. One hundred five Acn(-) (``ACetate Nonutilizing'') mutants were sorted into 21 complementation groups with an additional 20 single mutants. Five of the groups have defects in TCA cycle enzymes: MDH1, CIT1, ACO1, IDH1, and IDH2. A defect in RTG2, involved in the retrograde communication between the mitochondrion and the nucleus, was also identified. Four genes encode enzymes of the glyoxylate cycle and gluconeogenesis: ICL1, MLS1, MDH2, and PCK1. Five other genes appear to be defective in regulating metabolic activity since elevated levels of enzymes in several metabolic pathways, including the glyoxylate cycle, gluconeogenesis, and acetyl-CoA metabolism, were detected in these mutants: ACN8, ACN9, ACN17, ACN18, and ACN42. In summary, this analysis has identified at least 22 and as many as 41 different genes involved in acetate metabolism. PMID:8878673

Adaptive evolution of complex innovations through stepwise metabolic niche expansion.

PubMed

Szappanos, Balázs; Fritzemeier, Jonathan; Csörgő, Bálint; Lázár, Viktória; Lu, Xiaowen; Fekete, Gergely; Bálint, Balázs; Herczeg, Róbert; Nagy, István; Notebaart, Richard A; Lercher, Martin J; Pál, Csaba; Papp, Balázs

2016-05-20

A central challenge in evolutionary biology concerns the mechanisms by which complex metabolic innovations requiring multiple mutations arise. Here, we propose that metabolic innovations accessible through the addition of a single reaction serve as stepping stones towards the later establishment of complex metabolic features in another environment. We demonstrate the feasibility of this hypothesis through three complementary analyses. First, using genome-scale metabolic modelling, we show that complex metabolic innovations in Escherichia coli can arise via changing nutrient conditions. Second, using phylogenetic approaches, we demonstrate that the acquisition patterns of complex metabolic pathways during the evolutionary history of bacterial genomes support the hypothesis. Third, we show how adaptation of laboratory populations of E. coli to one carbon source facilitates the later adaptation to another carbon source. Our work demonstrates how complex innovations can evolve through series of adaptive steps without the need to invoke non-adaptive processes.

Adaptive evolution of complex innovations through stepwise metabolic niche expansion

PubMed Central

Szappanos, Balázs; Fritzemeier, Jonathan; Csörgő, Bálint; Lázár, Viktória; Lu, Xiaowen; Fekete, Gergely; Bálint, Balázs; Herczeg, Róbert; Nagy, István; Notebaart, Richard A.; Lercher, Martin J.; Pál, Csaba; Papp, Balázs

2016-01-01

A central challenge in evolutionary biology concerns the mechanisms by which complex metabolic innovations requiring multiple mutations arise. Here, we propose that metabolic innovations accessible through the addition of a single reaction serve as stepping stones towards the later establishment of complex metabolic features in another environment. We demonstrate the feasibility of this hypothesis through three complementary analyses. First, using genome-scale metabolic modelling, we show that complex metabolic innovations in Escherichia coli can arise via changing nutrient conditions. Second, using phylogenetic approaches, we demonstrate that the acquisition patterns of complex metabolic pathways during the evolutionary history of bacterial genomes support the hypothesis. Third, we show how adaptation of laboratory populations of E. coli to one carbon source facilitates the later adaptation to another carbon source. Our work demonstrates how complex innovations can evolve through series of adaptive steps without the need to invoke non-adaptive processes. PMID:27197754

Complex networks analysis of obstructive nephropathy data

NASA Astrophysics Data System (ADS)

Zanin, M.; Boccaletti, S.

2011-09-01

Congenital obstructive nephropathy (ON) is one of the most frequent and complex diseases affecting children, characterized by an abnormal flux of the urine, due to a partial or complete obstruction of the urinary tract; as a consequence, urine may accumulate in the kidney and disturb the normal operation of the organ. Despite important advances, pathological mechanisms are not yet fully understood. In this contribution, the topology of complex networks, based on vectors of features of control and ON subjects, is related with the severity of the pathology. Nodes in these networks represent genetic and metabolic profiles, while connections between them indicate an abnormal relation between their expressions. Resulting topologies allow discriminating ON subjects and detecting which genetic or metabolic elements are responsible for the malfunction.

GSA-PCA: gene set generation by principal component analysis of the Laplacian matrix of a metabolic network

PubMed Central

2012-01-01

Background Gene Set Analysis (GSA) has proven to be a useful approach to microarray analysis. However, most of the method development for GSA has focused on the statistical tests to be used rather than on the generation of sets that will be tested. Existing methods of set generation are often overly simplistic. The creation of sets from individual pathways (in isolation) is a poor reflection of the complexity of the underlying metabolic network. We have developed a novel approach to set generation via the use of Principal Component Analysis of the Laplacian matrix of a metabolic network. We have analysed a relatively simple data set to show the difference in results between our method and the current state-of-the-art pathway-based sets. Results The sets generated with this method are semi-exhaustive and capture much of the topological complexity of the metabolic network. The semi-exhaustive nature of this method has also allowed us to design a hypergeometric enrichment test to determine which genes are likely responsible for set significance. We show that our method finds significant aspects of biology that would be missed (i.e. false negatives) and addresses the false positive rates found with the use of simple pathway-based sets. Conclusions The set generation step for GSA is often neglected but is a crucial part of the analysis as it defines the full context for the analysis. As such, set generation methods should be robust and yield as complete a representation of the extant biological knowledge as possible. The method reported here achieves this goal and is demonstrably superior to previous set analysis methods. PMID:22876834

Metabolic responses in Candida tropicalis to complex inhibitors during xylitol bioconversion.

PubMed

Wang, Shizeng; Li, Hao; Fan, Xiaoguang; Zhang, Jingkun; Tang, Pingwah; Yuan, Qipeng

2015-09-01

During xylitol fermentation, Candida tropicalis is often inhibited by inhibitors in hemicellulose hydrolysate. The mechanisms involved in the metabolic responses to inhibitor stress and the resistances to inhibitors are still not clear. To understand the inhibition mechanisms and the metabolic responses to inhibitors, a GC/MS-based metabolomics approach was performed on C. tropicalis treated with and without complex inhibitors (CI, including furfural, phenol and acetic acid). Partial least squares discriminant analysis was used to determine the metabolic variability between CI-treated groups and control groups, and 25 metabolites were identified as possible entities responsible for the discrimination caused by inhibitors. We found that xylose uptake rate and xylitol oxidation rate were promoted by CI treatment. Metabolomics analysis showed that the flux from xylulose to pentose phosphate pathway increased, and tricarboxylic acid cycle was disturbed by CI. Moreover, the changes in levels of 1,3-propanediol, trehalose, saturated fatty acids and amino acids showed different mechanisms involved in metabolic responses to inhibitor stress. The increase of 1,3-propanediol was considered to be correlated with regulating redox balance and osmoregulation. The increase of trehalose might play a role in protein stabilization and cellular membranes protection. Saturated fatty acids could cause the decrease of membrane fluidity and make the plasma membrane rigid to maintain the integrity of plasma membrane. The deeper understanding of the inhibition mechanisms and the metabolic responses to inhibitors will provide us with more information on the metabolism regulation during xylitol bioconversion and the construction of industrial strains with inhibitor tolerance for better utilization of bioresource. Copyright © 2015 Elsevier Inc. All rights reserved.

Cell-selective metabolic labeling of biomolecules with bioorthogonal functionalities.

PubMed

Xie, Ran; Hong, Senlian; Chen, Xing

2013-10-01

Metabolic labeling of biomolecules with bioorthogonal functionalities enables visualization, enrichment, and analysis of the biomolecules of interest in their physiological environments. This versatile strategy has found utility in probing various classes of biomolecules in a broad range of biological processes. On the other hand, metabolic labeling is nonselective with respect to cell type, which imposes limitations for studies performed in complex biological systems. Herein, we review the recent methodological developments aiming to endow metabolic labeling strategies with cell-type selectivity. The cell-selective metabolic labeling strategies have emerged from protein and glycan labeling. We envision that these strategies can be readily extended to labeling of other classes of biomolecules. Copyright © 2013 Elsevier Ltd. All rights reserved.

Insight into genome variability in the Fusarium Incarnatum-equiseti species complex through comparative analysis of secondary metabolic biosynthetic gene clusters

USDA-ARS?s Scientific Manuscript database

The genus Fusarium comprises 22 species complexes that together include approximately 300 phylogenetically distinct species. A major focus in Fusarium literature is to understand the genetic basis of niche specialization, secondary metabolites (SM) production, and host interactions in closely relate...

Determining the Composition and Stability of Protein Complexes Using an Integrated Label-Free and Stable Isotope Labeling Strategy

PubMed Central

Greco, Todd M.; Guise, Amanda J.; Cristea, Ileana M.

2016-01-01

In biological systems, proteins catalyze the fundamental reactions that underlie all cellular functions, including metabolic processes and cell survival and death pathways. These biochemical reactions are rarely accomplished alone. Rather, they involve a concerted effect from many proteins that may operate in a directed signaling pathway and/or may physically associate in a complex to achieve a specific enzymatic activity. Therefore, defining the composition and regulation of protein complexes is critical for understanding cellular functions. In this chapter, we describe an approach that uses quantitative mass spectrometry (MS) to assess the specificity and the relative stability of protein interactions. Isolation of protein complexes from mammalian cells is performed by rapid immunoaffinity purification, and followed by in-solution digestion and high-resolution mass spectrometry analysis. We employ complementary quantitative MS workflows to assess the specificity of protein interactions using label-free MS and statistical analysis, and the relative stability of the interactions using a metabolic labeling technique. For each candidate protein interaction, scores from the two workflows can be correlated to minimize nonspecific background and profile protein complex composition and relative stability. PMID:26867737

Achieving optimal growth: lessons from simple metabolic modules

NASA Astrophysics Data System (ADS)

Goyal, Sidhartha; Chen, Thomas; Wingreen, Ned

2009-03-01

Metabolism is a universal property of living organisms. While the metabolic network itself has been well characterized, the logic of its regulation remains largely mysterious. Recent work has shown that growth rates of microorganisms, including the bacterium Escherichia coli, correlate well with optimal growth rates predicted by flux-balance analysis (FBA), a constraint-based computational method. How difficult is it for cells to achieve optimal growth? Our analysis of representative metabolic modules drawn from real metabolism shows that, in all cases, simple feedback inhibition allows nearly optimal growth. Indeed, product-feedback inhibition is found in every biosynthetic pathway and constitutes about 80% of metabolic regulation. However, we find that product-feedback systems designed to approach optimal growth necessarily produce large pool sizes of metabolites, with potentially detrimental effects on cells via toxicity and osmotic imbalance. Interestingly, the sizes of metabolite pools can be strongly restricted if the feedback inhibition is ultrasensitive (i.e. with high Hill coefficient). The need for ultrasensitive mechanisms to limit pool sizes may therefore explain some of the ubiquitous, puzzling complexity found in metabolic feedback regulation at both the transcriptional and post-transcriptional levels.

Plasma metabolic profiling of dairy cows affected with clinical ketosis using LC/MS technology.

PubMed

Li, Y; Xu, C; Xia, C; Zhang, Hy; Sun, Lw; Gao, Y

2014-01-01

Ketosis in dairy cattle is an important metabolic disorder. Currently, the plasma metabolic profile of ketosis as determined using liquid chromatography-mass spectrometry (LC/MS) has not been reported. To investigate plasma metabolic profiles from cows with clinical ketosis in comparison to control cows. Twenty Holstein dairy cows were divided into two groups based on clinical signs and plasma β-hydroxybutyric acid and glucose concentrations 7-21 days postpartum: clinical ketosis and control cows. Plasma metabolic profiles were analyzed using LC/MS. Data were processed using principal component analysis and orthogonal partial least-squares discriminant analysis. Compared to control cows, the levels of valine, glycine, glycocholic, tetradecenoic acid, and palmitoleic acid increased significantly in clinical ketosis. On the other hand, the levels of arginine, aminobutyric acid, leucine/isoleucine, tryptophan, creatinine, lysine, norcotinine, and undecanoic acid decreased markedly. Our results showed that the metabolic changes in cows with clinical ketosis involve complex metabolic networks and signal transduction. These results are important for future studies elucidating the pathogenesis, diagnosis, and prevention of clinical ketosis in dairy cows.

Gene Coexpression Analysis Reveals Complex Metabolism of the Monoterpene Alcohol Linalool in Arabidopsis Flowers[W][OPEN

PubMed Central

Ginglinger, Jean-François; Boachon, Benoit; Höfer, René; Paetz, Christian; Köllner, Tobias G.; Miesch, Laurence; Lugan, Raphael; Baltenweck, Raymonde; Mutterer, Jérôme; Ullmann, Pascaline; Beran, Franziska; Claudel, Patricia; Verstappen, Francel; Fischer, Marc J.C.; Karst, Francis; Bouwmeester, Harro; Miesch, Michel; Schneider, Bernd; Gershenzon, Jonathan; Ehlting, Jürgen; Werck-Reichhart, Danièle

2013-01-01

The cytochrome P450 family encompasses the largest family of enzymes in plant metabolism, and the functions of many of its members in Arabidopsis thaliana are still unknown. Gene coexpression analysis pointed to two P450s that were coexpressed with two monoterpene synthases in flowers and were thus predicted to be involved in monoterpenoid metabolism. We show that all four selected genes, the two terpene synthases (TPS10 and TPS14) and the two cytochrome P450s (CYP71B31 and CYP76C3), are simultaneously expressed at anthesis, mainly in upper anther filaments and in petals. Upon transient expression in Nicotiana benthamiana, the TPS enzymes colocalize in vesicular structures associated with the plastid surface, whereas the P450 proteins were detected in the endoplasmic reticulum. Whether they were expressed in Saccharomyces cerevisiae or in N. benthamiana, the TPS enzymes formed two different enantiomers of linalool: (−)-(R)-linalool for TPS10 and (+)-(S)-linalool for TPS14. Both P450 enzymes metabolize the two linalool enantiomers to form different but overlapping sets of hydroxylated or epoxidized products. These oxygenated products are not emitted into the floral headspace, but accumulate in floral tissues as further converted or conjugated metabolites. This work reveals complex linalool metabolism in Arabidopsis flowers, the ecological role of which remains to be determined. PMID:24285789

Grade-Dependent Metabolic Reprogramming in Kidney Cancer Revealed by Combined Proteomics and Metabolomics Analysis [Combined Proteomics and Metabolomics Analysis Reveals Grade-Dependent Metabolism Pathways in Kidney Cancer

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

Wettersten, Hiromi I.; Hakimi, A. Ari; Morin, Dexter

Kidney cancer [or renal cell carcinoma (RCC)] is known as “the internist's tumor” because it has protean systemic manifestations, suggesting that it utilizes complex, nonphysiologic metabolic pathways. Given the increasing incidence of this cancer and its lack of effective therapeutic targets, we undertook an extensive analysis of human RCC tissue employing combined grade-dependent proteomics and metabolomics analysis to determine how metabolic reprogramming occurring in this disease allows it to escape available therapeutic approaches. After validation experiments in RCC cell lines that were wild-type or mutant for the Von Hippel–Lindau tumor suppressor, in characterizing higher-grade tumors, we found that the Warburgmore » effect is relatively more prominent at the expense of the tricarboxylic acid cycle and oxidative metabolism in general. Further, we found that the glutamine metabolism pathway acts to inhibit reactive oxygen species, as evidenced by an upregulated glutathione pathway, whereas the β-oxidation pathway is inhibited, leading to increased fatty acylcarnitines. In support of findings from previous urine metabolomics analyses, we also documented tryptophan catabolism associated with immune suppression, which was highly represented in RCC compared with other metabolic pathways. Altogether, our results offer a rationale to evaluate novel antimetabolic treatment strategies being developed in other disease settings as therapeutic strategies in RCC« less

Grade-Dependent Metabolic Reprogramming in Kidney Cancer Revealed by Combined Proteomics and Metabolomics Analysis [Combined Proteomics and Metabolomics Analysis Reveals Grade-Dependent Metabolism Pathways in Kidney Cancer

DOE PAGES

Wettersten, Hiromi I.; Hakimi, A. Ari; Morin, Dexter; ...

2015-05-07

Kidney cancer [or renal cell carcinoma (RCC)] is known as “the internist's tumor” because it has protean systemic manifestations, suggesting that it utilizes complex, nonphysiologic metabolic pathways. Given the increasing incidence of this cancer and its lack of effective therapeutic targets, we undertook an extensive analysis of human RCC tissue employing combined grade-dependent proteomics and metabolomics analysis to determine how metabolic reprogramming occurring in this disease allows it to escape available therapeutic approaches. After validation experiments in RCC cell lines that were wild-type or mutant for the Von Hippel–Lindau tumor suppressor, in characterizing higher-grade tumors, we found that the Warburgmore » effect is relatively more prominent at the expense of the tricarboxylic acid cycle and oxidative metabolism in general. Further, we found that the glutamine metabolism pathway acts to inhibit reactive oxygen species, as evidenced by an upregulated glutathione pathway, whereas the β-oxidation pathway is inhibited, leading to increased fatty acylcarnitines. In support of findings from previous urine metabolomics analyses, we also documented tryptophan catabolism associated with immune suppression, which was highly represented in RCC compared with other metabolic pathways. Altogether, our results offer a rationale to evaluate novel antimetabolic treatment strategies being developed in other disease settings as therapeutic strategies in RCC« less

Genetic and environmental pathways to complex diseases.

PubMed

Gohlke, Julia M; Thomas, Reuben; Zhang, Yonqing; Rosenstein, Michael C; Davis, Allan P; Murphy, Cynthia; Becker, Kevin G; Mattingly, Carolyn J; Portier, Christopher J

2009-05-05

Pathogenesis of complex diseases involves the integration of genetic and environmental factors over time, making it particularly difficult to tease apart relationships between phenotype, genotype, and environmental factors using traditional experimental approaches. Using gene-centered databases, we have developed a network of complex diseases and environmental factors through the identification of key molecular pathways associated with both genetic and environmental contributions. Comparison with known chemical disease relationships and analysis of transcriptional regulation from gene expression datasets for several environmental factors and phenotypes clustered in a metabolic syndrome and neuropsychiatric subnetwork supports our network hypotheses. This analysis identifies natural and synthetic retinoids, antipsychotic medications, Omega 3 fatty acids, and pyrethroid pesticides as potential environmental modulators of metabolic syndrome phenotypes through PPAR and adipocytokine signaling and organophosphate pesticides as potential environmental modulators of neuropsychiatric phenotypes. Identification of key regulatory pathways that integrate genetic and environmental modulators define disease associated targets that will allow for efficient screening of large numbers of environmental factors, screening that could set priorities for further research and guide public health decisions.

Proteolytic regulation of metabolic enzymes by E3 ubiquitin ligase complexes: lessons from yeast.

PubMed

Nakatsukasa, Kunio; Okumura, Fumihiko; Kamura, Takumi

2015-01-01

Eukaryotic organisms use diverse mechanisms to control metabolic rates in response to changes in the internal and/or external environment. Fine metabolic control is a highly responsive, energy-saving process that is mediated by allosteric inhibition/activation and/or reversible modification of preexisting metabolic enzymes. In contrast, coarse metabolic control is a relatively long-term and expensive process that involves modulating the level of metabolic enzymes. Coarse metabolic control can be achieved through the degradation of metabolic enzymes by the ubiquitin-proteasome system (UPS), in which substrates are specifically ubiquitinated by an E3 ubiquitin ligase and targeted for proteasomal degradation. Here, we review select multi-protein E3 ligase complexes that directly regulate metabolic enzymes in Saccharomyces cerevisiae. The first part of the review focuses on the endoplasmic reticulum (ER) membrane-associated Hrd1 and Doa10 E3 ligase complexes. In addition to their primary roles in the ER-associated degradation pathway that eliminates misfolded proteins, recent quantitative proteomic analyses identified native substrates of Hrd1 and Doa10 in the sterol synthesis pathway. The second part focuses on the SCF (Skp1-Cul1-F-box protein) complex, an abundant prototypical multi-protein E3 ligase complex. While the best-known roles of the SCF complex are in the regulation of the cell cycle and transcription, accumulating evidence indicates that the SCF complex also modulates carbon metabolism pathways. The increasing number of metabolic enzymes whose stability is directly regulated by the UPS underscores the importance of the proteolytic regulation of metabolic processes for the acclimation of cells to environmental changes.

Genome-directed analysis of prophage excision, host defence systems, and central fermentative metabolism in Clostridium pasteurianum.

PubMed

Pyne, Michael E; Liu, Xuejia; Moo-Young, Murray; Chung, Duane A; Chou, C Perry

2016-09-19

Clostridium pasteurianum is emerging as a prospective host for the production of biofuels and chemicals, and has recently been shown to directly consume electric current. Despite this growing biotechnological appeal, the organism's genetics and central metabolism remain poorly understood. Here we present a concurrent genome sequence for the C. pasteurianum type strain and provide extensive genomic analysis of the organism's defence mechanisms and central fermentative metabolism. Next generation genome sequencing produced reads corresponding to spontaneous excision of a novel phage, designated φ6013, which could be induced using mitomycin C and detected using PCR and transmission electron microscopy. Methylome analysis of sequencing reads provided a near-complete glimpse into the organism's restriction-modification systems. We also unveiled the chief C. pasteurianum Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) locus, which was found to exemplify a Type I-B system. Finally, we show that C. pasteurianum possesses a highly complex fermentative metabolism whereby the metabolic pathways enlisted by the cell is governed by the degree of reductance of the substrate. Four distinct fermentation profiles, ranging from exclusively acidogenic to predominantly alcohologenic, were observed through redox consideration of the substrate. A detailed discussion of the organism's central metabolism within the context of metabolic engineering is provided.

Grade-dependent metabolic reprogramming in kidney cancer revealed by combined proteomics and metabolomics analysis

PubMed Central

Wettersten, Hiromi I.; Hakimi, A. Ari; Morin, Dexter; Bianchi, Cristina; Johnstone, Megan E.; Donohoe, Dallas R.; Trott, Josephine F.; Aboud, Omran Abu; Stirdivant, Steven; Neri, Bruce; Wolfert, Robert; Stewart, Benjamin; Perego, Roberto; Hsieh, James J.; Weiss, Robert H.

2015-01-01

Kidney cancer (or renal cell carcinoma [RCC]) is known as “the internist’s tumor” because it has protean systemic manifestations suggesting it utilizes complex, non-physiologic metabolic pathways. Given the increasing incidence of this cancer and its lack of effective therapeutic targets, we undertook an extensive analysis of human RCC tissue employing combined grade-dependent proteomics and metabolomics analysis to determine how metabolic reprogramming occurring in this disease allows it to escape available therapeutic approaches. After validation experiments in RCC cell lines that were wild-type or mutant for the VHL tumor suppressor, in characterizing higher grade tumors we found that the Warburg effect is relatively more prominent at the expense of the tricarboxylic acid cycle and oxidative metabolism in general. Further, we found that the glutamine metabolism pathway acts to inhibit reactive oxygen species, as evidenced by an upregulated glutathione pathway, while the β-oxidation pathway is inhibited leading to increased fatty acyl-carnitines. In support of findings from previous urine metabolomics analyses, we also documented tryptophan catabolism associated with immune suppression, which was highly represented in RCC compared to other metabolic pathways. Together, our results offer a rationale to evaluate novel anti-metabolic treatment strategies being developed in other disease settings as therapeutic strategies in RCC. PMID:25952651

Hypoxia induces a HIF-1α dependent signaling cascade to make a complex metabolic switch in SGBS-adipocytes.

PubMed

Leiherer, Andreas; Geiger, Kathrin; Muendlein, Axel; Drexel, Heinz

2014-03-05

To elucidate the complex impact of hypoxia on adipose tissue, resulting in biased metabolism, insulin resistance and finally diabetes we used mature adipocytes derived from a Simpson-Golabi-Behmel syndrome patient for microarray analysis. We found a significantly increased transcription rate of genes involved in glycolysis and a striking association between the pattern of upregulated genes and disease biomarkers for diabetes mellitus and insulin resistance. Although their upregulation turned out to be HIF-1α-dependent, we identified further transcription factors mainly AP-1 components to play also an important role in hypoxia response. Analyzing the regulatory network of mentioned transcription factors and glycolysis targets we revealed a clear hint for directing glycolysis to glutathione and glycogen synthesis. This metabolic switch in adipocytes enables the cell to prevent oxidative damage in the short term but might induce lipogenesis and establish systemic metabolic disorders in the long run. Copyright © 2013 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

Genome-Wide Analysis of the Complex Transcriptional Networks of Rice Developing Seeds

PubMed Central

Xue, Liang-Jiao; Zhang, Jing-Jing; Xue, Hong-Wei

2012-01-01

Background The development of rice (Oryza sativa) seed is closely associated with assimilates storage and plant yield, and is fine controlled by complex regulatory networks. Exhaustive transcriptome analysis of developing rice embryo and endosperm will help to characterize the genes possibly involved in the regulation of seed development and provide clues of yield and quality improvement. Principal Findings Our analysis showed that genes involved in metabolism regulation, hormone response and cellular organization processes are predominantly expressed during rice development. Interestingly, 191 transcription factor (TF)-encoding genes are predominantly expressed in seed and 59 TFs are regulated during seed development, some of which are homologs of seed-specific TFs or regulators of Arabidopsis seed development. Gene co-expression network analysis showed these TFs associated with multiple cellular and metabolism pathways, indicating a complex regulation of rice seed development. Further, by employing a cold-resistant cultivar Hanfeng (HF), genome-wide analyses of seed transcriptome at normal and low temperature reveal that rice seed is sensitive to low temperature at early stage and many genes associated with seed development are down-regulated by low temperature, indicating that the delayed development of rice seed by low temperature is mainly caused by the inhibition of the development-related genes. The transcriptional response of seed and seedling to low temperature is different, and the differential expressions of genes in signaling and metabolism pathways may contribute to the chilling tolerance of HF during seed development. Conclusions These results provide informative clues and will significantly improve the understanding of rice seed development regulation and the mechanism of cold response in rice seed. PMID:22363552

Spectroscopic and Statistical Techniques for Information Recovery in Metabonomics and Metabolomics

NASA Astrophysics Data System (ADS)

Lindon, John C.; Nicholson, Jeremy K.

2008-07-01

Methods for generating and interpreting metabolic profiles based on nuclear magnetic resonance (NMR) spectroscopy, mass spectrometry (MS), and chemometric analysis methods are summarized and the relative strengths and weaknesses of NMR and chromatography-coupled MS approaches are discussed. Given that all data sets measured to date only probe subsets of complex metabolic profiles, we describe recent developments for enhanced information recovery from the resulting complex data sets, including integration of NMR- and MS-based metabonomic results and combination of metabonomic data with data from proteomics, transcriptomics, and genomics. We summarize the breadth of applications, highlight some current activities, discuss the issues relating to metabonomics, and identify future trends.

Spectroscopic and statistical techniques for information recovery in metabonomics and metabolomics.

PubMed

Lindon, John C; Nicholson, Jeremy K

2008-01-01

Methods for generating and interpreting metabolic profiles based on nuclear magnetic resonance (NMR) spectroscopy, mass spectrometry (MS), and chemometric analysis methods are summarized and the relative strengths and weaknesses of NMR and chromatography-coupled MS approaches are discussed. Given that all data sets measured to date only probe subsets of complex metabolic profiles, we describe recent developments for enhanced information recovery from the resulting complex data sets, including integration of NMR- and MS-based metabonomic results and combination of metabonomic data with data from proteomics, transcriptomics, and genomics. We summarize the breadth of applications, highlight some current activities, discuss the issues relating to metabonomics, and identify future trends.

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.

Structured plant metabolomics for the simultaneous exploration of multiple factors.

PubMed

Vasilev, Nikolay; Boccard, Julien; Lang, Gerhard; Grömping, Ulrike; Fischer, Rainer; Goepfert, Simon; Rudaz, Serge; Schillberg, Stefan

2016-11-17

Multiple factors act simultaneously on plants to establish complex interaction networks involving nutrients, elicitors and metabolites. Metabolomics offers a better understanding of complex biological systems, but evaluating the simultaneous impact of different parameters on metabolic pathways that have many components is a challenging task. We therefore developed a novel approach that combines experimental design, untargeted metabolic profiling based on multiple chromatography systems and ionization modes, and multiblock data analysis, facilitating the systematic analysis of metabolic changes in plants caused by different factors acting at the same time. Using this method, target geraniol compounds produced in transgenic tobacco cell cultures were grouped into clusters based on their response to different factors. We hypothesized that our novel approach may provide more robust data for process optimization in plant cell cultures producing any target secondary metabolite, based on the simultaneous exploration of multiple factors rather than varying one factor each time. The suitability of our approach was verified by confirming several previously reported examples of elicitor-metabolite crosstalk. However, unravelling all factor-metabolite networks remains challenging because it requires the identification of all biochemically significant metabolites in the metabolomics dataset.

Genome scale engineering techniques for metabolic engineering.

PubMed

Liu, Rongming; Bassalo, Marcelo C; Zeitoun, Ramsey I; Gill, Ryan T

2015-11-01

Metabolic engineering has expanded from a focus on designs requiring a small number of genetic modifications to increasingly complex designs driven by advances in genome-scale engineering technologies. Metabolic engineering has been generally defined by the use of iterative cycles of rational genome modifications, strain analysis and characterization, and a synthesis step that fuels additional hypothesis generation. This cycle mirrors the Design-Build-Test-Learn cycle followed throughout various engineering fields that has recently become a defining aspect of synthetic biology. This review will attempt to summarize recent genome-scale design, build, test, and learn technologies and relate their use to a range of metabolic engineering applications. Copyright © 2015 International Metabolic Engineering Society. Published by Elsevier Inc. All rights reserved.

Quantitative analysis of drug effects at the whole-body level: a case study for glucose metabolism in malaria patients.

PubMed

Snoep, Jacky L; Green, Kathleen; Eicher, Johann; Palm, Daniel C; Penkler, Gerald; du Toit, Francois; Walters, Nicolas; Burger, Robert; Westerhoff, Hans V; van Niekerk, David D

2015-12-01

We propose a hierarchical modelling approach to construct models for disease states at the whole-body level. Such models can simulate effects of drug-induced inhibition of reaction steps on the whole-body physiology. We illustrate the approach for glucose metabolism in malaria patients, by merging two detailed kinetic models for glucose metabolism in the parasite Plasmodium falciparum and the human red blood cell with a coarse-grained model for whole-body glucose metabolism. In addition we use a genome-scale metabolic model for the parasite to predict amino acid production profiles by the malaria parasite that can be used as a complex biomarker. © 2015 Authors; published by Portland Press Limited.

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

Expression of the glutamine metabolism-related proteins glutaminase 1 and glutamate dehydrogenase in canine mammary tumours.

PubMed

Ryu, J-E; Park, H-K; Choi, H-J; Lee, H-B; Lee, H-J; Lee, H; Yu, E-S; Son, W-C

2018-06-01

Glutamine metabolism is an important metabolic pathway for cancer cell survival, and there is a critical connection between tumour growth and glutamine metabolism. Because of their similarities, canine mammary carcinomas are useful for studying human breast cancer. Accordingly, we investigated the correlations between the expression of glutamine metabolism-related proteins and the pathological features of canine mammary tumours. We performed immunohistochemical and western blot analysis of 39 mammary tumour tissues. In immunohistochemical analysis, the expression of glutaminase 1 (GLS1) in the epithelial region increased according to the histological grade (P < .005). In the stromal region, complex-type tumours displayed significantly higher GLS1 intensity than simple-type tumours. However, glutamate dehydrogenase expression did not show the same tendencies as GLS1. The western blot results were consistent with the immunohistochemical findings. These results suggest that the expression of GLS1 is correlates with clinicopathological factors in canine mammary tumours and shows a similar pattern to human breast cancer. © 2017 John Wiley & Sons Ltd.

LC-MS Analysis of Human Platelets as a Platform for Studying Mitochondrial Metabolism

PubMed Central

Parry, Robert C.; Wang, Qingqing; Gillespie, Kevin P.; Saillant, Noelle N.; Sims, Carrie; Mesaros, Clementina; Snyder, Nathaniel W.; Blair, Ian A.

2016-01-01

Perturbed mitochondrial metabolism has received renewed interest as playing a causative role in a range of diseases. Probing alterations to metabolic pathways requires a model in which external factors can be well controlled, allowing for reproducible and meaningful results. Many studies employ transformed cellular models for these purposes; however, metabolic reprogramming that occurs in many cancer cell lines may introduce confounding variables. For this reason primary cells are desirable, though attaining adequate biomass for metabolic studies can be challenging. Here we show that human platelets can be utilized as a platform to carry out metabolic studies in combination with liquid chromatography-tandem mass spectrometry analysis. This approach is amenable to relative quantification and isotopic labeling to probe the activity of specific metabolic pathways. Availability of platelets from individual donors or from blood banks makes this model system applicable to clinical studies and feasible to scale up. Here we utilize isolated platelets to confirm previously identified compensatory metabolic shifts in response to the complex I inhibitor rotenone. More specifically, a decrease in glycolysis is accompanied by an increase in fatty acid oxidation to maintain acetyl-CoA levels. Our results show that platelets can be used as an easily accessible and medically relevant model to probe the effects of xenobiotics on cellular metabolism. PMID:27077278

Physiological and Comparative Proteomic Analysis Reveals Different Drought Responses in Roots and Leaves of Drought-Tolerant Wild Wheat (Triticum boeoticum)

PubMed Central

Liu, Hui; Sultan, Muhammad Abdul Rab Faisal; Liu, Xiang li; Zhang, Jin; Yu, Fei; Zhao, Hui xian

2015-01-01

To determine the proteomic-level responses of drought tolerant wild wheat (Triticum boeoticum), physiological and comparative proteomic analyses were conducted using the roots and the leaves of control and short term drought-stressed plants. Drought stress was imposed by transferring hydroponically grown seedlings at the 3-leaf stage into 1/2 Hoagland solution containing 20% PEG-6000 for 48 h. Root and leaf samples were separately collected at 0 (control), 24, and 48 h of drought treatment for analysis. Physiological analysis indicated that abscisic acid (ABA) level was greatly increased in the drought-treated plants, but the increase was greater and more rapid in the leaves than in the roots. The net photosynthetic rate of the wild wheat leaves was significantly decreased under short-term drought stress. The deleterious effects of drought on the studied traits mainly targeted photosynthesis. Comparative proteomic analysis identified 98 and 85 differently changed protein spots (DEPs) (corresponding to 87 and 80 unique proteins, respectively) in the leaves and the roots, respectively, with only 6 mutual unique proteins in the both organs. An impressive 86% of the DEPs were implicated in detoxification and defense, carbon metabolism, amino acid and nitrogen metabolism, proteins metabolism, chaperones, transcription and translation, photosynthesis, nucleotide metabolism, and signal transduction. Further analysis revealed some mutual and tissue-specific responses to short-term drought in the leaves and the roots. The differences of drought-response between the roots and the leaves mainly included that signal sensing and transduction-associated proteins were greatly up-regulated in the roots. Photosynthesis and carbon fixation ability were decreased in the leaves. Glycolysis was down-regulated but PPP pathway enhanced in the roots, resulting in occurrence of complex changes in energy metabolism and establishment of a new homeostasis. Protein metabolism was down-regulated in the roots, but enhanced in the leaves. These results will contribute to the existing knowledge on the complexity of root and leaf protein changes that occur in response to drought, and also provide a framework for further functional studies on the identified proteins. PMID:25859656

A novel untargeted metabolomics correlation-based network analysis incorporating human metabolic reconstructions

PubMed Central

2013-01-01

Background Metabolomics has become increasingly popular in the study of disease phenotypes and molecular pathophysiology. One branch of metabolomics that encompasses the high-throughput screening of cellular metabolism is metabolic profiling. In the present study, the metabolic profiles of different tumour cells from colorectal carcinoma and breast adenocarcinoma were exposed to hypoxic and normoxic conditions and these have been compared to reveal the potential metabolic effects of hypoxia on the biochemistry of the tumour cells; this may contribute to their survival in oxygen compromised environments. In an attempt to analyse the complex interactions between metabolites beyond routine univariate and multivariate data analysis methods, correlation analysis has been integrated with a human metabolic reconstruction to reveal connections between pathways that are associated with normoxic or hypoxic oxygen environments. Results Correlation analysis has revealed statistically significant connections between metabolites, where differences in correlations between cells exposed to different oxygen levels have been highlighted as markers of hypoxic metabolism in cancer. Network mapping onto reconstructed human metabolic models is a novel addition to correlation analysis. Correlated metabolites have been mapped onto the Edinburgh human metabolic network (EHMN) with the aim of interlinking metabolites found to be regulated in a similar fashion in response to oxygen. This revealed novel pathways within the metabolic network that may be key to tumour cell survival at low oxygen. Results show that the metabolic responses to lowering oxygen availability can be conserved or specific to a particular cell line. Network-based correlation analysis identified conserved metabolites including malate, pyruvate, 2-oxoglutarate, glutamate and fructose-6-phosphate. In this way, this method has revealed metabolites not previously linked, or less well recognised, with respect to hypoxia before. Lactate fermentation is one of the key themes discussed in the field of hypoxia; however, malate, pyruvate, 2-oxoglutarate, glutamate and fructose-6-phosphate, which are connected by a single pathway, may provide a more significant marker of hypoxia in cancer. Conclusions Metabolic networks generated for each cell line were compared to identify conserved metabolite pathway responses to low oxygen environments. Furthermore, we believe this methodology will have general application within metabolomics. PMID:24153255

Metabolomic studies identify changes in transmethylation and polyamine metabolism in a brain-specific mouse model of tuberous sclerosis complex.

PubMed

McKenna, James; Kapfhamer, David; Kinchen, Jason M; Wasek, Brandi; Dunworth, Matthew; Murray-Stewart, Tracy; Bottiglieri, Teodoro; Casero, Robert A; Gambello, Michael J

2018-06-15

Tuberous sclerosis complex (TSC) is an autosomal dominant neurodevelopmental disorder and the quintessential disorder of mechanistic Target of Rapamycin Complex 1 (mTORC1) dysregulation. Loss of either causative gene, TSC1 or TSC2, leads to constitutive mTORC1 kinase activation and a pathologically anabolic state of macromolecular biosynthesis. Little is known about the organ-specific metabolic reprogramming that occurs in TSC-affected organs. Using a mouse model of TSC in which Tsc2 is disrupted in radial glial precursors and their neuronal and glial descendants, we performed an unbiased metabolomic analysis of hippocampi to identify Tsc2-dependent metabolic changes. Significant metabolic reprogramming was found in well-established pathways associated with mTORC1 activation, including redox homeostasis, glutamine/tricarboxylic acid cycle, pentose and nucleotide metabolism. Changes in two novel pathways were identified: transmethylation and polyamine metabolism. Changes in transmethylation included reduced methionine, cystathionine, S-adenosylmethionine (SAM-the major methyl donor), reduced SAM/S-adenosylhomocysteine ratio (cellular methylation potential), and elevated betaine, an alternative methyl donor. These changes were associated with alterations in SAM-dependent methylation pathways and expression of the enzymes methionine adenosyltransferase 2A and cystathionine beta synthase. We also found increased levels of the polyamine putrescine due to increased activity of ornithine decarboxylase, the rate-determining enzyme in polyamine synthesis. Treatment of Tsc2+/- mice with the ornithine decarboxylase inhibitor α-difluoromethylornithine, to reduce putrescine synthesis dose-dependently reduced hippocampal astrogliosis. These data establish roles for SAM-dependent methylation reactions and polyamine metabolism in TSC neuropathology. Importantly, both pathways are amenable to nutritional or pharmacologic therapy.

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.

Mitochondrial Respiration in Human Colorectal and Breast Cancer Clinical Material Is Regulated Differently

PubMed Central

Koit, Andre; Ounpuu, Lyudmila; Klepinin, Aleksandr; Chekulayev, Vladimir; Timohhina, Natalja; Tepp, Kersti; Puurand, Marju; Truu, Laura; Heck, Karoliina; Valvere, Vahur; Guzun, Rita

2017-01-01

We conducted quantitative cellular respiration analysis on samples taken from human breast cancer (HBC) and human colorectal cancer (HCC) patients. Respiratory capacity is not lost as a result of tumor formation and even though, functionally, complex I in HCC was found to be suppressed, it was not evident on the protein level. Additionally, metabolic control analysis was used to quantify the role of components of mitochondrial interactosome. The main rate-controlling steps in HBC are complex IV and adenine nucleotide transporter, but in HCC, complexes I and III. Our kinetic measurements confirmed previous studies that respiratory chain complexes I and III in HBC and HCC can be assembled into supercomplexes with a possible partial addition from the complex IV pool. Therefore, the kinetic method can be a useful addition in studying supercomplexes in cell lines or human samples. In addition, when results from culture cells were compared to those from clinical samples, clear differences were present, but we also detected two different types of mitochondria within clinical HBC samples, possibly linked to two-compartment metabolism. Taken together, our data show that mitochondrial respiration and regulation of mitochondrial membrane permeability have substantial differences between these two cancer types when compared to each other to their adjacent healthy tissue or to respective cell cultures. PMID:28781720

Structural insights into xenobiotic and inhibitor binding to human aldehyde oxidase.

PubMed

Coelho, Catarina; Foti, Alessandro; Hartmann, Tobias; Santos-Silva, Teresa; Leimkühler, Silke; Romão, Maria João

2015-10-01

Aldehyde oxidase (AOX) is a xanthine oxidase (XO)-related enzyme with emerging importance due to its role in the metabolism of drugs and xenobiotics. We report the first crystal structures of human AOX1, substrate free (2.6-Å resolution) and in complex with the substrate phthalazine and the inhibitor thioridazine (2.7-Å resolution). Analysis of the protein active site combined with steady-state kinetic studies highlight the unique features, including binding and substrate orientation at the active site, that characterize human AOX1 as an important drug-metabolizing enzyme. Structural analysis of the complex with the noncompetitive inhibitor thioridazine revealed a new, unexpected and fully occupied inhibitor-binding site that is structurally conserved among mammalian AOXs and XO. The new structural insights into the catalytic and inhibition mechanisms of human AOX that we now report will be of great value for the rational analysis of clinical drug interactions involving inhibition of AOX1 and for the prediction and design of AOX-stable putative drugs.

Mitochondrial Gene Expression Profiles and Metabolic Pathways in the Amygdala Associated with Exaggerated Fear in an Animal Model of PTSD.

PubMed

Li, He; Li, Xin; Smerin, Stanley E; Zhang, Lei; Jia, Min; Xing, Guoqiang; Su, Yan A; Wen, Jillian; Benedek, David; Ursano, Robert

2014-01-01

The metabolic mechanisms underlying the development of exaggerated fear in post-traumatic stress disorder (PTSD) are not well defined. In the present study, alteration in the expression of genes associated with mitochondrial function in the amygdala of an animal model of PTSD was determined. Amygdala tissue samples were excised from 10 non-stressed control rats and 10 stressed rats, 14 days post-stress treatment. Total RNA was isolated, cDNA was synthesized, and gene expression levels were determined using a cDNA microarray. During the development of the exaggerated fear associated with PTSD, 48 genes were found to be significantly upregulated and 37 were significantly downregulated in the amygdala complex based on stringent criteria (p < 0.01). Ingenuity pathway analysis revealed up- or downregulation in the amygdala complex of four signaling networks - one associated with inflammatory and apoptotic pathways, one with immune mediators and metabolism, one with transcriptional factors, and one with chromatin remodeling. Thus, informatics of a neuronal gene array allowed us to determine the expression profile of mitochondrial genes in the amygdala complex of an animal model of PTSD. The result is a further understanding of the metabolic and neuronal signaling mechanisms associated with delayed and exaggerated fear.

Cardiac metabolic pathways affected in the mouse model of barth syndrome.

PubMed

Huang, Yan; Powers, Corey; Madala, Satish K; Greis, Kenneth D; Haffey, Wendy D; Towbin, Jeffrey A; Purevjav, Enkhsaikhan; Javadov, Sabzali; Strauss, Arnold W; Khuchua, Zaza

2015-01-01

Cardiolipin (CL) is a mitochondrial phospholipid essential for electron transport chain (ETC) integrity. CL-deficiency in humans is caused by mutations in the tafazzin (Taz) gene and results in a multisystem pediatric disorder, Barth syndrome (BTHS). It has been reported that tafazzin deficiency destabilizes mitochondrial respiratory chain complexes and affects supercomplex assembly. The aim of this study was to investigate the impact of Taz-knockdown on the mitochondrial proteomic landscape and metabolic processes, such as stability of respiratory chain supercomplexes and their interactions with fatty acid oxidation enzymes in cardiac muscle. Proteomic analysis demonstrated reduction of several polypeptides of the mitochondrial respiratory chain, including Rieske and cytochrome c1 subunits of complex III, NADH dehydrogenase alpha subunit 5 of complex I and the catalytic core-forming subunit of F0F1-ATP synthase. Taz gene knockdown resulted in upregulation of enzymes of folate and amino acid metabolic pathways in heart mitochondria, demonstrating that Taz-deficiency causes substantive metabolic remodeling in cardiac muscle. Mitochondrial respiratory chain supercomplexes are destabilized in CL-depleted mitochondria from Taz knockdown hearts resulting in disruption of the interactions between ETC and the fatty acid oxidation enzymes, very long-chain acyl-CoA dehydrogenase and long-chain 3-hydroxyacyl-CoA dehydrogenase, potentially affecting the metabolic channeling of reducing equivalents between these two metabolic pathways. Mitochondria-bound myoglobin was significantly reduced in Taz-knockdown hearts, potentially disrupting intracellular oxygen delivery to the oxidative phosphorylation system. Our results identify the critical pathways affected by the Taz-deficiency in mitochondria and establish a future framework for development of therapeutic options for BTHS.

Analysis of PETT images in psychiatric disorders

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

Brodie, J.D.; Gomez-Mont, F.; Volkow, N.D.

1983-01-01

A quantitative method is presented for studying the pattern of metabolic activity in a set of Positron Emission Transaxial Tomography (PETT) images. Using complex Fourier coefficients as a feature vector for each image, cluster, principal components, and discriminant function analyses are used to empirically describe metabolic differences between control subjects and patients with DSM III diagnosis for schizophrenia or endogenous depression. We also present data on the effects of neuroleptic treatment on the local cerebral metabolic rate of glucose utilization (LCMRGI) in a group of chronic schizophrenics using the region of interest approach. 15 references, 4 figures, 3 tables.

Knowledge representation in metabolic pathway databases.

PubMed

Stobbe, Miranda D; Jansen, Gerbert A; Moerland, Perry D; van Kampen, Antoine H C

2014-05-01

The accurate representation of all aspects of a metabolic network in a structured format, such that it can be used for a wide variety of computational analyses, is a challenge faced by a growing number of researchers. Analysis of five major metabolic pathway databases reveals that each database has made widely different choices to address this challenge, including how to deal with knowledge that is uncertain or missing. In concise overviews, we show how concepts such as compartments, enzymatic complexes and the direction of reactions are represented in each database. Importantly, also concepts which a database does not represent are described. Which aspects of the metabolic network need to be available in a structured format and to what detail differs per application. For example, for in silico phenotype prediction, a detailed representation of gene-protein-reaction relations and the compartmentalization of the network is essential. Our analysis also shows that current databases are still limited in capturing all details of the biology of the metabolic network, further illustrated with a detailed analysis of three metabolic processes. Finally, we conclude that the conceptual differences between the databases, which make knowledge exchange and integration a challenge, have not been resolved, so far, by the exchange formats in which knowledge representation is standardized.

Alternative assembly of respiratory complex II connects energy stress to metabolic checkpoints.

PubMed

Bezawork-Geleta, Ayenachew; Wen, He; Dong, LanFeng; Yan, Bing; Vider, Jelena; Boukalova, Stepana; Krobova, Linda; Vanova, Katerina; Zobalova, Renata; Sobol, Margarita; Hozak, Pavel; Novais, Silvia Magalhaes; Caisova, Veronika; Abaffy, Pavel; Naraine, Ravindra; Pang, Ying; Zaw, Thiri; Zhang, Ping; Sindelka, Radek; Kubista, Mikael; Zuryn, Steven; Molloy, Mark P; Berridge, Michael V; Pacak, Karel; Rohlena, Jakub; Park, Sunghyouk; Neuzil, Jiri

2018-06-07

Cell growth and survival depend on a delicate balance between energy production and synthesis of metabolites. Here, we provide evidence that an alternative mitochondrial complex II (CII) assembly, designated as CII low , serves as a checkpoint for metabolite biosynthesis under bioenergetic stress, with cells suppressing their energy utilization by modulating DNA synthesis and cell cycle progression. Depletion of CII low leads to an imbalance in energy utilization and metabolite synthesis, as evidenced by recovery of the de novo pyrimidine pathway and unlocking cell cycle arrest from the S-phase. In vitro experiments are further corroborated by analysis of paraganglioma tissues from patients with sporadic, SDHA and SDHB mutations. These findings suggest that CII low is a core complex inside mitochondria that provides homeostatic control of cellular metabolism depending on the availability of energy.

Engineering in complex systems.

PubMed

Bujara, Matthias; Panke, Sven

2010-10-01

The implementation of the engineering design cycle of measure, model, manipulate would drastically enhance the success rate of biotechnological designs. Recent progress for the three elements suggests that the scope of the traditional engineering paradigm in biotechnology is expanding. Substantial advances were made in dynamic in vivo analysis of metabolism, which is essential for the accurate prediction of metabolic pathway behavior. Novel methods that require variable degrees of system knowledge facilitate metabolic system manipulation. The combinatorial testing of pre-characterized parts is particularly promising, because it can profit from automation and limits the search space. Finally, conceptual advances in orthogonalizing cells should enhance the reliability of engineering designs in the future. Coupled to improved in silico models of metabolism, these advances should allow a more rational design of metabolic systems. Copyright © 2010 Elsevier Ltd. All rights reserved.

The Relationship between the Triglyceride to High-Density Lipoprotein Cholesterol Ratio and Metabolic Syndrome.

PubMed

Shin, Hyun-Gyu; Kim, Young-Kwang; Kim, Yong-Hwan; Jung, Yo-Han; Kang, Hee-Cheol

2017-11-01

Metabolic syndrome is associated with cardiovascular diseases and is characterized by insulin resistance. Recent studies suggest that the triglyceride/high-density lipoprotein cholesterol (TG/HDLC) ratio predicts insulin resistance better than individual lipid levels, including TG, total cholesterol, low-density lipoprotein cholesterol (LDLC), or HDLC. We aimed to elucidate the relationship between the TG/HDLC ratio and metabolic syndrome in the general Korean population. We evaluated the data of adults ≥20 years old who were enrolled in the Korean National Health and Nutrition Examination Survey in 2013 and 2014. Subjects with angina pectoris, myocardial infarction, stroke, or cancer were excluded. Metabolic syndrome was defined by the harmonized definition. We examined the odds ratios (ORs) of metabolic syndrome according to TG/HDLC ratio quartiles using logistic regression analysis (SAS ver. 9.4; SAS Institute Inc., Cary, NC, USA). Weighted complex sample analysis was also conducted. We found a significant association between the TG/HDLC ratio and metabolic syndrome. The cutoff value of the TG/HDLC ratio for the fourth quartile was ≥3.52. After adjustment, the OR for metabolic syndrome in the fourth quartile compared with that of the first quartile was 29.65 in men and 20.60 in women (P<0.001). The TG/HDLC ratio is significantly associated with metabolic syndrome.

Direct analysis of phycobilisomal antenna proteins and metabolites in small cyanobacterial populations by laser ablation electrospray ionization mass spectrometry.

PubMed

Parsiegla, Goetz; Shrestha, Bindesh; Carrière, Frédéric; Vertes, Akos

2012-01-03

Due to their significance in energy and environmental and natural product research, as well as their large genetic diversity, rapid in situ analysis of cyanobacteria is of increasing interest. Metabolic profiles and the composition of energy harvesting antenna protein complexes are needed to understand how environmental factors affect the functioning of these microorganisms. Here, we show that laser ablation electrospray ionization (LAESI) mass spectrometry enables the direct analysis of phycobilisomal antenna proteins and report on numerous metabolites from intact cyanobacteria. Small populations (n < 616 ± 76) of vegetative Anabaena sp. PCC7120 cyanobacterial cells are analyzed by LAESI mass spectrometry. The spectra reveal the ratio of phycocyanin (C-PC) and allophycocyanin (APC) in the antenna complex, the subunit composition of the phycobiliproteins, and the tentative identity of over 30 metabolites and lipids. Metabolites are tentatively identified by accurate mass measurements, isotope distribution patterns, and literature searches. The rapid simultaneous analysis of abundant proteins and diverse metabolites enables the evaluation of the environmental response and metabolic adaptation of cyanobacteria and other microorganisms. © 2011 American Chemical Society

Interdisciplinary Pathways for Urban Metabolism Research

NASA Astrophysics Data System (ADS)

Newell, J. P.

2011-12-01

With its rapid rise as a metaphor to express coupled natural-human systems in cities, the concept of urban metabolism is evolving into a series of relatively distinct research frameworks amongst various disciplines, with varying definitions, theories, models, and emphases. In industrial ecology, housed primarily within the disciplinary domain of engineering, urban metabolism research has focused on quantifying material and energy flows into, within, and out of cities, using methodologies such as material flow analysis and life cycle assessment. In the field of urban ecology, which is strongly influenced by ecology and urban planning, research focus has been placed on understanding and modeling the complex patterns and processes of human-ecological systems within urban areas. Finally, in political ecology, closely aligned with human geography and anthropology, scholars theorize about the interwoven knots of social and natural processes, material flows, and spatial structures that form the urban metabolism. This paper offers three potential interdisciplinary urban metabolism research tracks that might integrate elements of these three "ecologies," thereby bridging engineering and the social and physical sciences. First, it presents the idea of infrastructure ecology, which explores the complex, emergent interdependencies between gray (water and wastewater, transportation, etc) and green (e.g. parks, greenways) infrastructure systems, as nested within a broader socio-economic context. For cities to be sustainable and resilient over time-space, the theory follows, these is a need to understand and redesign these infrastructure linkages. Second, there is the concept of an urban-scale carbon metabolism model which integrates consumption-based material flow analysis (including goods, water, and materials), with the carbon sink and source dynamics of the built environment (e.g. buildings, etc) and urban ecosystems. Finally, there is the political ecology of the material urban metabolism, which adds spatial differentiation to materials flows and form, as well as a focus on equity, access, and governance dimensions of the urban metabolism.

Complex systems in metabolic engineering.

PubMed

Winkler, James D; Erickson, Keesha; Choudhury, Alaksh; Halweg-Edwards, Andrea L; Gill, Ryan T

2015-12-01

Metabolic engineers manipulate intricate biological networks to build efficient biological machines. The inherent complexity of this task, derived from the extensive and often unknown interconnectivity between and within these networks, often prevents researchers from achieving desired performance. Other fields have developed methods to tackle the issue of complexity for their unique subset of engineering problems, but to date, there has not been extensive and comprehensive examination of how metabolic engineers use existing tools to ameliorate this effect on their own research projects. In this review, we examine how complexity affects engineering at the protein, pathway, and genome levels within an organism, and the tools for handling these issues to achieve high-performing strain designs. Quantitative complexity metrics and their applications to metabolic engineering versus traditional engineering fields are also discussed. We conclude by predicting how metabolic engineering practices may advance in light of an explicit consideration of design complexity. Copyright © 2015 Elsevier Ltd. All rights reserved.

Identification of novel extracellular protein for PCB/biphenyl metabolism in Rhodococcus jostii RHA1.

PubMed

Atago, Yuki; Shimodaira, Jun; Araki, Naoto; Bin Othman, Nor'azizi; Zakaria, Zuriati; Fukuda, Masao; Futami, Junichiro; Hara, Hirofumi

2016-05-01

Rhodococcus jostii RHA1 (RHA1) degrades polychlorinated biphenyl (PCB) via co-metabolism with biphenyl. To identify the novel open reading frames (ORFs) that contribute to PCB/biphenyl metabolism in RHA1, we compared chromatin immunoprecipitation chip and transcriptomic data. Six novel ORFs involved in PCB/biphenyl metabolism were identified. Gene deletion mutants of these 6 ORFs were made and were tested for their ability to grow on biphenyl. Interestingly, only the ro10225 deletion mutant showed deficient growth on biphenyl. Analysis of Ro10225 protein function showed that growth of the ro10225 deletion mutant on biphenyl was recovered when exogenous recombinant Ro10225 protein was added to the culture medium. Although Ro10225 protein has no putative secretion signal sequence, partially degraded Ro10225 protein was detected in conditioned medium from wild-type RHA1 grown on biphenyl. This Ro10225 fragment appeared to form a complex with another PCB/biphenyl oxidation enzyme. These results indicated that Ro10225 protein is essential for the formation of the PCB/biphenyl dioxygenase complex in RHA1.

Hippocampus and serum metabolomic studies to explore the regulation of Chaihu-Shu-Gan-San on metabolic network disturbances of rats exposed to chronic variable stress.

PubMed

Su, Zhi-heng; Jia, Hong-mei; Zhang, Hong-wu; Feng, Yu-Fei; An, Lei; Zou, Zhong-mei

2014-03-04

Chaihu-Shu-Gan-San (CSGS), a traditional Chinese medicine formula, has been effectively used for the treatment of depression. However, studies of its anti-depressive mechanism are challenging, due to the complex pathophysiology of depression, and complexity of CSGS with multiple constituents acting on different receptors. In the present work, metabolomic studies of biochemical changes in the hippocampus and serum of chronic variable stress (CVS)-induced depression rats after treatment with CSGS were performed using ultra performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-QTOF-MS). Partial least squares-discriminate analysis indicated that the metabolic perturbation induced by CVS was reduced by treatment with CSGS. A total of twenty-six metabolites (16 from the hippocampus and 10 from serum) were considered as potential biomarkers involved in the development of depression. Among them, 11 were first reported to have potential relevance in the pathogenesis of depression, and 25 may correlate to the regulation of CSGS treatment on depression. The results combined with a previous study indicated that CSGS mediated synergistically abnormalities of the metabolic network, composed of energy metabolism, synthesis of neurotransmitters, tryptophan, phospholipids, fatty acid and bile acid metabolism, bone loss and liver detoxification, which may be helpful for understanding its mechanism of action. Furthermore, the extracellular signal-regulated kinase (ERK) signal pathway, involved in the neuronal protective mechanism of depression related to energy metabolism, was investigated by western blot analysis. The results showed that CSGS reversed disruptions of BDNF, ERK1/2 and pERK1/2 in CVS rats, which provides the first evidence that the ERK signal system may be one of the targets related to the antidepressant action of CSGS.

Mitofusin 2 as a driver that controls energy metabolism and insulin signaling.

PubMed

Zorzano, Antonio; Hernández-Alvarez, María Isabel; Sebastián, David; Muñoz, Juan Pablo

2015-04-20

Mitochondrial dynamics is a complex process that impacts on mitochondrial biology. Recent evidence indicates that proteins participating in mitochondrial dynamics have additional cellular roles. Mitofusin 2 (Mfn2) is a potent modulator of mitochondrial metabolism with an impact on energy metabolism in muscle, liver, and hypothalamic neurons. In addition, Mfn2 is subjected to tight regulation. Hence, factors such as proinflammatory cytokines, lipid availability, or glucocorticoids block its expression, whereas exercise and increased energy expenditure promote its upregulation. Importantly, Mfn2 controls cell metabolism and insulin signaling by limiting reactive oxygen species production and by modulation of endoplasmic reticulum stress. In this connection, it is critical to understand precisely the molecular mechanisms involved in the global actions of Mfn2. Future directions should concentrate into the analysis of those mechanisms, and to fully demonstrate that Mfn2 represents a cellular hub that senses the metabolic and hormonal milieu and drives the control of metabolic homeostasis.

Metabolic Pathways and Networks Associated with Tobacco Use in Military Personnel

PubMed Central

Jones, Dean P.; Walker, Douglas I.; Uppal, Karan; Rohrbeck, Patricia; Mallon, Timothy M.; Go, Young-Mi

2016-01-01

Objective Use high-resolution metabolomics (HRM) to identify metabolic pathways and networks associated with tobacco use in military personnel. Methods Four hundred de-identified samples obtained from the Department of Defense Serum Repository were classified as tobacco users or non-users according to cotinine content. HRM and bioinformatic methods were used to determine pathways and networks associated with classification. Results Eighty individuals were classified as tobacco users compared to 320 non-users based on cotinine levels ≥10 ng/mL. Alterations in lipid and xenobiotic metabolism, and diverse effects on amino acid, sialic acid and purine and pyrimidine metabolism were observed. Importantly, network analysis showed broad effects on metabolic associations not simply linked to well-defined pathways. Conclusions Tobacco use has complex metabolic effects which must be considered in evaluation of deployment-associated environmental exposures in military personnel. PMID:27501098

Metabolic Pathways and Networks Associated With Tobacco Use in Military Personnel.

PubMed

Jones, Dean P; Walker, Douglas I; Uppal, Karan; Rohrbeck, Patricia; Mallon, Col Timothy M; Go, Young-Mi

2016-08-01

The aim of this study is to use high-resolution metabolomics (HRM) to identify metabolic pathways and networks associated with tobacco use in military personnel. Four hundred deidentified samples obtained from the Department of Defense Serum Repository were classified as tobacco users or nonusers according to cotinine content. HRM and bioinformatic methods were used to determine pathways and networks associated with classification. Eighty individuals were classified as tobacco users compared with 320 nonusers on the basis of cotinine levels at least 10 ng/mL. Alterations in lipid and xenobiotic metabolism, and diverse effects on amino acid, sialic acid, and purine and pyrimidine metabolism were observed. Importantly, network analysis showed broad effects on metabolic associations not simply linked to well-defined pathways. Tobacco use has complex metabolic effects that must be considered in evaluation of deployment-associated environmental exposures in military personnel.

Engineering electron metabolism to increase ethanol production in Clostridium thermocellum

DOE PAGES

Lo, Jonathan; Olson, Daniel G.; Murphy, Sean Jean-Loup; ...

2016-10-28

Here, the NfnAB (NADH-dependent reduced ferredoxin:NADP + oxidoreductase) and Rnf ( Rhodobacter nitrogen fixation) complexes are thought to catalyze electron transfer between reduced ferredoxin and NAD(P) +. Efficient electron flux is critical for engineering fuel production pathways, but little is known about the relative importance of these enzymes in vivo. In this study we investigate the importance of the NfnAB and Rnf complexes in Clostridium thermocellum for growth on cellobiose and Avicel using gene deletion, enzyme assays, and fermentation product analysis. The NfnAB complex does not seem to play a major role in metabolism, since deletion of nfnAB genes hadmore » little effect on the distribution of fermentation products. By contrast, the Rnf complex appears to play an important role in ethanol formation. Deletion of rnf genes resulted in a decrease in ethanol formation. Overexpression of rnf genes resulted in an increase in ethanol production of about 30%, but only in strains where the hydG hydrogenase maturation gene was also deleted.« less

Engineering electron metabolism to increase ethanol production in Clostridium thermocellum

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

Lo, Jonathan; Olson, Daniel G.; Murphy, Sean Jean-Loup

Here, the NfnAB (NADH-dependent reduced ferredoxin:NADP + oxidoreductase) and Rnf ( Rhodobacter nitrogen fixation) complexes are thought to catalyze electron transfer between reduced ferredoxin and NAD(P) +. Efficient electron flux is critical for engineering fuel production pathways, but little is known about the relative importance of these enzymes in vivo. In this study we investigate the importance of the NfnAB and Rnf complexes in Clostridium thermocellum for growth on cellobiose and Avicel using gene deletion, enzyme assays, and fermentation product analysis. The NfnAB complex does not seem to play a major role in metabolism, since deletion of nfnAB genes hadmore » little effect on the distribution of fermentation products. By contrast, the Rnf complex appears to play an important role in ethanol formation. Deletion of rnf genes resulted in a decrease in ethanol formation. Overexpression of rnf genes resulted in an increase in ethanol production of about 30%, but only in strains where the hydG hydrogenase maturation gene was also deleted.« less

[Characterization of the Structure of the Prokaryotic Complex of Antarctic Permafrost by Molecular Genetic Techniques].

PubMed

Manucharova, N A; Trosheva, E V; Kol'tsova, E M; Demkina, E V; Karaevskaya, E V; Rivkina, E M; Mardanov, A V; El'-Registan, G I

2016-01-01

A prokaryotic mesophilic organotrophic community responsible for 10% of the total microbial number determined by epifluorescence microscopy was reactivated in the samples ofAntarctic permafrost retrieved from the environment favoring long-term preservation of microbial communities (7500 years). No culturable forms were obtained without resuscitation procedures (CFU = 0). Proteobacteria, Actinobacteria, and Firmicutes were the dominant microbial groups in the complex. Initiation of the reactivated microbial complex by addition of chitin (0.1% wt/vol) resulted in an increased share of metabolically active biomass (up to 50%) due to the functional domination of chitinolytics caused by the target resource. Thus, sequential application of resuscitation procedures and initiation of a specific physiological group (in this case, chitinolytics) to a permafrost-preserved microbial community made it possible to reveal a prokaryotic complex capable of reversion of metabolic activity (FISH data), to determine its phylogenetic structure by metagenomic anal-ysis, and to isolate a pure culture of the dominant microorganism with high chitinolytic activity.

Consensus-phenotype integration of transcriptomic and metabolomic data implies a role for metabolism in the chemosensitivity of tumour cells.

PubMed

Cavill, Rachel; Kamburov, Atanas; Ellis, James K; Athersuch, Toby J; Blagrove, Marcus S C; Herwig, Ralf; Ebbels, Timothy M D; Keun, Hector C

2011-03-01

Using transcriptomic and metabolomic measurements from the NCI60 cell line panel, together with a novel approach to integration of molecular profile data, we show that the biochemical pathways associated with tumour cell chemosensitivity to platinum-based drugs are highly coincident, i.e. they describe a consensus phenotype. Direct integration of metabolome and transcriptome data at the point of pathway analysis improved the detection of consensus pathways by 76%, and revealed associations between platinum sensitivity and several metabolic pathways that were not visible from transcriptome analysis alone. These pathways included the TCA cycle and pyruvate metabolism, lipoprotein uptake and nucleotide synthesis by both salvage and de novo pathways. Extending the approach across a wide panel of chemotherapeutics, we confirmed the specificity of the metabolic pathway associations to platinum sensitivity. We conclude that metabolic phenotyping could play a role in predicting response to platinum chemotherapy and that consensus-phenotype integration of molecular profiling data is a powerful and versatile tool for both biomarker discovery and for exploring the complex relationships between biological pathways and drug response.

A General Map of Iron Metabolism and Tissue-specific Subnetworks

PubMed Central

Hower, Valerie; Mendes, Pedro; Torti, Frank M.; Laubenbacher, Reinhard; Akman, Steven; Shulaev, Vladmir; Torti, Suzy V.

2009-01-01

Iron is required for survival of mammalian cells. Recently, understanding of iron metabolism and trafficking has increased dramatically, revealing a complex, interacting network largely unknown just a few years ago. This provides an excellent model for systems biology development and analysis. The first step in such an analysis is the construction of a structural network of iron metabolism, which we present here. This network was created using CellDesigner version 3.5.2 and includes reactions occurring in mammalian cells of numerous tissue types. The iron metabolic network contains 151 chemical species and 107 reactions and transport steps. Starting from this general model, we construct iron networks for specific tissues and cells that are fundamental to maintaining body iron homeostasis. We include subnetworks for cells of the intestine and liver, tissues important in iron uptake and storage, respectively; as well as the reticulocyte and macrophage, key cells in iron utilization and recycling. The addition of kinetic information to our structural network will permit the simulation of iron metabolism in different tissues as well as in health and disease. PMID:19381358

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

Effect of two complex training protocols of back squats in blood indicators of muscular damage in military athletes

PubMed Central

Ojeda, Álvaro Huerta; Ríos, Luis Chirosa; Barrilao, Rafael Guisado; Ríos, Ignacio Chirosa; Serrano, Pablo Cáceres

2016-01-01

[Purpose] The aim of this study was to determine the variations in the blood muscular damage indicators post application of two complex training programs for back squats. [Subjects and Methods] Seven military athletes were the subjects of this study. The study had a quasi-experimental cross-over intra-subject design. Two complex training protocols were applied, and the variables to be measured were cortisol, metabolic creatine kinase, and total creatine kinase. For the statistical analysis, Student’s t-test was used. [Results] Twenty-four hours post effort, a significant decrease in cortisol level was shown for both protocols; however, the metabolic creatine kinase and total creatine kinase levels showed a significant increase. [Conclusion] Both protocols lowered the indicator of main muscular damage in the blood supply (cortisol). This proved that the work weight did not generate significant muscular damage in the 24-hour post-exercise period. PMID:27313356

Effect of two complex training protocols of back squats in blood indicators of muscular damage in military athletes.

PubMed

Ojeda, Álvaro Huerta; Ríos, Luis Chirosa; Barrilao, Rafael Guisado; Ríos, Ignacio Chirosa; Serrano, Pablo Cáceres

2016-05-01

[Purpose] The aim of this study was to determine the variations in the blood muscular damage indicators post application of two complex training programs for back squats. [Subjects and Methods] Seven military athletes were the subjects of this study. The study had a quasi-experimental cross-over intra-subject design. Two complex training protocols were applied, and the variables to be measured were cortisol, metabolic creatine kinase, and total creatine kinase. For the statistical analysis, Student's t-test was used. [Results] Twenty-four hours post effort, a significant decrease in cortisol level was shown for both protocols; however, the metabolic creatine kinase and total creatine kinase levels showed a significant increase. [Conclusion] Both protocols lowered the indicator of main muscular damage in the blood supply (cortisol). This proved that the work weight did not generate significant muscular damage in the 24-hour post-exercise period.

Integrated network analysis and effective tools in plant systems biology

PubMed Central

Fukushima, Atsushi; Kanaya, Shigehiko; Nishida, Kozo

2014-01-01

One of the ultimate goals in plant systems biology is to elucidate the genotype-phenotype relationship in plant cellular systems. Integrated network analysis that combines omics data with mathematical models has received particular attention. Here we focus on the latest cutting-edge computational advances that facilitate their combination. We highlight (1) network visualization tools, (2) pathway analyses, (3) genome-scale metabolic reconstruction, and (4) the integration of high-throughput experimental data and mathematical models. Multi-omics data that contain the genome, transcriptome, proteome, and metabolome and mathematical models are expected to integrate and expand our knowledge of complex plant metabolisms. PMID:25408696

A Global Protein Kinase and Phosphatase Interaction Network in Yeast

PubMed Central

Breitkreutz, Ashton; Choi, Hyungwon; Sharom, Jeffrey R.; Boucher, Lorrie; Neduva, Victor; Larsen, Brett; Lin, Zhen-Yuan; Breitkreutz, Bobby-Joe; Stark, Chris; Liu, Guomin; Ahn, Jessica; Dewar-Darch, Danielle; Reguly, Teresa; Tang, Xiaojing; Almeida, Ricardo; Qin, Zhaohui Steve; Pawson, Tony; Gingras, Anne-Claude; Nesvizhskii, Alexey I.; Tyers, Mike

2011-01-01

The interactions of protein kinases and phosphatases with their regulatory subunits and substrates underpin cellular regulation. We identified a kinase and phosphatase interaction (KPI) network of 1844 interactions in budding yeast by mass spectrometric analysis of protein complexes. The KPI network contained many dense local regions of interactions that suggested new functions. Notably, the cell cycle phosphatase Cdc14 associated with multiple kinases that revealed roles for Cdc14 in mitogen-activated protein kinase signaling, the DNA damage response, and metabolism, whereas interactions of the target of rapamycin complex 1 (TORC1) uncovered new effector kinases in nitrogen and carbon metabolism. An extensive backbone of kinase-kinase interactions cross-connects the proteome and may serve to coordinate diverse cellular responses. PMID:20489023

Reconstruction and Analysis of Human Kidney-Specific Metabolic Network Based on Omics Data

PubMed Central

Zhang, Ai-Di; Dai, Shao-Xing; Huang, Jing-Fei

2013-01-01

With the advent of the high-throughput data production, recent studies of tissue-specific metabolic networks have largely advanced our understanding of the metabolic basis of various physiological and pathological processes. However, for kidney, which plays an essential role in the body, the available kidney-specific model remains incomplete. This paper reports the reconstruction and characterization of the human kidney metabolic network based on transcriptome and proteome data. In silico simulations revealed that house-keeping genes were more essential than kidney-specific genes in maintaining kidney metabolism. Importantly, a total of 267 potential metabolic biomarkers for kidney-related diseases were successfully explored using this model. Furthermore, we found that the discrepancies in metabolic processes of different tissues are directly corresponding to tissue's functions. Finally, the phenotypes of the differentially expressed genes in diabetic kidney disease were characterized, suggesting that these genes may affect disease development through altering kidney metabolism. Thus, the human kidney-specific model constructed in this study may provide valuable information for the metabolism of kidney and offer excellent insights into complex kidney diseases. PMID:24222897

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.

Metabonomics and its role in amino acid nutrition research.

PubMed

He, Qinghua; Yin, Yulong; Zhao, Feng; Kong, Xiangfeng; Wu, Guoyao; Ren, Pingping

2011-06-01

Metabonomics combines metabolic profiling and multivariate data analysis to facilitate the high-throughput analysis of metabolites in biological samples. This technique has been developed as a powerful analytical tool and hence has found successful widespread applications in many areas of bioscience. Metabonomics has also become an important part of systems biology. As a sensitive and powerful method, metabonomics can quantitatively measure subtle dynamic perturbations of metabolic pathways in organisms due to changes in pathophysiological, nutritional, and epigenetic states. Therefore, metabonomics holds great promise to enhance our understanding of the complex relationship between amino acids and metabolism to define the roles for dietary amino acids in maintaining health and the development of disease. Such a technique also aids in the studies of functions, metabolic regulation, safety, and individualized requirements of amino acids. Here, we highlight the common workflow of metabonomics and some of the applications to amino acid nutrition research to illustrate the great potential of this exciting new frontier in bioscience.

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/.

Systematic Sensitivity Analysis of Metabolic Controllers During Reductions in Skeletal Muscle Blood Flow

NASA Technical Reports Server (NTRS)

Radhakrishnan, Krishnan; Cabrera, Marco

2000-01-01

An acute reduction in oxygen delivery to skeletal muscle is generally associated with profound derangements in substrate metabolism. Given the complexity of the human bioenergetic system and its components, it is difficult to quantify the interaction of cellular metabolic processes 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 oxygen availability affect the pathways of ATP synthesis and their regulation. In this study, we apply a previously developed mathematical model of human bioenergetics to study effects of ischemia during periods of increased ATP turnover (e.g., exercise). By using systematic sensitivity analysis the oxidative phosphorylation rate was found to be the most important rate parameter affecting lactate production during ischemia under resting conditions. Here we examine whether mild exercise under ischemic conditions alters the relative importance of pathways and parameters previously obtained.

Metabolic Mapping of the Brain's Response to Visual Stimulation: Studies in Humans.

ERIC Educational Resources Information Center

Phelps, Michael E.; Kuhl, David E.

1981-01-01

Studies demonstrate increasing glucose metabolic rates in human primary (PVC) and association (AVC) visual cortex as complexity of visual scenes increase. AVC increased more rapidly with scene complexity than PVC and increased local metabolic activities above control subject with eyes closed; indicates wide range and metabolic reserve of visual…

Glucose: detection and analysis

USDA-ARS?s Scientific Manuscript database

Glucose is an aldosic monosaccharide that is centrally entrenched in the processes of photosynthesis and respiration, serving as an energy reserve and metabolic fuel in most organisms. As both a monomer and as part of more complex structures such as polysaccharides and glucosides, glucose also pla...

Cerebral metabonomics study on Parkinson's disease mice treated with extract of Acanthopanax senticosus harms.

PubMed

Li, Xu-zhao; Zhang, Shuai-nan; Lu, Fang; Liu, Chang-feng; Wang, Yu; Bai, Yu; Wang, Na; Liu, Shu-min

2013-10-15

Extract of Acanthopanax senticosus harms (EAS) has neuroprotective effect on Parkinson's disease (PD) mice against dopaminergic neuronal damage. However, studies of its anti-PD mechanism are challenging, owing to the complex pathophysiology of PD, and complexity of EAS with multiple constituents acting on different metabolic pathways. Here, we have investigated the metabolic profiles and potential biomarkers in a mice model of MPTP-induced PD after treatment of EAS. Metabonomics based on ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-QTOF-MS) was used to profile the metabolic fingerprints of mesencephalon obtained from 1-Methyl-4-phenyl-1, 2, 3, 6-tetrahydropyridine Hydrochloride (MPTP-HCl)-induced PD mice model with and without EAS treatment. Through partial least squares-discriminate analysis (PLS-DA), it was observed that metabolic perturbations induced by MPTP were restored after treatment with EAS. Metabolites with significant changes induced by MPTP, including L-dopa, 5'-methylthioadenosine, tetradecanoylcarnitine, phytosphingosine-1-P, Cer(d18:0/18:0), LysoPC(20:4(5Z,8Z,11Z,14Z)), L-palmitoyl -carnitine, tetracosanoylglycine, morphiceptin and stearoylcarnitine, were characterized as potential biomarkers involved in the pathogenesis of PD. The derivations of all those biomarkers can be regulated by EAS treatment except Cer(d18:0/18:0), LysoPC(20:4(5Z,8Z,11Z,14Z)), morphiceptin. The therapeutic effect of EAS on PD may involve in regulating the tyrosine metabolism, mitochondrial beta-oxidation of long chain saturated fatty acids, fatty acid metabolism, methionine metabolism, and sphingolipid metabolism. This study indicated that changed metabolites can be certainly recovered by EAS, and the treatment of EAS can be connected with the regulation of related metabolic pathways. Copyright © 2013 Elsevier GmbH. All rights reserved.

Brain glucose sensing in homeostatic and hedonic regulation.

PubMed

Steinbusch, Laura; Labouèbe, Gwenaël; Thorens, Bernard

2015-09-01

Glucose homeostasis as well as homeostatic and hedonic control of feeding is regulated by hormonal, neuronal, and nutrient-related cues. Glucose, besides its role as a source of metabolic energy, is an important signal controlling hormone secretion and neuronal activity, hence contributing to whole-body metabolic integration in coordination with feeding control. Brain glucose sensing plays a key, but insufficiently explored, role in these metabolic and behavioral controls, which when deregulated may contribute to the development of obesity and diabetes. The recent introduction of innovative transgenic, pharmacogenetic, and optogenetic techniques allows unprecedented analysis of the complexity of central glucose sensing at the molecular, cellular, and neuronal circuit levels, which will lead to a new understanding of the pathogenesis of metabolic diseases. Copyright © 2015 Elsevier Ltd. All rights reserved.

Mitochondrial phenotype during torpor: Modulation of mitochondrial electron transport system in the Chilean mouse-opossum Thylamys elegans.

PubMed

Cortes, Pablo A; Bozinovic, Francisco; Blier, Pierre U

2018-07-01

Mammalian torpor is a phenotype characterized by a controlled decline of metabolic rate, generally followed by a reduction in body temperature. During arousal from torpor, both metabolic rate and body temperature rapidly returns to resting levels. Metabolic rate reduction experienced by torpid animals is triggered by active suppression of mitochondrial respiration, which is rapidly reversed during rewarming process. In this study, we analyzed the changes in the maximal activity of key enzymes related to electron transport system (complexes I, III and IV) in six tissues of torpid, arousing and euthermic Chilean mouse-opossums (Thylamys elegans). We observed higher maximal activities of complexes I and IV during torpor in brain, heart and liver, the most metabolically active organs in mammals. On the contrary, higher enzymatic activities of complexes III were observed during torpor in kidneys and lungs. Moreover, skeletal muscle was the only tissue without significant differences among stages in all complexes evaluated, suggesting no modulation of oxidative capacities of electron transport system components in this thermogenic tissue. In overall, our data suggest that complexes I and IV activity plays a major role in initiation and maintenance of metabolic suppression during torpor in Chilean mouse-opossum, whereas improvement of oxidative capacities in complex III might be critical to sustain metabolic machinery in organs that remains metabolically active during torpor. Copyright © 2018 Elsevier Inc. All rights reserved.

Modeling cancer metabolism on a genome scale

PubMed Central

Yizhak, Keren; Chaneton, Barbara; Gottlieb, Eyal; Ruppin, Eytan

2015-01-01

Cancer cells have fundamentally altered cellular metabolism that is associated with their tumorigenicity and malignancy. In addition to the widely studied Warburg effect, several new key metabolic alterations in cancer have been established over the last decade, leading to the recognition that altered tumor metabolism is one of the hallmarks of cancer. Deciphering the full scope and functional implications of the dysregulated metabolism in cancer requires both the advancement of a variety of omics measurements and the advancement of computational approaches for the analysis and contextualization of the accumulated data. Encouragingly, while the metabolic network is highly interconnected and complex, it is at the same time probably the best characterized cellular network. Following, this review discusses the challenges that genome-scale modeling of cancer metabolism has been facing. We survey several recent studies demonstrating the first strides that have been done, testifying to the value of this approach in portraying a network-level view of the cancer metabolism and in identifying novel drug targets and biomarkers. Finally, we outline a few new steps that may further advance this field. PMID:26130389

The role of the mitochondrial pyruvate carrier in substrate regulation

PubMed Central

Vacanti, Nathaniel M.; Divakaruni, Ajit S.; Green, Courtney R.; Parker, Seth J.; Henry, Robert R.; Ciaraldi, Theodore P.; Murphy, Anne N.; Metallo, Christian M.

2014-01-01

SUMMARY Pyruvate lies at a central biochemical node connecting carbohydrate, amino acid, and fatty acid metabolism, and the regulation of pyruvate flux into mitochondria represents a critical step in intermediary metabolism impacting numerous diseases. To characterize changes in mitochondrial substrate utilization in the context of compromised mitochondrial pyruvate transport, we applied 13C metabolic flux analysis (MFA) to cells after transcriptional or pharmacological inhibition of the mitochondrial pyruvate carrier (MPC). Despite profound suppression of both glucose and pyruvate oxidation, cell growth, oxygen consumption, and tricarboxylic acid (TCA) metabolism were surprisingly maintained. Oxidative TCA flux was achieved through enhanced reliance on glutaminolysis through malic enzyme and pyruvate dehydrogenase (PDH) as well as fatty acid and branched chain amino acid oxidation. Thus, in contrast to inhibition of complex I or PDH, suppression of pyruvate transport induces a form of metabolic flexibility associated with use of lipids and amino acids as catabolic and anabolic fuels. PMID:25458843

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

Proteomic Analysis of the Mediator Complex Interactome in Saccharomyces cerevisiae.

PubMed

Uthe, Henriette; Vanselow, Jens T; Schlosser, Andreas

2017-02-27

Here we present the most comprehensive analysis of the yeast Mediator complex interactome to date. Particularly gentle cell lysis and co-immunopurification conditions allowed us to preserve even transient protein-protein interactions and to comprehensively probe the molecular environment of the Mediator complex in the cell. Metabolic 15 N-labeling thereby enabled stringent discrimination between bona fide interaction partners and nonspecifically captured proteins. Our data indicates a functional role for Mediator beyond transcription initiation. We identified a large number of Mediator-interacting proteins and protein complexes, such as RNA polymerase II, general transcription factors, a large number of transcriptional activators, the SAGA complex, chromatin remodeling complexes, histone chaperones, highly acetylated histones, as well as proteins playing a role in co-transcriptional processes, such as splicing, mRNA decapping and mRNA decay. Moreover, our data provides clear evidence, that the Mediator complex interacts not only with RNA polymerase II, but also with RNA polymerases I and III, and indicates a functional role of the Mediator complex in rRNA processing and ribosome biogenesis.

Artificial intelligence techniques for colorectal cancer drug metabolism: ontology and complex network.

PubMed

Martínez-Romero, Marcos; Vázquez-Naya, José M; Rabuñal, Juan R; Pita-Fernández, Salvador; Macenlle, Ramiro; Castro-Alvariño, Javier; López-Roses, Leopoldo; Ulla, José L; Martínez-Calvo, Antonio V; Vázquez, Santiago; Pereira, Javier; Porto-Pazos, Ana B; Dorado, Julián; Pazos, Alejandro; Munteanu, Cristian R

2010-05-01

Colorectal cancer is one of the most frequent types of cancer in the world and generates important social impact. The understanding of the specific metabolism of this disease and the transformations of the specific drugs will allow finding effective prevention, diagnosis and treatment of the colorectal cancer. All the terms that describe the drug metabolism contribute to the construction of ontology in order to help scientists to link the correlated information and to find the most useful data about this topic. The molecular components involved in this metabolism are included in complex network such as metabolic pathways in order to describe all the molecular interactions in the colorectal cancer. The graphical method of processing biological information such as graphs and complex networks leads to the numerical characterization of the colorectal cancer drug metabolic network by using invariant values named topological indices. Thus, this method can help scientists to study the most important elements in the metabolic pathways and the dynamics of the networks during mutations, denaturation or evolution for any type of disease. This review presents the last studies regarding ontology and complex networks of the colorectal cancer drug metabolism and a basic topology characterization of the drug metabolic process sub-ontology from the Gene Ontology.

Doing more with less (data): complexities of resource flow analysis in the Gauteng City-Region

NASA Astrophysics Data System (ADS)

Culwick, Christina; Götz, Graeme; Butcher, Siân; Harber, Jesse; Maree, Gillian; Mushongera, Darlington

2017-12-01

Urban metabolism is a growing field of study into resource flows through cities, and how these could be managed more sustainably. There are two main schools of thought on urban metabolism—metabolic flow analysis (MFA) and urban political ecology (UPE). The two schools remain siloed despite common foundations. This paper reflects on recent research by the Gauteng City-Region Observatory (GCRO) into urban sustainability transitions in South Africa’s Gauteng City-Region, a large and sprawling urban formation that faces a host of sustainability challenges including water deficits, erratic electricity supply, stretched infrastructure networks and increasingly carbon-intensive settlement patterns. Three GCRO research projects are reviewed. Each project began with the assumption that data collection on the region’s metabolism could enable an MFA or MFA-like analysis to highlight where possible resource efficiency and sustainability gains might be achieved. However, in each case we confronted severe data-limitations, and ended up asking UPE-style questions on the reasons for and implications of the chronic paucity of urban metabolism data. We have been led to conclude that urban metabolism research will require much more than just assembling and modelling flows data, although these efforts should not be abandoned. A synthesis of MFA and UPE is needed, which simultaneously builds a deeper understanding of resource flows and the systems that govern these flows. We support the emerging approach in political-industrial ecology literature which values both material data on and socio-political insight into urban metabolism, and emphasises the importance of multi-disciplinary and multi-dimensional analysis to inform decision-making in urban sustainability transitions.

Metabolomic Modularity Analysis (MMA) to Quantify Human Liver Perfusion Dynamics.

PubMed

Sridharan, Gautham Vivek; Bruinsma, Bote Gosse; Bale, Shyam Sundhar; Swaminathan, Anandh; Saeidi, Nima; Yarmush, Martin L; Uygun, Korkut

2017-11-13

Large-scale -omics data are now ubiquitously utilized to capture and interpret global responses to perturbations in biological systems, such as the impact of disease states on cells, tissues, and whole organs. Metabolomics data, in particular, are difficult to interpret for providing physiological insight because predefined biochemical pathways used for analysis are inherently biased and fail to capture more complex network interactions that span multiple canonical pathways. In this study, we introduce a nov-el approach coined Metabolomic Modularity Analysis (MMA) as a graph-based algorithm to systematically identify metabolic modules of reactions enriched with metabolites flagged to be statistically significant. A defining feature of the algorithm is its ability to determine modularity that highlights interactions between reactions mediated by the production and consumption of cofactors and other hub metabolites. As a case study, we evaluated the metabolic dynamics of discarded human livers using time-course metabolomics data and MMA to identify modules that explain the observed physiological changes leading to liver recovery during subnormothermic machine perfusion (SNMP). MMA was performed on a large scale liver-specific human metabolic network that was weighted based on metabolomics data and identified cofactor-mediated modules that would not have been discovered by traditional metabolic pathway analyses.

Redirection of the Respiro-Fermentative Flux Distribution in Saccharomyces cerevisiae by Overexpression of the Transcription Factor Hap4p

PubMed Central

Blom, Jolanda; De Mattos, M. Joost Teixeira; Grivell, Leslie A.

2000-01-01

Reduction of aerobic fermentation on sugars by altering the fermentative/oxidative balance is of significant interest for optimization of industrial production of Saccharomyces cerevisiae. Glucose control of oxidative metabolism in baker's yeast is partly mediated through transcriptional regulation of the Hap4p subunit of the Hap2/3/4/5p transcriptional activator complex. To alleviate glucose repression of oxidative metabolism, we constructed a yeast strain with constitutively elevated levels of Hap4p. Genetic analysis of expression levels of glucose-repressed genes and analysis of respiratory capacity showed that Hap4p overexpression (partly) relieves glucose repression of respiration. Analysis of the physiological properties of the Hap4p overproducer in batch cultures in fermentors (aerobic, glucose excess) has shown that the metabolism of this strain is more oxidative than in the wild-type strain, resulting in a significant reduced ethanol production and improvement of growth rate and a 40% gain in biomass yield. Our results show that modification of one or more transcriptional regulators can be a powerful and a widely applicable tool for redirection of metabolic fluxes in microorganisms. PMID:10788368

Urban water metabolism efficiency assessment: integrated analysis of available and virtual water.

PubMed

Huang, Chu-Long; Vause, Jonathan; Ma, Hwong-Wen; Yu, Chang-Ping

2013-05-01

Resolving the complex environmental problems of water pollution and shortage which occur during urbanization requires the systematic assessment of urban water metabolism efficiency (WME). While previous research has tended to focus on either available or virtual water metabolism, here we argue that the systematic problems arising during urbanization require an integrated assessment of available and virtual WME, using an indicator system based on material flow analysis (MFA) results. Future research should focus on the following areas: 1) analysis of available and virtual water flow patterns and processes through urban districts in different urbanization phases in years with varying amounts of rainfall, and their environmental effects; 2) based on the optimization of social, economic and environmental benefits, establishment of an indicator system for urban WME assessment using MFA results; 3) integrated assessment of available and virtual WME in districts with different urbanization levels, to facilitate study of the interactions between the natural and social water cycles; 4) analysis of mechanisms driving differences in WME between districts with different urbanization levels, and the selection of dominant social and economic driving indicators, especially those impacting water resource consumption. Combinations of these driving indicators could then be used to design efficient water resource metabolism solutions, and integrated management policies for reduced water consumption. Copyright © 2013 Elsevier B.V. All rights reserved.

Global metabolic interaction network of the human gut microbiota for context-specific community-scale analysis

PubMed Central

Sung, Jaeyun; Kim, Seunghyeon; Cabatbat, Josephine Jill T.; Jang, Sungho; Jin, Yong-Su; Jung, Gyoo Yeol; Chia, Nicholas; Kim, Pan-Jun

2017-01-01

A system-level framework of complex microbe–microbe and host–microbe chemical cross-talk would help elucidate the role of our gut microbiota in health and disease. Here we report a literature-curated interspecies network of the human gut microbiota, called NJS16. This is an extensive data resource composed of ∼570 microbial species and 3 human cell types metabolically interacting through >4,400 small-molecule transport and macromolecule degradation events. Based on the contents of our network, we develop a mathematical approach to elucidate representative microbial and metabolic features of the gut microbial community in a given population, such as a disease cohort. Applying this strategy to microbiome data from type 2 diabetes patients reveals a context-specific infrastructure of the gut microbial ecosystem, core microbial entities with large metabolic influence, and frequently produced metabolic compounds that might indicate relevant community metabolic processes. Our network presents a foundation towards integrative investigations of community-scale microbial activities within the human gut. PMID:28585563

Global metabolic interaction network of the human gut microbiota for context-specific community-scale analysis.

PubMed

Sung, Jaeyun; Kim, Seunghyeon; Cabatbat, Josephine Jill T; Jang, Sungho; Jin, Yong-Su; Jung, Gyoo Yeol; Chia, Nicholas; Kim, Pan-Jun

2017-06-06

A system-level framework of complex microbe-microbe and host-microbe chemical cross-talk would help elucidate the role of our gut microbiota in health and disease. Here we report a literature-curated interspecies network of the human gut microbiota, called NJS16. This is an extensive data resource composed of ∼570 microbial species and 3 human cell types metabolically interacting through >4,400 small-molecule transport and macromolecule degradation events. Based on the contents of our network, we develop a mathematical approach to elucidate representative microbial and metabolic features of the gut microbial community in a given population, such as a disease cohort. Applying this strategy to microbiome data from type 2 diabetes patients reveals a context-specific infrastructure of the gut microbial ecosystem, core microbial entities with large metabolic influence, and frequently produced metabolic compounds that might indicate relevant community metabolic processes. Our network presents a foundation towards integrative investigations of community-scale microbial activities within the human gut.

[Definite of nutritional status in patients with metabolic syndrome with the use of modern methods of nutrimetabolomica].

PubMed

Viskunova, A A; Kaganov, B S; Sharafetdinov, Kh Kh; Plotnikova, O A; Pogozheva, A V; Vorozhko, I V

2010-01-01

A comprehensive assessment of nutritional status in 73 patients with metabolic syndrome was assessed. The consumption food pattern of the majority of examined patients have had increased energy intake with excessive fat consumption inadequate intake of complex carbohydrates. In patients with type 2 diabetes inadequate compensation of carbohydrate and lipid metabolism was marked. When assessing body composition method bioelectrical impedance analysis increased content of adipose tissue was revealed are positively correlated with insulin and tumor necrosis factor-alpha. According to indirect calorimetry, increase in the level of resting energy expenditure, reducing the rate of oxidation of fat, increase the rate of oxidation of protein and carbohydrates was noted.

Systematic identification of genes involved in metabolic acid stress resistance in yeast and their potential as cancer targets.

PubMed

Shin, John J; Aftab, Qurratulain; Austin, Pamela; McQueen, Jennifer A; Poon, Tak; Li, Shu Chen; Young, Barry P; Roskelley, Calvin D; Loewen, Christopher J R

2016-09-01

A hallmark of all primary and metastatic tumours is their high rate of glucose uptake and glycolysis. A consequence of the glycolytic phenotype is the accumulation of metabolic acid; hence, tumour cells experience considerable intracellular acid stress. To compensate, tumour cells upregulate acid pumps, which expel the metabolic acid into the surrounding tumour environment, resulting in alkalization of intracellular pH and acidification of the tumour microenvironment. Nevertheless, we have only a limited understanding of the consequences of altered intracellular pH on cell physiology, or of the genes and pathways that respond to metabolic acid stress. We have used yeast as a genetic model for metabolic acid stress with the rationale that the metabolic changes that occur in cancer that lead to intracellular acid stress are likely fundamental. Using a quantitative systems biology approach we identified 129 genes required for optimal growth under conditions of metabolic acid stress. We identified six highly conserved protein complexes with functions related to oxidative phosphorylation (mitochondrial respiratory chain complex III and IV), mitochondrial tRNA biosynthesis [glutamyl-tRNA(Gln) amidotransferase complex], histone methylation (Set1C-COMPASS), lysosome biogenesis (AP-3 adapter complex), and mRNA processing and P-body formation (PAN complex). We tested roles for two of these, AP-3 adapter complex and PAN deadenylase complex, in resistance to acid stress using a myeloid leukaemia-derived human cell line that we determined to be acid stress resistant. Loss of either complex inhibited growth of Hap1 cells at neutral pH and caused sensitivity to acid stress, indicating that AP-3 and PAN complexes are promising new targets in the treatment of cancer. Additionally, our data suggests that tumours may be genetically sensitized to acid stress and hence susceptible to acid stress-directed therapies, as many tumours accumulate mutations in mitochondrial respiratory chain complexes required for their proliferation. © 2016. Published by The Company of Biologists Ltd.

Environmental metabolomics with data science for investigating ecosystem homeostasis.

PubMed

Kikuchi, Jun; Ito, Kengo; Date, Yasuhiro

2018-02-01

A natural ecosystem can be viewed as the interconnections between complex metabolic reactions and environments. Humans, a part of these ecosystems, and their activities strongly affect the environments. To account for human effects within ecosystems, understanding what benefits humans receive by facilitating the maintenance of environmental homeostasis is important. This review describes recent applications of several NMR approaches to the evaluation of environmental homeostasis by metabolic profiling and data science. The basic NMR strategy used to evaluate homeostasis using big data collection is similar to that used in human health studies. Sophisticated metabolomic approaches (metabolic profiling) are widely reported in the literature. Further challenges include the analysis of complex macromolecular structures, and of the compositions and interactions of plant biomass, soil humic substances, and aqueous particulate organic matter. To support the study of these topics, we also discuss sample preparation techniques and solid-state NMR approaches. Because NMR approaches can produce a number of data with high reproducibility and inter-institution compatibility, further analysis of such data using machine learning approaches is often worthwhile. We also describe methods for data pretreatment in solid-state NMR and for environmental feature extraction from heterogeneously-measured spectroscopic data by machine learning approaches. Copyright © 2017. Published by Elsevier B.V.

Metaproteome analysis to determine the metabolically active part of a thermophilic microbial community producing biogas from agricultural biomass.

PubMed

Hanreich, Angelika; Heyer, Robert; Benndorf, Dirk; Rapp, Erdmann; Pioch, Markus; Reichl, Udo; Klocke, Michael

2012-07-01

Complex consortia of microorganisms are responsible for biogas production. A lot of information about the taxonomic structure and enzymatic potential of such communities has been collected by a variety of gene-based approaches, yet little is known about which of all the assumable metabolic pathways are active throughout the process of biogas formation. To tackle this problem, we established a protocol for the metaproteomic analysis of samples taken from biogas reactors fed with agricultural biomass. In contrast to previous studies where an anaerobic digester was fed with synthetic wastewater, the complex matrix in this study required the extraction of proteins with liquid phenol and the application of paper bridge loading for 2-dimensional gel electrophoresis. Proteins were subjected to nanoHPLC (high-performance liquid chromatography) coupled to tandem mass spectrometry for characterization. Several housekeeping proteins as well as methanogenesis-related enzymes were identified by a MASCOT search and de novo sequencing, which proved the feasibility of our approach. The establishment of such an approach is the basis for further metaproteomic studies of biogas-producing communities. In particular, the apparent status of metabolic activities within the communities can be monitored. The knowledge collected from such experiments could lead to further improvements of biogas production.

MALDI Mass Spectrometry Imaging of Lipids and Gene Expression Reveals Differences in Fatty Acid Metabolism between Follicular Compartments in Porcine Ovaries

PubMed Central

Uzbekova, Svetlana; Elis, Sebastien; Teixeira-Gomes, Ana-Paula; Desmarchais, Alice; Maillard, Virginie; Labas, Valerie

2015-01-01

In mammals, oocytes develop inside the ovarian follicles; this process is strongly supported by the surrounding follicular environment consisting of cumulus, granulosa and theca cells, and follicular fluid. In the antral follicle, the final stages of oogenesis require large amounts of energy that is produced by follicular cells from substrates including glucose, amino acids and fatty acids (FAs). Since lipid metabolism plays an important role in acquiring oocyte developmental competence, the aim of this study was to investigate site-specificity of lipid metabolism in ovaries by comparing lipid profiles and expression of FA metabolism-related genes in different ovarian compartments. Using MALDI Mass Spectrometry Imaging, images of porcine ovary sections were reconstructed from lipid ion signals for the first time. Cluster analysis of ion spectra revealed differences in spatial distribution of lipid species among ovarian compartments, notably between the follicles and interstitial tissue. Inside the follicles analysis differentiated follicular fluid, granulosa, theca and the oocyte-cumulus complex. Moreover, by transcript quantification using real time PCR, we showed that expression of five key genes in FA metabolism significantly varied between somatic follicular cells (theca, granulosa and cumulus) and the oocyte. In conclusion, lipid metabolism differs between ovarian and follicular compartments. PMID:25756245

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

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.

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.

A global evolutionary and metabolic analysis of human obesity gene risk variants.

PubMed

Castillo, Joseph J; Hazlett, Zachary S; Orlando, Robert A; Garver, William S

2017-09-05

It is generally accepted that the selection of gene variants during human evolution optimized energy metabolism that now interacts with our obesogenic environment to increase the prevalence of obesity. The purpose of this study was to perform a global evolutionary and metabolic analysis of human obesity gene risk variants (110 human obesity genes with 127 nearest gene risk variants) identified using genome-wide association studies (GWAS) to enhance our knowledge of early and late genotypes. As a result of determining the mean frequency of these obesity gene risk variants in 13 available populations from around the world our results provide evidence for the early selection of ancestral risk variants (defined as selection before migration from Africa) and late selection of derived risk variants (defined as selection after migration from Africa). Our results also provide novel information for association of these obesity genes or encoded proteins with diverse metabolic pathways and other human diseases. The overall results indicate a significant differential evolutionary pattern for the selection of obesity gene ancestral and derived risk variants proposed to optimize energy metabolism in varying global environments and complex association with metabolic pathways and other human diseases. These results are consistent with obesity genes that encode proteins possessing a fundamental role in maintaining energy metabolism and survival during the course of human evolution. Copyright © 2017. Published by Elsevier B.V.

Analysis of the Enhanced Stability of R(+)-Alpha Lipoic Acid by the Complex Formation with Cyclodextrins

PubMed Central

Ikuta, Naoko; Sugiyama, Hironori; Shimosegawa, Hiroshi; Nakane, Rie; Ishida, Yoshiyuki; Uekaji, Yukiko; Nakata, Daisuke; Pallauf, Kathrin; Rimbach, Gerald; Terao, Keiji; Matsugo, Seiichi

2013-01-01

R(+)-alpha lipoic acid (RALA) is one of the cofactors for mitochondrial enzymes and, therefore, plays a central role in energy metabolism. RALA is unstable when exposed to low pH or heat, and therefore, it is difficult to use enantiopure RALA as a pharma- and nutra-ceutical. In this study, we have aimed to stabilize RALA through complex formation with cyclodextrins (CDs). α-CD, β-CD and γ-CD were used for the formation of these RALA-CD complexes. We confirmed the complex formation using differential scanning calorimetry and showed by using HPLC analysis that complexed RALA is more stable than free RALA when subjected to humidity and high temperature or acidic pH conditions. Scanning electron microscopy studies showed that the particle size and shape differed depending on the cyclodextrin used for complexation. Further, the complexes of CD and RALA showed a different particle size distribution pattern compared with that of CD itself or that of the physical mixture of RALA and CD. PMID:23434662

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.

Vector analysis of postcardiotomy behavioral phenomena.

PubMed

Caston, J C; Miller, W C; Felber, W J

1975-04-01

The classification of postcardiotomy behavioral phenomena in Figure 1 is proposed for use as a clinical instrument to analyze etiological determinants. The utilization of a vector analysis analogy inherently denies absolutism. Classifications A-P are presented as prototypes of certain ratio imbalances of the metabolic, hemodynamic, environmental, and psychic vectors. Such a system allows for change from one type to another according to the individuality of the patient and the highly specific changes in his clinical presentation. A vector analysis also allows for infinite intermediary ratio imbalances between classification types as a function of time. Thus, postcardiotomy behavioral phenomena could be viewed as the vector summation of hemodynamic, metabolic, environmental, and psychic processes at a given point in time. Elaboration of unknown determinants in this complex syndrome appears to be task for the future.

Effect of High-Carbohydrate Diet on Plasma Metabolome in Mice with Mitochondrial Respiratory Chain Complex III Deficiency

PubMed Central

Rajendran, Jayasimman; Tomašić, Nikica; Kotarsky, Heike; Hansson, Eva; Velagapudi, Vidya; Kallijärvi, Jukka; Fellman, Vineta

2016-01-01

Mitochondrial disorders cause energy failure and metabolic derangements. Metabolome profiling in patients and animal models may identify affected metabolic pathways and reveal new biomarkers of disease progression. Using liver metabolomics we have shown a starvation-like condition in a knock-in (Bcs1lc.232A>G) mouse model of GRACILE syndrome, a neonatal lethal respiratory chain complex III dysfunction with hepatopathy. Here, we hypothesized that a high-carbohydrate diet (HCD, 60% dextrose) will alleviate the hypoglycemia and promote survival of the sick mice. However, when fed HCD the homozygotes had shorter survival (mean ± SD, 29 ± 2.5 days, n = 21) than those on standard diet (33 ± 3.8 days, n = 30), and no improvement in hypoglycemia or liver glycogen depletion. We investigated the plasma metabolome of the HCD- and control diet-fed mice and found that several amino acids and urea cycle intermediates were increased, and arginine, carnitines, succinate, and purine catabolites decreased in the homozygotes. Despite reduced survival the increase in aromatic amino acids, an indicator of liver mitochondrial dysfunction, was normalized on HCD. Quantitative enrichment analysis revealed that glycine, serine and threonine metabolism, phenylalanine and tyrosine metabolism, and urea cycle were also partly normalized on HCD. This dietary intervention revealed an unexpected adverse effect of high-glucose diet in complex III deficiency, and suggests that plasma metabolomics is a valuable tool in evaluation of therapies in mitochondrial disorders. PMID:27809283

Identification of Conserved Moieties in Metabolic Networks by Graph Theoretical Analysis of Atom Transition Networks

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

Haraldsdóttir, Hulda S.; Fleming, Ronan M. T.

Conserved moieties are groups of atoms that remain intact in all reactions of a metabolic network. Identification of conserved moieties gives insight into the structure and function of metabolic networks and facilitates metabolic modelling. All moiety conservation relations can be represented as nonnegative integer vectors in the left null space of the stoichiometric matrix corresponding to a biochemical network. Algorithms exist to compute such vectors based only on reaction stoichiometry but their computational complexity has limited their application to relatively small metabolic networks. Moreover, the vectors returned by existing algorithms do not, in general, represent conservation of a specific moietymore » with a defined atomic structure. Here, we show that identification of conserved moieties requires data on reaction atom mappings in addition to stoichiometry. We present a novel method to identify conserved moieties in metabolic networks by graph theoretical analysis of their underlying atom transition networks. Our method returns the exact group of atoms belonging to each conserved moiety as well as the corresponding vector in the left null space of the stoichiometric matrix. It can be implemented as a pipeline of polynomial time algorithms. Our implementation completes in under five minutes on a metabolic network with more than 4,000 mass balanced reactions. The scalability of the method enables extension of existing applications for moiety conservation relations to genome-scale metabolic networks. Finally, we also give examples of new applications made possible by elucidating the atomic structure of conserved moieties.« less

Computational Functional Analysis of Lipid Metabolic Enzymes.

PubMed

Bagnato, Carolina; Have, Arjen Ten; Prados, María B; Beligni, María V

2017-01-01

The computational analysis of enzymes that participate in lipid metabolism has both common and unique challenges when compared to the whole protein universe. Some of the hurdles that interfere with the functional annotation of lipid metabolic enzymes that are common to other pathways include the definition of proper starting datasets, the construction of reliable multiple sequence alignments, the definition of appropriate evolutionary models, and the reconstruction of phylogenetic trees with high statistical support, particularly for large datasets. Most enzymes that take part in lipid metabolism belong to complex superfamilies with many members that are not involved in lipid metabolism. In addition, some enzymes that do not have sequence similarity catalyze similar or even identical reactions. Some of the challenges that, albeit not unique, are more specific to lipid metabolism refer to the high compartmentalization of the routes, the catalysis in hydrophobic environments and, related to this, the function near or in biological membranes.In this work, we provide guidelines intended to assist in the proper functional annotation of lipid metabolic enzymes, based on previous experiences related to the phospholipase D superfamily and the annotation of the triglyceride synthesis pathway in algae. We describe a pipeline that starts with the definition of an initial set of sequences to be used in similarity-based searches and ends in the reconstruction of phylogenies. We also mention the main issues that have to be taken into consideration when using tools to analyze subcellular localization, hydrophobicity patterns, or presence of transmembrane domains in lipid metabolic enzymes.

Identification of Conserved Moieties in Metabolic Networks by Graph Theoretical Analysis of Atom Transition Networks

PubMed Central

Haraldsdóttir, Hulda S.; Fleming, Ronan M. T.

2016-01-01

Conserved moieties are groups of atoms that remain intact in all reactions of a metabolic network. Identification of conserved moieties gives insight into the structure and function of metabolic networks and facilitates metabolic modelling. All moiety conservation relations can be represented as nonnegative integer vectors in the left null space of the stoichiometric matrix corresponding to a biochemical network. Algorithms exist to compute such vectors based only on reaction stoichiometry but their computational complexity has limited their application to relatively small metabolic networks. Moreover, the vectors returned by existing algorithms do not, in general, represent conservation of a specific moiety with a defined atomic structure. Here, we show that identification of conserved moieties requires data on reaction atom mappings in addition to stoichiometry. We present a novel method to identify conserved moieties in metabolic networks by graph theoretical analysis of their underlying atom transition networks. Our method returns the exact group of atoms belonging to each conserved moiety as well as the corresponding vector in the left null space of the stoichiometric matrix. It can be implemented as a pipeline of polynomial time algorithms. Our implementation completes in under five minutes on a metabolic network with more than 4,000 mass balanced reactions. The scalability of the method enables extension of existing applications for moiety conservation relations to genome-scale metabolic networks. We also give examples of new applications made possible by elucidating the atomic structure of conserved moieties. PMID:27870845

Identification of Conserved Moieties in Metabolic Networks by Graph Theoretical Analysis of Atom Transition Networks

DOE PAGES

Haraldsdóttir, Hulda S.; Fleming, Ronan M. T.

2016-11-21

Conserved moieties are groups of atoms that remain intact in all reactions of a metabolic network. Identification of conserved moieties gives insight into the structure and function of metabolic networks and facilitates metabolic modelling. All moiety conservation relations can be represented as nonnegative integer vectors in the left null space of the stoichiometric matrix corresponding to a biochemical network. Algorithms exist to compute such vectors based only on reaction stoichiometry but their computational complexity has limited their application to relatively small metabolic networks. Moreover, the vectors returned by existing algorithms do not, in general, represent conservation of a specific moietymore » with a defined atomic structure. Here, we show that identification of conserved moieties requires data on reaction atom mappings in addition to stoichiometry. We present a novel method to identify conserved moieties in metabolic networks by graph theoretical analysis of their underlying atom transition networks. Our method returns the exact group of atoms belonging to each conserved moiety as well as the corresponding vector in the left null space of the stoichiometric matrix. It can be implemented as a pipeline of polynomial time algorithms. Our implementation completes in under five minutes on a metabolic network with more than 4,000 mass balanced reactions. The scalability of the method enables extension of existing applications for moiety conservation relations to genome-scale metabolic networks. Finally, we also give examples of new applications made possible by elucidating the atomic structure of conserved moieties.« less

Identification of Conserved Moieties in Metabolic Networks by Graph Theoretical Analysis of Atom Transition Networks.

PubMed

Haraldsdóttir, Hulda S; Fleming, Ronan M T

2016-11-01

Conserved moieties are groups of atoms that remain intact in all reactions of a metabolic network. Identification of conserved moieties gives insight into the structure and function of metabolic networks and facilitates metabolic modelling. All moiety conservation relations can be represented as nonnegative integer vectors in the left null space of the stoichiometric matrix corresponding to a biochemical network. Algorithms exist to compute such vectors based only on reaction stoichiometry but their computational complexity has limited their application to relatively small metabolic networks. Moreover, the vectors returned by existing algorithms do not, in general, represent conservation of a specific moiety with a defined atomic structure. Here, we show that identification of conserved moieties requires data on reaction atom mappings in addition to stoichiometry. We present a novel method to identify conserved moieties in metabolic networks by graph theoretical analysis of their underlying atom transition networks. Our method returns the exact group of atoms belonging to each conserved moiety as well as the corresponding vector in the left null space of the stoichiometric matrix. It can be implemented as a pipeline of polynomial time algorithms. Our implementation completes in under five minutes on a metabolic network with more than 4,000 mass balanced reactions. The scalability of the method enables extension of existing applications for moiety conservation relations to genome-scale metabolic networks. We also give examples of new applications made possible by elucidating the atomic structure of conserved moieties.

Emergence of microbial diversity due to cross-feeding interactions in a spatial model of gut microbial metabolism.

PubMed

Hoek, Milan J A van; Merks, Roeland M H

2017-05-16

The human gut contains approximately 10 14 bacteria, belonging to hundreds of different species. Together, these microbial species form a complex food web that can break down nutrient sources that our own digestive enzymes cannot handle, including complex polysaccharides, producing short chain fatty acids and additional metabolites, e.g., vitamin K. Microbial diversity is important for colonic health: Changes in the composition of the microbiota have been associated with inflammatory bowel disease, diabetes, obesity and Crohn's disease, and make the microbiota more vulnerable to infestation by harmful species, e.g., Clostridium difficile. To get a grip on the controlling factors of microbial diversity in the gut, we here propose a multi-scale, spatiotemporal dynamic flux-balance analysis model to study the emergence of metabolic diversity in a spatial gut-like, tubular environment. The model features genome-scale metabolic models (GEM) of microbial populations, resource sharing via extracellular metabolites, and spatial population dynamics and evolution. In this model, cross-feeding interactions emerge readily, despite the species' ability to metabolize sugars autonomously. Interestingly, the community requires cross-feeding for producing a realistic set of short-chain fatty acids from an input of glucose, If we let the composition of the microbial subpopulations change during invasion of adjacent space, a complex and stratified microbiota evolves, with subspecies specializing on cross-feeding interactions via a mechanism of compensated trait loss. The microbial diversity and stratification collapse if the flux through the gut is enhanced to mimic diarrhea. In conclusion, this in silico model is a helpful tool in systems biology to predict and explain the controlling factors of microbial diversity in the gut. It can be extended to include, e.g., complex nutrient sources, and host-microbiota interactions via the intestinal wall.

Systematic identification and analysis of frequent gene fusion events in metabolic pathways

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

Henry, Christopher S.; Lerma-Ortiz, Claudia; Gerdes, Svetlana Y.

Here, gene fusions are the most powerful type of in silico-derived functional associations. However, many fusion compilations were made when <100 genomes were available, and algorithms for identifying fusions need updating to handle the current avalanche of sequenced genomes. The availability of a large fusion dataset would help probe functional associations and enable systematic analysis of where and why fusion events occur. As a result, here we present a systematic analysis of fusions in prokaryotes. We manually generated two training sets: (i) 121 fusions in the model organism Escherichia coli; (ii) 131 fusions found in B vitamin metabolism. These setsmore » were used to develop a fusion prediction algorithm that captured the training set fusions with only 7 % false negatives and 50 % false positives, a substantial improvement over existing approaches. This algorithm was then applied to identify 3.8 million potential fusions across 11,473 genomes. The results of the analysis are available in a searchable database. A functional analysis identified 3,000 reactions associated with frequent fusion events and revealed areas of metabolism where fusions are particularly prevalent. In conclusion, customary definitions of fusions were shown to be ambiguous, and a stricter one was proposed. Exploring the genes participating in fusion events showed that they most commonly encode transporters, regulators, and metabolic enzymes. The major rationales for fusions between metabolic genes appear to be overcoming pathway bottlenecks, avoiding toxicity, controlling competing pathways, and facilitating expression and assembly of protein complexes. Finally, our fusion dataset provides powerful clues to decipher the biological activities of domains of unknown function.« less

Systematic identification and analysis of frequent gene fusion events in metabolic pathways

DOE PAGES

Henry, Christopher S.; Lerma-Ortiz, Claudia; Gerdes, Svetlana Y.; ...

2016-06-24

Here, gene fusions are the most powerful type of in silico-derived functional associations. However, many fusion compilations were made when <100 genomes were available, and algorithms for identifying fusions need updating to handle the current avalanche of sequenced genomes. The availability of a large fusion dataset would help probe functional associations and enable systematic analysis of where and why fusion events occur. As a result, here we present a systematic analysis of fusions in prokaryotes. We manually generated two training sets: (i) 121 fusions in the model organism Escherichia coli; (ii) 131 fusions found in B vitamin metabolism. These setsmore » were used to develop a fusion prediction algorithm that captured the training set fusions with only 7 % false negatives and 50 % false positives, a substantial improvement over existing approaches. This algorithm was then applied to identify 3.8 million potential fusions across 11,473 genomes. The results of the analysis are available in a searchable database. A functional analysis identified 3,000 reactions associated with frequent fusion events and revealed areas of metabolism where fusions are particularly prevalent. In conclusion, customary definitions of fusions were shown to be ambiguous, and a stricter one was proposed. Exploring the genes participating in fusion events showed that they most commonly encode transporters, regulators, and metabolic enzymes. The major rationales for fusions between metabolic genes appear to be overcoming pathway bottlenecks, avoiding toxicity, controlling competing pathways, and facilitating expression and assembly of protein complexes. Finally, our fusion dataset provides powerful clues to decipher the biological activities of domains of unknown function.« less

The antioxidant uncoupling protein 2 stimulates hnRNPA2/B1, GLUT1 and PKM2 expression and sensitizes pancreas cancer cells to glycolysis inhibition.

PubMed

Brandi, Jessica; Cecconi, Daniela; Cordani, Marco; Torrens-Mas, Margalida; Pacchiana, Raffaella; Dalla Pozza, Elisa; Butera, Giovanna; Manfredi, Marcello; Marengo, Emilio; Oliver, Jordi; Roca, Pilar; Dando, Ilaria; Donadelli, Massimo

2016-12-01

Several evidence indicate that metabolic alterations play a pivotal role in cancer development. Here, we report that the mitochondrial uncoupling protein 2 (UCP2) sustains the metabolic shift from mitochondrial oxidative phosphorylation (mtOXPHOS) to glycolysis in pancreas cancer cells. Indeed, we show that UCP2 sensitizes pancreas cancer cells to the treatment with the glycolytic inhibitor 2-deoxy-D-glucose. Through a bidimensional electrophoresis analysis, we identify 19 protein species differentially expressed after treatment with the UCP2 inhibitor genipin and, by bioinformatic analyses, we show that these proteins are mainly involved in metabolic processes. In particular, we demonstrate that the antioxidant UCP2 induces the expression of hnRNPA2/B1, which is involved in the regulation of both GLUT1 and PKM2 mRNAs, and of lactate dehydrogenase (LDH) increasing the secretion of L-lactic acid. We further demonstrate that the radical scavenger N-acetyl-L-cysteine reverts hnRNPA2/B1 and PKM2 inhibition by genipin indicating a role for reactive oxygen species in the metabolic reprogramming of cancer cells mediated by UCP2. We also observe an UCP2-dependent decrease in mtOXPHOS complex I (NADH dehydrogenase), complex IV (cytochrome c oxidase), complex V (ATPase) and in mitochondrial oxygen consumption, suggesting a role for UCP2 in the counteraction of pancreatic cancer cellular respiration. All these results reveal novel mechanisms through which UCP2 promotes cancer cell proliferation with the concomitant metabolic shift from mtOXPHOS to the glycolytic pathway. Copyright © 2016 Elsevier Inc. All rights reserved.

Arctigenin, a natural compound, activates AMP-activated protein kinase via inhibition of mitochondria complex I and ameliorates metabolic disorders in ob/ob mice.

PubMed

Huang, S-L; Yu, R-T; Gong, J; Feng, Y; Dai, Y-L; Hu, F; Hu, Y-H; Tao, Y-D; Leng, Y

2012-05-01

Arctigenin is a natural compound that had never been previously demonstrated to have a glucose-lowering effect. Here it was found to activate AMP-activated protein kinase (AMPK), and the mechanism by which this occurred, as well as the effects on glucose and lipid metabolism were investigated. 2-Deoxyglucose uptake and AMPK phosphorylation were examined in L6 myotubes and isolated skeletal muscle. Gluconeogenesis and lipid synthesis were evaluated in rat primary hepatocytes. The acute and chronic effects of arctigenin on metabolic abnormalities were observed in C57BL/6J and ob/ob mice. Changes in mitochondrial membrane potential were measured using the J-aggregate-forming dye, JC-1. Analysis of respiration of L6 myotubes or isolated mitochondria was conducted in a channel oxygen system. Arctigenin increased AMPK phosphorylation and stimulated glucose uptake in L6 myotubes and isolated skeletal muscles. In primary hepatocytes, it decreased gluconeogenesis and lipid synthesis. The enhancement of glucose uptake and suppression of hepatic gluconeogenesis and lipid synthesis by arctigenin were prevented by blockade of AMPK activation. The respiration of L6 myotubes or isolated mitochondria was inhibited by arctigenin with a specific effect on respiratory complex I. A single oral dose of arctigenin reduced gluconeogenesis in C57BL/6J mice. Chronic oral administration of arctigenin lowered blood glucose and improved lipid metabolism in ob/ob mice. This study demonstrates a new role for arctigenin as a potent indirect activator of AMPK via inhibition of respiratory complex I, with beneficial effects on metabolic disorders in ob/ob mice. This highlights the potential value of arctigenin as a possible treatment of type 2 diabetes.

Dissecting Leishmania infantum Energy Metabolism - A Systems Perspective

PubMed Central

Subramanian, Abhishek; Jhawar, Jitesh; Sarkar, Ram Rup

2015-01-01

Leishmania infantum, causative agent of visceral leishmaniasis in humans, illustrates a complex lifecycle pertaining to two extreme environments, namely, the gut of the sandfly vector and human macrophages. Leishmania is capable of dynamically adapting and tactically switching between these critically hostile situations. The possible metabolic routes ventured by the parasite to achieve this exceptional adaptation to its varying environments are still poorly understood. In this study, we present an extensively reconstructed energy metabolism network of Leishmania infantum as an attempt to identify certain strategic metabolic routes preferred by the parasite to optimize its survival in such dynamic environments. The reconstructed network consists of 142 genes encoding for enzymes performing 237 reactions distributed across five distinct model compartments. We annotated the subcellular locations of different enzymes and their reactions on the basis of strong literature evidence and sequence-based detection of cellular localization signal within a protein sequence. To explore the diverse features of parasite metabolism the metabolic network was implemented and analyzed as a constraint-based model. Using a systems-based approach, we also put forth an extensive set of lethal reaction knockouts; some of which were validated using published data on Leishmania species. Performing a robustness analysis, the model was rigorously validated and tested for the secretion of overflow metabolites specific to Leishmania under varying extracellular oxygen uptake rate. Further, the fate of important non-essential amino acids in L. infantum metabolism was investigated. Stage-specific scenarios of L. infantum energy metabolism were incorporated in the model and key metabolic differences were outlined. Analysis of the model revealed the essentiality of glucose uptake, succinate fermentation, glutamate biosynthesis and an active TCA cycle as driving forces for parasite energy metabolism and its optimal growth. Finally, through our in silico knockout analysis, we could identify possible therapeutic targets that provide experimentally testable hypotheses. PMID:26367006

Salmonella Modulates Metabolism During Growth under Conditions that Induce Expression of Virulence Genes

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

Kim, Young-Mo; Schmidt, Brian; Kidwai, Afshan S.

Salmonella enterica serovar Typhimurium (S. Typhimurium) is a facultative pathogen that uses complex mechanisms to invade and proliferate within mammalian host cells. To investigate possible contributions of metabolic processes in S. Typhimurium grown under conditions known to induce expression of virulence genes, we used a metabolomics-driven systems biology approach coupled with genome scale modeling. First, we identified distinct metabolite profiles associated with bacteria grown in either rich or virulence-inducing media and report the most comprehensive coverage of the S. Typhimurium metabolome to date. Second, we applied an omics-informed genome scale modeling analysis of the functional consequences of adaptive alterations inmore » S. Typhimurium metabolism during growth under our conditions. Excitingly, we observed possible sequestration of metabolites recently suggested to have immune modulating roles. Modeling efforts highlighted a decreased cellular capability to both produce and utilize intracellular amino acids during stationary phase culture in virulence conditions, despite significant abundance increases for these molecules as observed by our metabolomics measurements. Model-guided analysis suggested that alterations in metabolism prioritized other activities necessary for pathogenesis instead, such as lipopolysaccharide biosynthesis.« less

Metabolome analysis for discovering biomarkers of gastroenterological cancer.

PubMed

Suzuki, Makoto; Nishiumi, Shin; Matsubara, Atsuki; Azuma, Takeshi; Yoshida, Masaru

2014-09-01

Improvements in analytical technologies have made it possible to rapidly determine the concentrations of thousands of metabolites in any biological sample, which has resulted in metabolome analysis being applied to various types of research, such as clinical, cell biology, and plant/food science studies. The metabolome represents all of the end products and by-products of the numerous complex metabolic pathways operating in a biological system. Thus, metabolome analysis allows one to survey the global changes in an organism's metabolic profile and gain a holistic understanding of the changes that occur in organisms during various biological processes, e.g., during disease development. In clinical metabolomic studies, there is a strong possibility that differences in the metabolic profiles of human specimens reflect disease-specific states. Recently, metabolome analysis of biofluids, e.g., blood, urine, or saliva, has been increasingly used for biomarker discovery and disease diagnosis. Mass spectrometry-based techniques have been extensively used for metabolome analysis because they exhibit high selectivity and sensitivity during the identification and quantification of metabolites. Here, we describe metabolome analysis using liquid chromatography-mass spectrometry, gas chromatography-mass spectrometry, and capillary electrophoresis-mass spectrometry. Furthermore, the findings of studies that attempted to discover biomarkers of gastroenterological cancer are also outlined. Finally, we discuss metabolome analysis-based disease diagnosis. Copyright © 2014 Elsevier B.V. All rights reserved.

Metagenomic insights into zooplankton‐associated bacterial communities

PubMed Central

Srivastava, Abhishek; Koski, Marja; Garcia, Juan Antonio L.; Takaki, Yoshihiro; Yokokawa, Taichi; Nunoura, Takuro; Elisabeth, Nathalie H.; Sintes, Eva; Herndl, Gerhard J.

2017-01-01

Summary Zooplankton and microbes play a key role in the ocean's biological cycles by releasing and consuming copious amounts of particulate and dissolved organic matter. Additionally, zooplankton provide a complex microhabitat rich in organic and inorganic nutrients in which bacteria thrive. In this study, we assessed the phylogenetic composition and metabolic potential of microbial communities associated with crustacean zooplankton species collected in the North Atlantic. Using Illumina sequencing of the 16S rRNA gene, we found significant differences between the microbial communities associated with zooplankton and those inhabiting the surrounding seawater. Metagenomic analysis of the zooplankton‐associated microbial community revealed a highly specialized bacterial community able to exploit zooplankton as microhabitat and thus, mediating biogeochemical processes generally underrepresented in the open ocean. The zooplankton‐associated bacterial community is able to colonize the zooplankton's internal and external surfaces using a large set of adhesion mechanisms and to metabolize complex organic compounds released or exuded by the zooplankton such as chitin, taurine and other complex molecules. Moreover, the high number of genes involved in iron and phosphorus metabolisms in the zooplankton‐associated microbiome suggests that this zooplankton‐associated bacterial community mediates specific biogeochemical processes (through the proliferation of specific taxa) that are generally underrepresented in the ambient waters. PMID:28967193

Mutations in Global Regulators Lead to Metabolic Selection during Adaptation to Complex Environments

PubMed Central

Saxer, Gerda; Krepps, Michael D.; Merkley, Eric D.; Ansong, Charles; Deatherage Kaiser, Brooke L.; Valovska, Marie-Thérèse; Ristic, Nikola; Yeh, Ping T.; Prakash, Vittal P.; Leiser, Owen P.; Nakhleh, Luay; Gibbons, Henry S.; Kreuzer, Helen W.; Shamoo, Yousif

2014-01-01

Adaptation to ecologically complex environments can provide insights into the evolutionary dynamics and functional constraints encountered by organisms during natural selection. Adaptation to a new environment with abundant and varied resources can be difficult to achieve by small incremental changes if many mutations are required to achieve even modest gains in fitness. Since changing complex environments are quite common in nature, we investigated how such an epistatic bottleneck can be avoided to allow rapid adaptation. We show that adaptive mutations arise repeatedly in independently evolved populations in the context of greatly increased genetic and phenotypic diversity. We go on to show that weak selection requiring substantial metabolic reprogramming can be readily achieved by mutations in the global response regulator arcA and the stress response regulator rpoS. We identified 46 unique single-nucleotide variants of arcA and 18 mutations in rpoS, nine of which resulted in stop codons or large deletions, suggesting that subtle modulations of ArcA function and knockouts of rpoS are largely responsible for the metabolic shifts leading to adaptation. These mutations allow a higher order metabolic selection that eliminates epistatic bottlenecks, which could occur when many changes would be required. Proteomic and carbohydrate analysis of adapting E. coli populations revealed an up-regulation of enzymes associated with the TCA cycle and amino acid metabolism, and an increase in the secretion of putrescine. The overall effect of adaptation across populations is to redirect and efficiently utilize uptake and catabolism of abundant amino acids. Concomitantly, there is a pronounced spread of more ecologically limited strains that results from specialization through metabolic erosion. Remarkably, the global regulators arcA and rpoS can provide a “one-step” mechanism of adaptation to a novel environment, which highlights the importance of global resource management as a powerful strategy to adaptation. PMID:25501822

Mutations in global regulators lead to metabolic selection during adaptation to complex environments

DOE PAGES

Saxer, Gerda; Krepps, Michael D.; Merkley, Eric D.; ...

2014-12-11

Adaptation to ecologically complex environments can provide insights into the evolutionary dynamics and functional constraints encountered by organisms during natural selection. Unlike adaptation to a single limiting resource, adaptation to a new environment with abundant and varied resources can be difficult to achieve by small incremental changes since many mutations are required to achieve even modest gains in fitness. Since changing complex environments are quite common in nature, we investigated how such an epistatic bottleneck can be avoided to allow rapid adaptation. We show that adaptive mutations arise repeatedly in independently evolved populations in the context of greatly increased geneticmore » and phenotypic diversity. We go on to show that weak selection requiring substantial metabolic reprogramming can be readily achieved by mutations in the global response regulator arcA and the stress response regulator rpoS. We identified 46 unique single-nucleotide variants of arcA and 18 mutations in rpoS, nine of which resulted in stop codons or large deletions, suggesting that a subtle modulation of ArcA function and knockouts of rpoS are largely responsible for the metabolic shifts leading to adaptation. These mutations allow a higher order “metabolic selection” that eliminates epistatic bottlenecks, which could occur when many changes would be required. Proteomic and carbohydrate analysis of adapting E. coli populations revealed an up-regulation of enzymes associated with the TCA cycle and amino acid metabolism and an increase in the secretion of putrescine. The overall effect of adaptation across populations is to redirect and efficiently utilize uptake and catabolism of abundant amino acids. Concomitantly, there is a pronounced spread of more ecologically limited strains that results from specialization through metabolic erosion. Remarkably, the global regulators arcA and rpoS can provide a “one-step” mechanism of adaptation to a novel environment, which highlights the importance of global resource management as a powerful strategy to adaptation.« less

Response to weaning and dietary L-glutamine supplementation: metabolomic analysis in piglets by gas chromatography/mass spectrometry.

PubMed

Xiao, Ying-ping; Wu, Tian-xing; Hong, Qi-hua; Sun, Jiang-ming; Chen, An-guo; Yang, Cai-mei; Li, Xiao-yan

2012-07-01

A novel metabolomic method based on gas chromatography/mass spectrometry (GC-MS) was applied to determine the metabolites in the serum of piglets in response to weaning and dietary L-glutamine (Gln) supplementation. Thirty-six 21-d-old piglets were randomly assigned into three groups. One group continued to suckle from the sows (suckling group), whereas the other two groups were weaned and their diets were supplemented with 1% (w/w) Gln or isonitrogenous L-alanine, respectively, representing Gln group or control group. Serum samples were collected to characterize metabolites after a 7-d treatment. Results showed that twenty metabolites were down-regulated significantly (P<0.05) in control piglets compared with suckling ones. These data demonstrated that early weaning causes a wide range of metabolic changes across arginine and proline metabolism, aminosugar and nucleotide metabolism, galactose metabolism, glycerophospholipid metabolism, biosynthesis of unsaturated fatty acid, and fatty acid metabolism. Dietary Gln supplementation increased the levels of creatinine, D-xylose, 2-hydroxybutyric acid, palmitelaidic acid, and α-L-galactofuranose (P<0.05) in early weaned piglets, and were involved in the arginine and proline metabolism, carbohydrate metabolism, and fatty acid metabolism. A leave-one-out cross-validation of random forest analysis indicated that creatinine was the most important metabolite among the three groups. Notably, the concentration of creatinine in control piglets was decreased (P=0.00001) compared to the suckling piglets, and increased (P=0.0003) in Gln-supplemented piglets. A correlation network for weaned and suckling piglets revealed that early weaning changed the metabolic pathways, leading to the abnormality of carbohydrate metabolism, amino acid metabolism, and lipid metabolism, which could be partially improved by dietary Gln supplementation. These findings provide fresh insight into the complex metabolic changes in response to early weaning and dietary Gln supplementation in piglets.

Response to weaning and dietary L-glutamine supplementation: metabolomic analysis in piglets by gas chromatography/mass spectrometry*

PubMed Central

Xiao, Ying-ping; Wu, Tian-xing; Hong, Qi-hua; Sun, Jiang-ming; Chen, An-guo; Yang, Cai-mei; Li, Xiao-yan

2012-01-01

A novel metabolomic method based on gas chromatography/mass spectrometry (GC-MS) was applied to determine the metabolites in the serum of piglets in response to weaning and dietary L-glutamine (Gln) supplementation. Thirty-six 21-d-old piglets were randomly assigned into three groups. One group continued to suckle from the sows (suckling group), whereas the other two groups were weaned and their diets were supplemented with 1% (w/w) Gln or isonitrogenous L-alanine, respectively, representing Gln group or control group. Serum samples were collected to characterize metabolites after a 7-d treatment. Results showed that twenty metabolites were down-regulated significantly (P<0.05) in control piglets compared with suckling ones. These data demonstrated that early weaning causes a wide range of metabolic changes across arginine and proline metabolism, aminosugar and nucleotide metabolism, galactose metabolism, glycerophospholipid metabolism, biosynthesis of unsaturated fatty acid, and fatty acid metabolism. Dietary Gln supplementation increased the levels of creatinine,D-xylose, 2-hydroxybutyric acid, palmitelaidic acid, and α-L-galactofuranose (P<0.05) in early weaned piglets, and were involved in the arginine and proline metabolism, carbohydrate metabolism, and fatty acid metabolism. A leave-one-out cross-validation of random forest analysis indicated that creatinine was the most important metabolite among the three groups. Notably, the concentration of creatinine in control piglets was decreased (P=0.00001) compared to the suckling piglets, and increased (P=0.0003) in Gln-supplemented piglets. A correlation network for weaned and suckling piglets revealed that early weaning changed the metabolic pathways, leading to the abnormality of carbohydrate metabolism, amino acid metabolism, and lipid metabolism, which could be partially improved by dietary Gln supplementation. These findings provide fresh insight into the complex metabolic changes in response to early weaning and dietary Gln supplementation in piglets. PMID:22761248

Linking Toluene Degradation with Specific Microbial Populations in Soil

PubMed Central

Hanson, Jessica R.; Macalady, Jennifer L.; Harris, David; Scow, Kate M.

1999-01-01

Phospholipid fatty acid (PLFA) analysis of a soil microbial community was coupled with 13C isotope tracer analysis to measure the community’s response to addition of 35 μg of [13C]toluene ml of soil solution−1. After 119 h of incubation with toluene, 96% of the incorporated 13C was detected in only 16 of the total 59 PLFAs (27%) extracted from the soil. Of the total 13C-enriched PLFAs, 85% were identical to the PLFAs contained in a toluene-metabolizing bacterium isolated from the same soil. In contrast, the majority of the soil PLFAs (91%) became labeled when the same soil was incubated with [13C]glucose. Our study showed that coupling 13C tracer analysis with PLFA analysis is an effective technique for distinguishing a specific microbial population involved in metabolism of a labeled substrate in complex environments such as soil. PMID:10583996

Toward Engineering Synthetic Microbial Metabolism

PubMed Central

McArthur, George H.; Fong, Stephen S.

2010-01-01

The generation of well-characterized parts and the formulation of biological design principles in synthetic biology are laying the foundation for more complex and advanced microbial metabolic engineering. Improvements in de novo DNA synthesis and codon-optimization alone are already contributing to the manufacturing of pathway enzymes with improved or novel function. Further development of analytical and computer-aided design tools should accelerate the forward engineering of precisely regulated synthetic pathways by providing a standard framework for the predictable design of biological systems from well-characterized parts. In this review we discuss the current state of synthetic biology within a four-stage framework (design, modeling, synthesis, analysis) and highlight areas requiring further advancement to facilitate true engineering of synthetic microbial metabolism. PMID:20037734

Metabolic Coevolution in the Bacterial Symbiosis of Whiteflies and Related Plant Sap-Feeding Insects.

PubMed

Luan, Jun-Bo; Chen, Wenbo; Hasegawa, Daniel K; Simmons, Alvin M; Wintermantel, William M; Ling, Kai-Shu; Fei, Zhangjun; Liu, Shu-Sheng; Douglas, Angela E

2015-09-15

Genomic decay is a common feature of intracellular bacteria that have entered into symbiosis with plant sap-feeding insects. This study of the whitefly Bemisia tabaci and two bacteria (Portiera aleyrodidarum and Hamiltonella defensa) cohoused in each host cell investigated whether the decay of Portiera metabolism genes is complemented by host and Hamiltonella genes, and compared the metabolic traits of the whitefly symbiosis with other sap-feeding insects (aphids, psyllids, and mealybugs). Parallel genomic and transcriptomic analysis revealed that the host genome contributes multiple metabolic reactions that complement or duplicate Portiera function, and that Hamiltonella may contribute multiple cofactors and one essential amino acid, lysine. Homologs of the Bemisia metabolism genes of insect origin have also been implicated in essential amino acid synthesis in other sap-feeding insect hosts, indicative of parallel coevolution of shared metabolic pathways across multiple symbioses. Further metabolism genes coded in the Bemisia genome are of bacterial origin, but phylogenetically distinct from Portiera, Hamiltonella and horizontally transferred genes identified in other sap-feeding insects. Overall, 75% of the metabolism genes of bacterial origin are functionally unique to one symbiosis, indicating that the evolutionary history of metabolic integration in these symbioses is strongly contingent on the pattern of horizontally acquired genes. Our analysis, further, shows that bacteria with genomic decay enable host acquisition of complex metabolic pathways by multiple independent horizontal gene transfers from exogenous bacteria. Specifically, each horizontally acquired gene can function with other genes in the pathway coded by the symbiont, while facilitating the decay of the symbiont gene coding the same reaction. © The Author(s) 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Integrative neurobiology of metabolic diseases, neuroinflammation, and neurodegeneration

PubMed Central

van Dijk, Gertjan; van Heijningen, Steffen; Reijne, Aaffien C.; Nyakas, Csaba; van der Zee, Eddy A.; Eisel, Ulrich L. M.

2015-01-01

Alzheimer's disease (AD) is a complex, multifactorial disease with a number of leading mechanisms, including neuroinflammation, processing of amyloid precursor protein (APP) to amyloid β peptide, tau protein hyperphosphorylation, relocalization, and deposition. These mechanisms are propagated by obesity, the metabolic syndrome and type-2 diabetes mellitus. Stress, sedentariness, dietary overconsumption of saturated fat and refined sugars, and circadian derangements/disturbed sleep contribute to obesity and related metabolic diseases, but also accelerate age-related damage and senescence that all feed the risk of developing AD too. The complex and interacting mechanisms are not yet completely understood and will require further analysis. Instead of investigating AD as a mono- or oligocausal disease we should address the disease by understanding the multiple underlying mechanisms and how these interact. Future research therefore might concentrate on integrating these by “systems biology” approaches, but also to regard them from an evolutionary medicine point of view. The current review addresses several of these interacting mechanisms in animal models and compares them with clinical data giving an overview about our current knowledge and puts them into an integrated framework. PMID:26041981

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 weakness of conventional FBA to rely on intuitive assumptions about the reversibility of biochemical reactions is overcome. This enables the computation of reliable flux distributions even under extreme conditions of the network (e.g. enzyme inhibition, depletion of substrates or accumulation of end products) where metabolite concentrations may be drastically altered. PMID:17543097

Analysis of Brain Recurrence

NASA Astrophysics Data System (ADS)

Frilot, Clifton; Kim, Paul Y.; Carrubba, Simona; McCarty, David E.; Chesson, Andrew L.; Marino, Andrew A.

Analysis of Brain Recurrence (ABR) is a method for extracting physiologically significant information from the electroencephalogram (EEG), a non-stationary electrical output of the brain, the ultimate complex dynamical system. ABR permits quantification of temporal patterns in the EEG produced by the non-autonomous differential laws that govern brain metabolism. In the context of appropriate experimental and statistical designs, ABR is ideally suited to the task of interpreting the EEG. Present applications of ABR include discovery of a human magnetic sense, increased mechanistic understanding of neuronal membrane processes, diagnosis of degenerative neurological disease, detection of changes in brain metabolism caused by weak environmental electromagnetic fields, objective characterization of the quality of human sleep, and evaluation of sleep disorders. ABR has important beneficial implications for the development of clinical and experimental neuroscience.

Gene expression profiles in whole blood and associations with metabolic dysregulation in obesity.

PubMed

Cox, Amanda J; Zhang, Ping; Evans, Tiffany J; Scott, Rodney J; Cripps, Allan W; West, Nicholas P

Gene expression data provides one tool to gain further insight into the complex biological interactions linking obesity and metabolic disease. This study examined associations between blood gene expression profiles and metabolic disease in obesity. Whole blood gene expression profiles, performed using the Illumina HT-12v4 Human Expression Beadchip, were compared between (i) individuals with obesity (O) or lean (L) individuals (n=21 each), (ii) individuals with (M) or without (H) Metabolic Syndrome (n=11 each) matched on age and gender. Enrichment of differentially expressed genes (DEG) into biological pathways was assessed using Ingenuity Pathway Analysis. Association between sets of genes from biological pathways considered functionally relevant and Metabolic Syndrome were further assessed using an area under the curve (AUC) and cross-validated classification rate (CR). For OvL, only 50 genes were significantly differentially expressed based on the selected differential expression threshold (1.2-fold, p<0.05). For MvH, 582 genes were significantly differentially expressed (1.2-fold, p<0.05) and pathway analysis revealed enrichment of DEG into a diverse set of pathways including immune/inflammatory control, insulin signalling and mitochondrial function pathways. Gene sets from the mTOR signalling pathways demonstrated the strongest association with Metabolic Syndrome (p=8.1×10 -8 ; AUC: 0.909, CR: 72.7%). These results support the use of expression profiling in whole blood in the absence of more specific tissue types for investigations of metabolic disease. Using a pathway analysis approach it was possible to identify an enrichment of DEG into biological pathways that could be targeted for in vitro follow-up. Copyright © 2017 Asia Oceania Association for the Study of Obesity. Published by Elsevier Ltd. All rights reserved.

Proteomic Analysis of the Mediator Complex Interactome in Saccharomyces cerevisiae

PubMed Central

Uthe, Henriette; Vanselow, Jens T.; Schlosser, Andreas

2017-01-01

Here we present the most comprehensive analysis of the yeast Mediator complex interactome to date. Particularly gentle cell lysis and co-immunopurification conditions allowed us to preserve even transient protein-protein interactions and to comprehensively probe the molecular environment of the Mediator complex in the cell. Metabolic 15N-labeling thereby enabled stringent discrimination between bona fide interaction partners and nonspecifically captured proteins. Our data indicates a functional role for Mediator beyond transcription initiation. We identified a large number of Mediator-interacting proteins and protein complexes, such as RNA polymerase II, general transcription factors, a large number of transcriptional activators, the SAGA complex, chromatin remodeling complexes, histone chaperones, highly acetylated histones, as well as proteins playing a role in co-transcriptional processes, such as splicing, mRNA decapping and mRNA decay. Moreover, our data provides clear evidence, that the Mediator complex interacts not only with RNA polymerase II, but also with RNA polymerases I and III, and indicates a functional role of the Mediator complex in rRNA processing and ribosome biogenesis. PMID:28240253

Dietary Aloe QDM Complex Reduces Obesity-Induced Insulin Resistance and Adipogenesis in Obese Mice Fed a High-Fat Diet.

PubMed

Shin, Seulmee; Kim, Seulah; Oh, Hee-Eun; Kong, Hyunseok; Shin, Eunju; Do, Seon-Gil; Jo, Tae Hyung; Park, Young-In; Lee, Chong-Kil; Kim, Kyungjae

2012-06-01

Obesity-induced disorders contribute to the development of metabolic diseases such as insulin resistance, fatty liver diseases, and type 2 diabetes (T2D). In this study, we evaluated whether the Aloe QDM complex could improve metabolic disorders related to blood glucose levels and insulin resistance. Male C57BL/6 obese mice fed a high-fat diet for 54 days received a supplement of Aloe QDM complex or pioglitazone (PGZ) or metformin (Met) and were compared with unsupplemented controls (high-fat diet; HFD) or mice fed a regular diet (RD). RT-PCR and western blot analysis were used to quantify the expression of obesity-induced inflammation. Dietary Aloe QDM complex lowered body weight, fasting blood glucose, plasma insulin, and leptin levels, and markedly reduced the impairment of glucose tolerance in obese mice. Also, Aloe QDM complex significantly enhanced plasma adiponectin levels and insulin sensitivity via AMPK activity in muscles. At the same time, Aloe QDM decreased the mRNA and protein of PPARγ/LXRα and scavenger receptors in white adipose tissue (WAT). Dietary Aloe QDM complex reduces obesity-induced glucose tolerance not only by suppressing PPARγ/LXRα but also by enhancing AMPK activity in the WAT and muscles, both of which are important peripheral tissues affecting insulin resistance. The Aloe QDM complex could be used as a nutritional intervention against T2D.

Dietary Aloe QDM Complex Reduces Obesity-Induced Insulin Resistance and Adipogenesis in Obese Mice Fed a High-Fat Diet

PubMed Central

Shin, Seulmee; Kim, Seulah; Oh, Hee-Eun; Kong, Hyunseok; Shin, Eunju; Do, Seon-Gil; Jo, Tae Hyung; Park, Young-In; Lee, Chong-Kil

2012-01-01

Obesity-induced disorders contribute to the development of metabolic diseases such as insulin resistance, fatty liver diseases, and type 2 diabetes (T2D). In this study, we evaluated whether the Aloe QDM complex could improve metabolic disorders related to blood glucose levels and insulin resistance. Male C57BL/6 obese mice fed a high-fat diet for 54 days received a supplement of Aloe QDM complex or pioglitazone (PGZ) or metformin (Met) and were compared with unsupplemented controls (high-fat diet; HFD) or mice fed a regular diet (RD). RT-PCR and western blot analysis were used to quantify the expression of obesity-induced inflammation. Dietary Aloe QDM complex lowered body weight, fasting blood glucose, plasma insulin, and leptin levels, and markedly reduced the impairment of glucose tolerance in obese mice. Also, Aloe QDM complex significantly enhanced plasma adiponectin levels and insulin sensitivity via AMPK activity in muscles. At the same time, Aloe QDM decreased the mRNA and protein of PPARγ/LXRα and scavenger receptors in white adipose tissue (WAT). Dietary Aloe QDM complex reduces obesity-induced glucose tolerance not only by suppressing PPARγ/LXRα but also by enhancing AMPK activity in the WAT and muscles, both of which are important peripheral tissues affecting insulin resistance. The Aloe QDM complex could be used as a nutritional intervention against T2D. PMID:22916045

Ethanol production improvement driven by genome-scale metabolic modeling and sensitivity analysis in Scheffersomyces stipitis

PubMed Central

2017-01-01

The yeast Scheffersomyces stipitis naturally produces ethanol from xylose, however reaching high ethanol yields is strongly dependent on aeration conditions. It has been reported that changes in the availability of NAD(H/+) cofactors can improve fermentation in some microorganisms. In this work genome-scale metabolic modeling and phenotypic phase plane analysis were used to characterize metabolic response on a range of uptake rates. Sensitivity analysis was used to assess the effect of ARC on ethanol production indicating that modifying ARC by inhibiting the respiratory chain ethanol production can be improved. It was shown experimentally in batch culture using Rotenone as an inhibitor of the mitochondrial NADH dehydrogenase complex I (CINADH), increasing ethanol yield by 18%. Furthermore, trajectories for uptakes rates, specific productivity and specific growth rate were determined by modeling the batch culture, to calculate ARC associated to the addition of CINADH inhibitor. Results showed that the increment in ethanol production via respiratory inhibition is due to excess in ARC, which generates an increase in ethanol production. Thus ethanol production improvement could be predicted by a change in ARC. PMID:28658270

Ethanol production improvement driven by genome-scale metabolic modeling and sensitivity analysis in Scheffersomyces stipitis.

PubMed

Acevedo, Alejandro; Conejeros, Raúl; Aroca, Germán

2017-01-01

The yeast Scheffersomyces stipitis naturally produces ethanol from xylose, however reaching high ethanol yields is strongly dependent on aeration conditions. It has been reported that changes in the availability of NAD(H/+) cofactors can improve fermentation in some microorganisms. In this work genome-scale metabolic modeling and phenotypic phase plane analysis were used to characterize metabolic response on a range of uptake rates. Sensitivity analysis was used to assess the effect of ARC on ethanol production indicating that modifying ARC by inhibiting the respiratory chain ethanol production can be improved. It was shown experimentally in batch culture using Rotenone as an inhibitor of the mitochondrial NADH dehydrogenase complex I (CINADH), increasing ethanol yield by 18%. Furthermore, trajectories for uptakes rates, specific productivity and specific growth rate were determined by modeling the batch culture, to calculate ARC associated to the addition of CINADH inhibitor. Results showed that the increment in ethanol production via respiratory inhibition is due to excess in ARC, which generates an increase in ethanol production. Thus ethanol production improvement could be predicted by a change in ARC.

Proteomic Profiles of Adipose and Liver Tissues from an Animal Model of Metabolic Syndrome Fed Purple Vegetables

PubMed Central

Ayoub, Hala M; McDonald, Mary Ruth; Sullivan, James Alan; Tsao, Rong; Meckling, Kelly A

2018-01-01

Metabolic Syndrome (MetS) is a complex disorder that predisposes an individual to Cardiovascular Diseases and type 2 Diabetes Mellitus. Proteomics and bioinformatics have proven to be an effective tool to study complex diseases and mechanisms of action of nutrients. We previously showed that substitution of the majority of carbohydrate in a high fat diet by purple potatoes (PP) or purple carrots (PC) improved insulin sensitivity and hypertension in an animal model of MetS (obese Zucker rats) compared to a control sucrose-rich diet. In the current study, we used TMT 10plex mass tag combined with LC-MS/MS technique to study proteomic modulation in the liver (n = 3 samples/diet) and adipose tissue (n = 3 samples/diet) of high fat diet-fed rats with or without substituting sucrose for purple vegetables, followed by functional enrichment analysis, in an attempt to elucidate potential molecular mechanisms responsible for the phenotypic changes seen with purple vegetable feeding. Protein folding, lipid metabolism and cholesterol efflux were identified as the main modulated biological themes in adipose tissue, whereas lipid metabolism, carbohydrate metabolism and oxidative stress were the main modulated themes in liver. We propose that enhanced protein folding, increased cholesterol efflux and higher free fatty acid (FFA) re-esterification are mechanisms by which PP and PC positively modulate MetS pathologies in adipose tissue, whereas, decreased de novo lipogenesis, oxidative stress and FFA uptake, are responsible for the beneficial effects in liver. In conclusion, we provide molecular evidence for the reported metabolic health benefits of purple carrots and potatoes and validate that these vegetables are good choices to replace other simple carbohydrate sources for better metabolic health. PMID:29642414

A metabolomics study delineating geographical location-associated primary metabolic changes in the leaves of growing tobacco plants by GC-MS and CE-MS

PubMed Central

Zhao, Yanni; Zhao, Jieyu; Zhao, Chunxia; Zhou, Huina; Li, Yanli; Zhang, Junjie; Li, Lili; Hu, Chunxiu; Li, Wenzheng; Peng, Xiaojun; Lu, Xin; Lin, Fucheng; Xu, Guowang

2015-01-01

Ecological conditions and developmental senescence significantly affect the physiological metabolism of plants, yet relatively little is known about the influence of geographical location on dynamic changes in plant leaves during growth. Pseudotargeted gas chromatography-selected ion monitoring-mass spectrometry and capillary electrophoresis-mass spectrometry were used to investigate a time course of the metabolic responses of tobacco leaves to geographical location. Principal component analysis revealed obvious metabolic discrimination between growing districts relative to cultivars. A complex carbon and nitrogen metabolic network was modulated by environmental factors during growth. When the Xuchang and Dali Districts in China were compared, the results indicated that higher rates of photosynthesis, photorespiration and respiration were utilized in Xuchang District to generate the energy and carbon skeletons needed for the biosynthesis of nitrogen-containing metabolites. The increased abundance of defense-associated metabolites generated from the shikimate-phenylpropanoid pathway in Xuchang relative to Dali was implicated in protection against stress. PMID:26549189

Study on Incompatibility of Traditional Chinese Medicine: Evidence from Formula Network, Chemical Space, and Metabolism Room

PubMed Central

Zhang, Xiao-Dong; Wu, Hong-Ying; Jin, Jin; Yu, Guang-Yun; He, Xin; Wang, Hao; Shen, Xiu; Zhou, Ze-Wei; Liu, Pei-Xun; Fan, Sai-Jun

2013-01-01

A traditional Chinese medicine (TCM) formula network including 362 TCM formulas was built by using complex network methodologies. The properties of this network were analyzed including network diameter, average distance, clustering coefficient, and average degree. Meanwhile, we built a TCM chemical space and a TCM metabolism room under the theory of chemical space. The properties of chemical space and metabolism room were calculated and analyzed. The properties of the medicine pairs in “eighteen antagonisms and nineteen mutual inhibitors,” an ancient rule for TCM incompatibility, were studied based on the TCM formula network, chemical space, and metabolism room. The results showed that the properties of these incompatible medicine pairs are different from those of the other TCM based on the analysis of the TCM formula network, chemical space, and metabolism room. The lines of evidence derived from our work demonstrated that the ancient rule of TCM incompatibility, “eighteen antagonisms and nineteen mutual inhibitors,” is probably scientifically based. PMID:24369478

Analysis of tumor metabolism reveals mitochondrial glucose oxidation in genetically diverse, human glioblastomas in the mouse brain in vivo

PubMed Central

Marin-Valencia, Isaac; Yang, Chendong; Mashimo, Tomoyuki; Cho, Steve; Baek, Hyeonman; Yang, Xiao-Li; Rajagopalan, Kartik N.; Maddie, Melissa; Vemireddy, Vamsidhara; Zhao, Zhenze; Cai, Ling; Good, Levi; Tu, Benjamin P.; Hatanpaa, Kimmo J.; Mickey, Bruce E.; Matés, José M.; Pascual, Juan M.; Maher, Elizabeth A.; Malloy, Craig R.; DeBerardinis, Ralph J.; Bachoo, Robert M.

2012-01-01

SUMMARY Dysregulated metabolism is a hallmark of cancer cell lines, but little is known about the fate of glucose and other nutrients in tumors growing in their native microenvironment. To study tumor metabolism in vivo, we used an orthotopic mouse model of primary human glioblastoma (GBM). We infused 13C-labeled nutrients into mice bearing three independent GBM lines, each with a distinct set of mutations. All three lines displayed glycolysis, as expected for aggressive tumors. They also displayed unexpected metabolic complexity, oxidizing glucose via pyruvate dehydrogenase and the citric acid cycle, and using glucose to supply anaplerosis and other biosynthetic activities. Comparing the tumors to surrounding brain revealed obvious metabolic differences, notably the accumulation of a large glutamine pool within the tumors. Many of these same activities were conserved in cells cultured ex vivo from the tumors. Thus GBM cells utilize mitochondrial glucose oxidation during aggressive tumor growth in vivo. PMID:22682223

Fisetin as a promising antifungal agent against Cryptocococcus neoformans species complex.

PubMed

Reis, M P C; Carvalho, C R C; Andrade, F A; Fernandes, O F L; Arruda, W; Silva, M R R

2016-08-01

The aim of this study was to investigate the mechanisms of action of fisetin, a flavonol with antifungal activity previously evaluated against the Cryptococcus neoformans species complex. Ergosterol content and flow cytometry analysis were determined for the C. neoformans species complex in the presence of fisetin and ultrastructural analysis of morphology was performed on Cryptococcus gattii and C. neoformans. Decrease in the total cellular ergosterol content after exposure to fisetin ranged from 25·4% after exposure to 128 μg ml(-1) to 21·6% after exposure to 64 μg ml(-1) of fisetin compared with the control (without fisetin). The fisetin effects obtained with flow cytometry showed metabolic impairment, and alterations in its normal morphology caused by fisetin in C. neoformans cells were verified using scanning electron microscopy. Fisetin is a compound that acts in the biosynthesis of ergosterol. Flow cytometry showed that fisetin reduced viability of the metabolically active cells of C. gattii, while morphological changes explain the action of fisetin in inhibiting growth of these fungi. This study supports the idea that fisetin may represent a good starting point for the development of future therapeutic substances for cryptococcosis. © 2016 The Society for Applied Microbiology.

Metabolic Reprogramming by 3-Iodothyronamine (T1AM): A New Perspective to Reverse Obesity through Co-Regulation of Sirtuin 4 and 6 Expression.

PubMed

Assadi-Porter, Fariba M; Reiland, Hannah; Sabatini, Martina; Lorenzini, Leonardo; Carnicelli, Vittoria; Rogowski, Micheal; Selen Alpergin, Ebru S; Tonelli, Marco; Ghelardoni, Sandra; Saba, Alessandro; Zucchi, Riccardo; Chiellini, Grazia

2018-05-22

Obesity is a complex disease associated with environmental and genetic factors. 3-Iodothyronamine (T1AM) has revealed great potential as an effective weight loss drug. We used metabolomics and associated transcriptional gene and protein expression analysis to investigate the tissue specific metabolic reprogramming effects of subchronic T1AM treatment at two pharmacological daily doses (10 and 25 mg/kg) on targeted metabolic pathways. Multi-analytical results indicated that T1AM at 25 mg/kg can act as a novel master regulator of both glucose and lipid metabolism in mice through sirtuin-mediated pathways. In liver, we observed an increased gene and protein expression of Sirt6 (a master gene regulator of glucose) and Gck (glucose kinase) and a decreased expression of Sirt4 (a negative regulator of fatty acids oxidation (FAO)), whereas in white adipose tissue only Sirt6 was increased. Metabolomics analysis supported physiological changes at both doses with most increases in FAO, glycolysis indicators and the mitochondrial substrate, at the highest dose of T1AM. Together our results suggest that T1AM acts through sirtuin-mediated pathways to metabolically reprogram fatty acid and glucose metabolism possibly through small molecules signaling. Our novel mechanistic findings indicate that T1AM has a great potential as a drug for the treatment of obesity and possibly diabetes.

Comparative analysis of respiratory chain and oxidative phosphorylation in Leishmania tarentolae, Crithidia fasciculata, Phytomonas serpens and procyclic stage of Trypanosoma brucei.

PubMed

Verner, Zdeněk; Cermáková, Petra; Skodová, Ingrid; Kováčová, Bianka; Lukeš, Julius; Horváth, Anton

2014-01-01

Trypanosomatids are unicellular parasites living in a wide range of host environments, which to large extent shaped their mitochondrial energy metabolism, resulting in quite large differences even among closely related flagellates. In a comparative manner, we analyzed the activities and composition of mitochondrial respiratory complexes in four species (Leishmania tarentolae, Crithidia fasciculata, Phytomonas serpens and Trypanosoma brucei), which represent the main model trypanosomatids. Moreover, we measured the activity of mitochondrial glycerol-3-phosphate dehydrogenase, the overall oxygen consumption and the mitochondrial membrane potential in each species. The comparative analysis suggests an inverse relationship between the activities of respiratory complexes I and II, as well as the overall activity of the canonical complexes and glycerol-3-phosphate dehydrogenase. Our comparative analysis shows that mitochondrial functions are highly variable in these versatile parasites. Copyright © 2014 Elsevier B.V. All rights reserved.

Modelling microbial metabolic rewiring during growth in a complex medium.

PubMed

Fondi, Marco; Bosi, Emanuele; Presta, Luana; Natoli, Diletta; Fani, Renato

2016-11-24

In their natural environment, bacteria face a wide range of environmental conditions that change over time and that impose continuous rearrangements at all the cellular levels (e.g. gene expression, metabolism). When facing a nutritionally rich environment, for example, microbes first use the preferred compound(s) and only later start metabolizing the other one(s). A systemic re-organization of the overall microbial metabolic network in response to a variation in the composition/concentration of the surrounding nutrients has been suggested, although the range and the entity of such modifications in organisms other than a few model microbes has been scarcely described up to now. We used multi-step constraint-based metabolic modelling to simulate the growth in a complex medium over several time steps of the Antarctic model organism Pseudoalteromonas haloplanktis TAC125. As each of these phases is characterized by a specific set of amino acids to be used as carbon and energy source our modelling framework describes the major consequences of nutrients switching at the system level. The model predicts that a deep metabolic reprogramming might be required to achieve optimal biomass production in different stages of growth (different medium composition), with at least half of the cellular metabolic network involved (more than 50% of the metabolic genes). Additionally, we show that our modelling framework is able to capture metabolic functional association and/or common regulatory features of the genes embedded in our reconstruction (e.g. the presence of common regulatory motifs). Finally, to explore the possibility of a sub-optimal biomass objective function (i.e. that cells use resources in alternative metabolic processes at the expense of optimal growth) we have implemented a MOMA-based approach (called nutritional-MOMA) and compared the outcomes with those obtained with Flux Balance Analysis (FBA). Growth simulations under this scenario revealed the deep impact of choosing among alternative objective functions on the resulting predictions of fluxes distribution. Here we provide a time-resolved, systems-level scheme of PhTAC125 metabolic re-wiring as a consequence of carbon source switching in a nutritionally complex medium. Our analyses suggest the presence of a potential efficient metabolic reprogramming machinery to continuously and promptly adapt to this nutritionally changing environment, consistent with adaptation to fast growth in a fairly, but probably inconstant and highly competitive, environment. Also, we show i) how functional partnership and co-regulation features can be predicted by integrating multi-step constraint-based metabolic modelling with fed-batch growth data and ii) that performing simulations under a sub-optimal objective function may lead to different flux distributions in respect to canonical FBA.

A study of deoxyribonucleotide metabolism and its relation to DNA synthesis. Supercomputer simulation and model-system analysis.

PubMed

Heinmets, F; Leary, R H

1991-06-01

A model system (1) was established to analyze purine and pyrimidine metabolism. This system has been expanded to include macrosimulation of DNA synthesis and the study of its regulation by terminal deoxynucleoside triphosphates (dNTPs) via a complex set of interactions. Computer experiments reveal that our model exhibits adequate and reasonable sensitivity in terms of dNTP pool levels and rates of DNA synthesis when inputs to the system are varied. These simulation experiments reveal that in order to achieve maximum DNA synthesis (in terms of purine metabolism), a proper balance is required in guanine and adenine input into this metabolic system. Excessive inputs will become inhibitory to DNA synthesis. In addition, studies are carried out on rates of DNA synthesis when various parameters are changed quantitatively. The current system is formulated by 110 differential equations.

Familial aggregation and linkage analysis with covariates for metabolic syndrome risk factors.

PubMed

Naseri, Parisa; Khodakarim, Soheila; Guity, Kamran; Daneshpour, Maryam S

2018-06-15

Mechanisms of metabolic syndrome (MetS) causation are complex, genetic and environmental factors are important factors for the pathogenesis of MetS In this study, we aimed to evaluate familial and genetic influences on metabolic syndrome risk factor and also assess association between FTO (rs1558902 and rs7202116) and CETP(rs1864163) genes' single nucleotide polymorphisms (SNP) with low HDL_C in the Tehran Lipid and Glucose Study (TLGS). The design was a cross-sectional study of 1776 members of 227 randomly-ascertained families. Selected families contained at least one affected metabolic syndrome and at least two members of the family had suffered a loss of HDL_C according to ATP III criteria. In this study, after confirming the familial aggregation with intra-trait correlation coefficients (ICC) of Metabolic syndrome (MetS) and the quantitative lipid traits, the genetic linkage analysis of HDL_C was performed using conditional logistic method with adjusted sex and age. The results of the aggregation analysis revealed a higher correlation between siblings than between parent-offspring pairs representing the role of genetic factors in MetS. In addition, the conditional logistic model with covariates showed that the linkage results between HDL_C and three marker, rs1558902, rs7202116 and rs1864163 were significant. In summary, a high risk of MetS was found in siblings confirming the genetic influences of metabolic syndrome risk factor. Moreover, the power to detect linkage increases in the one parameter conditional logistic model regarding the use of age and sex as covariates. Copyright © 2018. Published by Elsevier B.V.

The coupling of cerebral blood flow and oxygen metabolism with brain activation is similar for simple and complex stimuli in human primary visual cortex.

PubMed

Griffeth, Valerie E M; Simon, Aaron B; Buxton, Richard B

2015-01-01

Quantitative functional MRI (fMRI) experiments to measure blood flow and oxygen metabolism coupling in the brain typically rely on simple repetitive stimuli. Here we compared such stimuli with a more naturalistic stimulus. Previous work on the primary visual cortex showed that direct attentional modulation evokes a blood flow (CBF) response with a relatively large oxygen metabolism (CMRO2) response in comparison to an unattended stimulus, which evokes a much smaller metabolic response relative to the flow response. We hypothesized that a similar effect would be associated with a more engaging stimulus, and tested this by measuring the primary human visual cortex response to two contrast levels of a radial flickering checkerboard in comparison to the response to free viewing of brief movie clips. We did not find a significant difference in the blood flow-metabolism coupling (n=%ΔCBF/%ΔCMRO2) between the movie stimulus and the flickering checkerboards employing two different analysis methods: a standard analysis using the Davis model and a new analysis using a heuristic model dependent only on measured quantities. This finding suggests that in the primary visual cortex a naturalistic stimulus (in comparison to a simple repetitive stimulus) is either not sufficient to provoke a change in flow-metabolism coupling by attentional modulation as hypothesized, that the experimental design disrupted the cognitive processes underlying the response to a more natural stimulus, or that the technique used is not sensitive enough to detect a small difference. Copyright © 2014 Elsevier Inc. All rights reserved.

Stable isotope-resolved metabolomics and applications for drug development

PubMed Central

Fan, Teresa W-M.; Lorkiewicz, Pawel; Sellers, Katherine; Moseley, Hunter N.B.; Higashi, Richard M.; Lane, Andrew N.

2012-01-01

Advances in analytical methodologies, principally nuclear magnetic resonance spectroscopy (NMR) and mass spectrometry (MS), during the last decade have made large-scale analysis of the human metabolome a reality. This is leading to the reawakening of the importance of metabolism in human diseases, particularly cancer. The metabolome is the functional readout of the genome, functional genome, and proteome; it is also an integral partner in molecular regulations for homeostasis. The interrogation of the metabolome, or metabolomics, is now being applied to numerous diseases, largely by metabolite profiling for biomarker discovery, but also in pharmacology and therapeutics. Recent advances in stable isotope tracer-based metabolomic approaches enable unambiguous tracking of individual atoms through compartmentalized metabolic networks directly in human subjects, which promises to decipher the complexity of the human metabolome at an unprecedented pace. This knowledge will revolutionize our understanding of complex human diseases, clinical diagnostics, as well as individualized therapeutics and drug response. In this review, we focus on the use of stable isotope tracers with metabolomics technologies for understanding metabolic network dynamics in both model systems and in clinical applications. Atom-resolved isotope tracing via the two major analytical platforms, NMR and MS, has the power to determine novel metabolic reprogramming in diseases, discover new drug targets, and facilitates ADME studies. We also illustrate new metabolic tracer-based imaging technologies, which enable direct visualization of metabolic processes in vivo. We further outline current practices and future requirements for biochemoinformatics development, which is an integral part of translating stable isotope-resolved metabolomics into clinical reality. PMID:22212615

Genomewide screen for negative regulators of sirtuin activity in Saccharomyces cerevisiae reveals 40 loci and links to metabolism.

PubMed

Raisner, Ryan M; Madhani, Hiten D

2008-08-01

Sirtuins are conserved proteins implicated in myriad key processes including gene control, aging, cell survival, metabolism, and DNA repair. In Saccharomyces cerevisiae, the sirtuin Silent information regulator 2 (Sir2) promotes silent chromatin formation, suppresses recombination between repeats, and inhibits senescence. We performed a genomewide screen for factors that negatively regulate Sir activity at a reporter gene placed immediately outside a silenced region. After linkage analysis, assessment of Sir dependency, and knockout tag verification, 40 loci were identified, including 20 that have not been previously described to regulate Sir. In addition to chromatin-associated factors known to prevent ectopic silencing (Bdf1, SAS-I complex, Rpd3L complex, Ku), we identified the Rtt109 DNA repair-associated histone H3 lysine 56 acetyltransferase as an anti-silencing factor. Our findings indicate that Rtt109 functions independently of its proposed effectors, the Rtt101 cullin, Mms1, and Mms22, and demonstrate unexpected interplay between H3K56 and H4K16 acetylation. The screen also identified subunits of mediator (Soh1, Srb2, and Srb5) and mRNA metabolism factors (Kem1, Ssd1), thus raising the possibility that weak silencing affects some aspect of mRNA structure. Finally, several factors connected to metabolism were identified. These include the PAS-domain metabolic sensor kinase Psk2, the mitochondrial homocysteine detoxification enzyme Lap3, and the Fe-S cluster protein maturase Isa2. We speculate that PAS kinase may integrate metabolic signals to control sirtuin activity.

Azoxystrobin, a mitochondrial complex III Qo site inhibitor, exerts beneficial metabolic effects in vivo and in vitro.

PubMed

Gao, An-Hui; Fu, Yan-Yun; Zhang, Kun-Zhi; Zhang, Mei; Jiang, Hao-Wen; Fan, Li-Xia; Nan, Fa-Jun; Yuan, Chong-Gang; Li, Jia; Zhou, Yu-Bo; Li, Jing-Ya

2014-07-01

Several anti-diabetes drugs exert beneficial effects against metabolic syndrome by inhibiting mitochondrial function. Although much progress has been made toward understanding the role of mitochondrial function inhibitors in treating metabolic diseases, the potential effects of these inhibitors on mitochondrial respiratory chain complex III remain unclear. We investigated the metabolic effects of azoxystrobin (AZOX), a Qo inhibitor of complex III, in a high-fat diet-fed mouse model with insulin resistance in order to elucidate the mechanism by which AZOX improves glucose and lipid metabolism at the metabolic cellular level. Acute administration of AZOX in mice increased the respiratory exchange ratio. Chronic treatment with AZOX reduced body weight and significantly improved glucose tolerance and insulin sensitivity in high-fat diet-fed mice. AZOX treatment resulted in decreased triacylglycerol accumulation and down-regulated the expression of genes involved in liver lipogenesis. AZOX increased glucose uptake in L6 myotubes and 3T3-L1 adipocytes and inhibited de novo lipogenesis in HepG2 cells. The findings indicate that AZOX-mediated alterations to lipid and glucose metabolism may depend on AMP-activated protein kinase (AMPK) signaling. AZOX, a Qo inhibitor of mitochondrial respiratory complex III, exerts whole-body beneficial effects on the regulation of glucose and lipid homeostasis in high-fat diet-fed mice. These findings provide evidence that a Qo inhibitor of mitochondrial respiratory complex III could represent a novel approach for the treatment of obesity. Copyright © 2014 Elsevier B.V. All rights reserved.

A top-down systems biology view of microbiome-mammalian metabolic interactions in a mouse model

PubMed Central

Martin, François-Pierre J; Dumas, Marc-Emmanuel; Wang, Yulan; Legido-Quigley, Cristina; Yap, Ivan K S; Tang, Huiru; Zirah, Séverine; Murphy, Gerard M; Cloarec, Olivier; Lindon, John C; Sprenger, Norbert; Fay, Laurent B; Kochhar, Sunil; van Bladeren, Peter; Holmes, Elaine; Nicholson, Jeremy K

2007-01-01

Symbiotic gut microorganisms (microbiome) interact closely with the mammalian host's metabolism and are important determinants of human health. Here, we decipher the complex metabolic effects of microbial manipulation, by comparing germfree mice colonized by a human baby flora (HBF) or a normal flora to conventional mice. We perform parallel microbiological profiling, metabolic profiling by 1H nuclear magnetic resonance of liver, plasma, urine and ileal flushes, and targeted profiling of bile acids by ultra performance liquid chromatography–mass spectrometry and short-chain fatty acids in cecum by GC-FID. Top-down multivariate analysis of metabolic profiles reveals a significant association of specific metabotypes with the resident microbiome. We derive a transgenomic graph model showing that HBF flora has a remarkably simple microbiome/metabolome correlation network, impacting directly on the host's ability to metabolize lipids: HBF mice present higher ileal concentrations of tauro-conjugated bile acids, reduced plasma levels of lipoproteins but higher hepatic triglyceride content associated with depletion of glutathione. These data indicate that the microbiome modulates absorption, storage and the energy harvest from the diet at the systems level. PMID:17515922

Metabolomic analysis of insulin resistance across different mouse strains and diets.

PubMed

Stöckli, Jacqueline; Fisher-Wellman, Kelsey H; Chaudhuri, Rima; Zeng, Xiao-Yi; Fazakerley, Daniel J; Meoli, Christopher C; Thomas, Kristen C; Hoffman, Nolan J; Mangiafico, Salvatore P; Xirouchaki, Chrysovalantou E; Yang, Chieh-Hsin; Ilkayeva, Olga; Wong, Kari; Cooney, Gregory J; Andrikopoulos, Sofianos; Muoio, Deborah M; James, David E

2017-11-24

Insulin resistance is a major risk factor for many diseases. However, its underlying mechanism remains unclear in part because it is triggered by a complex relationship between multiple factors, including genes and the environment. Here, we used metabolomics combined with computational methods to identify factors that classified insulin resistance across individual mice derived from three different mouse strains fed two different diets. Three inbred ILSXISS strains were fed high-fat or chow diets and subjected to metabolic phenotyping and metabolomics analysis of skeletal muscle. There was significant metabolic heterogeneity between strains, diets, and individual animals. Distinct metabolites were changed with insulin resistance, diet, and between strains. Computational analysis revealed 113 metabolites that were correlated with metabolic phenotypes. Using these 113 metabolites, combined with machine learning to segregate mice based on insulin sensitivity, we identified C22:1-CoA, C2-carnitine, and C16-ceramide as the best classifiers. Strikingly, when these three metabolites were combined into one signature, they classified mice based on insulin sensitivity more accurately than each metabolite on its own or other published metabolic signatures. Furthermore, C22:1-CoA was 2.3-fold higher in insulin-resistant mice and correlated significantly with insulin resistance. We have identified a metabolomic signature composed of three functionally unrelated metabolites that accurately predicts whole-body insulin sensitivity across three mouse strains. These data indicate the power of simultaneous analysis of individual, genetic, and environmental variance in mice for identifying novel factors that accurately predict metabolic phenotypes like whole-body insulin sensitivity. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

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.

Adipocyte Metabolic Pathways Regulated by Diet Control the Female Germline Stem Cell Lineage in Drosophila melanogaster.

PubMed

Matsuoka, Shinya; Armstrong, Alissa R; Sampson, Leesa L; Laws, Kaitlin M; Drummond-Barbosa, Daniela

2017-06-01

Nutrients affect adult stem cells through complex mechanisms involving multiple organs. Adipocytes are highly sensitive to diet and have key metabolic roles, and obesity increases the risk for many cancers. How diet-regulated adipocyte metabolic pathways influence normal stem cell lineages, however, remains unclear. Drosophila melanogaster has highly conserved adipocyte metabolism and a well-characterized female germline stem cell (GSC) lineage response to diet. Here, we conducted an isobaric tags for relative and absolute quantification (iTRAQ) proteomic analysis to identify diet-regulated adipocyte metabolic pathways that control the female GSC lineage. On a rich (relative to poor) diet, adipocyte Hexokinase-C and metabolic enzymes involved in pyruvate/acetyl-CoA production are upregulated, promoting a shift of glucose metabolism toward macromolecule biosynthesis. Adipocyte-specific knockdown shows that these enzymes support early GSC progeny survival. Further, enzymes catalyzing fatty acid oxidation and phosphatidylethanolamine synthesis in adipocytes promote GSC maintenance, whereas lipid and iron transport from adipocytes controls vitellogenesis and GSC number, respectively. These results show a functional relationship between specific metabolic pathways in adipocytes and distinct processes in the GSC lineage, suggesting the adipocyte metabolism-stem cell link as an important area of investigation in other stem cell systems. Copyright © 2017 by the Genetics Society of America.

Serum metabolomics of slow vs. rapid motor progression Parkinson's disease: a pilot study.

PubMed

Roede, James R; Uppal, Karan; Park, Youngja; Lee, Kichun; Tran, Vilinh; Walker, Douglas; Strobel, Frederick H; Rhodes, Shannon L; Ritz, Beate; Jones, Dean P

2013-01-01

Progression of Parkinson's disease (PD) is highly variable, indicating that differences between slow and rapid progression forms could provide valuable information for improved early detection and management. Unfortunately, this represents a complex problem due to the heterogeneous nature of humans in regards to demographic characteristics, genetics, diet, environmental exposures and health behaviors. In this pilot study, we employed high resolution mass spectrometry-based metabolic profiling to investigate the metabolic signatures of slow versus rapidly progressing PD present in human serum. Archival serum samples from PD patients obtained within 3 years of disease onset were analyzed via dual chromatography-high resolution mass spectrometry, with data extraction by xMSanalyzer and used to predict rapid or slow motor progression of these patients during follow-up. Statistical analyses, such as false discovery rate analysis and partial least squares discriminant analysis, yielded a list of statistically significant metabolic features and further investigation revealed potential biomarkers. In particular, N8-acetyl spermidine was found to be significantly elevated in the rapid progressors compared to both control subjects and slow progressors. Our exploratory data indicate that a fast motor progression disease phenotype can be distinguished early in disease using high resolution mass spectrometry-based metabolic profiling and that altered polyamine metabolism may be a predictive marker of rapidly progressing PD.

Metabolomics Tools for Describing Complex Pesticide Exposure in Pregnant Women in Brittany (France)

PubMed Central

Bonvallot, Nathalie; Tremblay-Franco, Marie; Chevrier, Cécile; Canlet, Cécile; Warembourg, Charline; Cravedi, Jean-Pierre; Cordier, Sylvaine

2013-01-01

Background The use of pesticides and the related environmental contaminations can lead to human exposure to various molecules. In early-life, such exposures could be responsible for adverse developmental effects. However, human health risks associated with exposure to complex mixtures are currently under-explored. Objective This project aims at answering the following questions: What is the influence of exposures to multiple pesticides on the metabolome? What mechanistic pathways could be involved in the metabolic changes observed? Methods Based on the PELAGIE cohort (Brittany, France), 83 pregnant women who provided a urine sample in early pregnancy, were classified in 3 groups according to the surface of land dedicated to agricultural cereal activities in their town of residence. Nuclear magnetic resonance-based metabolomics analyses were performed on urine samples. Partial Least Squares Regression-Discriminant Analysis (PLS-DA) and polytomous regressions were used to separate the urinary metabolic profiles from the 3 exposure groups after adjusting for potential confounders. Results The 3 groups of exposure were correctly separated with a PLS-DA model after implementing an orthogonal signal correction with pareto standardizations (R2 = 90.7% and Q2 = 0.53). After adjusting for maternal age, parity, body mass index and smoking habits, the most statistically significant changes were observed for glycine, threonine, lactate and glycerophosphocholine (upward trend), and for citrate (downward trend). Conclusion This work suggests that an exposure to complex pesticide mixtures induces modifications of metabolic fingerprints. It can be hypothesized from identified discriminating metabolites that the pesticide mixtures could increase oxidative stress and disturb energy metabolism. PMID:23704985

The pleiotropic effects of decanoic acid treatment on mitochondrial function in fibroblasts from patients with complex I deficient Leigh syndrome.

PubMed

Kanabus, Marta; Fassone, Elisa; Hughes, Sean David; Bilooei, Sara Farahi; Rutherford, Tricia; Donnell, Maura O'; Heales, Simon J R; Rahman, Shamima

2016-05-01

There is growing interest in the use of the ketogenic diet (KD) to treat inherited metabolic diseases including mitochondrial disorders. However, neither the mechanism whereby the diet may be working, nor if it could benefit all patients with mitochondrial disease, is known. This study focusses on decanoic acid (C10), a component of the medium chain triglyceride KD, and a ligand for the nuclear receptor PPAR-γ known to be involved in mitochondrial biogenesis. The effects of C10 were investigated in primary fibroblasts from a cohort of patients with Leigh syndrome (LS) caused by nuclear-encoded defects of respiratory chain complex I, using mitochondrial respiratory chain enzyme assays, gene expression microarray, qPCR and flow cytometry. Treatment with C10 increased citrate synthase activity, a marker of cellular mitochondrial content, in 50 % of fibroblasts obtained from individuals diagnosed with LS in a PPAR-γ-mediated manner. Gene expression analysis and qPCR studies suggested that treating cells with C10 supports fatty acid metabolism, through increasing ACADVL and CPT1 expression, whilst downregulating genes involved in glucose metabolism (PDK3, PDK4). PCK2, involved in blocking glucose metabolism, was upregulated, as was CAT, encoding catalase. Moreover, treatment with C10 also decreased oxidative stress in complex I deficient (rotenone treated) cells. However, since not all cells from subjects with LS appeared to respond to C10, prior cellular testing in vitro could be employed as a means for selecting individuals for subsequent clinical studies involving C10 preparations.

Developmental Transcriptome for a Facultatively Eusocial Bee, Megalopta genalis

PubMed Central

Jones, Beryl M.; Wcislo, William T.; Robinson, Gene E.

2015-01-01

Transcriptomes provide excellent foundational resources for mechanistic and evolutionary analyses of complex traits. We present a developmental transcriptome for the facultatively eusocial bee Megalopta genalis, which represents a potential transition point in the evolution of eusociality. A de novo transcriptome assembly of Megalopta genalis was generated using paired-end Illumina sequencing and the Trinity assembler. Males and females of all life stages were aligned to this transcriptome for analysis of gene expression profiles throughout development. Gene Ontology analysis indicates that stage-specific genes are involved in ion transport, cell–cell signaling, and metabolism. A number of distinct biological processes are upregulated in each life stage, and transitions between life stages involve shifts in dominant functional processes, including shifts from transcriptional regulation in embryos to metabolism in larvae, and increased lipid metabolism in adults. We expect that this transcriptome will provide a useful resource for future analyses to better understand the molecular basis of the evolution of eusociality and, more generally, phenotypic plasticity. PMID:26276382

Developmental Transcriptome for a Facultatively Eusocial Bee, Megalopta genalis.

PubMed

Jones, Beryl M; Wcislo, William T; Robinson, Gene E

2015-08-14

Transcriptomes provide excellent foundational resources for mechanistic and evolutionary analyses of complex traits. We present a developmental transcriptome for the facultatively eusocial bee Megalopta genalis, which represents a potential transition point in the evolution of eusociality. A de novo transcriptome assembly of Megalopta genalis was generated using paired-end Illumina sequencing and the Trinity assembler. Males and females of all life stages were aligned to this transcriptome for analysis of gene expression profiles throughout development. Gene Ontology analysis indicates that stage-specific genes are involved in ion transport, cell-cell signaling, and metabolism. A number of distinct biological processes are upregulated in each life stage, and transitions between life stages involve shifts in dominant functional processes, including shifts from transcriptional regulation in embryos to metabolism in larvae, and increased lipid metabolism in adults. We expect that this transcriptome will provide a useful resource for future analyses to better understand the molecular basis of the evolution of eusociality and, more generally, phenotypic plasticity. Copyright © 2015 Jones et al.

Urine metabolic profile changes of CCl4-liver fibrosis in rats and intervention effects of Yi Guan Jian Decoction using metabonomic approach

PubMed Central

2013-01-01

Background Yi Guan Jian Decoction (YGJD), a famous Chinese prescription, has long been employed clinically to treat liver fibrosis. However, as of date, there is no report on the effects of YGJD from a metabonomic approach. In this study, a urine metabonomic method based on gas chromatography coupled with mass spectrometry (GC/MS) was employed to study the protective efficacy and metabolic profile changes caused by YGJD in carbon tetrachloride (CCl4)-induced liver fibrosis. Methods Urine samples from Wistar rats of three randomly divided groups (control, model, and YGJD treated) were collected at various time-points, and the metabolic profile changes were analyzed by GC/MS with principal component analysis (PCA) and partial least squares-discriminate analysis (PLS-DA). Furthermore, histopathology and biochemical examination were also carried out to ensure the success of CCl4-induced liver fibrosis model. Results Urine metabolic profile studies suggested distinct clustering of the three groups, and YGJD group was much closer to the control group by showing a tendency of recovering towards the control group. Fourteen significantly changed metabolites were found, and YGJD treatment could reverse the levels of these metabolites to normal levels or close to normal levels. Conclusions The current study indicates that the YGJD has significant anti-fibrotic effects on CCl4-induced liver fibrosis in rats, which might be by regulating the dysfunction of energy metabolism, amino acid metabolism, tryptophan metabolism, cytochrome P450 metabolism, and gut microflora metabolism. The metabonomic approach can be recommended to study the pharmacological effect and mechanism of complex Chinese medicines. PMID:23725349

Therapeutic potential of Mediator complex subunits in metabolic diseases.

PubMed

Ranjan, Amol; Ansari, Suraiya A

2018-01-01

The multisubunit Mediator is an evolutionary conserved transcriptional coregulatory complex in eukaryotes. It is needed for the transcriptional regulation of gene expression in general as well as in a gene specific manner. Mediator complex subunits interact with different transcription factors as well as components of RNA Pol II transcription initiation complex and in doing so act as a bridge between gene specific transcription factors and general Pol II transcription machinery. Specific interaction of various Mediator subunits with nuclear receptors (NRs) and other transcription factors involved in metabolism has been reported in different studies. Evidences indicate that ligand-activated NRs recruit Mediator complex for RNA Pol II-dependent gene transcription. These NRs have been explored as therapeutic targets in different metabolic diseases; however, they show side-effects as targets due to their overlapping involvement in different signaling pathways. Here we discuss the interaction of various Mediator subunits with transcription factors involved in metabolism and whether specific interaction of these transcription factors with Mediator subunits could be potentially utilized as therapeutic strategy in a variety of metabolic diseases. Copyright © 2017 Elsevier B.V. and Société Française de Biochimie et Biologie Moléculaire (SFBBM). All rights reserved.

Elucidation of new condition-dependent roles for fructose-1,6-bisphosphatase linked to cofactor balances

PubMed Central

Kilian, Stephanus G.; du Preez, James C.

2017-01-01

The cofactor balances in metabolism is of paramount importance in the design of a metabolic engineering strategy and understanding the regulation of metabolism in general. ATP, NAD+ and NADP+ balances are central players linking the various fluxes in central metabolism as well as biomass formation. NADP+ is especially important in the metabolic engineering of yeasts for xylose fermentation, since NADPH is required by most yeasts in the initial step of xylose utilisation, including the fast-growing Kluyveromyces marxianus. In this simulation study of yeast metabolism, the complex interplay between these cofactors was investigated; in particular, how they may affect the possible roles of fructose-1,6-bisphosphatase, the pentose phosphate pathway, glycerol production and the pyruvate dehydrogenase bypass. Using flux balance analysis, it was found that the potential role of fructose-1,6-bisphosphatase was highly dependent on the cofactor specificity of the oxidative pentose phosphate pathway and on the carbon source. Additionally, the excessive production of ATP under certain conditions might be involved in some of the phenomena observed, which may have been overlooked to date. Based on these findings, a strategy is proposed for the metabolic engineering of a future xylose-fermenting yeast for biofuel production. PMID:28542187

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.

Linking gene regulation and the exo-metabolome: A comparative transcriptomics approach to identify genes that impact on the production of volatile aroma compounds in yeast

PubMed Central

Rossouw, Debra; Næs, Tormod; Bauer, Florian F

2008-01-01

Background 'Omics' tools provide novel opportunities for system-wide analysis of complex cellular functions. Secondary metabolism is an example of a complex network of biochemical pathways, which, although well mapped from a biochemical point of view, is not well understood with regards to its physiological roles and genetic and biochemical regulation. Many of the metabolites produced by this network such as higher alcohols and esters are significant aroma impact compounds in fermentation products, and different yeast strains are known to produce highly divergent aroma profiles. Here, we investigated whether we can predict the impact of specific genes of known or unknown function on this metabolic network by combining whole transcriptome and partial exo-metabolome analysis. Results For this purpose, the gene expression levels of five different industrial wine yeast strains that produce divergent aroma profiles were established at three different time points of alcoholic fermentation in synthetic wine must. A matrix of gene expression data was generated and integrated with the concentrations of volatile aroma compounds measured at the same time points. This relatively unbiased approach to the study of volatile aroma compounds enabled us to identify candidate genes for aroma profile modification. Five of these genes, namely YMR210W, BAT1, AAD10, AAD14 and ACS1 were selected for overexpression in commercial wine yeast, VIN13. Analysis of the data show a statistically significant correlation between the changes in the exo-metabome of the overexpressing strains and the changes that were predicted based on the unbiased alignment of transcriptomic and exo-metabolomic data. Conclusion The data suggest that a comparative transcriptomics and metabolomics approach can be used to identify the metabolic impacts of the expression of individual genes in complex systems, and the amenability of transcriptomic data to direct applications of biotechnological relevance. PMID:18990252

Atomic Resolution Modeling of the Ferredoxin:[FeFe] Hydrogenase Complex from Chlamydomonas reinhardtii

PubMed Central

Chang, Christopher H.; King, Paul W.; Ghirardi, Maria L.; Kim, Kwiseon

2007-01-01

The [FeFe] hydrogenases HydA1 and HydA2 in the green alga Chlamydomonas reinhardtii catalyze the final reaction in a remarkable metabolic pathway allowing this photosynthetic organism to produce H2 from water in the chloroplast. A [2Fe-2S] ferredoxin is a critical branch point in electron flow from Photosystem I toward a variety of metabolic fates, including proton reduction by hydrogenases. To better understand the binding determinants involved in ferredoxin:hydrogenase interactions, we have modeled Chlamydomonas PetF1 and HydA2 based on amino-acid sequence homology, and produced two promising electron-transfer model complexes by computational docking. To characterize these models, quantitative free energy calculations at atomic resolution were carried out, and detailed analysis of the interprotein interactions undertaken. The protein complex model we propose for ferredoxin:HydA2 interaction is energetically favored over the alternative candidate by 20 kcal/mol. This proposed model of the electron-transfer complex between PetF1 and HydA2 permits a more detailed view of the molecular events leading up to H2 evolution, and suggests potential mutagenic strategies to modulate electron flow to HydA2. PMID:17660315

Atomic resolution modeling of the ferredoxin:[FeFe] hydrogenase complex from Chlamydomonas reinhardtii.

PubMed

Chang, Christopher H; King, Paul W; Ghirardi, Maria L; Kim, Kwiseon

2007-11-01

The [FeFe] hydrogenases HydA1 and HydA2 in the green alga Chlamydomonas reinhardtii catalyze the final reaction in a remarkable metabolic pathway allowing this photosynthetic organism to produce H(2) from water in the chloroplast. A [2Fe-2S] ferredoxin is a critical branch point in electron flow from Photosystem I toward a variety of metabolic fates, including proton reduction by hydrogenases. To better understand the binding determinants involved in ferredoxin:hydrogenase interactions, we have modeled Chlamydomonas PetF1 and HydA2 based on amino-acid sequence homology, and produced two promising electron-transfer model complexes by computational docking. To characterize these models, quantitative free energy calculations at atomic resolution were carried out, and detailed analysis of the interprotein interactions undertaken. The protein complex model we propose for ferredoxin:HydA2 interaction is energetically favored over the alternative candidate by 20 kcal/mol. This proposed model of the electron-transfer complex between PetF1 and HydA2 permits a more detailed view of the molecular events leading up to H(2) evolution, and suggests potential mutagenic strategies to modulate electron flow to HydA2.

Data processing, multi-omic pathway mapping, and metabolite activity analysis using XCMS Online

PubMed Central

Forsberg, Erica M; Huan, Tao; Rinehart, Duane; Benton, H Paul; Warth, Benedikt; Hilmers, Brian; Siuzdak, Gary

2018-01-01

Systems biology is the study of complex living organisms, and as such, analysis on a systems-wide scale involves the collection of information-dense data sets that are representative of an entire phenotype. To uncover dynamic biological mechanisms, bioinformatics tools have become essential to facilitating data interpretation in large-scale analyses. Global metabolomics is one such method for performing systems biology, as metabolites represent the downstream functional products of ongoing biological processes. We have developed XCMS Online, a platform that enables online metabolomics data processing and interpretation. A systems biology workflow recently implemented within XCMS Online enables rapid metabolic pathway mapping using raw metabolomics data for investigating dysregulated metabolic processes. In addition, this platform supports integration of multi-omic (such as genomic and proteomic) data to garner further systems-wide mechanistic insight. Here, we provide an in-depth procedure showing how to effectively navigate and use the systems biology workflow within XCMS Online without a priori knowledge of the platform, including uploading liquid chromatography (LCLC)–mass spectrometry (MS) data from metabolite-extracted biological samples, defining the job parameters to identify features, correcting for retention time deviations, conducting statistical analysis of features between sample classes and performing predictive metabolic pathway analysis. Additional multi-omics data can be uploaded and overlaid with previously identified pathways to enhance systems-wide analysis of the observed dysregulations. We also describe unique visualization tools to assist in elucidation of statistically significant dysregulated metabolic pathways. Parameter input takes 5–10 min, depending on user experience; data processing typically takes 1–3 h, and data analysis takes ~30 min. PMID:29494574

Structural characterization of Staphylococcus aureus biotin protein ligase and interaction partners: an antibiotic target.

PubMed

Pendini, Nicole R; Yap, Min Y; Traore, D A K; Polyak, Steven W; Cowieson, Nathan P; Abell, Andrew; Booker, Grant W; Wallace, John C; Wilce, Jacqueline A; Wilce, Matthew C J

2013-06-01

The essential metabolic enzyme biotin protein ligase (BPL) is a potential target for the development of new antibiotics required to combat drug-resistant pathogens. Staphylococcus aureus BPL (SaBPL) is a bifunctional protein, possessing both biotin ligase and transcription repressor activities. This positions BPL as a key regulator of several important metabolic pathways. Here, we report the structural analysis of both holo- and apo-forms of SaBPL using X-ray crystallography. We also present small-angle X-ray scattering data of SaBPL in complex with its biotin-carboxyl carrier protein substrate as well as the SaBPL:DNA complex that underlies repression. This has revealed the molecular basis of ligand (biotinyl-5'-AMP) binding and conformational changes associated with catalysis and repressor function. These data provide new information to better understand the bifunctional activities of SaBPL and to inform future strategies for antibiotic discovery. © 2013 The Protein Society.

Structural characterization of Staphylococcus aureus biotin protein ligase and interaction partners: An antibiotic target

PubMed Central

Pendini, Nicole R; Yap, Min Y; Polyak, Steven W; Cowieson, Nathan P; Abell, Andrew; Booker, Grant W; Wallace, John C; Wilce, Jacqueline A; Wilce, Matthew C J

2013-01-01

The essential metabolic enzyme biotin protein ligase (BPL) is a potential target for the development of new antibiotics required to combat drug-resistant pathogens. Staphylococcus aureus BPL (SaBPL) is a bifunctional protein, possessing both biotin ligase and transcription repressor activities. This positions BPL as a key regulator of several important metabolic pathways. Here, we report the structural analysis of both holo- and apo-forms of SaBPL using X-ray crystallography. We also present small-angle X-ray scattering data of SaBPL in complex with its biotin-carboxyl carrier protein substrate as well as the SaBPL:DNA complex that underlies repression. This has revealed the molecular basis of ligand (biotinyl-5′-AMP) binding and conformational changes associated with catalysis and repressor function. These data provide new information to better understand the bifunctional activities of SaBPL and to inform future strategies for antibiotic discovery. PMID:23559560

Topological analysis of metabolic networks integrating co-segregating transcriptomes and metabolomes in type 2 diabetic rat congenic series.

PubMed

Dumas, Marc-Emmanuel; Domange, Céline; Calderari, Sophie; Martínez, Andrea Rodríguez; Ayala, Rafael; Wilder, Steven P; Suárez-Zamorano, Nicolas; Collins, Stephan C; Wallis, Robert H; Gu, Quan; Wang, Yulan; Hue, Christophe; Otto, Georg W; Argoud, Karène; Navratil, Vincent; Mitchell, Steve C; Lindon, John C; Holmes, Elaine; Cazier, Jean-Baptiste; Nicholson, Jeremy K; Gauguier, Dominique

2016-09-30

The genetic regulation of metabolic phenotypes (i.e., metabotypes) in type 2 diabetes mellitus occurs through complex organ-specific cellular mechanisms and networks contributing to impaired insulin secretion and insulin resistance. Genome-wide gene expression profiling systems can dissect the genetic contributions to metabolome and transcriptome regulations. The integrative analysis of multiple gene expression traits and metabolic phenotypes (i.e., metabotypes) together with their underlying genetic regulation remains a challenge. Here, we introduce a systems genetics approach based on the topological analysis of a combined molecular network made of genes and metabolites identified through expression and metabotype quantitative trait locus mapping (i.e., eQTL and mQTL) to prioritise biological characterisation of candidate genes and traits. We used systematic metabotyping by 1 H NMR spectroscopy and genome-wide gene expression in white adipose tissue to map molecular phenotypes to genomic blocks associated with obesity and insulin secretion in a series of rat congenic strains derived from spontaneously diabetic Goto-Kakizaki (GK) and normoglycemic Brown-Norway (BN) rats. We implemented a network biology strategy approach to visualize the shortest paths between metabolites and genes significantly associated with each genomic block. Despite strong genomic similarities (95-99 %) among congenics, each strain exhibited specific patterns of gene expression and metabotypes, reflecting the metabolic consequences of series of linked genetic polymorphisms in the congenic intervals. We subsequently used the congenic panel to map quantitative trait loci underlying specific mQTLs and genome-wide eQTLs. Variation in key metabolites like glucose, succinate, lactate, or 3-hydroxybutyrate and second messenger precursors like inositol was associated with several independent genomic intervals, indicating functional redundancy in these regions. To navigate through the complexity of these association networks we mapped candidate genes and metabolites onto metabolic pathways and implemented a shortest path strategy to highlight potential mechanistic links between metabolites and transcripts at colocalized mQTLs and eQTLs. Minimizing the shortest path length drove prioritization of biological validations by gene silencing. These results underline the importance of network-based integration of multilevel systems genetics datasets to improve understanding of the genetic architecture of metabotype and transcriptomic regulation and to characterize novel functional roles for genes determining tissue-specific metabolism.

Using the principle of entropy maximization to infer genetic interaction networks from gene expression patterns.

PubMed

Lezon, Timothy R; Banavar, Jayanth R; Cieplak, Marek; Maritan, Amos; Fedoroff, Nina V

2006-12-12

We describe a method based on the principle of entropy maximization to identify the gene interaction network with the highest probability of giving rise to experimentally observed transcript profiles. In its simplest form, the method yields the pairwise gene interaction network, but it can also be extended to deduce higher-order interactions. Analysis of microarray data from genes in Saccharomyces cerevisiae chemostat cultures exhibiting energy metabolic oscillations identifies a gene interaction network that reflects the intracellular communication pathways that adjust cellular metabolic activity and cell division to the limiting nutrient conditions that trigger metabolic oscillations. The success of the present approach in extracting meaningful genetic connections suggests that the maximum entropy principle is a useful concept for understanding living systems, as it is for other complex, nonequilibrium systems.

Parametric studies of metabolic cooperativity in Escherichia coli colonies: Strain and geometric confinement effects

PubMed Central

Cole, John A.; Luthey-Schulten, Zaida

2017-01-01

Characterizing the complex spatial and temporal interactions among cells in a biological system (i.e. bacterial colony, microbiome, tissue, etc.) remains a challenge. Metabolic cooperativity in these systems can arise due to the subtle interplay between microenvironmental conditions and the cells’ regulatory machinery, often involving cascades of intra- and extracellular signalling molecules. In the simplest of cases, as demonstrated in a recent study of the model organism Escherichia coli, metabolic cross-feeding can arise in monoclonal colonies of bacteria driven merely by spatial heterogeneity in the availability of growth substrates; namely, acetate, glucose and oxygen. Another recent study demonstrated that even closely related E. coli strains evolved different glucose utilization and acetate production capabilities, hinting at the possibility of subtle differences in metabolic cooperativity and the resulting growth behavior of these organisms. Taking a first step towards understanding the complex spatio-temporal interactions within microbial populations, we performed a parametric study of E. coli growth on an agar substrate and probed the dependence of colony behavior on: 1) strain-specific metabolic characteristics, and 2) the geometry of the underlying substrate. To do so, we employed a recently developed multiscale technique named 3D dynamic flux balance analysis which couples reaction-diffusion simulations with iterative steady-state metabolic modeling. Key measures examined include colony growth rate and shape (height vs. width), metabolite production/consumption and concentration profiles, and the emergence of metabolic cooperativity and the fractions of cell phenotypes. Five closely related strains of E. coli, which exhibit large variation in glucose consumption and organic acid production potential, were studied. The onset of metabolic cooperativity was found to vary substantially between these five strains by up to 10 hours and the relative fraction of acetate utilizing cells within the colonies varied by a factor of two. Additionally, growth with six different geometries designed to mimic those that might be found in a laboratory, a microfluidic device, and inside a living organism were considered. Geometries were found to have complex, often nonlinear effects on colony growth and cross-feeding with “hard” features resulting in larger effect than “soft” features. These results demonstrate that strain-specific features and spatial constraints imposed by the growth substrate can have significant effects even for microbial populations as simple as isogenic E. coli colonies. PMID:28820904

Parametric studies of metabolic cooperativity in Escherichia coli colonies: Strain and geometric confinement effects.

PubMed

Peterson, Joseph R; Cole, John A; Luthey-Schulten, Zaida

2017-01-01

Characterizing the complex spatial and temporal interactions among cells in a biological system (i.e. bacterial colony, microbiome, tissue, etc.) remains a challenge. Metabolic cooperativity in these systems can arise due to the subtle interplay between microenvironmental conditions and the cells' regulatory machinery, often involving cascades of intra- and extracellular signalling molecules. In the simplest of cases, as demonstrated in a recent study of the model organism Escherichia coli, metabolic cross-feeding can arise in monoclonal colonies of bacteria driven merely by spatial heterogeneity in the availability of growth substrates; namely, acetate, glucose and oxygen. Another recent study demonstrated that even closely related E. coli strains evolved different glucose utilization and acetate production capabilities, hinting at the possibility of subtle differences in metabolic cooperativity and the resulting growth behavior of these organisms. Taking a first step towards understanding the complex spatio-temporal interactions within microbial populations, we performed a parametric study of E. coli growth on an agar substrate and probed the dependence of colony behavior on: 1) strain-specific metabolic characteristics, and 2) the geometry of the underlying substrate. To do so, we employed a recently developed multiscale technique named 3D dynamic flux balance analysis which couples reaction-diffusion simulations with iterative steady-state metabolic modeling. Key measures examined include colony growth rate and shape (height vs. width), metabolite production/consumption and concentration profiles, and the emergence of metabolic cooperativity and the fractions of cell phenotypes. Five closely related strains of E. coli, which exhibit large variation in glucose consumption and organic acid production potential, were studied. The onset of metabolic cooperativity was found to vary substantially between these five strains by up to 10 hours and the relative fraction of acetate utilizing cells within the colonies varied by a factor of two. Additionally, growth with six different geometries designed to mimic those that might be found in a laboratory, a microfluidic device, and inside a living organism were considered. Geometries were found to have complex, often nonlinear effects on colony growth and cross-feeding with "hard" features resulting in larger effect than "soft" features. These results demonstrate that strain-specific features and spatial constraints imposed by the growth substrate can have significant effects even for microbial populations as simple as isogenic E. coli colonies.

The potential for phytoremediation of iron cyanide complex by willows.

PubMed

Yu, Xiao-Zhang; Zhou, Pu-Hua; Yang, Yong-Miao

2006-07-01

Hybrid willows (Salix matsudana Koidz x Salix alba L.), weeping willows (Salix babylonica L.) and hankow willows (Salix matsudana Koidz) were exposed to potassium ferrocyanide to determine the potential of these plants to extract, transport and metabolize this iron cyanide complex. Young rooted cuttings were grown in hydroponic solution at 24.0 +/- 0.5 degrees C for 144 h. Ferrocyanide in solution, air, and aerial tissues of plants was analyzed spectrophotometrically. Uptake of ferrocyanide from the aqueous solution by plants was evident for all treatments and varied with plant species, ranging from 8.64 to 15.67% of initial mass. The uptake processes observed from hydroponic solution showed exponential disappearance kinetics. Very little amounts of the applied ferrocyanide were detected in all parts of plant materials, confirming passage of ferrocyanide through the plants. No ferrocyanide in air was found due to plant transpiration. Mass balance analysis showed that a large fraction of the reduction of initial mass in hydroponic solution was metabolized during transport within the plant materials. The difference in the metabolic rate of ferrocyanide between the three plant species was comparably small, indicating transport of ferrocyanide from hydroponic solution to plant materials and further transport within plant materials was a limiting step for assimilating this iron cyanide complex. In conclusion, phytoremediation of ferrocyanide by the plants tested in this study has potential field application.

Acid-base disturbances in nephrotic syndrome: analysis using the CO2/HCO3 method (traditional Boston model) and the physicochemical method (Stewart model).

PubMed

Kasagi, Tomomichi; Imai, Hirokazu; Miura, Naoto; Suzuki, Keisuke; Yoshino, Masabumi; Nobata, Hironobu; Nagai, Takuhito; Banno, Shogo

2017-10-01

The Stewart model for analyzing acid-base disturbances emphasizes serum albumin levels, which are ignored in the traditional Boston model. We compared data derived using the Stewart model to those using the Boston model in patients with nephrotic syndrome. Twenty-nine patients with nephrotic syndrome and six patients without urinary protein or acid-base disturbances provided blood and urine samples for analysis that included routine biochemical and arterial blood gas tests, plasma renin activity, and aldosterone. The total concentration of non-volatile weak acids (A TOT ), apparent strong ion difference (SIDa), effective strong ion difference (SIDe), and strong ion gap (SIG) were calculated according to the formulas of Agrafiotis in the Stewart model. According to the Boston model, 25 of 29 patients (90%) had alkalemia. Eighteen patients had respiratory alkalosis, 11 had metabolic alkalosis, and 4 had both conditions. Only three patients had hyperreninemic hyperaldosteronism. The Stewart model demonstrated respiratory alkalosis based on decreased PaCO 2 , metabolic alkalosis based on decreased A TOT , and metabolic acidosis based on decreased SIDa. We could diagnose metabolic alkalosis or acidosis with a normal anion gap after comparing delta A TOT [(14.09 - measured A TOT ) or (11.77 - 2.64 × Alb (g/dL))] and delta SIDa [(42.7 - measured SIDa) or (42.7 - (Na + K - Cl)]). We could also identify metabolic acidosis with an increased anion gap using SIG > 7.0 (SIG = 0.9463 × corrected anion gap-8.1956). Patients with nephrotic syndrome had primary respiratory alkalosis, decreased A TOT due to hypoalbuminemia (power to metabolic alkalosis), and decreased levels of SIDa (power to metabolic acidosis). We could detect metabolic acidosis with an increased anion gap by calculating SIG. The Stewart model in combination with the Boston model facilitates the analysis of complex acid-base disturbances in nephrotic syndrome.

The Tangled Circuitry of Metabolism and Apoptosis

PubMed Central

Andersen, Joshua L.; Kornbluth, Sally

2013-01-01

For single cell organisms, nutrient uptake and metabolism are at the crux of their most basic decision of whether to grow or divide. In metazoans, cell fate decisions are more complex: organismal homeostasis must be strictly maintained by balancing cell proliferation and death. Despite this increased complexity, cell fate within multicellular organisms is also influenced by metabolism; recent studies, triggered in part be an interest tumor metabolism, are beginning to illuminate the mechanisms through which proliferation, death, and metabolism are intertwined. In particular, work on Bcl-2 family proteins suggests that the signaling pathways governing metabolism and apoptosis are inextricably linked. Here, we review the crosstalk between these pathways, emphasizing recent work that illustrates the emerging dual nature of several core apoptotic proteins in regulating both metabolism and cell death. PMID:23395270

The tangled circuitry of metabolism and apoptosis.

PubMed

Andersen, Joshua L; Kornbluth, Sally

2013-02-07

For single-cell organisms, nutrient uptake and metabolism are central to the fundamental decision of whether to grow or divide. In metazoans, cell fate decisions are more complex: organismal homeostasis must be strictly maintained by balancing cell proliferation and death. Despite this increased complexity, cell fate within multicellular organisms is also influenced by metabolism; recent studies, triggered in part by an interest in tumor metabolism, are beginning to illuminate the mechanisms through which proliferation, death, and metabolism are intertwined. In particular, work on Bcl-2 family proteins suggests that the signaling pathways governing metabolism and apoptosis are inextricably linked. Here we review the crosstalk between these pathways, emphasizing recent work that illustrates the emerging dual nature of several core apoptotic proteins in regulating both metabolism and cell death. Copyright © 2013 Elsevier Inc. All rights reserved.

The TORC1-Regulated CPA Complex Rewires an RNA Processing Network to Drive Autophagy and Metabolic Reprogramming.

PubMed

Tang, Hong-Wen; Hu, Yanhui; Chen, Chiao-Lin; Xia, Baolong; Zirin, Jonathan; Yuan, Min; Asara, John M; Rabinow, Leonard; Perrimon, Norbert

2018-05-01

Nutrient deprivation induces autophagy through inhibiting TORC1 activity. We describe a novel mechanism in Drosophila by which TORC1 regulates RNA processing of Atg transcripts and alters ATG protein levels and activities via the cleavage and polyadenylation (CPA) complex. We show that TORC1 signaling inhibits CDK8 and DOA kinases, which directly phosphorylate CPSF6, a component of the CPA complex. These phosphorylation events regulate CPSF6 localization, RNA binding, and starvation-induced alternative RNA processing of transcripts involved in autophagy, nutrient, and energy metabolism, thereby controlling autophagosome formation and metabolism. Similarly, we find that mammalian CDK8 and CLK2, a DOA ortholog, phosphorylate CPSF6 to regulate autophagy and metabolic changes upon starvation, revealing an evolutionarily conserved mechanism linking TORC1 signaling with RNA processing, autophagy, and metabolism. Copyright © 2018 Elsevier Inc. All rights reserved.

Imaging flow cytometry for phytoplankton analysis.

PubMed

Dashkova, Veronika; Malashenkov, Dmitry; Poulton, Nicole; Vorobjev, Ivan; Barteneva, Natasha S

2017-01-01

This review highlights the concepts and instrumentation of imaging flow cytometry technology and in particular its use for phytoplankton analysis. Imaging flow cytometry, a hybrid technology combining speed and statistical capabilities of flow cytometry with imaging features of microscopy, is rapidly advancing as a cell imaging platform that overcomes many of the limitations of current techniques and contributed significantly to the advancement of phytoplankton analysis in recent years. This review presents the various instrumentation relevant to the field and currently used for assessment of complex phytoplankton communities' composition and abundance, size structure determination, biovolume estimation, detection of harmful algal bloom species, evaluation of viability and metabolic activity and other applications. Also we present our data on viability and metabolic assessment of Aphanizomenon sp. cyanobacteria using Imagestream X Mark II imaging cytometer. Herein, we highlight the immense potential of imaging flow cytometry for microalgal research, but also discuss limitations and future developments. Copyright © 2016 Elsevier Inc. All rights reserved.

Determination of cell metabolite VEGF₁₆₅ and dynamic analysis of protein-DNA interactions by combination of microfluidic technique and luminescent switch-on probe.

PubMed

Lin, Xuexia; Leung, Ka-Ho; Lin, Ling; Lin, Luyao; Lin, Sheng; Leung, Chung-Hang; Ma, Dik-Lung; Lin, Jin-Ming

2016-05-15

In this paper, we rationally design a novel G-quadruplex-selective luminescent iridium (III) complex for rapid detection of oligonucleotide and VEGF165 in microfluidics. This new probe is applied as a convenient biosensor for label-free quantitative analysis of VEGF165 protein from cell metabolism, as well as for studying the kinetics of the aptamer-protein interaction combination with a microfluidic platform. As a result, we have successfully established a quantitative analysis of VEGF165 from cell metabolism. Furthermore, based on the principles of hydrodynamic focusing and diffusive mixing, different transient states during kinetics process were monitored and recorded. Thus, the combination of microfluidic technique and G-quadruplex luminescent probe will be potentially applied in the studies of intramolecular interactions and molecule recognition in the future. Copyright © 2015 Elsevier B.V. All rights reserved.

Chronic innate immune activation of TBK1 suppresses mTORC1 activity and dysregulates cellular metabolism.

PubMed

Hasan, Maroof; Gonugunta, Vijay K; Dobbs, Nicole; Ali, Aktar; Palchik, Guillermo; Calvaruso, Maria A; DeBerardinis, Ralph J; Yan, Nan

2017-01-24

Three-prime repair exonuclease 1 knockout (Trex1 -/- ) mice suffer from systemic inflammation caused largely by chronic activation of the cyclic GMP-AMP synthase-stimulator of interferon genes-TANK-binding kinase-interferon regulatory factor 3 (cGAS-STING-TBK1-IRF3) signaling pathway. We showed previously that Trex1-deficient cells have reduced mammalian target of rapamycin complex 1 (mTORC1) activity, although the underlying mechanism is unclear. Here, we performed detailed metabolic analysis in Trex1 -/- mice and cells that revealed both cellular and systemic metabolic defects, including reduced mitochondrial respiration and increased glycolysis, energy expenditure, and fat metabolism. We also genetically separated the inflammatory and metabolic phenotypes by showing that Sting deficiency rescued both inflammatory and metabolic phenotypes, whereas Irf3 deficiency only rescued inflammation on the Trex1 -/- background, and many metabolic defects persist in Trex1 -/- Irf3 -/- cells and mice. We also showed that Leptin deficiency (ob/ob) increased lipogenesis and prolonged survival of Trex1 -/- mice without dampening inflammation. Mechanistically, we identified TBK1 as a key regulator of mTORC1 activity in Trex1 -/- cells. Together, our data demonstrate that chronic innate immune activation of TBK1 suppresses mTORC1 activity, leading to dysregulated cellular metabolism.

Adipocyte Metabolic Pathways Regulated by Diet Control the Female Germline Stem Cell Lineage in Drosophila melanogaster

PubMed Central

Matsuoka, Shinya; Armstrong, Alissa R.; Sampson, Leesa L.; Laws, Kaitlin M.; Drummond-Barbosa, Daniela

2017-01-01

Nutrients affect adult stem cells through complex mechanisms involving multiple organs. Adipocytes are highly sensitive to diet and have key metabolic roles, and obesity increases the risk for many cancers. How diet-regulated adipocyte metabolic pathways influence normal stem cell lineages, however, remains unclear. Drosophila melanogaster has highly conserved adipocyte metabolism and a well-characterized female germline stem cell (GSC) lineage response to diet. Here, we conducted an isobaric tags for relative and absolute quantification (iTRAQ) proteomic analysis to identify diet-regulated adipocyte metabolic pathways that control the female GSC lineage. On a rich (relative to poor) diet, adipocyte Hexokinase-C and metabolic enzymes involved in pyruvate/acetyl-CoA production are upregulated, promoting a shift of glucose metabolism toward macromolecule biosynthesis. Adipocyte-specific knockdown shows that these enzymes support early GSC progeny survival. Further, enzymes catalyzing fatty acid oxidation and phosphatidylethanolamine synthesis in adipocytes promote GSC maintenance, whereas lipid and iron transport from adipocytes controls vitellogenesis and GSC number, respectively. These results show a functional relationship between specific metabolic pathways in adipocytes and distinct processes in the GSC lineage, suggesting the adipocyte metabolism–stem cell link as an important area of investigation in other stem cell systems. PMID:28396508

Construction and simulation of the Bradyrhizobium diazoefficiens USDA110 metabolic network: a comparison between free-living and symbiotic states.

PubMed

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

2017-02-28

Bradyrhizobium diazoefficiens is a rhizobium able to convert atmospheric nitrogen into ammonium by establishing mutualistic symbiosis with soybean. It has been recognized as an important parent strain for microbial agents and is widely applied in agricultural and environmental fields. In order to study the metabolic properties of symbiotic nitrogen fixation and the differences between a free-living cell and a symbiotic bacteroid, a genome-scale metabolic network of B. diazoefficiens USDA110 was constructed and analyzed. The metabolic network, iYY1101, contains 1031 reactions, 661 metabolites, and 1101 genes in total. Metabolic models reflecting free-living and symbiotic states were determined by defining the corresponding objective functions and substrate input sets, and were further constrained by high-throughput transcriptomic and proteomic data. Constraint-based flux analysis was used to compare the metabolic capacities and the effects on the metabolic targets of genes and reactions between the two physiological states. The results showed that a free-living rhizobium possesses a steady state flux distribution for sustaining a complex supply of biomass precursors while a symbiotic bacteroid maintains a relatively condensed one adapted to nitrogen-fixation. Our metabolic models may serve as a promising platform for better understanding the symbiotic nitrogen fixation of this species.

Short-Chain 3-Hydroxyacyl-Coenzyme A Dehydrogenase Associates with a Protein Super-Complex Integrating Multiple Metabolic Pathways

PubMed Central

Narayan, Srinivas B.; Master, Stephen R.; Sireci, Anthony N.; Bierl, Charlene; Stanley, Paige E.; Li, Changhong; Stanley, Charles A.; Bennett, Michael J.

2012-01-01

Proteins involved in mitochondrial metabolic pathways engage in functionally relevant multi-enzyme complexes. We previously described an interaction between short-chain 3-hydroxyacyl-coenzyme A dehydrogenase (SCHAD) and glutamate dehydrogenase (GDH) explaining the clinical phenotype of hyperinsulinism in SCHAD-deficient patients and adding SCHAD to the list of mitochondrial proteins capable of forming functional, multi-pathway complexes. In this work, we provide evidence of SCHAD's involvement in additional interactions forming tissue-specific metabolic super complexes involving both membrane-associated and matrix-dwelling enzymes and spanning multiple metabolic pathways. As an example, in murine liver, we find SCHAD interaction with aspartate transaminase (AST) and GDH from amino acid metabolic pathways, carbamoyl phosphate synthase I (CPS-1) from ureagenesis, other fatty acid oxidation and ketogenesis enzymes and fructose-bisphosphate aldolase, an extra-mitochondrial enzyme of the glycolytic pathway. Most of the interactions appear to be independent of SCHAD's role in the penultimate step of fatty acid oxidation suggesting an organizational, structural or non-enzymatic role for the SCHAD protein. PMID:22496890

Zebularine: A Novel DNL Methylation Inhibitor that Forms a Covalent Complex with DNA Methyltransferases

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

Zhou, L.; Cheng, X; Connolly, B

2009-01-01

Mechanism-based inhibitors of enzymes, which mimic reactive intermediates in the reaction pathway, have been deployed extensively in the analysis of metabolic pathways and as candidate drugs. The inhibition of cytosine-[C5]-specific DNA methyltransferases (C5 MTases) by oligodeoxynucleotides containing 5-azadeoxycytidine (AzadC) and 5-fluorodeoxycytidine (FdC) provides a well-documented example of mechanism-based inhibition of enzymes central to nucleic acid metabolism. Here, we describe the interaction between the C5 MTase from Haemophilus haemolyticus (M.HhaI) and an oligodeoxynucleotide duplex containing 2-H pyrimidinone, an analogue often referred to as zebularine and known to give rise to high-affinity complexes with MTases. X-ray crystallography has demonstrated the formation ofmore » a covalent bond between M.HhaI and the 2-H pyrimidinone-containing oligodeoxynucleotide. This observation enables a comparison between the mechanisms of action of 2-H pyrimidinone with other mechanism-based inhibitors such as FdC. This novel complex provides a molecular explanation for the mechanism of action of the anti-cancer drug zebularine.« less

The connectivity structure, giant strong component and centrality of metabolic networks.

PubMed

Ma, Hong-Wu; Zeng, An-Ping

2003-07-22

Structural and functional analysis of genome-based large-scale metabolic networks is important for understanding the design principles and regulation of the metabolism at a system level. The metabolic network is conventionally considered to be highly integrated and very complex. A rational reduction of the metabolic network to its core structure and a deeper understanding of its functional modules are important. In this work, we show that the metabolites in a metabolic network are far from fully connected. A connectivity structure consisting of four major subsets of metabolites and reactions, i.e. a fully connected sub-network, a substrate subset, a product subset and an isolated subset is found to exist in metabolic networks of 65 fully sequenced organisms. The largest fully connected part of a metabolic network, called 'the giant strong component (GSC)', represents the most complicated part and the core of the network and has the feature of scale-free networks. The average path length of the whole network is primarily determined by that of the GSC. For most of the organisms, GSC normally contains less than one-third of the nodes of the network. This connectivity structure is very similar to the 'bow-tie' structure of World Wide Web. Our results indicate that the bow-tie structure may be common for large-scale directed networks. More importantly, the uncovered structure feature makes a structural and functional analysis of large-scale metabolic network more amenable. As shown in this work, comparing the closeness centrality of the nodes in the GSC can identify the most central metabolites of a metabolic network. To quantitatively characterize the overall connection structure of the GSC we introduced the term 'overall closeness centralization index (OCCI)'. OCCI correlates well with the average path length of the GSC and is a useful parameter for a system-level comparison of metabolic networks of different organisms. http://genome.gbf.de/bioinformatics/

SensA: web-based sensitivity analysis of SBML models.

PubMed

Floettmann, Max; Uhlendorf, Jannis; Scharp, Till; Klipp, Edda; Spiesser, Thomas W

2014-10-01

SensA is a web-based application for sensitivity analysis of mathematical models. The sensitivity analysis is based on metabolic control analysis, computing the local, global and time-dependent properties of model components. Interactive visualization facilitates interpretation of usually complex results. SensA can contribute to the analysis, adjustment and understanding of mathematical models for dynamic systems. SensA is available at http://gofid.biologie.hu-berlin.de/ and can be used with any modern browser. The source code can be found at https://bitbucket.org/floettma/sensa/ (MIT license) © The Author 2014. Published by Oxford University Press.

EPR Characterization of Dinitrosyl Iron Complexes with Thiol-Containing Ligands as an Approach to Their Identification in Biological Objects: An Overview.

PubMed

Vanin, Anatoly F

2018-06-01

The overview demonstrates how the use of only one physico-chemical approach, viz., the electron paramagnetic resonance method, allowed detection and identification of dinitrosyl iron complexes with thiol-containing ligands in various animal and bacterial cells. These complexes are formed in biological objects in the paramagnetic (electron paramagnetic resonance-active) mononuclear and diamagnetic (electron paramagnetic resonance-silent) binuclear forms and control the activity of nitrogen monoxide, one of the most universal regulators of metabolic processes in the organism. The analysis of electronic and spatial structures of dinitrosyl iron complex sheds additional light on the mechanism whereby dinitrosyl iron complex with thiol-containing ligands function in human and animal cells as donors of nitrogen monoxide and its ionized form, viz., nitrosonium ions (NO + ).

Metabolic Network Modeling of Microbial Interactions in Natural and Engineered Environmental Systems

PubMed Central

Perez-Garcia, Octavio; Lear, Gavin; Singhal, Naresh

2016-01-01

We review approaches to characterize metabolic interactions within microbial communities using Stoichiometric Metabolic Network (SMN) models for applications in environmental and industrial biotechnology. SMN models are computational tools used to evaluate the metabolic engineering potential of various organisms. They have successfully been applied to design and optimize the microbial production of antibiotics, alcohols and amino acids by single strains. To date however, such models have been rarely applied to analyze and control the metabolism of more complex microbial communities. This is largely attributed to the diversity of microbial community functions, metabolisms, and interactions. Here, we firstly review different types of microbial interaction and describe their relevance for natural and engineered environmental processes. Next, we provide a general description of the essential methods of the SMN modeling workflow including the steps of network reconstruction, simulation through Flux Balance Analysis (FBA), experimental data gathering, and model calibration. Then we broadly describe and compare four approaches to model microbial interactions using metabolic networks, i.e., (i) lumped networks, (ii) compartment per guild networks, (iii) bi-level optimization simulations, and (iv) dynamic-SMN methods. These approaches can be used to integrate and analyze diverse microbial physiology, ecology and molecular community data. All of them (except the lumped approach) are suitable for incorporating species abundance data but so far they have been used only to model simple communities of two to eight different species. Interactions based on substrate exchange and competition can be directly modeled using the above approaches. However, interactions based on metabolic feedbacks, such as product inhibition and synthropy require extensions to current models, incorporating gene regulation and compounding accumulation mechanisms. SMN models of microbial interactions can be used to analyze complex “omics” data and to infer and optimize metabolic processes. Thereby, SMN models are suitable to capitalize on advances in high-throughput molecular and metabolic data generation. SMN models are starting to be applied to describe microbial interactions during wastewater treatment, in-situ bioremediation, microalgae blooms methanogenic fermentation, and bioplastic production. Despite their current challenges, we envisage that SMN models have future potential for the design and development of novel growth media, biochemical pathways and synthetic microbial associations. PMID:27242701

Metabolic Reprogramming and Oncogenesis: One Hallmark, Many Organelles.

PubMed

Costa, A S H; Frezza, C

2017-01-01

The process of tumorigenesis can be described by a series of molecular features, among which alteration of cellular metabolism has recently emerged. This metabolic rewiring fulfills the energy and biosynthetic demands of fast proliferating cancer cells and amplifies their metabolic repertoire to survive and proliferate in the poorly oxygenated and nutrient-deprived tumor microenvironment. During the last decade, the complex reprogramming of cancer cell metabolism has been widely investigated, revealing cancer-specific metabolic alterations. These include dysregulation of glucose and glutamine metabolism, alterations of lipid synthesis and oxidation, and a complex rewiring of mitochondrial function. However, mitochondria are not the only metabolically active organelles within the cell, and other organelles, including lysosomes, peroxisomes, and endoplasmic reticulum, harbor components of the metabolic network. Of note, dysregulation of the function of these organelles is increasingly recognized in cancer cells. However, to what extent these organelles contribute to the metabolic reprogramming of cancer is not fully understood. In this review, we describe the main metabolic functions of these organelles and provide insights into how they communicate to orchestrate a coordinated metabolic reprogramming during transformation. © 2017 Elsevier Inc. All rights reserved.

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

Metabolic analysis of the soil microbe Dechloromonas aromatica str. RCB: indications of a surprisingly complex life-style and cryptic anaerobic pathways for aromatic degradation

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

Salinero, Kennan Kellaris; Keller, Keith; Feil, William S.

2008-11-17

Initial interest in Dechloromonas aromatica strain RCB arose from its ability to anaerobically degrade benzene. It is also able to reduce perchlorate and oxidize chlorobenzoate, toluene, and xylene, creating interest in using this organism for bioremediation. Little physiological data has been published for this microbe. It is considered to be a free-living organism. The a priori prediction that the D. aromatica genome would contain previously characterized 'central' enzymes involved in anaerobic aromatic degradation proved to be false, suggesting the presence of novel anaerobic aromatic degradation pathways in this species. These missing pathways include the benzyl succinyl synthase (bssABC) genes (responsiblemore » for formate addition to toluene) and the central benzoylCoA pathway for monoaromatics. In depth analyses using existing TIGRfam, COG, and InterPro models, and the creation of de novo HMM models, indicate a highly complex lifestyle with a large number of environmental sensors and signaling pathways, including a relatively large number of GGDEF domain signal receptors and multiple quorum sensors. A number of proteins indicate interactions with an as yet unknown host, as indicated by the presence of predicted cell host remodeling enzymes, effector enzymes, hemolysin-like proteins, adhesins, NO reductase, and both type III and type VI secretory complexes. Evidence of biofilm formation including a proposed exopolysaccharide complex with the somewhat rare exosortase (epsH), is also present. Annotation described in this paper also reveals evidence for several metabolic pathways that have yet to be observed experimentally, including a sulphur oxidation (soxFCDYZAXB) gene cluster, Calvin cycle enzymes, and nitrogen fixation (including RubisCo, ribulose-phosphate 3-epimerase, and nif gene families, respectively). Analysis of the D. aromatica genome indicates there is much to be learned regarding the metabolic capabilities, and life-style, for this microbial species. Examples of recent gene duplication events in signaling as well as dioxygenase clusters are present, indicating selective gene family expansion as a relatively recent event in D. aromatica's evolutionary history. Gene families that constitute metabolic cycles presumed to create D. aromatica's environmental 'foot-print' indicate a high level of diversification between its predicted capabilities and those of its close relatives, A. aromaticum str EbN1 and Azoarcus BH72.« less

Identification and analysis of chemical constituents and rat serum metabolites in Suan-Zao-Ren granule using ultra high performance liquid chromatography quadrupole time-of-flight mass spectrometry combined with multiple data processing approaches.

PubMed

Du, Yiyang; He, Bosai; Li, Qing; He, Jiao; Wang, Di; Bi, Kaishun

2017-07-01

Suan-Zao-Ren granule is widely used to treat insomnia in China. However, because of the complexity and diversity of the chemical compositions in traditional Chinese medicine formula, the comprehensive analysis of constituents in vitro and in vivo is rather difficult. In our study, an ultra high performance liquid chromatography with quadrupole time-of-flight mass spectrometry and the PeakView® software, which uses multiple data processing approaches including product ion filter, neutral loss filter, and mass defect filter, method was developed to characterize the ingredients and rat serum metabolites in Suan-Zao-Ren granule. A total of 101 constituents were detected in vitro. Under the same analysis conditions, 68 constituents were characterized in rat serum, including 35 prototype components and 33 metabolites. The metabolic pathways of main components were also illustrated. Among them, the metabolic pathways of timosaponin AI were firstly revealed. The bioactive compounds mainly underwent the phase I metabolic pathways including hydroxylation, oxidation, hydrolysis, and phase II metabolic pathways including sulfate conjugation, glucuronide conjugation, cysteine conjugation, acetycysteine conjugation, and glutathione conjugation. In conclusion, our results showed that this analysis approach was extremely useful for the in-depth pharmacological research of Suan-Zao-Ren granule and provided a chemical basis for its rational. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Rapamycin impairs metabolism-secretion coupling in rat pancreatic islets by suppressing carbohydrate metabolism.

PubMed

Shimodahira, Makiko; Fujimoto, Shimpei; Mukai, Eri; Nakamura, Yasuhiko; Nishi, Yuichi; Sasaki, Mayumi; Sato, Yuichi; Sato, Hiroki; Hosokawa, Masaya; Nagashima, Kazuaki; Seino, Yutaka; Inagaki, Nobuya

2010-01-01

Rapamycin, an immunosuppressant used in human transplantation, impairs beta-cell function, but the mechanism is unclear. Chronic (24 h) exposure to rapamycin concentration dependently suppressed 16.7 mM glucose-induced insulin release from islets (1.65+/-0.06, 30 nM rapamycin versus 2.35+/-0.11 ng/islet per 30 min, control, n=30, P<0.01) without affecting insulin and DNA contents. Rapamycin also decreased alpha-ketoisocaproate-induced insulin release, suggesting reduced mitochondrial carbohydrate metabolism. ATP content in the presence of 16.7 mM glucose was significantly reduced in rapamycin-treated islets (13.42+/-0.47, rapamycin versus 16.04+/-0.46 pmol/islet, control, n=30, P<0.01). Glucose oxidation, which indicates the velocity of metabolism in the Krebs cycle, was decreased by rapamycin in the presence of 16.7 mM glucose (30.1+/-2.7, rapamycin versus 42.2+/-3.3 pmol/islet per 90 min, control, n=9, P<0.01). Immunoblotting revealed that the expression of complex I, III, IV, and V was not affected by rapamycin. Mitochondrial ATP production indicated that the respiratory chain downstream of complex II was not affected, but that carbohydrate metabolism in the Krebs cycle was reduced by rapamycin. Analysis of enzymes in the Krebs cycle revealed that activity of alpha-ketoglutarate dehydrogenase (KGDH), which catalyzes one of the slowest reactions in the Krebs cycle, was reduced by rapamycin (10.08+/-0.82, rapamycin versus 13.82+/-0.84 nmol/mg mitochondrial protein per min, control, n=5, P<0.01). Considered together, these findings indicate that rapamycin suppresses high glucose-induced insulin secretion from pancreatic islets by reducing mitochondrial ATP production through suppression of carbohydrate metabolism in the Krebs cycle, together with reduced KGDH activity.

Genome-enabled Modeling of Microbial Biogeochemistry using a Trait-based Approach. Does Increasing Metabolic Complexity Increase Predictive Capabilities?

NASA Astrophysics Data System (ADS)

King, E.; Karaoz, U.; Molins, S.; Bouskill, N.; Anantharaman, K.; Beller, H. R.; Banfield, J. F.; Steefel, C. I.; Brodie, E.

2015-12-01

The biogeochemical functioning of ecosystems is shaped in part by genomic information stored in the subsurface microbiome. Cultivation-independent approaches allow us to extract this information through reconstruction of thousands of genomes from a microbial community. Analysis of these genomes, in turn, gives an indication of the organisms present and their functional roles. However, metagenomic analyses can currently deliver thousands of different genomes that range in abundance/importance, requiring the identification and assimilation of key physiologies and metabolisms to be represented as traits for successful simulation of subsurface processes. Here we focus on incorporating -omics information into BioCrunch, a genome-informed trait-based model that represents the diversity of microbial functional processes within a reactive transport framework. This approach models the rate of nutrient uptake and the thermodynamics of coupled electron donors and acceptors for a range of microbial metabolisms including heterotrophs and chemolithotrophs. Metabolism of exogenous substrates fuels catabolic and anabolic processes, with the proportion of energy used for cellular maintenance, respiration, biomass development, and enzyme production based upon dynamic intracellular and environmental conditions. This internal resource partitioning represents a trade-off against biomass formation and results in microbial community emergence across a fitness landscape. Biocrunch was used here in simulations that included organisms and metabolic pathways derived from a dataset of ~1200 non-redundant genomes reflecting a microbial community in a floodplain aquifer. Metagenomic data was directly used to parameterize trait values related to growth and to identify trait linkages associated with respiration, fermentation, and key enzymatic functions such as plant polymer degradation. Simulations spanned a range of metabolic complexities and highlight benefits originating from simulations including a larger number of organisms that more appropriately reflect the in situ microbial community.

Metabolic pathways for the whole community.

PubMed

Hanson, Niels W; Konwar, Kishori M; Hawley, Alyse K; Altman, Tomer; Karp, Peter D; Hallam, Steven J

2014-07-22

A convergence of high-throughput sequencing and computational power is transforming biology into information science. Despite these technological advances, converting bits and bytes of sequence information into meaningful insights remains a challenging enterprise. Biological systems operate on multiple hierarchical levels from genomes to biomes. Holistic understanding of biological systems requires agile software tools that permit comparative analyses across multiple information levels (DNA, RNA, protein, and metabolites) to identify emergent properties, diagnose system states, or predict responses to environmental change. Here we adopt the MetaPathways annotation and analysis pipeline and Pathway Tools to construct environmental pathway/genome databases (ePGDBs) that describe microbial community metabolism using MetaCyc, a highly curated database of metabolic pathways and components covering all domains of life. We evaluate Pathway Tools' performance on three datasets with different complexity and coding potential, including simulated metagenomes, a symbiotic system, and the Hawaii Ocean Time-series. We define accuracy and sensitivity relationships between read length, coverage and pathway recovery and evaluate the impact of taxonomic pruning on ePGDB construction and interpretation. Resulting ePGDBs provide interactive metabolic maps, predict emergent metabolic pathways associated with biosynthesis and energy production and differentiate between genomic potential and phenotypic expression across defined environmental gradients. This multi-tiered analysis provides the user community with specific operating guidelines, performance metrics and prediction hazards for more reliable ePGDB construction and interpretation. Moreover, it demonstrates the power of Pathway Tools in predicting metabolic interactions in natural and engineered ecosystems.

Modeling central metabolism and energy biosynthesis across microbial life

DOE PAGES

Edirisinghe, Janaka N.; Weisenhorn, Pamela; Conrad, Neal; ...

2016-08-08

Here, automatically generated bacterial metabolic models, and even some curated models, lack accuracy in predicting energy yields due to poor representation of key pathways in energy biosynthesis and the electron transport chain (ETC). Further compounding the problem, complex interlinking pathways in genome-scale metabolic models, and the need for extensive gapfilling to support complex biomass reactions, often results in predicting unrealistic yields or unrealistic physiological flux profiles. As a result, to overcome this challenge, we developed methods and tools to build high quality core metabolic models (CMM) representing accurate energy biosynthesis based on a well studied, phylogenetically diverse set of modelmore » organisms. We compare these models to explore the variability of core pathways across all microbial life, and by analyzing the ability of our core models to synthesize ATP and essential biomass precursors, we evaluate the extent to which the core metabolic pathways and functional ETCs are known for all microbes. 6,600 (80 %) of our models were found to have some type of aerobic ETC, whereas 5,100 (62 %) have an anaerobic ETC, and 1,279 (15 %) do not have any ETC. Using our manually curated ETC and energy biosynthesis pathways with no gapfilling at all, we predict accurate ATP yields for nearly 5586 (70 %) of the models under aerobic and anaerobic growth conditions. This study revealed gaps in our knowledge of the central pathways that result in 2,495 (30 %) CMMs being unable to produce ATP under any of the tested conditions. We then established a methodology for the systematic identification and correction of inconsistent annotations using core metabolic models coupled with phylogenetic analysis. In conclusion, we predict accurate energy yields based on our improved annotations in energy biosynthesis pathways and the implementation of diverse ETC reactions across the microbial tree of life. We highlighted missing annotations that were essential to energy biosynthesis in our models. We examine the diversity of these pathways across all microbial life and enable the scientific community to explore the analyses generated from this large-scale analysis of over 8000 microbial genomes.« less

Modeling central metabolism and energy biosynthesis across microbial life

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

Edirisinghe, Janaka N.; Weisenhorn, Pamela; Conrad, Neal

Here, automatically generated bacterial metabolic models, and even some curated models, lack accuracy in predicting energy yields due to poor representation of key pathways in energy biosynthesis and the electron transport chain (ETC). Further compounding the problem, complex interlinking pathways in genome-scale metabolic models, and the need for extensive gapfilling to support complex biomass reactions, often results in predicting unrealistic yields or unrealistic physiological flux profiles. As a result, to overcome this challenge, we developed methods and tools to build high quality core metabolic models (CMM) representing accurate energy biosynthesis based on a well studied, phylogenetically diverse set of modelmore » organisms. We compare these models to explore the variability of core pathways across all microbial life, and by analyzing the ability of our core models to synthesize ATP and essential biomass precursors, we evaluate the extent to which the core metabolic pathways and functional ETCs are known for all microbes. 6,600 (80 %) of our models were found to have some type of aerobic ETC, whereas 5,100 (62 %) have an anaerobic ETC, and 1,279 (15 %) do not have any ETC. Using our manually curated ETC and energy biosynthesis pathways with no gapfilling at all, we predict accurate ATP yields for nearly 5586 (70 %) of the models under aerobic and anaerobic growth conditions. This study revealed gaps in our knowledge of the central pathways that result in 2,495 (30 %) CMMs being unable to produce ATP under any of the tested conditions. We then established a methodology for the systematic identification and correction of inconsistent annotations using core metabolic models coupled with phylogenetic analysis. In conclusion, we predict accurate energy yields based on our improved annotations in energy biosynthesis pathways and the implementation of diverse ETC reactions across the microbial tree of life. We highlighted missing annotations that were essential to energy biosynthesis in our models. We examine the diversity of these pathways across all microbial life and enable the scientific community to explore the analyses generated from this large-scale analysis of over 8000 microbial genomes.« less

Modeling central metabolism and energy biosynthesis across microbial life.

PubMed

Edirisinghe, Janaka N; Weisenhorn, Pamela; Conrad, Neal; Xia, Fangfang; Overbeek, Ross; Stevens, Rick L; Henry, Christopher S

2016-08-08

Automatically generated bacterial metabolic models, and even some curated models, lack accuracy in predicting energy yields due to poor representation of key pathways in energy biosynthesis and the electron transport chain (ETC). Further compounding the problem, complex interlinking pathways in genome-scale metabolic models, and the need for extensive gapfilling to support complex biomass reactions, often results in predicting unrealistic yields or unrealistic physiological flux profiles. To overcome this challenge, we developed methods and tools ( http://coremodels.mcs.anl.gov ) to build high quality core metabolic models (CMM) representing accurate energy biosynthesis based on a well studied, phylogenetically diverse set of model organisms. We compare these models to explore the variability of core pathways across all microbial life, and by analyzing the ability of our core models to synthesize ATP and essential biomass precursors, we evaluate the extent to which the core metabolic pathways and functional ETCs are known for all microbes. 6,600 (80 %) of our models were found to have some type of aerobic ETC, whereas 5,100 (62 %) have an anaerobic ETC, and 1,279 (15 %) do not have any ETC. Using our manually curated ETC and energy biosynthesis pathways with no gapfilling at all, we predict accurate ATP yields for nearly 5586 (70 %) of the models under aerobic and anaerobic growth conditions. This study revealed gaps in our knowledge of the central pathways that result in 2,495 (30 %) CMMs being unable to produce ATP under any of the tested conditions. We then established a methodology for the systematic identification and correction of inconsistent annotations using core metabolic models coupled with phylogenetic analysis. We predict accurate energy yields based on our improved annotations in energy biosynthesis pathways and the implementation of diverse ETC reactions across the microbial tree of life. We highlighted missing annotations that were essential to energy biosynthesis in our models. We examine the diversity of these pathways across all microbial life and enable the scientific community to explore the analyses generated from this large-scale analysis of over 8000 microbial genomes.

Combining proteomics and metabolite analyses to unravel cadmium stress-response in poplar leaves.

PubMed

Kieffer, Pol; Planchon, Sébastien; Oufir, Mouhssin; Ziebel, Johanna; Dommes, Jacques; Hoffmann, Lucien; Hausman, Jean-François; Renaut, Jenny

2009-01-01

A proteomic analysis of poplar leaves exposed to cadmium, combined with biochemical analysis of pigments and carbohydrates revealed changes in primary carbon metabolism. Proteomic results suggested that photosynthesis was slightly affected. Together with a growth inhibition, photoassimilates were less needed for developmental processes and could be stored in the form of hexoses or complex sugars, acting also as osmoprotectants. Simultaneously, mitochondrial respiration was upregulated, providing energy needs of cadmium-exposed plants.

Proteome profiling of early seed development in Cunninghamia lanceolata (Lamb.) Hook

PubMed Central

Shi, Jisen; Zhen, Yan; Zheng, Ren-Hua

2010-01-01

Knowledge of the proteome of the early gymnosperm embryo could provide important information for optimizing plant cloning procedures and for establishing platforms for research into plant development/regulation and in vitro transgenic studies. Compared with angiosperms, it is more difficult to induce somatic embryogenesis in gymnosperms; success in this endeavour could be increased, however, if proteomic information was available on the complex, dynamic, and multistage processes of gymnosperm embryogenesis in vivo. A proteomic analysis of Chinese fir seeds in six developmental stages was carried out during early embryogenesis. Proteins were extracted from seeds dissected from immature cones and separated by two-dimensional difference gel electrophoresis. Analysis with DeCyder 6.5 software revealed 136 spots that differed in kinetics of appearance. Analysis by liquid chromatography coupled to tandem mass spectrometry and MALDI-TOF mass spectrometry identified proteins represented by 71 of the spots. Functional annotation of these seed proteins revealed their involvement in programmed cell death and chromatin modification, indicating that the proteins may play a central role in determining the number of zygotic embryos generated and controlling embryo patterning and shape remodelling. The analysis also revealed other proteins involved in carbon metabolism, methionine metabolism, energy production, protein storage, synthesis and stabilization, disease/defence, the cytoskeleton, and embryo development. The comprehensive protein expression profiles generated by our study provide new insights into the complex developmental processes in the seeds of the Chinese fir. PMID:20363864

Composition Influences the Pathway but not the Outcome of the Metabolic Response of Bacterioplankton to Resource Shifts

PubMed Central

Comte, Jérôme; del Giorgio, Paul A.

2011-01-01

Bacterioplankton community metabolism is central to the functioning of aquatic ecosystems, and strongly reactive to changes in the environment, yet the processes underlying this response remain unclear. Here we explore the role that community composition plays in shaping the bacterial metabolic response to resource gradients that occur along aquatic ecotones in a complex watershed in Québec. Our results show that the response is mediated by complex shifts in community structure, and structural equation analysis confirmed two main pathways, one involving adjustments in the level of activity of existing phylotypes, and the other the replacement of the dominant phylotypes. These contrasting response pathways were not determined by the type or the intensity of the gradients involved, as we had hypothesized, but rather it would appear that some compositional configurations may be intrinsically more plastic than others. Our results suggest that community composition determines this overall level of community plasticity, but that composition itself may be driven by factors independent of the environmental gradients themselves, such that the response of bacterial communities to a given type of gradient may alternate between the adjustment and replacement pathways. We conclude that community composition influences the pathways of response in these bacterial communities, but not the metabolic outcome itself, which is driven by the environment, and which can be attained through multiple alternative configurations. PMID:21980410

The influence of a sports drink on the postexercise metabolism of elite athletes as investigated by NMR-based metabolomics.

PubMed

Miccheli, Alfredo; Marini, Federico; Capuani, Giorgio; Miccheli, Alberta Tomassini; Delfini, Maurizio; Di Cocco, Maria Enrica; Puccetti, Caterina; Paci, Maurizio; Rizzo, Marta; Spataro, Antonio

2009-10-01

The aim of this study is to evaluate the systemic effects of an isotonic sports drink on the metabolic status of athletes of the Italian Olympic rowing team during recovery after strenuous and prolonged physical exercise by means of nuclear magnetic resonance (NMR)-based metabolomics analysis on plasma and urine. Forty-four male athletes of the Italian Olympic rowing team were enrolled in a double-blind crossover study. All subjects underwent 2 evaluations at 1-week intervals. The evaluation was performed on a rowing ergometer after strenuous physical exercise to produce a state of dehydration. Afterward, the athletes were rehydrated either with a green tea-based carbohydrate-hydroelectrolyte drink or with oligomineral water. Three blood samples were drawn for each subject: at rest, after the exercise, and following rehydratation, while 2 urine samples were collected: at rest and after the rehydratation period. Biofluid samples were analyzed by high-resolution (1)H NMR metabolic profiling combined with multilevel simultaneous data-analysis (MSCA) and partial-least squares-discriminant analysis (PLS-DA). The between-subject variations, as evaluated by MSCA, reflected the variations of lactate levels induced by the physical exercise. Analysis of the within-individual variance using multilevel PLS-DA models of plasma and urine metabolic profiles showed an effect of the green tea-based sports drink on glucose, citrate, and lactate levels in plasma and on acetone, 3-OH-butyrate, and lactate levels in urine. The increase of caffeine and hippuric acid levels in urine indicated the absorption of green tea extract components. NMR-based metabolomics allowed the complex effects of a green tea extract-based carbohydrate/hydroelectrolyte beverage on the energy metabolism of athletes during recovery by postexercise rehydration to be evaluated.

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.

Redox homeostasis and respiratory metabolism in camels (Camelus dromedaries): comparisons with domestic goats and laboratory rats and mice.

PubMed

Al-Otaiba, Amna; John, Annie; Al-Belooshi, Thekra; Raza, Haider

2010-11-01

We have previously reported the occurrence of multiple forms of drug-metabolizing enzymes in camel tissues. Here, we investigate glutathione (GSH)-dependent redox homeostasis, reactive oxygen species (ROS) production and mitochondrial respiratory functions in camel tissues and compare them with imported domestic goats and laboratory rats and mice. Cytochrome P450 2E1 (CYP 2E1) and GSH-metabolizing enzymes were differentially expressed in the liver and kidney of these animals. Camel liver has significantly lower GSH pool than that in goats, rats and mice. Mitochondria isolated from the tissues of these animals showed a comparable ability to metabolize specific substrates for respiratory enzyme complexes I, II/III and IV. These complexes were metabolically more active in the kidney than in the liver of all the species. Furthermore, the activity of complex IV in camel tissues was significantly lower than in other species. On the other hand, complex II/III activity in camel kidney was higher compared to the other species. In addition, as expected, we observed that inhibitors of these enzyme complexes augment the production of mitochondrial ROS in camel and goat tissues. These results help to better understand the metabolic ability and adaptation in desert camels in comparison with domestic goats and laboratory rats and mice since they are exposed to different environmental and dietary conditions. Our study may also have implications in the pharmacology and toxicology of drugs and pollutants in these species.

Proteomics Analysis of Skeletal Muscle from Leptin-Deficient ob/ob Mice Reveals Adaptive Remodeling of Metabolic Characteristics and Fiber Type Composition.

PubMed

Schönke, Milena; Björnholm, Marie; Chibalin, Alexander V; Zierath, Juleen R; Deshmukh, Atul S

2018-03-01

Skeletal muscle insulin resistance, an early metabolic defect in the pathogenesis of type 2 diabetes (T2D), may be a cause or consequence of altered protein expression profiles. Proteomics technology offers enormous promise to investigate molecular mechanisms underlying pathologies, however, the analysis of skeletal muscle is challenging. Using state-of-the-art multienzyme digestion and filter-aided sample preparation (MED-FASP) and a mass spectrometry (MS)-based workflow, we performed a global proteomics analysis of skeletal muscle from leptin-deficient, obese, insulin resistant (ob/ob) and lean mice in mere two fractions in a short time (8 h per sample). We identified more than 6000 proteins with 118 proteins differentially regulated in obesity. This included protein kinases, phosphatases, and secreted and fiber type associated proteins. Enzymes involved in lipid metabolism in skeletal muscle from ob/ob mice were increased, providing evidence against reduced fatty acid oxidation in lipid-induced insulin resistance. Mitochondrial and peroxisomal proteins, as well as components of pyruvate and lactate metabolism, were increased. Finally, the skeletal muscle proteome from ob/ob mice displayed a shift toward the "slow fiber type." This detailed characterization of an obese rodent model of T2D demonstrates an efficient workflow for skeletal muscle proteomics, which may easily be adapted to other complex tissues. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Nutritional Lipidomics: Molecular Metabolism, Analytics, and Diagnostics

PubMed Central

Smilowitz, Jennifer T.; Zivkovic, Angela M.; Wan, Yu-Jui Yvonne; Watkins, Steve M.; Nording, Malin L.; Hammock, Bruce D.; German, J. Bruce

2013-01-01

The field of lipidomics is providing nutritional science a more comprehensive view of lipid intermediates. Lipidomics research takes advantage of the increase in accuracy and sensitivity of mass detection of mass spectrometry with new bioinformatics toolsets to characterize the structures and abundances of complex lipids. Yet, translating lipidomics to practice via nutritional interventions is still in its infancy. No single instrumentation platform is able to solve the varying analytical challenges of the different molecular lipid species. Biochemical pathways of lipid metabolism remain incomplete and the tools to map lipid compositional data to pathways are still being assembled. Biology itself is dauntingly complex and simply separating biological structures remains a key challenge to lipidomics. Nonetheless, the strategy of combining tandem analytical methods to perform the sensitive, high-throughput, quantitative and comprehensive analysis of lipid metabolites of very large numbers of molecules is poised to drive the field forward rapidly. Among the next steps for nutrition to understand the changes in structures, compositions and function of lipid biomolecules in response to diet is to describe their distribution within discrete functional compartments-lipoproteins. Additionally, lipidomics must tackle the task of assigning the functions of lipids as signaling molecules, nutrient sensors, and intermediates of metabolic pathways. PMID:23818328

LC–MS Proteomics Analysis of the Insulin/IGF-1-Deficient Caenorhabditis elegans daf-2(e1370) Mutant Reveals Extensive Restructuring of Intermediary Metabolism

PubMed Central

2015-01-01

The insulin/IGF-1 receptor is a major known determinant of dauer formation, stress resistance, longevity, and metabolism in Caenorhabditis elegans. In the past, whole-genome transcript profiling was used extensively to study differential gene expression in response to reduced insulin/IGF-1 signaling, including the expression levels of metabolism-associated genes. Taking advantage of the recent developments in quantitative liquid chromatography mass spectrometry (LC–MS)-based proteomics, we profiled the proteomic changes that occur in response to activation of the DAF-16 transcription factor in the germline-less glp-4(bn2);daf-2(e1370) receptor mutant. Strikingly, the daf-2 profile suggests extensive reorganization of intermediary metabolism, characterized by the upregulation of many core intermediary metabolic pathways. These include glycolysis/gluconeogenesis, glycogenesis, pentose phosphate cycle, citric acid cycle, glyoxylate shunt, fatty acid β-oxidation, one-carbon metabolism, propionate and tyrosine catabolism, and complexes I, II, III, and V of the electron transport chain. Interestingly, we found simultaneous activation of reciprocally regulated metabolic pathways, which is indicative of spatiotemporal coordination of energy metabolism and/or extensive post-translational regulation of these enzymes. This restructuring of daf-2 metabolism is reminiscent to that of hypometabolic dauers, allowing the efficient and economical utilization of internal nutrient reserves and possibly also shunting metabolites through alternative energy-generating pathways to sustain longevity. PMID:24555535

Ca2+-Citrate Uptake and Metabolism in Lactobacillus casei ATCC 334

PubMed Central

Mortera, Pablo; Pudlik, Agata; Magni, Christian; Alarcón, Sergio

2013-01-01

The putative citrate metabolic pathway in Lactobacillus casei ATCC 334 consists of the transporter CitH, a proton symporter of the citrate-divalent metal ion family of transporters CitMHS, citrate lyase, and the membrane-bound oxaloacetate decarboxylase complex OAD-ABDH. Resting cells of Lactobacillus casei ATCC 334 metabolized citrate in complex with Ca2+ and not as free citrate or the Mg2+-citrate complex, thereby identifying Ca2+-citrate as the substrate of the transporter CitH. The pathway was induced in the presence of Ca2+ and citrate during growth and repressed by the presence of glucose and of galactose, most likely by a carbon catabolite repression mechanism. The end products of Ca2+-citrate metabolism by resting cells of Lb. casei were pyruvate, acetate, and acetoin, demonstrating the activity of the membrane-bound oxaloacetate decarboxylase complex OAD-ABDH. Following pyruvate, the pathway splits into two branches. One branch is the classical citrate fermentation pathway producing acetoin by α-acetolactate synthase and α-acetolactate decarboxylase. The other branch yields acetate, for which the route is still obscure. Ca2+-citrate metabolism in a modified MRS medium lacking a carbohydrate did not significantly affect the growth characteristics, and generation of metabolic energy in the form of proton motive force (PMF) was not observed in resting cells. In contrast, carbohydrate/Ca2+-citrate cometabolism resulted in a higher biomass yield in batch culture. However, also with these cells, no generation of PMF was associated with Ca2+-citrate metabolism. It is concluded that citrate metabolism in Lb. casei is beneficial when it counteracts acidification by carbohydrate metabolism in later growth stages. PMID:23709502

Quantitative Proteomics Analysis of Streptomyces coelicolor Development Demonstrates That Onset of Secondary Metabolism Coincides with Hypha Differentiation*

PubMed Central

Manteca, Angel; Sanchez, Jesus; Jung, Hye R.; Schwämmle, Veit; Jensen, Ole N.

2010-01-01

Streptomyces species produce many clinically important secondary metabolites, including antibiotics and antitumorals. They have a complex developmental cycle, including programmed cell death phenomena, that makes this bacterium a multicellular prokaryotic model. There are two differentiated mycelial stages: an early compartmentalized vegetative mycelium (first mycelium) and a multinucleated reproductive mycelium (second mycelium) arising after programmed cell death processes. In the present study, we made a detailed proteomics analysis of the distinct developmental stages of solid confluent Streptomyces coelicolor cultures using iTRAQ (isobaric tags for relative and absolute quantitation) labeling and LC-MS/MS. A new experimental approach was developed to obtain homogeneous samples at each developmental stage (temporal protein analysis) and also to obtain membrane and cytosolic protein fractions (spatial protein analysis). A total of 345 proteins were quantified in two biological replicates. Comparative bioinformatics analyses revealed the switch from primary to secondary metabolism between the initial compartmentalized mycelium and the multinucleated hyphae. PMID:20224110

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 the NADPH requirements on the intracellular flux distribution. The two different approaches to the calculation of fluxes are compared and deviations in the results are discussed. Copyright 1998 John Wiley & Sons, Inc.

System-Level and Granger Network Analysis of Integrated Proteomic and Metabolomic Dynamics Identifies Key Points of Grape Berry Development at the Interface of Primary and Secondary Metabolism.

PubMed

Wang, Lei; Sun, Xiaoliang; Weiszmann, Jakob; Weckwerth, Wolfram

2017-01-01

Grapevine is a fruit crop with worldwide economic importance. The grape berry undergoes complex biochemical changes from fruit set until ripening. This ripening process and production processes define the wine quality. Thus, a thorough understanding of berry ripening is crucial for the prediction of wine quality. For a systemic analysis of grape berry development we applied mass spectrometry based platforms to analyse the metabolome and proteome of Early Campbell at 12 stages covering major developmental phases. Primary metabolites involved in central carbon metabolism, such as sugars, organic acids and amino acids together with various bioactive secondary metabolites like flavonols, flavan-3-ols and anthocyanins were annotated and quantified. At the same time, the proteomic analysis revealed the protein dynamics of the developing grape berries. Multivariate statistical analysis of the integrated metabolomic and proteomic dataset revealed the growth trajectory and corresponding metabolites and proteins contributing most to the specific developmental process. K-means clustering analysis revealed 12 highly specific clusters of co-regulated metabolites and proteins. Granger causality network analysis allowed for the identification of time-shift correlations between metabolite-metabolite, protein- protein and protein-metabolite pairs which is especially interesting for the understanding of developmental processes. The integration of metabolite and protein dynamics with their corresponding biochemical pathways revealed an energy-linked metabolism before veraison with high abundances of amino acids and accumulation of organic acids, followed by protein and secondary metabolite synthesis. Anthocyanins were strongly accumulated after veraison whereas other flavonoids were in higher abundance at early developmental stages and decreased during the grape berry developmental processes. A comparison of the anthocyanin profile of Early Campbell to other cultivars revealed similarities to Concord grape and indicates the strong effect of genetic background on metabolic partitioning in primary and secondary metabolism.

System-Level and Granger Network Analysis of Integrated Proteomic and Metabolomic Dynamics Identifies Key Points of Grape Berry Development at the Interface of Primary and Secondary Metabolism

PubMed Central

Wang, Lei; Sun, Xiaoliang; Weiszmann, Jakob; Weckwerth, Wolfram

2017-01-01

Grapevine is a fruit crop with worldwide economic importance. The grape berry undergoes complex biochemical changes from fruit set until ripening. This ripening process and production processes define the wine quality. Thus, a thorough understanding of berry ripening is crucial for the prediction of wine quality. For a systemic analysis of grape berry development we applied mass spectrometry based platforms to analyse the metabolome and proteome of Early Campbell at 12 stages covering major developmental phases. Primary metabolites involved in central carbon metabolism, such as sugars, organic acids and amino acids together with various bioactive secondary metabolites like flavonols, flavan-3-ols and anthocyanins were annotated and quantified. At the same time, the proteomic analysis revealed the protein dynamics of the developing grape berries. Multivariate statistical analysis of the integrated metabolomic and proteomic dataset revealed the growth trajectory and corresponding metabolites and proteins contributing most to the specific developmental process. K-means clustering analysis revealed 12 highly specific clusters of co-regulated metabolites and proteins. Granger causality network analysis allowed for the identification of time-shift correlations between metabolite-metabolite, protein- protein and protein-metabolite pairs which is especially interesting for the understanding of developmental processes. The integration of metabolite and protein dynamics with their corresponding biochemical pathways revealed an energy-linked metabolism before veraison with high abundances of amino acids and accumulation of organic acids, followed by protein and secondary metabolite synthesis. Anthocyanins were strongly accumulated after veraison whereas other flavonoids were in higher abundance at early developmental stages and decreased during the grape berry developmental processes. A comparison of the anthocyanin profile of Early Campbell to other cultivars revealed similarities to Concord grape and indicates the strong effect of genetic background on metabolic partitioning in primary and secondary metabolism. PMID:28713396

Quantifying interictal metabolic activity in human temporal lobe epilepsy

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

Henry, T.R.; Mazziotta, J.C.; Engel, J. Jr.

1990-09-01

The majority of patients with complex partial seizures of unilateral temporal lobe origin have interictal temporal hypometabolism on (18F)fluorodeoxyglucose positron emission tomography (FDG PET) studies. Often, this hypometabolism extends to ipsilateral extratemporal sites. The use of accurately quantified metabolic data has been limited by the absence of an equally reliable method of anatomical analysis of PET images. We developed a standardized method for visual placement of anatomically configured regions of interest on FDG PET studies, which is particularly adapted to the widespread, asymmetric, and often severe interictal metabolic alterations of temporal lobe epilepsy. This method was applied by a singlemore » investigator, who was blind to the identity of subjects, to 10 normal control and 25 interictal temporal lobe epilepsy studies. All subjects had normal brain anatomical volumes on structural neuroimaging studies. The results demonstrate ipsilateral thalamic and temporal lobe involvement in the interictal hypometabolism of unilateral temporal lobe epilepsy. Ipsilateral frontal, parietal, and basal ganglial metabolism is also reduced, although not as markedly as is temporal and thalamic metabolism.« less

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

SS-mPMG and SS-GA: tools for finding pathways and dynamic simulation of metabolic networks.

PubMed

Katsuragi, Tetsuo; Ono, Naoaki; Yasumoto, Keiichi; Altaf-Ul-Amin, Md; Hirai, Masami Y; Sriyudthsak, Kansuporn; Sawada, Yuji; Yamashita, Yui; Chiba, Yukako; Onouchi, Hitoshi; Fujiwara, Toru; Naito, Satoshi; Shiraishi, Fumihide; Kanaya, Shigehiko

2013-05-01

Metabolomics analysis tools can provide quantitative information on the concentration of metabolites in an organism. In this paper, we propose the minimum pathway model generator tool for simulating the dynamics of metabolite concentrations (SS-mPMG) and a tool for parameter estimation by genetic algorithm (SS-GA). SS-mPMG can extract a subsystem of the metabolic network from the genome-scale pathway maps to reduce the complexity of the simulation model and automatically construct a dynamic simulator to evaluate the experimentally observed behavior of metabolites. Using this tool, we show that stochastic simulation can reproduce experimentally observed dynamics of amino acid biosynthesis in Arabidopsis thaliana. In this simulation, SS-mPMG extracts the metabolic network subsystem from published databases. The parameters needed for the simulation are determined using a genetic algorithm to fit the simulation results to the experimental data. We expect that SS-mPMG and SS-GA will help researchers to create relevant metabolic networks and carry out simulations of metabolic reactions derived from metabolomics data.

The genome of Syntrophorhabdus aromaticivorans strain UI provides new insights for syntrophic aromatic compound metabolism and electron flow.

PubMed

Nobu, Masaru K; Narihiro, Takashi; Hideyuki, Tamaki; Qiu, Yan-Ling; Sekiguchi, Yuji; Woyke, Tanja; Goodwin, Lynne; Davenport, Karen W; Kamagata, Yoichi; Liu, Wen-Tso

2015-12-01

How aromatic compounds are degraded in various anaerobic ecosystems (e.g. groundwater, sediments, soils and wastewater) is currently poorly understood. Under methanogenic conditions (i.e. groundwater and wastewater treatment), syntrophic metabolizers are known to play an important role. This study explored the draft genome of Syntrophorhabdus aromaticivorans strain UI and identified the first syntrophic phenol-degrading phenylphosphate synthase (PpsAB) and phenylphosphate carboxylase (PpcABCD) and syntrophic terephthalate-degrading decarboxylase complexes. The strain UI genome also encodes benzoate degradation through hydration of the dienoyl-coenzyme A intermediate as observed in Geobacter metallireducens and Syntrophus aciditrophicus. Strain UI possesses electron transfer flavoproteins, hydrogenases and formate dehydrogenases essential for syntrophic metabolism. However, the biochemical mechanisms for electron transport between these H2 /formate-generating proteins and syntrophic substrate degradation remain unknown for many syntrophic metabolizers, including strain UI. Analysis of the strain UI genome revealed that heterodisulfide reductases (HdrABC), which are poorly understood electron transfer genes, may contribute to syntrophic H2 and formate generation. The genome analysis further identified a putative ion-translocating ferredoxin : NADH oxidoreductase (IfoAB) that may interact with HdrABC and dissimilatory sulfite reductase gamma subunit (DsrC) to perform novel electron transfer mechanisms associated with syntrophic metabolism. © 2014 Society for Applied Microbiology and John Wiley & Sons Ltd.

Computational identification of a new SelD-like family that may participate in sulfur metabolism in hyperthermophilic sulfur-reducing archaea.

PubMed

Li, Gao-Peng; Jiang, Liang; Ni, Jia-Zuan; Liu, Qiong; Zhang, Yan

2014-10-17

Selenium (Se) and sulfur (S) are closely related elements that exhibit similar chemical properties. Some genes related to S metabolism are also involved in Se utilization in many organisms. However, the evolutionary relationship between the two utilization traits is unclear. In this study, we conducted a comparative analysis of the selenophosphate synthetase (SelD) family, a key protein for all known Se utilization traits, in all sequenced archaea. Our search showed a very limited distribution of SelD and Se utilization in this kingdom. Interestingly, a SelD-like protein was detected in two orders of Crenarchaeota: Sulfolobales and Thermoproteales. Sequence and phylogenetic analyses revealed that SelD-like protein contains the same domain and conserved functional residues as those of SelD, and might be involved in S metabolism in these S-reducing organisms. Further genome-wide analysis of patterns of gene occurrence in different thermoproteales suggested that several genes, including SirA-like, Prx-like and adenylylsulfate reductase, were strongly related to SelD-like gene. Based on these findings, we proposed a simple model wherein SelD-like may play an important role in the biosynthesis of certain thiophosphate compound. Our data suggest novel genes involved in S metabolism in hyperthermophilic S-reducing archaea, and may provide a new window for understanding the complex relationship between Se and S metabolism in archaea.

Untargeted metabolomics unravels functionalities of phosphorylation sites in Saccharomyces cerevisiae.

PubMed

Raguz Nakic, Zrinka; Seisenbacher, Gerhard; Posas, Francesc; Sauer, Uwe

2016-11-15

Coordinated through a complex network of kinases and phosphatases, protein phosphorylation regulates essentially all cellular processes in eukaryotes. Recent advances in proteomics enable detection of thousands of phosphorylation sites (phosphosites) in single experiments. However, functionality of the vast majority of these sites remains unclear and we lack suitable approaches to evaluate functional relevance at a pace that matches their detection. Here, we assess functionality of 26 phosphosites by introducing phosphodeletion and phosphomimic mutations in 25 metabolic enzymes and regulators from the TOR and HOG signaling pathway in Saccharomyces cerevisiae by phenotypic analysis and untargeted metabolomics. We show that metabolomics largely outperforms growth analysis and recovers 10 out of the 13 previously characterized phosphosites and suggests functionality for several novel sites, including S79 on the TOR regulatory protein Tip41. We analyze metabolic profiles to identify consequences underlying regulatory phosphorylation events and detecting glycerol metabolism to have a so far unknown influence on arginine metabolism via phosphoregulation of the glycerol dehydrogenases. Further, we also find S508 in the MAPKK Pbs2 as a potential link for cross-talking between HOG signaling and the cell wall integrity pathway. We demonstrate that metabolic profiles can be exploited for gaining insight into regulatory consequences and biological roles of phosphosites. Altogether, untargeted metabolomics is a fast, sensitive and informative approach appropriate for future large-scale functional analyses of phosphosites.

Systems Biology of Industrial Microorganisms

NASA Astrophysics Data System (ADS)

Papini, Marta; Salazar, Margarita; Nielsen, Jens

The field of industrial biotechnology is expanding rapidly as the chemical industry is looking towards more sustainable production of chemicals that can be used as fuels or building blocks for production of solvents and materials. In connection with the development of sustainable bioprocesses, it is a major challenge to design and develop efficient cell factories that can ensure cost efficient conversion of the raw material into the chemical of interest. This is achieved through metabolic engineering, where the metabolism of the cell factory is engineered such that there is an efficient conversion of sugars, the typical raw materials in the fermentation industry, into the desired product. However, engineering of cellular metabolism is often challenging due to the complex regulation that has evolved in connection with adaptation of the different microorganisms to their ecological niches. In order to map these regulatory structures and further de-regulate them, as well as identify ingenious metabolic engineering strategies that full-fill mass balance constraints, tools from systems biology can be applied. This involves both high-throughput analysis tools like transcriptome, proteome and metabolome analysis, as well as the use of mathematical modeling to simulate the phenotypes resulting from the different metabolic engineering strategies. It is in fact expected that systems biology may substantially improve the process of cell factory development, and we therefore propose the term Industrial Systems Biology for how systems biology will enhance the development of industrial biotechnology for sustainable chemical production.

Systems biology of industrial microorganisms.

PubMed

Papini, Marta; Salazar, Margarita; Nielsen, Jens

2010-01-01

The field of industrial biotechnology is expanding rapidly as the chemical industry is looking towards more sustainable production of chemicals that can be used as fuels or building blocks for production of solvents and materials. In connection with the development of sustainable bioprocesses, it is a major challenge to design and develop efficient cell factories that can ensure cost efficient conversion of the raw material into the chemical of interest. This is achieved through metabolic engineering, where the metabolism of the cell factory is engineered such that there is an efficient conversion of sugars, the typical raw materials in the fermentation industry, into the desired product. However, engineering of cellular metabolism is often challenging due to the complex regulation that has evolved in connection with adaptation of the different microorganisms to their ecological niches. In order to map these regulatory structures and further de-regulate them, as well as identify ingenious metabolic engineering strategies that full-fill mass balance constraints, tools from systems biology can be applied. This involves both high-throughput analysis tools like transcriptome, proteome and metabolome analysis, as well as the use of mathematical modeling to simulate the phenotypes resulting from the different metabolic engineering strategies. It is in fact expected that systems biology may substantially improve the process of cell factory development, and we therefore propose the term Industrial Systems Biology for how systems biology will enhance the development of industrial biotechnology for sustainable chemical production.

Proteome- and transcriptome-driven reconstruction of the human myocyte metabolic network and its use for identification of markers for diabetes.

PubMed

Väremo, Leif; Scheele, Camilla; Broholm, Christa; Mardinoglu, Adil; Kampf, Caroline; Asplund, Anna; Nookaew, Intawat; Uhlén, Mathias; Pedersen, Bente Klarlund; Nielsen, Jens

2015-05-12

Skeletal myocytes are metabolically active and susceptible to insulin resistance and are thus implicated in type 2 diabetes (T2D). This complex disease involves systemic metabolic changes, and their elucidation at the systems level requires genome-wide data and biological networks. Genome-scale metabolic models (GEMs) provide a network context for the integration of high-throughput data. We generated myocyte-specific RNA-sequencing data and investigated their correlation with proteome data. These data were then used to reconstruct a comprehensive myocyte GEM. Next, we performed a meta-analysis of six studies comparing muscle transcription in T2D versus healthy subjects. Transcriptional changes were mapped on the myocyte GEM, revealing extensive transcriptional regulation in T2D, particularly around pyruvate oxidation, branched-chain amino acid catabolism, and tetrahydrofolate metabolism, connected through the downregulated dihydrolipoamide dehydrogenase. Strikingly, the gene signature underlying this metabolic regulation successfully classifies the disease state of individual samples, suggesting that regulation of these pathways is a ubiquitous feature of myocytes in response to T2D. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Interactions between Gut Microbiota, Host Genetics and Diet Modulate the Predisposition to Obesity and Metabolic Syndrome.

PubMed

Ussar, Siegfried; Griffin, Nicholas W; Bezy, Olivier; Fujisaka, Shiho; Vienberg, Sara; Softic, Samir; Deng, Luxue; Bry, Lynn; Gordon, Jeffrey I; Kahn, C Ronald

2015-09-01

Obesity, diabetes, and metabolic syndrome result from complex interactions between genetic and environmental factors, including the gut microbiota. To dissect these interactions, we utilized three commonly used inbred strains of mice-obesity/diabetes-prone C57Bl/6J mice, obesity/diabetes-resistant 129S1/SvImJ from Jackson Laboratory, and obesity-prone but diabetes-resistant 129S6/SvEvTac from Taconic-plus three derivative lines generated by breeding these strains in a new, common environment. Analysis of metabolic parameters and gut microbiota in all strains and their environmentally normalized derivatives revealed strong interactions between microbiota, diet, breeding site, and metabolic phenotype. Strain-dependent and strain-independent correlations were found between specific microbiota and phenotypes, some of which could be transferred to germ-free recipient animals by fecal transplantation. Environmental reprogramming of microbiota resulted in 129S6/SvEvTac becoming obesity resistant. Thus, development of obesity/metabolic syndrome is the result of interactions between gut microbiota, host genetics, and diet. In permissive genetic backgrounds, environmental reprograming of microbiota can ameliorate development of metabolic syndrome. Copyright © 2015 Elsevier Inc. All rights reserved.

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

1H NMR Spectroscopy and MVA Analysis of Diplodus sargus Eating the Exotic Pest Caulerpa cylindracea.

PubMed

De Pascali, Sandra A; Del Coco, Laura; Felline, Serena; Mollo, Ernesto; Terlizzi, Antonio; Fanizzi, Francesco P

2015-06-05

The green alga Caulerpa cylindracea is a non-autochthonous and invasive species that is severely affecting the native communities in the Mediterranean Sea. Recent researches show that the native edible fish Diplodus sargus actively feeds on this alga and cellular and physiological alterations have been related to the novel alimentary habits. The complex effects of such a trophic exposure to the invasive pest are still poorly understood. Here we report on the metabolic profiles of plasma from D. sargus individuals exposed to C. cylindracea along the southern Italian coast, using 1H NMR spectroscopy and multivariate analysis (Principal Component Analysis, PCA, Orthogonal Partial Least Square, PLS, and Orthogonal Partial Least Square Discriminant Analysis, OPLS-DA). Fish were sampled in two seasonal periods from three different locations, each characterized by a different degree of algal abundance. The levels of the algal bisindole alkaloid caulerpin, which is accumulated in the fish tissues, was used as an indicator of the trophic exposure to the seaweed and related to the plasma metabolic profiles. The profiles appeared clearly influenced by the sampling period beside the content of caulerpin, while the analyses also supported a moderate alteration of lipid and choline metabolism related to the Caulerpa-based diet.

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 knowledge will form the basis for the development of future metabolically engineered hyper-PHA-producing strains derived from the versatile bacterium P. putida KT2440.

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 critical sugar ratio that is known to allow galactose to enter the cell. Additionally, we report a number of fluxomic changes associated with these growth rate increases and unexpected flux profile redistributions resulting from deletion of SIP1 in glucose-only medium.« less

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 critical sugar ratio that is known to allow galactose to enter the cell. Additionally, we report a number of fluxomic changes associated with these growth rate increases and unexpected flux profile redistributions resulting from deletion of SIP1 in glucose-only medium.« less

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 sugar ratio that is known to allow galactose to enter the cell. Additionally, we report a number of fluxomic changes associated with these growth rate increases and unexpected flux profile redistributions resulting from deletion of SIP1 in glucose-only medium. PMID:28596955

Proteomic Analysis of the Relationship between Metabolism and Nonhost Resistance in Soybean Exposed to Bipolaris maydis.

PubMed

Dong, Yumei; Su, Yuan; Yu, Ping; Yang, Min; Zhu, Shusheng; Mei, Xinyue; He, Xiahong; Pan, Manhua; Zhu, Youyong; Li, Chengyun

2015-01-01

Nonhost resistance (NHR) pertains to the most common form of plant resistance against pathogenic microorganisms of other species. Bipolaris maydis is a non-adapted pathogen affecting soybeans, particularly of maize/soybean intercropping systems. However, no experimental evidence has described the immune response of soybeans against B. maydis. To elucidate the molecular mechanism underlying NHR in soybeans, proteomics analysis based on two-dimensional polyacrylamide gel electrophoresis (2-DE) was performed to identify proteins involved in the soybean response to B. maydis. The spread of B. maydis spores across soybean leaves induced NHR throughout the plant, which mobilized almost all organelles and various metabolic processes in response to B. maydis. Some enzymes, including ribulose-1,5-bisphosphate carboxylase/oxygenase (RuBisCO), mitochondrial processing peptidase (MPP), oxygen evolving enhancer (OEE), and nucleoside diphosphate kinase (NDKs), were found to be related to NHR in soybeans. These enzymes have been identified in previous studies, and STRING analysis showed that most of the protein functions related to major metabolic processes were induced as a response to B. maydis, which suggested an array of complex interactions between soybeans and B. maydis. These findings suggest a systematic NHR against non-adapted pathogens in soybeans. This response was characterized by an overlap between metabolic processes and response to stimulus. Several metabolic processes provide the soybean with innate immunity to the non-adapted pathogen, B. maydis. This research investigation on NHR in soybeans may foster a better understanding of plant innate immunity, as well as the interactions between plant and non-adapted pathogens in intercropping systems.

Proteomic Analysis of the Relationship between Metabolism and Nonhost Resistance in Soybean Exposed to Bipolaris maydis

PubMed Central

Dong, Yumei; Su, Yuan; Yu, Ping; Yang, Min; Zhu, Shusheng; Mei, Xinyue; He, Xiahong; Pan, Manhua; Zhu, Youyong; Li, Chengyun

2015-01-01

Nonhost resistance (NHR) pertains to the most common form of plant resistance against pathogenic microorganisms of other species. Bipolaris maydis is a non-adapted pathogen affecting soybeans, particularly of maize/soybean intercropping systems. However, no experimental evidence has described the immune response of soybeans against B. maydis. To elucidate the molecular mechanism underlying NHR in soybeans, proteomics analysis based on two-dimensional polyacrylamide gel electrophoresis (2-DE) was performed to identify proteins involved in the soybean response to B. maydis. The spread of B. maydis spores across soybean leaves induced NHR throughout the plant, which mobilized almost all organelles and various metabolic processes in response to B. maydis. Some enzymes, including ribulose-1,5-bisphosphate carboxylase/oxygenase (RuBisCO), mitochondrial processing peptidase (MPP), oxygen evolving enhancer (OEE), and nucleoside diphosphate kinase (NDKs), were found to be related to NHR in soybeans. These enzymes have been identified in previous studies, and STRING analysis showed that most of the protein functions related to major metabolic processes were induced as a response to B. maydis, which suggested an array of complex interactions between soybeans and B. maydis. These findings suggest a systematic NHR against non-adapted pathogens in soybeans. This response was characterized by an overlap between metabolic processes and response to stimulus. Several metabolic processes provide the soybean with innate immunity to the non-adapted pathogen, B. maydis. This research investigation on NHR in soybeans may foster a better understanding of plant innate immunity, as well as the interactions between plant and non-adapted pathogens in intercropping systems. PMID:26513657

ChloroKB: A Web Application for the Integration of Knowledge Related to Chloroplast Metabolic Network1[OPEN

PubMed Central

Gloaguen, Pauline; Alban, Claude; Ravanel, Stéphane; Seigneurin-Berny, Daphné; Matringe, Michel; Ferro, Myriam; Bruley, Christophe; Rolland, Norbert; Vandenbrouck, Yves

2017-01-01

Higher plants, as autotrophic organisms, are effective sources of molecules. They hold great promise for metabolic engineering, but the behavior of plant metabolism at the network level is still incompletely described. Although structural models (stoichiometry matrices) and pathway databases are extremely useful, they cannot describe the complexity of the metabolic context, and new tools are required to visually represent integrated biocurated knowledge for use by both humans and computers. Here, we describe ChloroKB, a Web application (http://chlorokb.fr/) for visual exploration and analysis of the Arabidopsis (Arabidopsis thaliana) metabolic network in the chloroplast and related cellular pathways. The network was manually reconstructed through extensive biocuration to provide transparent traceability of experimental data. Proteins and metabolites were placed in their biological context (spatial distribution within cells, connectivity in the network, participation in supramolecular complexes, and regulatory interactions) using CellDesigner software. The network contains 1,147 reviewed proteins (559 localized exclusively in plastids, 68 in at least one additional compartment, and 520 outside the plastid), 122 proteins awaiting biochemical/genetic characterization, and 228 proteins for which genes have not yet been identified. The visual presentation is intuitive and browsing is fluid, providing instant access to the graphical representation of integrated processes and to a wealth of refined qualitative and quantitative data. ChloroKB will be a significant support for structural and quantitative kinetic modeling, for biological reasoning, when comparing novel data with established knowledge, for computer analyses, and for educational purposes. ChloroKB will be enhanced by continuous updates following contributions from plant researchers. PMID:28442501

Using the principle of entropy maximization to infer genetic interaction networks from gene expression patterns

PubMed Central

Lezon, Timothy R.; Banavar, Jayanth R.; Cieplak, Marek; Maritan, Amos; Fedoroff, Nina V.

2006-01-01

We describe a method based on the principle of entropy maximization to identify the gene interaction network with the highest probability of giving rise to experimentally observed transcript profiles. In its simplest form, the method yields the pairwise gene interaction network, but it can also be extended to deduce higher-order interactions. Analysis of microarray data from genes in Saccharomyces cerevisiae chemostat cultures exhibiting energy metabolic oscillations identifies a gene interaction network that reflects the intracellular communication pathways that adjust cellular metabolic activity and cell division to the limiting nutrient conditions that trigger metabolic oscillations. The success of the present approach in extracting meaningful genetic connections suggests that the maximum entropy principle is a useful concept for understanding living systems, as it is for other complex, nonequilibrium systems. PMID:17138668

Genome-scale modelling of microbial metabolism with temporal and spatial resolution.

PubMed

Henson, Michael A

2015-12-01

Most natural microbial systems have evolved to function in environments with temporal and spatial variations. A major limitation to understanding such complex systems is the lack of mathematical modelling frameworks that connect the genomes of individual species and temporal and spatial variations in the environment to system behaviour. The goal of this review is to introduce the emerging field of spatiotemporal metabolic modelling based on genome-scale reconstructions of microbial metabolism. The extension of flux balance analysis (FBA) to account for both temporal and spatial variations in the environment is termed spatiotemporal FBA (SFBA). Following a brief overview of FBA and its established dynamic extension, the SFBA problem is introduced and recent progress is described. Three case studies are reviewed to illustrate the current state-of-the-art and possible future research directions are outlined. The author posits that SFBA is the next frontier for microbial metabolic modelling and a rapid increase in methods development and system applications is anticipated. © 2015 Authors; published by Portland Press Limited.

The metabolic sensor AKIN10 modulates the Arabidopsis circadian clock in a light-dependent manner.

PubMed

Shin, Jieun; Sánchez-Villarreal, Alfredo; Davis, Amanda M; Du, Shen-Xiu; Berendzen, Kenneth W; Koncz, Csaba; Ding, Zhaojun; Li, Cuiling; Davis, Seth J

2017-07-01

Plants generate rhythmic metabolism during the repetitive day/night cycle. The circadian clock produces internal biological rhythms to synchronize numerous metabolic processes such that they occur at the required time of day. Metabolism conversely influences clock function by controlling circadian period and phase and the expression of core-clock genes. Here, we show that AKIN10, a catalytic subunit of the evolutionarily conserved key energy sensor sucrose non-fermenting 1 (Snf1)-related kinase 1 (SnRK1) complex, plays an important role in the circadian clock. Elevated AKIN10 expression led to delayed peak expression of the circadian clock evening-element GIGANTEA (GI) under diurnal conditions. Moreover, it lengthened clock period specifically under light conditions. Genetic analysis showed that the clock regulator TIME FOR COFFEE (TIC) is required for this effect of AKIN10. Taken together, we propose that AKIN10 conditionally works in a circadian clock input pathway to the circadian oscillator. © 2017 John Wiley & Sons Ltd.

Transcriptomic and Proteomic Responses of Sweetpotato Whitefly, Bemisia tabaci, to Thiamethoxam

PubMed Central

Yang, Nina; Xie, Wen; Yang, Xin; Wang, Shaoli; Wu, Qingjun; Li, Rumei; Pan, Huipeng; Liu, Baiming; Shi, Xiaobin; Fang, Yong; Xu, Baoyun; Zhou, Xuguo; Zhang, Youjun

2013-01-01

Background The sweetpotato whitefly, Bemisia tabaci (Hemiptera: Aleyrodidae), is one of the most widely distributed agricultural pests. Although it has developed resistance to many registered insecticides including the neonicotinoid insecticide thiamethoxam, the mechanisms that regulate the resistance are poorly understood. To understand the molecular basis of thiamethoxam resistance, “omics” analyses were carried out to examine differences between resistant and susceptible B. tabaci at both transcriptional and translational levels. Results A total of 1,338 mRNAs and 52 proteins were differentially expressed between resistant and susceptible B. tabaci. Among them, 11 transcripts had concurrent transcription and translation profiles. KEGG analysis mapped 318 and 35 differentially expressed genes and proteins, respectively, to 160 and 59 pathways (p<0.05). Thiamethoxam treatment activated metabolic pathways (e.g., drug metabolism), in which 118 transcripts were putatively linked to insecticide resistance, including up-regulated glutathione-S-transferase, UDP glucuronosyltransferase, glucosyl/glucuronosyl transferase, and cytochrome P450. Gene Ontology analysis placed these genes and proteins into protein complex, metabolic process, cellular process, signaling, and response to stimulus categories. Quantitative real-time PCR analysis validated “omics” response, and suggested a highly overexpressed P450, CYP6CX1, as a candidate molecular basis for the mechanistic study of thiamethoxam resistance in whiteflies. Finally, enzymatic activity assays showed elevated detoxification activities in the resistant B. tabaci. Conclusions This study demonstrates the applicability of high-throughput omics tools for identifying molecular candidates related to thiamethoxam resistance in an agricultural important insect pest. In addition, transcriptomic and proteomic analyses provide a solid foundation for future functional investigations into the complex molecular mechanisms governing the neonicotinoid resistance in whiteflies. PMID:23671574

Respiratory Pathways Reconstructed by Multi-Omics Analysis in Melioribacter roseus, Residing in a Deep Thermal Aquifer of the West-Siberian Megabasin

PubMed Central

Gavrilov, Sergey; Podosokorskaya, Olga; Alexeev, Dmitry; Merkel, Alexander; Khomyakova, Maria; Muntyan, Maria; Altukhov, Ilya; Butenko, Ivan; Bonch-Osmolovskaya, Elizaveta; Govorun, Vadim; Kublanov, Ilya

2017-01-01

Melioribacter roseus, a representative of recently proposed Ignavibacteriae phylum, is a metabolically versatile thermophilic bacterium, inhabiting subsurface biosphere of the West-Siberian megabasin and capable of growing on various substrates and electron acceptors. Genomic analysis followed by inhibitor studies and membrane potential measurements of aerobically grown M. roseus cells revealed the activity of aerobic respiratory electron transfer chain comprised of respiratory complexes I and IV, and an alternative complex III. Phylogeny reconstruction revealed that oxygen reductases belonged to atypical cc(o/b)o3-type and canonical cbb3–type cytochrome oxidases. Also, two molybdoenzymes of M. roseus were affiliated either with Ttr or Psr/Phs clades, but not with typical respiratory arsenate reductases of the Arr clade. Expression profiling, both at transcripts and protein level, allowed us to assign the role of the terminal respiratory oxidase under atmospheric oxygen concentration for the cc(o/b)o3 cytochrome oxidase, previously proposed to serve for oxygen detoxification only. Transcriptomic analysis revealed the involvement of both molybdoenzymes of M. roseus in As(V) respiration, yet differences in the genomic context of their gene clusters allow to hypothesize about their distinct roles in arsenate metabolism with the ‘Psr/Phs’-type molybdoenzyme being the most probable candidate respiratory arsenate reductase. Basing on multi-omics data, the pathways for aerobic and arsenate respiration were proposed. Our results start to bridge the vigorously increasing gap between homology-based predictions and experimentally verified metabolic processes, what is especially important for understudied microorganisms of novel lineages from deep subsurface environments of Eurasia, which remained separated from the rest of the biosphere for several geological periods. PMID:28713355

Deciphering the Magainin Resistance Process of Escherichia coli Strains in Light of the Cytosolic Proteome

PubMed Central

Maria-Neto, Simone; Cândido, Elizabete de Souza; Rodrigues, Diana Ribas; de Sousa, Daniel Amaro; da Silva, Ezequiel Marcelino; de Moraes, Lidia Maria Pepe; Otero-Gonzalez, Anselmo de Jesus; Magalhães, Beatriz Simas; Dias, Simoni Campos

2012-01-01

Antimicrobial peptides (AMPs) are effective antibiotic agents commonly found in plants, animals, and microorganisms, and they have been suggested as the future of antimicrobial chemotherapies. It is vital to understand the molecular details that define the mechanism of action of resistance to AMPs for a rational planning of the next antibiotic generation and also to shed some light on the complex AMP mechanism of action. Here, the antibiotic resistance of Escherichia coli ATCC 8739 to magainin I was evaluated in the cytosolic subproteome. Magainin-resistant strains were selected after 10 subsequent spreads at subinhibitory concentrations of magainin I (37.5 mg · liter−1), and their cytosolic proteomes were further compared to those of magainin-susceptible strains through two-dimensional electrophoresis analysis. As a result, 41 differentially expressed proteins were detected by in silico analysis and further identified by tandem mass spectrometry de novo sequencing. Functional categorization indicated an intense metabolic response mainly in energy and nitrogen uptake, stress response, amino acid conversion, and cell wall thickness. Indeed, data reported here show that resistance to cationic antimicrobial peptides possesses a greater molecular complexity than previously supposed, resulting in cell commitment to several metabolic pathways. PMID:22290970

Response to dietary L-glutamine supplementation in weaned piglets: a serum metabolomic comparison and hepatic metabolic regulation analysis.

PubMed

Xiao, Y P; Wu, T X; Sun, J M; Yang, L; Hong, Q H; Chen, A G; Yang, C M

2012-12-01

A novel metabolomic method based on gas chromatography-mass spectrometry was applied to investigate serum metabolites in response to dietary Gln supplementation in piglets. Sixteen, 21-d-old pigs were weaned and assigned randomly to 2 isonitrogenous diets: 1) Gln diet, which contained 1% L-Gln (as-fed basis), and 2) control diet, which contained L-Ala to make this diet isonitrogenous with the Gln diet. Serum samples were collected to characterize metabolites after a 30-d treatment. in addition, 4 liver samples per treatment were collected to examine enzyme activity and gene expression involved in metabolic regulation. Results indicated that 12 metabolites were altered (P < 0.05) by Gln treatment, including carbohydrates, AA, and fatty acids. A leave-one-out cross validation of random forest analysis indicated that Pro was most important among the 12 metabolites. Thus, these data demonstrate that the control and Gln-supplemented pigs differed (P < 0.05) in terms of metabolism of carbohydrates, Pro, Tyr, and glycerophospholipids. Principal component analysis yielded separate clusters of profiles between the Gln and control groups. Metabolic enzyme activities of Ala aminotransferase and hexokinase increased by 26.8% (P = 0.026) and 26.2% (P = 0.004) in the liver of Gln-supplemented pigs vs. control, respectively, whereas pyruvate kinase (PK) activity decreased by 29.1% (P = 0.001). The gene expression of PK in the liver decreased by 66.1% (P = 0.034) by Gln treatment for 30 d. No differences were observed for the mRNA abundance of mammalian target of rapamycin and PPARγ. On the basis of these data, Gln treatment affected carbohydrate, lipid, and AA metabolism in the whole body of the early weaned piglets. These findings provide insight into specific metabolic pathways and lay the groundwork for the complex metabolic alteration in response to dietary Gln supplementation of pigs.

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 rational bioreactor design and in the development of novel culture media for hESC maintenance and expansion. PMID:25412279

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.

Metabolic imaging for breast cancer detection and treatment: a role for mitochondrial Complex I function

NASA Astrophysics Data System (ADS)

Ramanujan, V. Krishnan

2018-02-01

Cancer cells are known to display a variety of metabolic reprogramming strategies to fulfill their own growth and proliferative agenda. With the advent of high resolution imaging strategies, metabolomics techniques etc., there is an increasing appreciation of critical role that tumor cell metabolism plays in the overall breast cancer (BC) growth. A recent study from our laboratory demonstrated that the development of invasive cancers could be causally connected to deficits in mitochondrial function. Using this study as a rationale, we hypothesize that the widely accepted multistep tumor growth model might have a strong metabolic component as well. In this study, we explore the possibility of targeting mitochondrial Complex I enzyme system for not only metabolic detection of cancer-associated redox changes but also for modulating breast cancer cell growth characteristics. As a proof-of-principle, we demonstrate two approaches (pharmacological and genetic) for modulating mitochondrial Complex I function so as to achieve breast cancer control.

Towards the Fecal Metabolome Derived from Moderate Red Wine Intake

PubMed Central

Jiménez-Girón, Ana; Muñoz-González, Irene; Martín-Álvarez, Pedro J.; Moreno-Arribas, María Victoria; Bartolomé, Begoña

2014-01-01

Dietary polyphenols, including red wine phenolic compounds, are extensively metabolized during their passage through the gastrointestinal tract; and their biological effects at the gut level (i.e., anti-inflammatory activity, microbiota modulation, interaction with cells, among others) seem to be due more to their microbial-derived metabolites rather than to the original forms found in food. In an effort to improve our understanding of the biological effects that phenolic compounds exert at the gut level, this paper summarizes the changes observed in the human fecal metabolome after an intervention study consisting of a daily consumption of 250 mL of wine during four weeks by healthy volunteers (n = 33). It assembles data from two analytical approaches: (1) UPLC-ESI-MS/MS analysis of phenolic metabolites in fecal solutions (targeted analysis); and (2) UHPLC-TOF MS analysis of the fecal solutions (non-targeted analysis). Both approaches revealed statistically-significant changes in the concentration of several metabolites as a consequence of the wine intake. Similarity and complementarity between targeted and non-targeted approaches in the analysis of the fecal metabolome are discussed. Both strategies allowed the definition of a complex metabolic profile derived from wine intake. Likewise, the identification of endogenous markers could lead to new hypotheses to unravel the relationship between moderate wine consumption and the metabolic functionality of gut microbiota. PMID:25532710

Dynamics of Marine Microbial Metabolism and Physiology at Station ALOHA

NASA Astrophysics Data System (ADS)

Casey, John R.

Marine microbial communities influence global biogeochemical cycles by coupling the transduction of free energy to the transformation of Earth's essential bio-elements: H, C, N, O, P, and S. The web of interactions between these processes is extraordinarily complex, though fundamental physical and thermodynamic principles should describe its dynamics. In this collection of 5 studies, aspects of the complexity of marine microbial metabolism and physiology were investigated as they interact with biogeochemical cycles and direct the flow of energy within the Station ALOHA surface layer microbial community. In Chapter 1, and at the broadest level of complexity discussed, a method to relate cell size to metabolic activity was developed to evaluate allometric power laws at fine scales within picoplankton populations. Although size was predictive of metabolic rates, within-population power laws deviated from the broader size spectrum, suggesting metabolic diversity as a key determinant of microbial activity. In Chapter 2, a set of guidelines was proposed by which organic substrates are selected and utilized by the heterotrophic community based on their nitrogen content, carbon content, and energy content. A hierarchical experimental design suggested that the heterotrophic microbial community prefers high nitrogen content but low energy density substrates, while carbon content was not important. In Chapter 3, a closer look at the light-dependent dynamics of growth on a single organic substrate, glycolate, suggested that growth yields were improved by photoheterotrophy. The remaining chapters were based on the development of a genome-scale metabolic network reconstruction of the cyanobacterium Prochlorococcus to probe its metabolic capabilities and quantify metabolic fluxes. Findings described in Chapter 4 pointed to evolution of the Prochlorococcus metabolic network to optimize growth at low phosphate concentrations. Finally, in Chapter 5 and at the finest scale of complexity, a method was developed to predict hourly changes in both physiology and metabolic fluxes in Prochlorococcus by incorporating gene expression time-series data within the metabolic network model. Growth rates predicted by this method more closely matched experimental data, and diel changes in elemental composition and the energy content of biomass were predicted. Collectively, these studies identify and quantify the potential impact of variations in metabolic and physiological traits on the melee of microbial community interactions.

Computational Modeling of Human Metabolism and Its Application to Systems Biomedicine.

PubMed

Aurich, Maike K; Thiele, Ines

2016-01-01

Modern high-throughput techniques offer immense opportunities to investigate whole-systems behavior, such as those underlying human diseases. However, the complexity of the data presents challenges in interpretation, and new avenues are needed to address the complexity of both diseases and data. Constraint-based modeling is one formalism applied in systems biology. It relies on a genome-scale reconstruction that captures extensive biochemical knowledge regarding an organism. The human genome-scale metabolic reconstruction is increasingly used to understand normal cellular and disease states because metabolism is an important factor in many human diseases. The application of human genome-scale reconstruction ranges from mere querying of the model as a knowledge base to studies that take advantage of the model's topology and, most notably, to functional predictions based on cell- and condition-specific metabolic models built based on omics data.An increasing number and diversity of biomedical questions are being addressed using constraint-based modeling and metabolic models. One of the most successful biomedical applications to date is cancer metabolism, but constraint-based modeling also holds great potential for inborn errors of metabolism or obesity. In addition, it offers great prospects for individualized approaches to diagnostics and the design of disease prevention and intervention strategies. Metabolic models support this endeavor by providing easy access to complex high-throughput datasets. Personalized metabolic models have been introduced. Finally, constraint-based modeling can be used to model whole-body metabolism, which will enable the elucidation of metabolic interactions between organs and disturbances of these interactions as either causes or consequence of metabolic diseases. This chapter introduces constraint-based modeling and describes some of its contributions to systems biomedicine.

Metabolic flexibility of mitochondrial respiratory chain disorders predicted by computer modelling.

PubMed

Zieliński, Łukasz P; Smith, Anthony C; Smith, Alexander G; Robinson, Alan J

2016-11-01

Mitochondrial respiratory chain dysfunction causes a variety of life-threatening diseases affecting about 1 in 4300 adults. These diseases are genetically heterogeneous, but have the same outcome; reduced activity of mitochondrial respiratory chain complexes causing decreased ATP production and potentially toxic accumulation of metabolites. Severity and tissue specificity of these effects varies between patients by unknown mechanisms and treatment options are limited. So far most research has focused on the complexes themselves, and the impact on overall cellular metabolism is largely unclear. To illustrate how computer modelling can be used to better understand the potential impact of these disorders and inspire new research directions and treatments, we simulated them using a computer model of human cardiomyocyte mitochondrial metabolism containing over 300 characterised reactions and transport steps with experimental parameters taken from the literature. Overall, simulations were consistent with patient symptoms, supporting their biological and medical significance. These simulations predicted: complex I deficiencies could be compensated using multiple pathways; complex II deficiencies had less metabolic flexibility due to impacting both the TCA cycle and the respiratory chain; and complex III and IV deficiencies caused greatest decreases in ATP production with metabolic consequences that parallel hypoxia. Our study demonstrates how results from computer models can be compared to a clinical phenotype and used as a tool for hypothesis generation for subsequent experimental testing. These simulations can enhance understanding of dysfunctional mitochondrial metabolism and suggest new avenues for research into treatment of mitochondrial disease and other areas of mitochondrial dysfunction. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Convergent Metabolic Specialization through Distinct Evolutionary Paths in Pseudomonas aeruginosa.

PubMed

La Rosa, Ruggero; Johansen, Helle Krogh; Molin, Søren

2018-04-10

Evolution by natural selection under complex and dynamic environmental conditions occurs through intricate and often counterintuitive trajectories affecting many genes and metabolic solutions. To study short- and long-term evolution of bacteria in vivo , we used the natural model system of cystic fibrosis (CF) infection. In this work, we investigated how and through which trajectories evolution of Pseudomonas aeruginosa occurs when migrating from the environment to the airways of CF patients, and specifically, we determined reduction of growth rate and metabolic specialization as signatures of adaptive evolution. We show that central metabolic pathways of three distinct Pseudomonas aeruginosa lineages coevolving within the same environment become restructured at the cost of versatility during long-term colonization. Cell physiology changes from naive to adapted phenotypes resulted in (i) alteration of growth potential that particularly converged to a slow-growth phenotype, (ii) alteration of nutritional requirements due to auxotrophy, (iii) tailored preference for carbon source assimilation from CF sputum, (iv) reduced arginine and pyruvate fermentation processes, and (v) increased oxygen requirements. Interestingly, although convergence was evidenced at the phenotypic level of metabolic specialization, comparative genomics disclosed diverse mutational patterns underlying the different evolutionary trajectories. Therefore, distinct combinations of genetic and regulatory changes converge to common metabolic adaptive trajectories leading to within-host metabolic specialization. This study gives new insight into bacterial metabolic evolution during long-term colonization of a new environmental niche. IMPORTANCE Only a few examples of real-time evolutionary investigations in environments outside the laboratory are described in the scientific literature. Remembering that biological evolution, as it has progressed in nature, has not taken place in test tubes, it is not surprising that conclusions from our investigations of bacterial evolution in the CF model system are different from what has been concluded from laboratory experiments. The analysis presented here of the metabolic and regulatory driving forces leading to successful adaptation to a new environment provides an important insight into the role of metabolism and its regulatory mechanisms for successful adaptation of microorganisms in dynamic and complex environments. Understanding the trajectories of adaptation, as well as the mechanisms behind slow growth and rewiring of regulatory and metabolic networks, is a key element to understand the adaptive robustness and evolvability of bacteria in the process of increasing their in vivo fitness when conquering new territories. Copyright © 2018 La Rosa et al.

Different exogenous sugars affect the hormone signal pathway and sugar metabolism in "Red Globe" (Vitis vinifera L.) plantlets grown in vitro as shown by transcriptomic analysis.

PubMed

Mao, Juan; Li, Wenfang; Mi, Baoqin; Dawuda, Mohammed Mujitaba; Calderón-Urrea, Alejandro; Ma, Zonghuan; Zhang, Yongmei; Chen, Baihong

2017-09-01

Exogenously applied 2% fructose is the most appropriate carbon source that enhances photosynthesis and growth of grape plantlets compared with the same concentrations of sucrose and glucose. The role of the sugars was regulated by the expression of key candidate genes related to hormones, key metabolic enzymes, and sugar metabolism of grape plantlets ( Vitis vinifera L.) grown in vitro. The addition of sugars including sucrose, glucose, and fructose is known to be very helpful for the development of grape (V. vinifera L.) plantlets in vitro. However, the mechanisms by which these sugars regulate plant development and sugar metabolism are poorly understood. In grape plantlets, sugar metabolism and hormone synthesis undergo special regulation. In the present study, transcriptomic analyses were performed on grape (V. vinifera L., cv. Red Globe) plantlets in an in vitro system, in which the plantlets were grown in 2% each of sucrose (S20), glucose (G20), and fructose (F20). The sugar metabolism and hormone synthesis of the plantlets were analyzed. In addition, 95.72-97.29% high-quality 125 bp reads were further analyzed out of which 52.65-60.80% were mapped to exonic regions, 13.13-28.38% to intronic regions, and 11.59-28.99% to intergenic regions. The F20, G20, and S20 displayed elevated sucrose synthase (SS) activities; relative chlorophyll contents; Rubisco activity; and IAA and zeatin (ZT) contents. We found F20 improved the growth and development of the plantlets better than G20 and S20. Sugar metabolism was a complex process, which depended on the balanced expression of key potential candidate genes related to hormones (TCP15, LOG3, IPT3, ETR1, HK2, HK3, CKX7, SPY, GH3s, MYBH, AGB1, MKK2, PP2C, PYL, ABF, SnRK, etc.), key metabolic enzymes (SUS, SPS, A/V-INV, and G6PDH), and sugar metabolism (BETAFRUCT4 and AMY). Moreover, sugar and starch metabolism controls the generation of plant hormone transduction pathway signaling molecules. Our dataset advances our knowledge of the genes involved in sugar metabolism and improves the understanding of complex regulatory networks involved in signal transduction in grape plantlets.

Reprogramming of leukemic cell metabolism through the naphthoquinonic compound Quambalarine B

PubMed Central

Vališ, Karel; Grobárová, Valéria; Hernychová, Lucie; Bugáňová, Martina; Kavan, Daniel; Kalous, Martin; Černý, Jiří; Stodůlková, Eva; Kuzma, Marek; Flieger, Miroslav; Černý, Jan; Novák, Petr

2017-01-01

Abnormalities in cancer metabolism represent potential targets for cancer therapy. We have recently identified a natural compound Quambalarine B (QB), which inhibits proliferation of several leukemic cell lines followed by cell death. We have predicted ubiquinone binding sites of mitochondrial respiratory complexes as potential molecular targets of QB in leukemia cells. Hence, we tracked the effect of QB on leukemia metabolism by applying several omics and biochemical techniques. We have confirmed the inhibition of respiratory complexes by QB and found an increase in the intracellular AMP levels together with respiratory substrates. Inhibition of mitochondrial respiration by QB triggered reprogramming of leukemic cell metabolism involving disproportions in glycolytic flux, inhibition of proteins O-glycosylation, stimulation of glycine synthesis pathway, and pyruvate kinase activity, followed by an increase in pyruvate and a decrease in lactate levels. Inhibition of mitochondrial complex I by QB suppressed folate metabolism as determined by a decrease in formate production. We have also observed an increase in cellular levels of several amino acids except for aspartate, indicating the dependence of Jurkat (T-ALL) cells on aspartate synthesis. These results indicate blockade of mitochondrial complex I and II activity by QB and reduction in aspartate and folate metabolism as therapeutic targets in T-ALL cells. Anti-cancer activity of QB was also confirmed during in vivo studies, suggesting the therapeutic potential of this natural compound. PMID:29262552

A novel regulatory defect in the branched-chain α-keto acid dehydrogenase complex due to a mutation in the PPM1K gene causes a mild variant phenotype of maple syrup urine disease.

PubMed

Oyarzabal, Alfonso; Martínez-Pardo, Mercedes; Merinero, Begoña; Navarrete, Rosa; Desviat, Lourdes R; Ugarte, Magdalena; Rodríguez-Pombo, Pilar

2013-02-01

This article describes a hitherto unreported involvement of the phosphatase PP2Cm, a recently described member of the branched-chain α-keto acid dehydrogenase (BCKDH) complex, in maple syrup urine disease (MSUD). The disease-causing mutation was identified in a patient with a mild variant phenotype, involving a gene not previously associated with MSUD. SNP array-based genotyping showed a copy-neutral homozygous pattern for chromosome 4 compatible with uniparental isodisomy. Mutation analysis of the candidate gene, PPM1K, revealed a homozygous c.417_418delTA change predicted to result in a truncated, unstable protein. No PP2Cm mutant protein was detected in immunocytochemical or Western blot expression analyses. The transient expression of wild-type PPM1K in PP2Cm-deficient fibroblasts recovered 35% of normal BCKDH activity. As PP2Cm has been described essential for cell survival, apoptosis and metabolism, the impact of its deficiency on specific metabolic stress variables was evaluated in PP2Cm-deficient fibroblasts. Increases were seen in ROS levels along with the activation of specific stress-signaling MAP kinases. Similar to that described for the pyruvate dehydrogenase complex, a defect in the regulation of BCKDH caused the aberrant metabolism of its substrate, contributing to the patient's MSUD phenotype--and perhaps others. © 2012 WILEY PERIODICALS, INC.

Syntrophic exchange in synthetic microbial communities

PubMed Central

Mee, Michael T.; Collins, James J.; Church, George M.; Wang, Harris H.

2014-01-01

Metabolic crossfeeding is an important process that can broadly shape microbial communities. However, little is known about specific crossfeeding principles that drive the formation and maintenance of individuals within a mixed population. Here, we devised a series of synthetic syntrophic communities to probe the complex interactions underlying metabolic exchange of amino acids. We experimentally analyzed multimember, multidimensional communities of Escherichia coli of increasing sophistication to assess the outcomes of synergistic crossfeeding. We find that biosynthetically costly amino acids including methionine, lysine, isoleucine, arginine, and aromatics, tend to promote stronger cooperative interactions than amino acids that are cheaper to produce. Furthermore, cells that share common intermediates along branching pathways yielded more synergistic growth, but exhibited many instances of both positive and negative epistasis when these interactions scaled to higher dimensions. In more complex communities, we find certain members exhibiting keystone species-like behavior that drastically impact the community dynamics. Based on comparative genomic analysis of >6,000 sequenced bacteria from diverse environments, we present evidence suggesting that amino acid biosynthesis has been broadly optimized to reduce individual metabolic burden in favor of enhanced crossfeeding to support synergistic growth across the biosphere. These results improve our basic understanding of microbial syntrophy while also highlighting the utility and limitations of current modeling approaches to describe the dynamic complexities underlying microbial ecosystems. This work sets the foundation for future endeavors to resolve key questions in microbial ecology and evolution, and presents a platform to develop better and more robust engineered synthetic communities for industrial biotechnology. PMID:24778240

The role of Pyruvate Dehydrogenase Complex in cardiovascular diseases.

PubMed

Sun, Wanqing; Liu, Quan; Leng, Jiyan; Zheng, Yang; Li, Ji

2015-01-15

The regulation of mammalian myocardial carbohydrate metabolism is complex; many factors such as arterial substrate and hormone levels, coronary flow, inotropic state and the nutritional status of the tissue play a role in regulating mammalian myocardial carbohydrate metabolism. The Pyruvate Dehydrogenase Complex (PDHc), a mitochondrial matrix multienzyme complex, plays an important role in energy homeostasis in the heart by providing the link between glycolysis and the tricarboxylic acid (TCA) cycle. In TCA cycle, PDHc catalyzes the conversion of pyruvate into acetyl-CoA. This review determines that there is altered cardiac glucose in various pathophysiological states consequently causing PDC to be altered. This review further summarizes evidence for the metabolism mechanism of the heart under normal and pathological conditions including ischemia, diabetes, hypertrophy and heart failure. Copyright © 2014 Elsevier Inc. All rights reserved.

Data Curation and Visualization for MuSIASEM Analysis of the Nexus

NASA Astrophysics Data System (ADS)

Renner, Ansel

2017-04-01

A novel software-based approach to relational analysis applying recent theoretical advancements of the Multi-Scale Integrated Analysis of Societal and Ecosystem Metabolism (MuSIASEM) accounting framework is presented. This research explores and explains underutilized ways software can assist complex system analysis across the stages of data collection, exploration, analysis and dissemination and in a transparent and collaborative manner. This work is being conducted as part of, and in support of, the four-year European Commission H2020 project: Moving Towards Adaptive Governance in Complexity: Informing Nexus Security (MAGIC). In MAGIC, theoretical advancements to MuSIASEM propose a powerful new approach to spatial-temporal WEFC relational analysis in accordance with a structural-functional scaling mechanism appropriate for biophysically relevant complex system analyses. Software is designed primarily with JavaScript using the Angular2 model-view-controller framework and the Data-Driven Documents (D3) library. These design choices clarify and modularize data flow, simplify research practitioner's work, allow for and assist stakeholder involvement and advance collaboration at all stages. Data requirements and scalable, robust yet light-weight structuring will first be explained. Following, algorithms to process this data will be explored. Data interfaces and data visualization approaches will lastly be presented and described.

[What is the contribution of Stewart's concept in acid-base disorders analysis?].

PubMed

Quintard, H; Hubert, S; Ichai, C

2007-05-01

To explain the different approaches for interpreting acid-base disorders; to develop the Stewart model which offers some advantages for the pathophysiological understanding and the clinical interpretation of acid-base imbalances. Record of french and english references from Medline data base. The keywords were: acid-base balance, hyperchloremic acidosis, metabolic acidosis, strong ion difference, strong ion gap. Data were selected including prospective and retrospective studies, reviews, and case reports. Acid-base disorders are commonly analysed by using the traditional Henderson-Hasselbalch approach which attributes the variations in plasma pH to the modifications in plasma bicarbonates or PaCO2. However, this approach seems to be inadequate because bicarbonates and PaCO2 are completely dependent. Moreover, it does not consider the role of weak acids such as albuminate, in the determination of plasma pH value. According to the Stewart concept, plasma pH results from the degree of plasma water dissociation which is determined by 3 independent variables: 1) strong ion difference (SID) which is the difference between all the strong plasma cations and anions; 2) quantity of plasma weak acids; 3) PaCO2. Thus, metabolic acid-base disorders are always induced by a variation in SID (decreased in acidosis) or in weak acids (increased in acidosis), whereas respiratory disorders remains the consequence of a change in PaCO2. These pathophysiological considerations are important to analyse complex acid-base imbalances in critically ill patients. For example, due to a decrease in weak acids, hypoalbuminemia increases SID which may counter-balance a decrease in pH and an elevated anion gap. Thus if using only traditional tools, hypoalbuminemia may mask a metabolic acidosis, because of a normal pH and a normal anion gap. In this case, the association of metabolic acidosis and alkalosis is only expressed by respectively a decreased SID and a decreased weak acids concentration. This concept allows to establish the relationship between hyperchloremic acidosis and infusion of solutes which contain large concentration of chloride such as NaCl 0.9%. Finally, the Stewart concept permits to understand that sodium bicarbonate as well as sodium lactate induces plasma alkalinization. In fact, sodium remains in plasma, whereas anion (lactate or bicarbonate) are metabolized leading to an increase in plasma SID. Due to its simplicity, the traditional Henderson-Hasselbalch approach of acid-base disorders, remains commonly used. However, it gives an inadequate pathophysiological analysis which may conduct to a false diagnosis, especially with complex acid-base imbalances. Despite its apparent complexity, the Stewart concept permits to understand precisely the mechanisms of acid-base disorders. It has to become the most appropriate approach to analyse complex acid-base abnormalities.

Metagenomic Analysis of Genes Encoding Nutrient Cycling Pathways in the Microbiota of Deep-Sea and Shallow-Water Sponges.

PubMed

Li, Zhiyong; Wang, Yuezhu; Li, Jinlong; Liu, Fang; He, Liming; He, Ying; Wang, Shenyue

2016-12-01

Sponges host complex symbiotic communities, but to date, the whole picture of the metabolic potential of sponge microbiota remains unclear, particularly the difference between the shallow-water and deep-sea sponge holobionts. In this study, two completely different sponges, shallow-water sponge Theonella swinhoei from the South China Sea and deep-sea sponge Neamphius huxleyi from the Indian Ocean, were selected to compare their whole symbiotic communities and metabolic potential, particularly in element transformation. Phylogenetically diverse bacteria, archaea, fungi, and algae were detected in both shallow-water sponge T. swinhoei and deep-sea sponge N. huxleyi, and different microbial community structures were indicated between these two sponges. Metagenome-based gene abundance analysis indicated that, though the two sponge microbiota have similar core functions, they showed different potential strategies in detailed metabolic processes, e.g., in the transformation and utilization of carbon, nitrogen, phosphorus, and sulfur by corresponding microbial symbionts. This study provides insight into the putative metabolic potentials of the microbiota associated with the shallow-water and deep-sea sponges at the whole community level, extending our knowledge of the sponge microbiota's functions, the association of sponge- microbes, as well as the adaption of sponge microbiota to the marine environment.

The post-transcriptional regulatory system CSR controls the balance of metabolic pools in upper glycolysis of Escherichia coli.

PubMed

Morin, Manon; Ropers, Delphine; Letisse, Fabien; Laguerre, Sandrine; Portais, Jean-Charles; Cocaign-Bousquet, Muriel; Enjalbert, Brice

2016-05-01

Metabolic control in Escherichia coli is a complex process involving multilevel regulatory systems but the involvement of post-transcriptional regulation is uncertain. The post-transcriptional factor CsrA is stated as being the only regulator essential for the use of glycolytic substrates. A dozen enzymes in the central carbon metabolism (CCM) have been reported as potentially controlled by CsrA, but its impact on the CCM functioning has not been demonstrated. Here, a multiscale analysis was performed in a wild-type strain and its isogenic mutant attenuated for CsrA (including growth parameters, gene expression levels, metabolite pools, abundance of enzymes and fluxes). Data integration and regulation analysis showed a coordinated control of the expression of glycolytic enzymes. This also revealed the imbalance of metabolite pools in the csrA mutant upper glycolysis, before the phosphofructokinase PfkA step. This imbalance is associated with a glucose-phosphate stress. Restoring PfkA activity in the csrA mutant strain suppressed this stress and increased the mutant growth rate on glucose. Thus, the carbon storage regulator system is essential for the effective functioning of the upper glycolysis mainly through its control of PfkA. This work demonstrates the pivotal role of post-transcriptional regulation to shape the carbon metabolism. © 2016 John Wiley & Sons Ltd.

Catalytic function of the mycobacterial binuclear iron monooxygenase in acetone metabolism.

PubMed

Furuya, Toshiki; Nakao, Tomomi; Kino, Kuniki

2015-10-01

Mycobacteria such as Mycobacterium smegmatis strain mc(2)155 and Mycobacterium goodii strain 12523 are able to grow on acetone and use it as a source of carbon and energy. We previously demonstrated by gene deletion analysis that the mimABCD gene cluster, which encodes a binuclear iron monooxygenase, plays an essential role in acetone metabolism in these mycobacteria. In the present study, we determined the catalytic function of MimABCD in acetone metabolism. Whole-cell assays were performed using Escherichia coli cells expressing the MimABCD complex. When the recombinant E. coli cells were incubated with acetone, a product was detected by gas chromatography (GC) analysis. Based on the retention time and the gas chromatography-mass spectrometry (GC-MS) spectrum, the reaction product was identified as acetol (hydroxyacetone). The recombinant E. coli cells produced 1.02 mM of acetol from acetone within 24 h. Furthermore, we demonstrated that MimABCD also was able to convert methylethylketone (2-butanone) to 1-hydroxy-2-butanone. Although it has long been known that microorganisms such as mycobacteria metabolize acetone via acetol, this study provides the first biochemical evidence for the existence of a microbial enzyme that catalyses the conversion of acetone to acetol. © FEMS 2015. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Metabolite signatures of exercise training in human skeletal muscle relate to mitochondrial remodelling and cardiometabolic fitness

PubMed Central

Huffman, Kim M.; Koves, Timothy R.; Hubal, Monica J.; Abouassi, Hiba; Beri, Nina; Bateman, Lori A.; Stevens, Robert D.; Ilkayeva, Olga R.; Hoffman, Eric P.; Muoio, Deborah M.; Kraus, William E.

2014-01-01

Aims/hypothesis Targeted metabolomic and transcriptomic approaches were used to evaluate the relationship between skeletal muscle metabolite signatures, gene expression profiles and clinical outcomes in response to various exercise training interventions. We hypothesised that changes in mitochondrial metabolic intermediates would predict improvements in clinical risk factors, thereby offering novel insights into potential mechanisms. Methods Subjects at risk of metabolic disease were randomised to six months of inactivity or one of five aerobic and/or resistance training programmes (n = 112). Pre/post-intervention assessments included cardiorespiratory fitness (V̇O2peak), serum triacylglycerols (TGs) and insulin sensitivity (SI). In this secondary analysis, muscle biopsy specimens were used for targeted mass spectrometry-based analysis of metabolic intermediates and measurement of mRNA expression of genes involved in metabolism. Results Exercise regimens with the largest energy expenditure produced robust increases in muscle concentrations of even-chain acylcarnitines (median 37–488%), which correlated positively with increased expression of genes involved in muscle uptake and oxidation of fatty acids. Along with free carnitine, the aforementioned acylcarnitine metabolites were related to improvements in V̇O2peak, TGs and SI (R = 0.20–0.31, p < 0.05). Muscle concentrations of the tricarboxylic acid cycle intermediates succinate and succinylcarnitine (R = 0.39 and 0.24, p < 0.05) emerged as the strongest correlates of SI. Conclusions/interpretation The metabolic signatures of exercise-trained skeletal muscle reflected reprogramming of mitochondrial function and intermediary metabolism and correlated with changes in cardiometabolic fitness. Succinate metabolism and the succinate dehydrogenase complex emerged as a potential regulatory node that intersects with whole-body insulin sensitivity. This study identifies new avenues for mechanistic research aimed at understanding the health benefits of physical activity. Trial registration ClinicalTrials.gov NCT00200993 and NCT00275145 PMID:25091629

Where systems biology meets postharvest

USDA-ARS?s Scientific Manuscript database

Interpreting fruit metabolism, particularly tree fruit metabolism, presents unique challenges. Long periods from tree establishment to fruiting render techniques directed towards reducing the complexity of metabolic mechanisms, such as genomic modification, relatively difficult. Consequently, holi...

Anaerobic Formate and Hydrogen Metabolism.

PubMed

Pinske, Constanze; Sawers, R Gary

2016-10-01

Numerous recent developments in the biochemistry, molecular biology, and physiology of formate and H2 metabolism and of the [NiFe]-hydrogenase (Hyd) cofactor biosynthetic machinery are highlighted. Formate export and import by the aquaporin-like pentameric formate channel FocA is governed by interaction with pyruvate formate-lyase, the enzyme that generates formate. Formate is disproportionated by the reversible formate hydrogenlyase (FHL) complex, which has been isolated, allowing biochemical dissection of evolutionary parallels with complex I of the respiratory chain. A recently identified sulfido-ligand attached to Mo in the active site of formate dehydrogenases led to the proposal of a modified catalytic mechanism. Structural analysis of the homologous, H2-oxidizing Hyd-1 and Hyd-5 identified a novel proximal [4Fe-3S] cluster in the small subunit involved in conferring oxygen tolerance to the enzymes. Synthesis of Salmonella Typhimurium Hyd-5 occurs aerobically, which is novel for an enterobacterial Hyd. The O2-sensitive Hyd-2 enzyme has been shown to be reversible: it presumably acts as a conformational proton pump in the H2-oxidizing mode and is capable of coupling reverse electron transport to drive H2 release. The structural characterization of all the Hyp maturation proteins has given new impulse to studies on the biosynthesis of the Fe(CN)2CO moiety of the [NiFe] cofactor. It is synthesized on a Hyp-scaffold complex, mainly comprising HypC and HypD, before insertion into the apo-large subunit. Finally, clear evidence now exists indicating that Escherichia coli can mature Hyd enzymes differentially, depending on metal ion availability and the prevailing metabolic state. Notably, Hyd-3 of the FHL complex takes precedence over the H2-oxidizing enzymes.

A hierarchical model of metabolic machinery based on the kcore decomposition of plant metabolic networks.

PubMed

Filho, Humberto A; Machicao, Jeaneth; Bruno, Odemir M

2018-01-01

Modeling the basic structure of metabolic machinery is a challenge for modern biology. Some models based on complex networks have provided important information regarding this machinery. In this paper, we constructed metabolic networks of 17 plants covering unicellular organisms to more complex dicotyledonous plants. The metabolic networks were built based on the substrate-product model and a topological percolation was performed using the kcore decomposition. The distribution of metabolites across the percolation layers showed correlations between the metabolic integration hierarchy and the network topology. We show that metabolites concentrated in the internal network (maximum kcore) only comprise molecules of the primary basal metabolism. Moreover, we found a high proportion of a set of common metabolites, among the 17 plants, centered at the inner kcore layers. Meanwhile, the metabolites recognized as participants in the secondary metabolism of plants are concentrated in the outermost layers of the network. This data suggests that the metabolites in the central layer form a basic molecular module in which the whole plant metabolism is anchored. The elements from this central core participate in almost all plant metabolic reactions, which suggests that plant metabolic networks follows a centralized topology.

A hierarchical model of metabolic machinery based on the kcore decomposition of plant metabolic networks

PubMed Central

Filho, Humberto A.; Machicao, Jeaneth

2018-01-01

Modeling the basic structure of metabolic machinery is a challenge for modern biology. Some models based on complex networks have provided important information regarding this machinery. In this paper, we constructed metabolic networks of 17 plants covering unicellular organisms to more complex dicotyledonous plants. The metabolic networks were built based on the substrate-product model and a topological percolation was performed using the kcore decomposition. The distribution of metabolites across the percolation layers showed correlations between the metabolic integration hierarchy and the network topology. We show that metabolites concentrated in the internal network (maximum kcore) only comprise molecules of the primary basal metabolism. Moreover, we found a high proportion of a set of common metabolites, among the 17 plants, centered at the inner kcore layers. Meanwhile, the metabolites recognized as participants in the secondary metabolism of plants are concentrated in the outermost layers of the network. This data suggests that the metabolites in the central layer form a basic molecular module in which the whole plant metabolism is anchored. The elements from this central core participate in almost all plant metabolic reactions, which suggests that plant metabolic networks follows a centralized topology. PMID:29734359

Gout and Metabolic Syndrome: a Tangled Web.

PubMed

Thottam, Gabrielle E; Krasnokutsky, Svetlana; Pillinger, Michael H

2017-08-26

The complexity of gout continues to unravel with each new investigation. Gout sits at the intersection of multiple intrinsically complex processes, and its prevalence, impact on healthcare costs, and association with important co-morbidities make it increasingly relevant. The association between gout and type 2 diabetes, hypertension, hyperlipidemia, cardiovascular disease, renal disease, and obesity suggest that either gout, or its necessary precursor hyperuricemia, may play an important role in the manifestations of the metabolic syndrome. In this review, we analyze the complex interconnections between gout and metabolic syndrome, by reviewing gout's physiologic and epidemiologic relationships with its major co-morbidities. Increasing evidence supports gout's association with metabolic syndrome. More specifically, both human studies and animal models suggest that hyperuricemia may play a role in promoting inflammation, hypertension and cardiovascular disease, adipogenesis and lipogenesis, insulin and glucose dysregulation, and liver disease. Fructose ingestion is associated with increased rates of hypertension, weight gain, impaired glucose tolerance, and dyslipidemia and is a key driver of urate biosynthesis. AMP kinase (AMPK) is a central regulator of processes that tend to mitigate against the metabolic syndrome. Within hepatocytes, leukocytes, and other cells, a fructose/urate metabolic loop drives key inhibitors of AMPK, including AMP deaminase and fructokinase, that may tilt the balance toward metabolic syndrome progression. Preliminary evidence suggests that agents that block the intracellular synthesis of urate may restore AMPK activity and help maintain metabolic homeostasis. Gout is both an inflammatory and a metabolic disease. With further investigation of urate's role, the possibility of proper gout management additionally mitigating metabolic syndrome is an evolving and important question.

Sustained Axenic Metabolic Activity by the Obligate Intracellular Bacterium Coxiella burnetii▿ †

PubMed Central

Omsland, Anders; Cockrell, Diane C.; Fischer, Elizabeth R.; Heinzen, Robert A.

2008-01-01

Growth of Coxiella burnetii, the agent of Q fever, is strictly limited to colonization of a viable eukaryotic host cell. Following infection, the pathogen replicates exclusively in an acidified (pH 4.5 to 5) phagolysosome-like parasitophorous vacuole. Axenic (host cell free) buffers have been described that activate C. burnetii metabolism in vitro, but metabolism is short-lived, with bacterial protein synthesis halting after a few hours. Here, we describe a complex axenic medium that supports sustained (>24 h) C. burnetii metabolic activity. As an initial step in medium development, several biological buffers (pH 4.5) were screened for C. burnetii metabolic permissiveness. Based on [35S]Cys-Met incorporation, C. burnetii displayed optimal metabolic activity in citrate buffer. To compensate for C. burnetii auxotrophies and other potential metabolic deficiencies, we developed a citrate buffer-based medium termed complex Coxiella medium (CCM) that contains a mixture of three complex nutrient sources (neopeptone, fetal bovine serum, and RPMI cell culture medium). Optimal C. burnetii metabolism occurred in CCM with a high chloride concentration (140 mM) while the concentrations of sodium and potassium had little effect on metabolism. CCM supported prolonged de novo protein and ATP synthesis by C. burnetii (>24 h). Moreover, C. burnetii morphological differentiation was induced in CCM as determined by the transition from small-cell variant to large-cell variant. The sustained in vitro metabolic activity of C. burnetii in CCM provides an important tool to investigate the physiology of this organism including developmental transitions and responses to antimicrobial factors associated with the host cell. PMID:18310349

Alteration in metabolic signature and lipid metabolism in patients with angina pectoris and myocardial infarction.

PubMed

Park, Ju Yeon; Lee, Sang-Hak; Shin, Min-Jeong; Hwang, Geum-Sook

2015-01-01

Lipid metabolites are indispensable regulators of physiological and pathological processes, including atherosclerosis and coronary artery disease (CAD). However, the complex changes in lipid metabolites and metabolism that occur in patients with these conditions are incompletely understood. We performed lipid profiling to identify alterations in lipid metabolism in patients with angina and myocardial infarction (MI). Global lipid profiling was applied to serum samples from patients with CAD (angina and MI) and age-, sex-, and body mass index-matched healthy subjects using ultra-performance liquid chromatography/quadruple time-of-flight mass spectrometry and multivariate statistical analysis. A multivariate analysis showed a clear separation between the patients with CAD and normal controls. Lysophosphatidylcholine (lysoPC) and lysophosphatidylethanolamine (lysoPE) species containing unsaturated fatty acids and free fatty acids were associated with an increased risk of CAD, whereas species of lysoPC and lyso-alkyl PC containing saturated fatty acids were associated with a decreased risk. Additionally, PC species containing palmitic acid, diacylglycerol, sphingomyelin, and ceramide were associated with an increased risk of MI, whereas PE-plasmalogen and phosphatidylinositol species were associated with a decreased risk. In MI patients, we found strong positive correlation between lipid metabolites related to the sphingolipid pathway, sphingomyelin, and ceramide and acute inflammatory markers (high-sensitivity C-reactive protein). The results of this study demonstrate altered signatures in lipid metabolism in patients with angina or MI. Lipidomic profiling could provide the information to identity the specific lipid metabolites under the presence of disturbed metabolic pathways in patients with CAD.

Relationships of Leaf Net Photosynthesis, Stomatal Conductance, and Mesophyll Conductance to Primary Metabolism: A Multispecies Meta-Analysis Approach1

PubMed Central

Gago, Jorge; Daloso, Danilo de Menezes; Flexas, Jaume; Fernie, Alisdair Robert

2016-01-01

Plant metabolism drives plant development and plant-environment responses, and data readouts from this cellular level could provide insights in the underlying molecular processes. Existing studies have already related key in vivo leaf gas-exchange parameters with structural traits and nutrient components across multiple species. However, insights in the relationships of leaf gas-exchange with leaf primary metabolism are still limited. We investigated these relationships through a multispecies meta-analysis approach based on data sets from 17 published studies describing net photosynthesis (A) and stomatal (gs) and mesophyll (gm) conductances, alongside the 53 data profiles from primary metabolism of 14 species grown in different experiments. Modeling results highlighted the conserved patterns between the different species. Consideration of species-specific effects increased the explanatory power of the models for some metabolites, including Glc-6-P, Fru-6-P, malate, fumarate, Xyl, and ribose. Significant relationships of A with sugars and phosphorylated intermediates were observed. While gs was related to sugars, organic acids, myo-inositol, and shikimate, gm showed a more complex pattern in comparison to the two other traits. Some metabolites, such as malate and Man, appeared in the models for both conductances, suggesting a metabolic coregulation between gs and gm. The resulting statistical models provide the first hints for coregulation patterns involving primary metabolism plus leaf water and carbon balances that are conserved across plant species, as well as species-specific trends that can be used to determine new biotechnological targets for crop improvement. PMID:26977088

Exercise-driven metabolic pathways in healthy cartilage.

PubMed

Blazek, A D; Nam, J; Gupta, R; Pradhan, M; Perera, P; Weisleder, N L; Hewett, T E; Chaudhari, A M; Lee, B S; Leblebicioglu, B; Butterfield, T A; Agarwal, S

2016-07-01

Exercise is vital for maintaining cartilage integrity in healthy joints. Here we examined the exercise-driven transcriptional regulation of genes in healthy rat articular cartilage to dissect the metabolic pathways responsible for the potential benefits of exercise. Transcriptome-wide gene expression in the articular cartilage of healthy Sprague-Dawley female rats exercised daily (low intensity treadmill walking) for 2, 5, or 15 days was compared to that of non-exercised rats, using Affymetrix GeneChip arrays. Database for Annotation, Visualization and Integrated Discovery (DAVID) was used for Gene Ontology (GO)-term enrichment and Functional Annotation analysis of differentially expressed genes (DEGs). Kyoto Encyclopedia of Genes and Genome (KEGG) pathway mapper was used to identify the metabolic pathways regulated by exercise. Microarray analysis revealed that exercise-induced 644 DEGs in healthy articular cartilage. The DAVID bioinformatics tool demonstrated high prevalence of functional annotation clusters with greater enrichment scores and GO-terms associated with extracellular matrix (ECM) biosynthesis/remodeling and inflammation/immune response. The KEGG database revealed that exercise regulates 147 metabolic pathways representing molecular interaction networks for Metabolism, Genetic Information Processing, Environmental Information Processing, Cellular Processes, Organismal Systems, and Diseases. These pathways collectively supported the complex regulation of the beneficial effects of exercise on the cartilage. Overall, the findings highlight that exercise is a robust transcriptional regulator of a wide array of metabolic pathways in healthy cartilage. The major actions of exercise involve ECM biosynthesis/cartilage strengthening and attenuation of inflammatory pathways to provide prophylaxis against onset of arthritic diseases in healthy cartilage. Copyright © 2016 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved.

Decoding the dynamics of cellular metabolism and the action of 3-bromopyruvate and 2-deoxyglucose using pulsed stable isotope-resolved metabolomics.

PubMed

Pietzke, Matthias; Zasada, Christin; Mudrich, Susann; Kempa, Stefan

2014-01-01

Cellular metabolism is highly dynamic and continuously adjusts to the physiological program of the cell. The regulation of metabolism appears at all biological levels: (post-) transcriptional, (post-) translational, and allosteric. This regulatory information is expressed in the metabolome, but in a complex manner. To decode such complex information, new methods are needed in order to facilitate dynamic metabolic characterization at high resolution. Here, we describe pulsed stable isotope-resolved metabolomics (pSIRM) as a tool for the dynamic metabolic characterization of cellular metabolism. We have adapted gas chromatography-coupled mass spectrometric methods for metabolomic profiling and stable isotope-resolved metabolomics. In addition, we have improved robustness and reproducibility and implemented a strategy for the absolute quantification of metabolites. By way of examples, we have applied this methodology to characterize central carbon metabolism of a panel of cancer cell lines and to determine the mode of metabolic inhibition of glycolytic inhibitors in times ranging from minutes to hours. Using pSIRM, we observed that 2-deoxyglucose is a metabolic inhibitor, but does not directly act on the glycolytic cascade.

LC-MS Proteomics Analysis of the Insulin/IGF-1 Deficient Caenorhabditis elegans daf-2(e1370) Mutant Reveals Extensive Restructuring of Intermediary Metabolism

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

Depuydt, Geert G.; Xie, Fang; Petyuk, Vladislav A.

2014-02-20

The insulin/IGF-1 receptor is a major known determinant of dauer formation, stress resistance, longevity and metabolism in C. elegans. In the past, whole-genome transcript profiling was used extensively to study differential gene expression in response to reduced insulin/IGF-1 signaling, including expression levels of metabolism-associated genes. Taking advantage of the recent developments in quantitative liquid chromatography mass-spectrometry (LC-MS) based proteomics, we profiled the proteomic changes that occur in response to activation of the DAF-16 transcription factor in the germline-less glp-4(bn2); daf-2(e1370) receptor mutant. Strikingly, the daf-2 profile suggests extensive reorganization of intermediary metabolism, characterized by the up-regulation of many core intermediarymore » metabolic pathways. These include, glycolysis/gluconeogenesis, glycogenesis, pentose phosphate cycle, citric acid cycle, glyoxylate shunt, fatty acid β-oxidation, one-carbon metabolism, propionate and tyrosine catabolism, and complex I, II, III and V of the electron transport chain. Interestingly, we found simultaneous activation of reciprocally regulated metabolic pathways, which is indicative for spatio-temporal coordination of energy metabolism and/or extensive post-translational regulation of these enzymes. This restructuring of daf-2 metabolism is reminiscent to that of hypometabolic dauers, allowing the efficient and economical utilization of internal nutrient reserves, possibly also shunting metabolites through alternative energy-generating pathways, in order to sustain longevity.« less

LC–MS Proteomics Analysis of the Insulin/IGF-1-Deficient Caenorhabditis elegans daf-2(e1370) Mutant Reveals Extensive Restructuring of Intermediary Metabolism

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

Depuydt, Geert; Xie, Fang; Petyuk, Vladislav A.

2014-04-04

The insulin/IGF-1 receptor is a major known determinant of dauer formation, stress resistance, longevity, and metabolism in Caenorhabditis elegans. In the past, whole-genome transcript profiling was used extensively to study differential gene expression in response to reduced insulin/IGF-1 signaling, including the expression levels of metabolism-associated genes. Taking advantage of the recent developments in quantitative liquid chromatography mass spectrometry (LC–MS)-based proteomics, we profiled the proteomic changes that occur in response to activation of the DAF-16 transcription factor in the germline-less glp-4(bn2);daf-2(e1370) receptor mutant. Strikingly, the daf-2 profile suggests extensive reorganization of intermediary metabolism, characterized by the upregulation of many core intermediarymore » metabolic pathways. These include glycolysis/gluconeogenesis, glycogenesis, pentose phosphate cycle, citric acid cycle, glyoxylate shunt, fatty acid β-oxidation, one-carbon metabolism, propionate and tyrosine catabolism, and complexes I, II, III, and V of the electron transport chain. Interestingly, we found simultaneous activation of reciprocally regulated metabolic pathways, which is indicative of spatiotemporal coordination of energy metabolism and/or extensive post-translational regulation of these enzymes. Finally, this restructuring of daf-2 metabolism is reminiscent to that of hypometabolic dauers, allowing the efficient and economical utilization of internal nutrient reserves and possibly also shunting metabolites through alternative energy-generating pathways to sustain longevity.« less

A systems biology approach toward understanding seed composition in soybean.

PubMed

Li, Ling; Hur, Manhoi; Lee, Joon-Yong; Zhou, Wenxu; Song, Zhihong; Ransom, Nick; Demirkale, Cumhur Yusuf; Nettleton, Dan; Westgate, Mark; Arendsee, Zebulun; Iyer, Vidya; Shanks, Jackie; Nikolau, Basil; Wurtele, Eve Syrkin

2015-01-01

The molecular, biochemical, and genetic mechanisms that regulate the complex metabolic network of soybean seed development determine the ultimate balance of protein, lipid, and carbohydrate stored in the mature seed. Many of the genes and metabolites that participate in seed metabolism are unknown or poorly defined; even more remains to be understood about the regulation of their metabolic networks. A global omics analysis can provide insights into the regulation of seed metabolism, even without a priori assumptions about the structure of these networks. With the future goal of predictive biology in mind, we have combined metabolomics, transcriptomics, and metabolic flux technologies to reveal the global developmental and metabolic networks that determine the structure and composition of the mature soybean seed. We have coupled this global approach with interactive bioinformatics and statistical analyses to gain insights into the biochemical programs that determine soybean seed composition. For this purpose, we used Plant/Eukaryotic and Microbial Metabolomics Systems Resource (PMR, http://www.metnetdb.org/pmr, a platform that incorporates metabolomics data to develop hypotheses concerning the organization and regulation of metabolic networks, and MetNet systems biology tools http://www.metnetdb.org for plant omics data, a framework to enable interactive visualization of metabolic and regulatory networks. This combination of high-throughput experimental data and bioinformatics analyses has revealed sets of specific genes, genetic perturbations and mechanisms, and metabolic changes that are associated with the developmental variation in soybean seed composition. Researchers can explore these metabolomics and transcriptomics data interactively at PMR.

Are there mild and serious metabolic syndromes? The need for a graded diagnosis.

PubMed

Cicero, Arrigo F G; Derosa, Giuseppe

2014-10-01

Metabolic syndrome is an increasingly incident complex metabolic disorder, affecting around 30% of adults in the USA as well as in Europe. In a meta-analysis that evaluated cardiovascular risk associated with the third National Cholesterol Education Program definition of metabolic syndrome in 951 083 patients, metabolic syndrome was associated with a two-fold increase in the risk of coronary heart disease, cerebrovascular disease, all cardiovascular lethal and nonlethal cardiovascular diseases, and a 1.5-fold increase in the risk of all-cause mortality.In this context, the article in this issue of the Journal of Cardiovascular Medicine further stresses the concept that a 'full' metabolic syndrome, including all or almost all its potential components, is associated with an earlier and more serious organ damage, at both cardiac and vascular levels, than the standard definition of metabolic syndrome on the basis of the presence of three out of five components. Moreover, it confirms the central role of waist circumference as the main metabolic syndrome component associated with early organ damage in the enrolled patients, in whom increased waist circumference could be considered as the clinical phenotype of insulin resistance. These data are relevant because they stress the need for a further definition of metabolic syndrome on the basis of its main clinical characteristics (i.e. insulin-resistance/central obesity) and a fix constellation of associated factors (i.e. mild hypertension, atherogenic dyslipidemia) in order to clearly identify those individuals needing a more aggressive diagnostic and therapeutic approach.

Regulation of Primary Metabolism in Response to Low Oxygen Availability as Revealed by Carbon and Nitrogen Isotope Redistribution.

PubMed

António, Carla; Päpke, Carola; Rocha, Marcio; Diab, Houssein; Limami, Anis M; Obata, Toshihiro; Fernie, Alisdair R; van Dongen, Joost T

2016-01-01

Based on enzyme activity assays and metabolic responses to waterlogging of the legume Lotus japonicus, it was previously suggested that, during hypoxia, the tricarboxylic acid cycle switches to a noncyclic operation mode. Hypotheses were postulated to explain the alternative metabolic pathways involved, but as yet, a direct analysis of the relative redistribution of label through the corresponding pathways was not made. Here, we describe the use of stable isotope-labeling experiments for studying metabolism under hypoxia using wild-type roots of the crop legume soybean (Glycine max). [(13)C]Pyruvate labeling was performed to compare metabolism through the tricarboxylic acid cycle, fermentation, alanine metabolism, and the γ-aminobutyric acid shunt, while [(13)C]glutamate and [(15)N]ammonium labeling were performed to address the metabolism via glutamate to succinate. Following these labelings, the time course for the redistribution of the (13)C/(15)N label throughout the metabolic network was evaluated with gas chromatography-time of flight-mass spectrometry. Our combined labeling data suggest the inhibition of the tricarboxylic acid cycle enzyme succinate dehydrogenase, also known as complex II of the mitochondrial electron transport chain, providing support for the bifurcation of the cycle and the down-regulation of the rate of respiration measured during hypoxic stress. Moreover, up-regulation of the γ-aminobutyric acid shunt and alanine metabolism explained the accumulation of succinate and alanine during hypoxia. © 2016 American Society of Plant Biologists. All Rights Reserved.

Reflections on my career in analytical chemistry and biochemistry

PubMed Central

SWEELEY, Charles C.

2010-01-01

My career has been focused in two major areas, analytical chemistry and biochemistry of complex lipids and glycoconjugates. Included here are the pioneering work on the gas chromatography of long-chain sphingolipid bases, carbohydrates, steroids and urinary organic acids. Mass spectrometry was utilized extensively in structural studies of sphingolipids, fatty acids, carbohydrates, steroids, urinary organic acids, polyisoprenoid alcohols, and juvenile hormone. Computer systems were developed for the acquisition and analysis of mass spectra, and were used for development of automated metabolic profiling of complex mixtures of metabolites. Fabry’s disease was discovered to be a glycosphingolipidosis. Enzymes of lysosomal metabolism of glycosphingolipids were purified, characterized, and used in one of the first demonstrations of the feasibility of enzyme replacement therapy in a lysosomal storage disorder (Fabry’s disease). Extracellular sialidases were studied to evaluate the hypothesis that they might be involved in the regulation of membrane growth factor receptors. The enzyme for hematoside synthesis was purified and characterized. PMID:20948176

Myopathology of Adult and Paediatric Mitochondrial Diseases

PubMed Central

Phadke, Rahul

2017-01-01

Mitochondria are dynamic organelles ubiquitously present in nucleated eukaryotic cells, subserving multiple metabolic functions, including cellular ATP generation by oxidative phosphorylation (OXPHOS). The OXPHOS machinery comprises five transmembrane respiratory chain enzyme complexes (RC). Defective OXPHOS gives rise to mitochondrial diseases (mtD). The incredible phenotypic and genetic diversity of mtD can be attributed at least in part to the RC dual genetic control (nuclear DNA (nDNA) and mitochondrial DNA (mtDNA)) and the complex interaction between the two genomes. Despite the increasing use of next-generation-sequencing (NGS) and various omics platforms in unravelling novel mtD genes and pathomechanisms, current clinical practice for investigating mtD essentially involves a multipronged approach including clinical assessment, metabolic screening, imaging, pathological, biochemical and functional testing to guide molecular genetic analysis. This review addresses the broad muscle pathology landscape including genotype–phenotype correlations in adult and paediatric mtD, the role of immunodiagnostics in understanding some of the pathomechanisms underpinning the canonical features of mtD, and recent diagnostic advances in the field. PMID:28677615

A new missense mutation in the BCKDHB gene causes the classic form of maple syrup urine disease (MSUD).

PubMed

Miryounesi, Mohammad; Ghafouri-Fard, Soudeh; Goodarzi, Hamedreza; Fardaei, Majid

2015-05-01

Maple syrup urine disease (MSUD) is an autosomal recessive metabolic disease caused by mutations in the BCKDHA, BCKDHB, DBT and DLD genes, which encode the E1α, E1β, E2 and E3 subunits of the branched chain α ketoacid dehydrogenase (BCKD) complex, respectively. This complex is involved in the metabolism of branched-chain amino acids. In this study, we analyzed the DNA sequences of BCKDHA and BCKDHB genes in an infant who suffered from MSUD and died at the age of 6 months. We found a new missense mutation in exon 5 of BCKDHB gene (c.508C>T). The heterozygosity of the parents for the mentioned nucleotide change was confirmed by direct sequence analysis of the corresponding segment. Another missense mutation has been found in the same codon previously and shown by in silico analyses to be deleterious. This report provides further evidence that this amino acid change can cause classic MSUD.

Metabolic Analysis of Wild-type Escherichia coli and a Pyruvate Dehydrogenase Complex (PDHC)-deficient Derivative Reveals the Role of PDHC in the Fermentative Metabolism of Glucose*

PubMed Central

Murarka, Abhishek; Clomburg, James M.; Moran, Sean; Shanks, Jacqueline V.; Gonzalez, Ramon

2010-01-01

Pyruvate is located at a metabolic junction of assimilatory and dissimilatory pathways and represents a switch point between respiratory and fermentative metabolism. In Escherichia coli, the pyruvate dehydrogenase complex (PDHC) and pyruvate formate-lyase are considered the primary routes of pyruvate conversion to acetyl-CoA for aerobic respiration and anaerobic fermentation, respectively. During glucose fermentation, the in vivo activity of PDHC has been reported as either very low or undetectable, and the role of this enzyme remains unknown. In this study, a comprehensive characterization of wild-type E. coli MG1655 and a PDHC-deficient derivative (Pdh) led to the identification of the role of PDHC in the anaerobic fermentation of glucose. The metabolism of these strains was investigated by using a mixture of 13C-labeled and -unlabeled glucose followed by the analysis of the labeling pattern in protein-bound amino acids via two-dimensional 13C,1H NMR spectroscopy. Metabolite balancing, biosynthetic 13C labeling of proteinogenic amino acids, and isotopomer balancing all indicated a large increase in the flux of the oxidative branch of the pentose phosphate pathway (ox-PPP) in response to the PDHC deficiency. Because both ox-PPP and PDHC generate CO2 and the calculated CO2 evolution rate was significantly reduced in Pdh, it was hypothesized that the role of PDHC is to provide CO2 for cell growth. The similarly negative impact of either PDHC or ox-PPP deficiencies, and an even more pronounced impairment of cell growth in a strain lacking both ox-PPP and PDHC, provided further support for this hypothesis. The three strains exhibited similar phenotypes in the presence of an external source of CO2, thus confirming the role of PDHC. Activation of formate hydrogen-lyase (which converts formate to CO2 and H2) rendered the PDHC deficiency silent, but its negative impact reappeared in a strain lacking both PDHC and formate hydrogen-lyase. A stoichiometric analysis of CO2 generation via PDHC and ox-PPP revealed that the PDHC route is more carbon- and energy-efficient, in agreement with its beneficial role in cell growth. PMID:20667837

Functional proteomic analysis of corticosteroid pharmacodynamics in rat liver: Relationship to hepatic stress, signaling, energy regulation, and drug metabolism.

PubMed

Ayyar, Vivaswath S; Almon, Richard R; DuBois, Debra C; Sukumaran, Siddharth; Qu, Jun; Jusko, William J

2017-05-08

Corticosteroids (CS) are anti-inflammatory agents that cause extensive pharmacogenomic and proteomic changes in multiple tissues. An understanding of the proteome-wide effects of CS in liver and its relationships to altered hepatic and systemic physiology remains incomplete. Here, we report the application of a functional pharmacoproteomic approach to gain integrated insight into the complex nature of CS responses in liver in vivo. An in-depth functional analysis was performed using rich pharmacodynamic (temporal-based) proteomic data measured over 66h in rat liver following a single dose of methylprednisolone (MPL). Data mining identified 451 differentially regulated proteins. These proteins were analyzed on the basis of temporal regulation, cellular localization, and literature-mined functional information. Of the 451 proteins, 378 were clustered into six functional groups based on major clinically-relevant effects of CS in liver. MPL-responsive proteins were highly localized in the mitochondria (20%) and cytosol (24%). Interestingly, several proteins were related to hepatic stress and signaling processes, which appear to be involved in secondary signaling cascades and in protecting the liver from CS-induced oxidative damage. Consistent with known adverse metabolic effects of CS, several rate-controlling enzymes involved in amino acid metabolism, gluconeogenesis, and fatty-acid metabolism were altered by MPL. In addition, proteins involved in the metabolism of endogenous compounds, xenobiotics, and therapeutic drugs including cytochrome P450 and Phase-II enzymes were differentially regulated. Proteins related to the inflammatory acute-phase response were up-regulated in response to MPL. Functionally-similar proteins showed large diversity in their temporal profiles, indicating complex mechanisms of regulation by CS. Clinical use of corticosteroid (CS) therapy is frequent and chronic. However, current knowledge on the proteome-level effects of CS in liver and other tissues is sparse. While transcriptomic regulation following methylprednisolone (MPL) dosing has been temporally examined in rat liver, proteomic assessments are needed to better characterize the tissue-specific functional aspects of MPL actions. This study describes a functional pharmacoproteomic analysis of dynamic changes in MPL-regulated proteins in liver and provides biological insight into how steroid-induced perturbations on a molecular level may relate to both adverse and therapeutic responses presented clinically. Copyright © 2017 Elsevier B.V. All rights reserved.

Mitochondrial respiratory chain Complex I defects in Fanconi anemia complementation group A.

PubMed

Ravera, Silvia; Vaccaro, Daniele; Cuccarolo, Paola; Columbaro, Marta; Capanni, Cristina; Bartolucci, Martina; Panfoli, Isabella; Morelli, Alessandro; Dufour, Carlo; Cappelli, Enrico; Degan, Paolo

2013-10-01

Fanconi anemia (FA) is a rare and complex inherited blood disorder of the child. At least 15 genes are associated with the disease. The highest frequency of mutations belongs to groups A, C and G. Genetic instability and cytokine hypersensitivity support the selection of leukemic over non-leukemic stem cells. FA cellular phenotype is characterized by alterations in red-ox state, mitochondrial functionality and energy metabolism as reported in the past however a clear picture of the altered biochemical phenotype in FA is still elusive and the final biochemical defect(s) still unknown. Here we report an analysis of the respiratory fluxes in FANCA primary fibroblasts, lymphocytes and lymphoblasts. FANCA mutants show defective respiration through Complex I, diminished ATP production and metabolic sufferance with an increased AMP/ATP ratio. Respiration in FANCC mutants is normal. Treatment with N-acetyl-cysteine (NAC) restores oxygen consumption to normal level. Defective respiration in FANCA mutants appear correlated with the FA pro-oxidative phenotype which is consistent with the altered morphology of FANCA mitochondria. Electron microscopy measures indeed show profound alterations in mitochondrial ultrastructure and shape. Copyright © 2013 Elsevier Masson SAS. All rights reserved.

Neuropsychological and FDG-PET profiles in VGKC autoimmune limbic encephalitis.

PubMed

Dodich, Alessandra; Cerami, Chiara; Iannaccone, Sandro; Marcone, Alessandra; Alongi, Pierpaolo; Crespi, Chiara; Canessa, Nicola; Andreetta, Francesca; Falini, Andrea; Cappa, Stefano F; Perani, Daniela

2016-10-01

Limbic encephalitis (LE) is characterized by an acute or subacute onset with memory impairments, confusional state, behavioral disorders, variably associated with seizures and dystonic movements. It is due to inflammatory processes that selectively affect the medial temporal lobe structures. Voltage-gate potassium channel (VGKC) autoantibodies are frequently observed. In this study, we assessed at the individual level FDG-PET brain metabolic dysfunctions and neuropsychological profiles in three autoimmune LE cases seropositive for neuronal VGKC-complex autoantibodies. LGI1 and CASPR2 potassium channel complex autoantibody subtyping was performed. Cognitive abilities were evaluated with an in-depth neuropsychological battery focused on episodic memory and affective recognition/processing skills. FDG-PET data were analyzed at single-subject level according to a standardized and validated voxel-based Statistical Parametric Mapping (SPM) method. Patients showed severe episodic memory and fear recognition deficits at the neuropsychological assessment. No disorder of mentalizing processing was present. Variable patterns of increases and decreases of brain glucose metabolism emerged in the limbic structures, highlighting the pathology-driven selective vulnerability of this system. Additional involvement of cortical and subcortical regions, particularly in the sensorimotor system and basal ganglia, was found. Episodic memory and fear recognition deficits characterize the cognitive profile of LE. Commonalities and differences may occur in the brain metabolic patterns. Single-subject voxel-based analysis of FDG-PET imaging could be useful in the early detection of the metabolic correlates of cognitive and non-cognitive deficits characterizing LE condition. Copyright © 2016 Elsevier Inc. All rights reserved.

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.

The Genome of Naegleria gruberi Illuminates Early Eukaryotic Versatility

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

Fritz-Laylin, Lillian K.; Prochnik, Simon E.; Ginger, Michael L.

2010-03-01

Genome sequences of diverse free-living protists are essential for understanding eukaryotic evolution and molecular and cell biology. The free-living amoeboflagellate Naegleria gruberi belongs to a varied and ubiquitous protist clade (Heterolobosea) that diverged from other eukaryotic lineages over a billion years ago. Analysis of the 15,727 protein-coding genes encoded by Naegleria's 41 Mb nuclear genome indicates a capacity for both aerobic respiration and anaerobic metabolism with concomitant hydrogen production, with fundamental implications for the evolution of organelle metabolism. The Naegleria genome facilitates substantially broader phylogenomic comparisons of free-living eukaryotes than previously possible, allowing us to identify thousands of genes likelymore » present in the pan-eukaryotic ancestor, with 40% likely eukaryotic inventions. Moreover, we construct a comprehensive catalog of amoeboid-motility genes. The Naegleria genome, analyzed in the context of other protists, reveals a remarkably complex ancestral eukaryote with a rich repertoire of cytoskeletal, sexual, signaling, and metabolic modules.« less

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.

Analysis of Prebiotic Oligosaccharides

NASA Astrophysics Data System (ADS)

Sanz, M. L.; Ruiz-Matute, A. I.; Corzo, N.; Martínez-Castro, I.

Carbohydrates and more specifically prebiotics, are complex mixtures of isomers with different degrees of polymerization (DP), monosaccharide units and/or glycosidic linkages. Many efforts are focused on the search for new products and the determination of their biological activity. However, the study of their chemical structure is fundamental to both acquire a basic knowledge of the carbohydrate and to increase the understanding of the mechanisms for their metabolic effect.

Unravelling the shape and structural assembly of the photosynthetic GAPDH-CP12-PRK complex from Arabidopsis thaliana by small-angle X-ray scattering analysis.

PubMed

Del Giudice, Alessandra; Pavel, Nicolae Viorel; Galantini, Luciano; Falini, Giuseppe; Trost, Paolo; Fermani, Simona; Sparla, Francesca

2015-12-01

Oxygenic photosynthetic organisms produce sugars through the Calvin-Benson cycle, a metabolism that is tightly linked to the light reactions of photosynthesis and is regulated by different mechanisms, including the formation of protein complexes. Two enzymes of the cycle, glyceraldehyde-3-phosphate dehydrogenase (GAPDH) and phosphoribulokinase (PRK), form a supramolecular complex with the regulatory protein CP12 with the formula (GAPDH-CP122-PRK)2, in which both enzyme activities are transiently inhibited during the night. Small-angle X-ray scattering analysis performed on both the GAPDH-CP12-PRK complex and its components, GAPDH-CP12 and PRK, from Arabidopsis thaliana showed that (i) PRK has an elongated, bent and screwed shape, (ii) the oxidized N-terminal region of CP12 that is not embedded in the GAPDH-CP12 complex prefers a compact conformation and (iii) the interaction of PRK with the N-terminal region of CP12 favours the approach of two GAPDH tetramers. The interaction between the GAPDH tetramers may contribute to the overall stabilization of the GAPDH-CP12-PRK complex, the structure of which is presented here for the first time.

Taxonomic characterization of the cellulose-degrading bacterium NCIB 10462

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

Dees, C.; Ringleberg, D.; Scott, T.C.

The gram negative cellulase-producing bacterium NCIB 10462 has been previously named Pseudomonas fluorescens subsp. or var. cellulosa. Since there is renewed interest in cellulose-degrading bacteria for use in bioconversion of cellulose to chemical feed stocks and fuels, we re-examined the characteristics of this microorganism to determine its proper taxonomic characterization and to further define it`s true metabolic potential. Metabolic and physical characterization of NCIB 10462 revealed that this was an alkalophilic, non-fermentative, gram negative, oxidase positive, motile, cellulose-degrading bacterium. The aerobic substrate utilization profile of this bacterium was found to have few characteristics consistent with a classification of P. fluorescensmore » with a very low probability match with the genus Sphingomonas. Total lipid analysis did not reveal that any sphingolipid bases are produced by this bacterium. NCIB 10462 was found to grow best aerobically but also grows well in complex media under reducing conditions. NCIB 10462 grew slowly under full anaerobic conditions on complex media but growth on cellulosic media was found only under aerobic conditions. Total fatty acid analysis (MIDI) of NCIB 10462 failed to group this bacterium with a known pseudomonas species. However, fatty acid analysis of the bacteria when grown at temperatures below 37{degrees}C suggest that the organism is a pseudomonad. Since a predominant characteristic of this bacterium is it`s ability to degrade cellulose, we suggest it be called Pseudomonas cellulosa.« less

Single-cell computational analysis of light harvesting in a flat-panel photo-bioreactor.

PubMed

Loomba, Varun; Huber, Gregor; von Lieres, Eric

2018-01-01

Flat-panel photo-bioreactors (PBRs) are customarily applied for investigating growth of microalgae. Optimal design and operation of such reactors is still a challenge due to complex non-linear combinations of various impact factors, particularly hydrodynamics, light irradiation, and cell metabolism. A detailed analysis of single-cell light reception can lead to novel insights into the complex interactions of light exposure and algae movement in the reactor. The combined impacts of hydrodynamics and light irradiation on algae cultivation in a flat-panel PBR were studied by tracing the light exposure of individual cells over time. Hydrodynamics and turbulent mixing in this air-sparged bioreactor were simulated using the Eulerian approach for the liquid phase and a slip model for the gas phase velocity profiles. The liquid velocity was then used for tracing single cells and their light exposure, using light intensity profiles obtained from solving the radiative transfer equation at different wavelengths. The residence times of algae cells in defined dark and light zones of the PBR were statistically analyzed for different algal concentrations and sparging rates. The results indicate poor mixing caused by the reactor design which can be only partially improved by increased sparging rates. The results provide important information for optimizing algal biomass productivity by improving bioreactor design and operation and can further be utilized for an in-depth analysis of algal growth by using advanced models of cell metabolism.

Metabolism-Based Herbicide Resistance and Cross-Resistance in Crop Weeds: A Threat to Herbicide Sustainability and Global Crop Production1

PubMed Central

Yu, Qin; Powles, Stephen

2014-01-01

Weedy plant species that have evolved resistance to herbicides due to enhanced metabolic capacity to detoxify herbicides (metabolic resistance) are a major issue. Metabolic herbicide resistance in weedy plant species first became evident in the 1980s in Australia (in Lolium rigidum) and the United Kingdom (in Alopecurus myosuroides) and is now increasingly recognized in several crop-weed species as a looming threat to herbicide sustainability and thus world crop production. Metabolic resistance often confers resistance to herbicides of different chemical groups and sites of action and can extend to new herbicide(s). Cytochrome P450 monooxygenase, glycosyl transferase, and glutathione S-transferase are often implicated in herbicide metabolic resistance. However, precise biochemical and molecular genetic elucidation of metabolic resistance had been stalled until recently. Complex cytochrome P450 superfamilies, high genetic diversity in metabolic resistant weedy plant species (especially cross-pollinated species), and the complexity of genetic control of metabolic resistance have all been barriers to advances in understanding metabolic herbicide resistance. However, next-generation sequencing technologies and transcriptome-wide gene expression profiling are now revealing the genes endowing metabolic herbicide resistance in plants. This Update presents an historical review to current understanding of metabolic herbicide resistance evolution in weedy plant species. PMID:25106819

Seed proteomics.

PubMed

Miernyk, Ján A; Hajduch, Martin

2011-04-01

Seeds comprise a protective covering, a small embryonic plant, and a nutrient-storage organ. Seeds are protein-rich, and have been the subject of many mass spectrometry-based analyses. Seed storage proteins (SSP), which are transient depots for reduced nitrogen, have been studied for decades by cell biologists, and many of the complicated aspects of their processing, assembly, and compartmentation are now well understood. Unfortunately, the abundance and complexity of the SSP requires that they be avoided or removed prior to gel-based analysis of non-SSP. While much of the extant data from MS-based proteomic analysis of seeds is descriptive, it has nevertheless provided a preliminary metabolic picture explaining much of their biology. Contemporary studies are moving more toward analysis of protein interactions and posttranslational modifications, and functions of metabolic networks. Many aspects of the biology of seeds make then an attractive platform for heterologous protein expression. Herein we present a broad review of the results from the proteomic studies of seeds, and speculate on a potential future research directions. Copyright © 2010 Elsevier B.V. All rights reserved.

DMPy: a Python package for automated mathematical model construction of large-scale metabolic systems.

PubMed

Smith, Robert W; van Rosmalen, Rik P; Martins Dos Santos, Vitor A P; Fleck, Christian

2018-06-19

Models of metabolism are often used in biotechnology and pharmaceutical research to identify drug targets or increase the direct production of valuable compounds. Due to the complexity of large metabolic systems, a number of conclusions have been drawn using mathematical methods with simplifying assumptions. For example, constraint-based models describe changes of internal concentrations that occur much quicker than alterations in cell physiology. Thus, metabolite concentrations and reaction fluxes are fixed to constant values. This greatly reduces the mathematical complexity, while providing a reasonably good description of the system in steady state. However, without a large number of constraints, many different flux sets can describe the optimal model and we obtain no information on how metabolite levels dynamically change. Thus, to accurately determine what is taking place within the cell, finer quality data and more detailed models need to be constructed. In this paper we present a computational framework, DMPy, that uses a network scheme as input to automatically search for kinetic rates and produce a mathematical model that describes temporal changes of metabolite fluxes. The parameter search utilises several online databases to find measured reaction parameters. From this, we take advantage of previous modelling efforts, such as Parameter Balancing, to produce an initial mathematical model of a metabolic pathway. We analyse the effect of parameter uncertainty on model dynamics and test how recent flux-based model reduction techniques alter system properties. To our knowledge this is the first time such analysis has been performed on large models of metabolism. Our results highlight that good estimates of at least 80% of the reaction rates are required to accurately model metabolic systems. Furthermore, reducing the size of the model by grouping reactions together based on fluxes alters the resulting system dynamics. The presented pipeline automates the modelling process for large metabolic networks. From this, users can simulate their pathway of interest and obtain a better understanding of how altering conditions influences cellular dynamics. By testing the effects of different parameterisations we are also able to provide suggestions to help construct more accurate models of complete metabolic systems in the future.

Modeling the Metabolism of Arabidopsis thaliana: Application of Network Decomposition and Network Reduction in the Context of Petri Nets.

PubMed

Koch, Ina; Nöthen, Joachim; Schleiff, Enrico

2017-01-01

Motivation: Arabidopsis thaliana is a well-established model system for the analysis of the basic physiological and metabolic pathways of plants. Nevertheless, the system is not yet fully understood, although many mechanisms are described, and information for many processes exists. However, the combination and interpretation of the large amount of biological data remain a big challenge, not only because data sets for metabolic paths are still incomplete. Moreover, they are often inconsistent, because they are coming from different experiments of various scales, regarding, for example, accuracy and/or significance. Here, theoretical modeling is powerful to formulate hypotheses for pathways and the dynamics of the metabolism, even if the biological data are incomplete. To develop reliable mathematical models they have to be proven for consistency. This is still a challenging task because many verification techniques fail already for middle-sized models. Consequently, new methods, like decomposition methods or reduction approaches, are developed to circumvent this problem. Methods: We present a new semi-quantitative mathematical model of the metabolism of Arabidopsis thaliana . We used the Petri net formalism to express the complex reaction system in a mathematically unique manner. To verify the model for correctness and consistency we applied concepts of network decomposition and network reduction such as transition invariants, common transition pairs, and invariant transition pairs. Results: We formulated the core metabolism of Arabidopsis thaliana based on recent knowledge from literature, including the Calvin cycle, glycolysis and citric acid cycle, glyoxylate cycle, urea cycle, sucrose synthesis, and the starch metabolism. By applying network decomposition and reduction techniques at steady-state conditions, we suggest a straightforward mathematical modeling process. We demonstrate that potential steady-state pathways exist, which provide the fixed carbon to nearly all parts of the network, especially to the citric acid cycle. There is a close cooperation of important metabolic pathways, e.g., the de novo synthesis of uridine-5-monophosphate, the γ-aminobutyric acid shunt, and the urea cycle. The presented approach extends the established methods for a feasible interpretation of biological network models, in particular of large and complex models.

Modeling the Metabolism of Arabidopsis thaliana: Application of Network Decomposition and Network Reduction in the Context of Petri Nets

PubMed Central

Koch, Ina; Nöthen, Joachim; Schleiff, Enrico

2017-01-01

Motivation: Arabidopsis thaliana is a well-established model system for the analysis of the basic physiological and metabolic pathways of plants. Nevertheless, the system is not yet fully understood, although many mechanisms are described, and information for many processes exists. However, the combination and interpretation of the large amount of biological data remain a big challenge, not only because data sets for metabolic paths are still incomplete. Moreover, they are often inconsistent, because they are coming from different experiments of various scales, regarding, for example, accuracy and/or significance. Here, theoretical modeling is powerful to formulate hypotheses for pathways and the dynamics of the metabolism, even if the biological data are incomplete. To develop reliable mathematical models they have to be proven for consistency. This is still a challenging task because many verification techniques fail already for middle-sized models. Consequently, new methods, like decomposition methods or reduction approaches, are developed to circumvent this problem. Methods: We present a new semi-quantitative mathematical model of the metabolism of Arabidopsis thaliana. We used the Petri net formalism to express the complex reaction system in a mathematically unique manner. To verify the model for correctness and consistency we applied concepts of network decomposition and network reduction such as transition invariants, common transition pairs, and invariant transition pairs. Results: We formulated the core metabolism of Arabidopsis thaliana based on recent knowledge from literature, including the Calvin cycle, glycolysis and citric acid cycle, glyoxylate cycle, urea cycle, sucrose synthesis, and the starch metabolism. By applying network decomposition and reduction techniques at steady-state conditions, we suggest a straightforward mathematical modeling process. We demonstrate that potential steady-state pathways exist, which provide the fixed carbon to nearly all parts of the network, especially to the citric acid cycle. There is a close cooperation of important metabolic pathways, e.g., the de novo synthesis of uridine-5-monophosphate, the γ-aminobutyric acid shunt, and the urea cycle. The presented approach extends the established methods for a feasible interpretation of biological network models, in particular of large and complex models. PMID:28713420

In vivo multiphoton and fluorescence lifetime imaging microscopy of the healthy and cholestatic liver

NASA Astrophysics Data System (ADS)

Kuznetsova, Daria S.; Dudenkova, Varvara V.; Rodimova, Svetlana A.; Bobrov, Nikolai V.; Zagainov, Vladimir E.; Zagaynova, Elena V.

2018-02-01

A cholestatic liver disease presents one of the most common liver diseases and can potentially progress to cirrhosis or even cholangiocarcinoma. Conventional techniques are insufficient to precisely describe the complex internal structure, heterogeneous cell populations and the dynamics of biological processes of the liver. Currently, the methods of multiphoton and fluorescence lifetime imaging microscopy are actively introducing to biomedical research. Those methods are extremely informative and non-destructive that allows studying of a large number of processes occurring inside cells and tissues, analyzing molecular cellular composition, as well as evaluating the state of connective tissue fibers due to their ability to generate a second optical harmonic. Multiphoton and FLIM microscopy do not need additional staining of samples or the incorporation of any markers to study metabolism, lipid composition, microstructure analysis, evaluation of fibrous structures. These parameters have pronounced changes in hepatocytes of liver with common pathological diseases. Thereby in this study we investigated metabolic changes in the healthy and cholestatic liver based on the fluorescence of the metabolic co-factors NAD(P)H and FAD by multiphoton microscopy combined with FLIM. To estimate the contribution of energy metabolism and lipogenesis in the observed changes of the metabolic profile, a separate analysis of NADH and NADPH was presented. The data can be used to develop new criteria for the identification of hepatic pathology at the level of hepatocyte changes directed to personalized medicine in the future.

Hormonal regulators of muscle and metabolism in aging (HORMA): Design and conduct of a complex, double-masked, multicenter trial

USDA-ARS?s Scientific Manuscript database

BACKGROUND: Older persons often lose muscle mass, strength, and physical function. This report describes the challenges of conducting a complex clinical investigation assessing the effects of anabolic hormones on body composition, physical function, and metabolism during aging. METHODS: HORMA is a m...

ChloroKB: A Web Application for the Integration of Knowledge Related to Chloroplast Metabolic Network.

PubMed

Gloaguen, Pauline; Bournais, Sylvain; Alban, Claude; Ravanel, Stéphane; Seigneurin-Berny, Daphné; Matringe, Michel; Tardif, Marianne; Kuntz, Marcel; Ferro, Myriam; Bruley, Christophe; Rolland, Norbert; Vandenbrouck, Yves; Curien, Gilles

2017-06-01

Higher plants, as autotrophic organisms, are effective sources of molecules. They hold great promise for metabolic engineering, but the behavior of plant metabolism at the network level is still incompletely described. Although structural models (stoichiometry matrices) and pathway databases are extremely useful, they cannot describe the complexity of the metabolic context, and new tools are required to visually represent integrated biocurated knowledge for use by both humans and computers. Here, we describe ChloroKB, a Web application (http://chlorokb.fr/) for visual exploration and analysis of the Arabidopsis ( Arabidopsis thaliana ) metabolic network in the chloroplast and related cellular pathways. The network was manually reconstructed through extensive biocuration to provide transparent traceability of experimental data. Proteins and metabolites were placed in their biological context (spatial distribution within cells, connectivity in the network, participation in supramolecular complexes, and regulatory interactions) using CellDesigner software. The network contains 1,147 reviewed proteins (559 localized exclusively in plastids, 68 in at least one additional compartment, and 520 outside the plastid), 122 proteins awaiting biochemical/genetic characterization, and 228 proteins for which genes have not yet been identified. The visual presentation is intuitive and browsing is fluid, providing instant access to the graphical representation of integrated processes and to a wealth of refined qualitative and quantitative data. ChloroKB will be a significant support for structural and quantitative kinetic modeling, for biological reasoning, when comparing novel data with established knowledge, for computer analyses, and for educational purposes. ChloroKB will be enhanced by continuous updates following contributions from plant researchers. © 2017 American Society of Plant Biologists. All Rights Reserved.

Metabolic Biomarkers and Neurodegeneration: A Pathway Enrichment Analysis of Alzheimer's Disease, Parkinson's Disease, and Amyotrophic Lateral Sclerosis.

PubMed

Kori, Medi; Aydın, Busra; Unal, Semra; Arga, Kazim Yalcin; Kazan, Dilek

2016-11-01

Neurodegenerative diseases such as Alzheimer's disease (AD), Parkinson's disease (PD), and amyotrophic lateral sclerosis (ALS) lack robust diagnostics and prognostic biomarkers. Metabolomics is a postgenomics field that offers fresh insights for biomarkers of common complex as well as rare diseases. Using data on metabolite-disease associations published in the previous decade (2006-2016) in PubMed, ScienceDirect, Scopus, and Web of Science, we identified 101 metabolites as putative biomarkers for these three neurodegenerative diseases. Notably, uric acid, choline, creatine, L-glutamine, alanine, creatinine, and N-acetyl-L-aspartate were the shared metabolite signatures among the three diseases. The disease-metabolite-pathway associations pointed out the importance of membrane transport (through ATP binding cassette transporters), particularly of arginine and proline amino acids in all three neurodegenerative diseases. When disease-specific and common metabolic pathways were queried by using the pathway enrichment analyses, we found that alanine, aspartate, glutamate, and purine metabolism might act as alternative pathways to overcome inadequate glucose supply and energy crisis in neurodegeneration. These observations underscore the importance of metabolite-based biomarker research in deciphering the elusive pathophysiology of neurodegenerative diseases. Future research investments in metabolomics of complex diseases might provide new insights on AD, PD, and ALS that continue to place a significant burden on global health.

Facing acid–base disorders in the third millennium – the Stewart approach revisited

PubMed Central

Kishen, R; Honoré, Patrick M; Jacobs, R; Joannes-Boyau, O; De Waele, E; De Regt, J; Van Gorp, V; Boer, W; Spapen, HD

2014-01-01

Acid–base disorders are common in the critically ill. Most of these disorders do not cause harm and are self-limiting after appropriate resuscitation and management. Unfortunately, clinicians tend to think about an acid–base disturbance as a “disease” and spend long hours effectively treating numbers rather than the patient. Moreover, a sizable number of intensive-care physicians experience difficulties in interpreting the significance of or understanding the etiology of certain forms of acid–base disequilibria. Traditional tools for interpreting acid–base disorders may not be adequate for analyzing the complex nature of these metabolic abnormalities. Inappropriate interpretation may also lead to wrong clinical conclusions and incorrectly influence clinical management (eg, bicarbonate therapy for metabolic acidosis in different clinical situations). The Stewart approach, based on physicochemical principles, is a robust physiological concept that can facilitate the interpretation and analysis of simple, mixed, and complex acid–base disorders, thereby allowing better diagnosis of the cause of the disturbance and more timely treatment. However, as the concept does not attach importance to plasma bicarbonate, clinicians may find it complicated to use in their daily clinical practice. This article reviews various approaches to interpreting acid–base disorders and suggests the integration of base-excess and Stewart approach for a better interpretation of these metabolic disorders. PMID:24959091

The Strawberry Pathogenesis-related 10 (PR-10) Fra a Proteins Control Flavonoid Biosynthesis by Binding to Metabolic Intermediates*

PubMed Central

Casañal, Ana; Zander, Ulrich; Muñoz, Cristina; Dupeux, Florine; Luque, Irene; Botella, Miguel Angel; Schwab, Wilfried; Valpuesta, Victoriano; Marquez, José A.

2013-01-01

Pathogenesis-related 10 (PR-10) proteins are involved in many aspects of plant biology but their molecular function is still unclear. They are related by sequence and structural homology to mammalian lipid transport and plant abscisic acid receptor proteins and are predicted to have cavities for ligand binding. Recently, three new members of the PR-10 family, the Fra a proteins, have been identified in strawberry, where they are required for the activity of the flavonoid biosynthesis pathway, which is essential for the development of color and flavor in fruits. Here, we show that Fra a proteins bind natural flavonoids with different selectivity and affinities in the low μm range. The structural analysis of Fra a 1 E and a Fra a 3-catechin complex indicates that loops L3, L5, and L7 surrounding the ligand-binding cavity show significant flexibility in the apo forms but close over the ligand in the Fra a 3-catechin complex. Our findings provide mechanistic insight on the function of Fra a proteins and suggest that PR-10 proteins, which are widespread in plants, may play a role in the control of secondary metabolic pathways by binding to metabolic intermediates. PMID:24133217

'Trophic' and 'source' amino acids in trophic estimation: a likely metabolic explanation.

PubMed

O'Connell, T C

2017-06-01

Amino acid nitrogen isotopic analysis is a relatively new method for estimating trophic position. It uses the isotopic difference between an individual's 'trophic' and 'source' amino acids to determine its trophic position. So far, there is no accepted explanation for the mechanism by which the isotopic signals in 'trophic' and 'source' amino acids arise. Yet without a metabolic understanding, the utility of nitrogen isotopic analyses as a method for probing trophic relations, at either bulk tissue or amino acid level, is limited. I draw on isotopic tracer studies of protein metabolism, together with a consideration of amino acid metabolic pathways, to suggest that the 'trophic'/'source' groupings have a fundamental metabolic origin, to do with the cycling of amino-nitrogen between amino acids. 'Trophic' amino acids are those whose amino-nitrogens are interchangeable, part of a metabolic amino-nitrogen pool, and 'source' amino acids are those whose amino-nitrogens are not interchangeable with the metabolic pool. Nitrogen isotopic values of 'trophic' amino acids will reflect an averaged isotopic signal of all such dietary amino acids, offset by the integrated effect of isotopic fractionation from nitrogen cycling, and modulated by metabolic and physiological effects. Isotopic values of 'source' amino acids will be more closely linked to those of equivalent dietary amino acids, but also modulated by metabolism and physiology. The complexity of nitrogen cycling suggests that a single identifiable value for 'trophic discrimination factors' is unlikely to exist. Greater consideration of physiology and metabolism should help in better understanding observed patterns in nitrogen isotopic values.

Effects of hypoglycaemia on neuronal metabolism in the adult brain: role of alternative substrates to glucose.

PubMed

Amaral, Ana I

2013-07-01

Hypoglycaemia is characterized by decreased blood glucose levels and is associated with different pathologies (e.g. diabetes, inborn errors of metabolism). Depending on its severity, it might affect cognitive functions, including impaired judgment and decreased memory capacity, which have been linked to alterations of brain energy metabolism. Glucose is the major cerebral energy substrate in the adult brain and supports the complex metabolic interactions between neurons and astrocytes, which are essential for synaptic activity. Therefore, hypoglycaemia disturbs cerebral metabolism and, consequently, neuronal function. Despite the high vulnerability of neurons to hypoglycaemia, important neurochemical changes enabling these cells to prolong their resistance to hypoglycaemia have been described. This review aims at providing an overview over the main metabolic effects of hypoglycaemia on neurons, covering in vitro and in vivo findings. Recent studies provided evidence that non-glucose substrates including pyruvate, glycogen, ketone bodies, glutamate, glutamine, and aspartate, are metabolized by neurons in the absence of glucose and contribute to prolong neuronal function and delay ATP depletion during hypoglycaemia. One of the pathways likely implicated in the process is the pyruvate recycling pathway, which allows for the full oxidation of glutamate and glutamine. The operation of this pathway in neurons, particularly after hypoglycaemia, has been re-confirmed recently using metabolic modelling tools (i.e. Metabolic Flux Analysis), which allow for a detailed investigation of cellular metabolism in cultured cells. Overall, the knowledge summarized herein might be used for the development of potential therapies targeting neuronal protection in patients vulnerable to hypoglycaemic episodes.

One step DNA assembly for combinatorial metabolic engineering.

PubMed

Coussement, Pieter; Maertens, Jo; Beauprez, Joeri; Van Bellegem, Wouter; De Mey, Marjan

2014-05-01

The rapid and efficient assembly of multi-step metabolic pathways for generating microbial strains with desirable phenotypes is a critical procedure for metabolic engineering, and remains a significant challenge in synthetic biology. Although several DNA assembly methods have been developed and applied for metabolic pathway engineering, many of them are limited by their suitability for combinatorial pathway assembly. The introduction of transcriptional (promoters), translational (ribosome binding site (RBS)) and enzyme (mutant genes) variability to modulate pathway expression levels is essential for generating balanced metabolic pathways and maximizing the productivity of a strain. We report a novel, highly reliable and rapid single strand assembly (SSA) method for pathway engineering. The method was successfully optimized and applied to create constructs containing promoter, RBS and/or mutant enzyme libraries. To demonstrate its efficiency and reliability, the method was applied to fine-tune multi-gene pathways. Two promoter libraries were simultaneously introduced in front of two target genes, enabling orthogonal expression as demonstrated by principal component analysis. This shows that SSA will increase our ability to tune multi-gene pathways at all control levels for the biotechnological production of complex metabolites, achievable through the combinatorial modulation of transcription, translation and enzyme activity. Copyright © 2014 International Metabolic Engineering Society. Published by Elsevier Inc. All rights reserved.

The Importance of Experimental Design, Quality Assurance, and Control in Plant Metabolomics Experiments.

PubMed

Martins, Marina C M; Caldana, Camila; Wolf, Lucia Daniela; de Abreu, Luis Guilherme Furlan

2018-01-01

The output of metabolomics relies to a great extent upon the methods and instrumentation to identify, quantify, and access spatial information on as many metabolites as possible. However, the most modern machines and sophisticated tools for data analysis cannot compensate for inappropriate harvesting and/or sample preparation procedures that modify metabolic composition and can lead to erroneous interpretation of results. In addition, plant metabolism has a remarkable degree of complexity, and the number of identified compounds easily surpasses the number of samples in metabolomics analyses, increasing false discovery risk. These aspects pose a large challenge when carrying out plant metabolomics experiments. In this chapter, we address the importance of a proper experimental design taking into consideration preventable complications and unavoidable factors to achieve success in metabolomics analysis. We also focus on quality control and standardized procedures during the metabolomics workflow.

Functional gene profiling through metaRNAseq approach reveals diet-dependent variation in rumen microbiota of buffalo (Bubalus bubalis).

PubMed

Hinsu, Ankit T; Parmar, Nidhi R; Nathani, Neelam M; Pandit, Ramesh J; Patel, Anand B; Patel, Amrutlal K; Joshi, Chaitanya G

2017-04-01

Recent advances in next generation sequencing technology have enabled analysis of complex microbial community from genome to transcriptome level. In the present study, metatranscriptomic approach was applied to elucidate functionally active bacteria and their biological processes in rumen of buffalo (Bubalus bubalis) adapted to different dietary treatments. Buffaloes were adapted to a diet containing 50:50, 75:25 and 100:0 forage to concentrate ratio, each for 6 weeks, before ruminal content sample collection. Metatranscriptomes from rumen fiber adherent and fiber-free active bacteria were sequenced using Ion Torrent PGM platform followed by annotation using MG-RAST server and CAZYmes (Carbohydrate active enzymes) analysis toolkit. In all the samples Bacteroidetes was the most abundant phylum followed by Firmicutes. Functional analysis using KEGG Orthology database revealed Metabolism as the most abundant category at level 1 within which Carbohydrate metabolism was dominating. Diet treatments also exerted significant differences in proportion of enzymes involved in metabolic pathways for VFA production. Carbohydrate Active Enzyme(CAZy) analysis revealed the abundance of genes encoding glycoside hydrolases with the highest representation of GH13 CAZy family in all the samples. The findings provide an overview of the activities occurring in the rumen as well as active bacterial population and the changes occurring through different dietary treatments. Copyright © 2017 Elsevier Ltd. All rights reserved.

Correlation analysis of targeted proteins and metabolites to assess and engineer microbial isopentenol production.

PubMed

George, Kevin W; Chen, Amy; Jain, Aakriti; Batth, Tanveer S; Baidoo, Edward E K; Wang, George; Adams, Paul D; Petzold, Christopher J; Keasling, Jay D; Lee, Taek Soon

2014-08-01

The ability to rapidly assess and optimize heterologous pathway function is critical for effective metabolic engineering. Here, we develop a systematic approach to pathway analysis based on correlations between targeted proteins and metabolites and apply it to the microbial production of isopentenol, a promising biofuel. Starting with a seven-gene pathway, we performed a correlation analysis to reduce pathway complexity and identified two pathway proteins as the primary determinants of efficient isopentenol production. Aided by the targeted quantification of relevant pathway intermediates, we constructed and subsequently validated a conceptual model of isopentenol pathway function. Informed by our analysis, we assembled a strain which produced isopentenol at a titer 1.5 g/L, or 46% of theoretical yield. Our engineering approach allowed us to accurately identify bottlenecks and determine appropriate pathway balance. Paired with high-throughput cloning techniques and analytics, this strategy should prove useful for the analysis and optimization of increasingly complex heterologous pathways. © 2014 Wiley Periodicals, Inc.

OCIAD1 Controls Electron Transport Chain Complex I Activity to Regulate Energy Metabolism in Human Pluripotent Stem Cells.

PubMed

Shetty, Deeti K; Kalamkar, Kaustubh P; Inamdar, Maneesha S

2018-06-14

Pluripotent stem cells (PSCs) derive energy predominantly from glycolysis and not the energy-efficient oxidative phosphorylation (OXPHOS). Differentiation is initiated with energy metabolic shift from glycolysis to OXPHOS. We investigated the role of mitochondrial energy metabolism in human PSCs using molecular, biochemical, genetic, and pharmacological approaches. We show that the carcinoma protein OCIAD1 interacts with and regulates mitochondrial complex I activity. Energy metabolic assays on live pluripotent cells showed that OCIAD1-depleted cells have increased OXPHOS and may be poised for differentiation. OCIAD1 maintains human embryonic stem cells, and its depletion by CRISPR/Cas9-mediated knockout leads to rapid and increased differentiation upon induction, whereas OCIAD1 overexpression has the opposite effect. Pharmacological alteration of complex I activity was able to rescue the defects of OCIAD1 modulation. Thus, hPSCs can exist in energy metabolic substates. OCIAD1 provides a target to screen for additional modulators of mitochondrial activity to promote transient multipotent precursor expansion or enhance differentiation. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Gut Microbiome and Obesity: A Plausible Explanation for Obesity.

PubMed

Sanmiguel, Claudia; Gupta, Arpana; Mayer, Emeran A

2015-06-01

Obesity is a multifactorial disorder that results in excessive accumulation of adipose tissue. Although obesity is caused by alterations in the energy consumption/expenditure balance, the factors promoting this disequilibrium are incompletely understood. The rapid development of new technologies and analysis strategies to decode the gut microbiota composition and metabolic pathways has opened a door into the complexity of the guest-host interactions between the gut microbiota and its human host in health and in disease. Pivotal studies have demonstrated that manipulation of the gut microbiota and its metabolic pathways can affect host's adiposity and metabolism. These observations have paved the way for further assessment of the mechanisms underlying these changes. In this review we summarize the current evidence for possible mechanisms underlying gut microbiota induced obesity. The review addresses some well-known effects of the gut microbiota on energy harvesting and changes in metabolic machinery, on metabolic and immune interactions and on possible changes in brain function and behavior. Although there is limited understanding on the symbiotic relationship between us and our gut microbiome, and how disturbances of this relationship affects our health, there is compelling evidence for an important role of the gut microbiota in the development and perpetuation of obesity.

Functional proteomics within the genus Lactobacillus.

PubMed

De Angelis, Maria; Calasso, Maria; Cavallo, Noemi; Di Cagno, Raffaella; Gobbetti, Marco

2016-03-01

Lactobacillus are mainly used for the manufacture of fermented dairy, sourdough, meat, and vegetable foods or used as probiotics. Under optimal processing conditions, Lactobacillus strains contribute to food functionality through their enzyme portfolio and the release of metabolites. An extensive genomic diversity analysis was conducted to elucidate the core features of the genus Lactobacillus, and to provide a better comprehension of niche adaptation of the strains. However, proteomics is an indispensable "omics" science to elucidate the proteome diversity, and the mechanisms of regulation and adaptation of Lactobacillus strains. This review focuses on the novel and comprehensive knowledge of functional proteomics and metaproteomics of Lactobacillus species. A large list of proteomic case studies of different Lactobacillus species is provided to illustrate the adaptability of the main metabolic pathways (e.g., carbohydrate transport and metabolism, pyruvate metabolism, proteolytic system, amino acid metabolism, and protein synthesis) to various life conditions. These investigations have highlighted that lactobacilli modulate the level of a complex panel of proteins to growth/survive in different ecological niches. In addition to the general regulation and stress response, specific metabolic pathways can be switched on and off, modifying the behavior of the strains. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Salmonella Modulates Metabolism during Growth under Conditions that Induce Expression of Virulence Genes

PubMed Central

Kim, Young-Mo; Schmidt, Brian J.; Kidwai, Afshan S.; Jones, Marcus B.; Deatherage Kaiser, Brooke L.; Brewer, Heather M.; Mitchell, Hugh D.; Palsson, Bernhard O.; McDermott, Jason E.; Heffron, Fred; Smith, Richard D.; Peterson, Scott N.; Ansong, Charles; Hyduke, Daniel R.; Metz, Thomas O.; Adkins, Joshua N.

2013-01-01

Salmonella enterica serovar Typhimurium (S. Typhimurium) is a facultative pathogen that uses complex mechanisms to invade and proliferate within mammalian host cells. To investigate possible contributions of metabolic processes to virulence in S. Typhimurium grown under conditions known to induce expression of virulence genes, we used a metabolomics-driven systems biology approach coupled with genome scale modeling. First, we identified distinct metabolite profiles associated with bacteria grown in either rich or virulence-inducing media and report the most comprehensive coverage of the S. Typhimurium metabolome to date. Second, we applied an omics-informed genome scale modeling analysis of the functional consequences of adaptive alterations in S. Typhimurium metabolism during growth under our conditions. Modeling efforts highlighted a decreased cellular capability to both produce and utilize intracellular amino acids during stationary phase culture in virulence conditions, despite significant abundance increases for these molecules as observed by our metabolomics measurements. Furthermore, analyses of omics data in the context of the metabolic model indicated rewiring of the metabolic network to support pathways associated with virulence. For example, cellular concentrations of polyamines were perturbed, as well as the predicted capacity for secretion and uptake. PMID:23559334

Gut Microbiome and Obesity: A Plausible Explanation for Obesity

PubMed Central

Sanmiguel, Claudia; Gupta, Arpana; Mayer, Emeran A.

2015-01-01

Obesity is a multifactorial disorder that results in excessive accumulation of adipose tissue. Although obesity is caused by alterations in the energy consumption/expenditure balance, the factors promoting this disequilibrium are incompletely understood. The rapid development of new technologies and analysis strategies to decode the gut microbiota composition and metabolic pathways has opened a door into the complexity of the guest-host interactions between the gut microbiota and its human host in health and in disease. Pivotal studies have demonstrated that manipulation of the gut microbiota and its metabolic pathways can affect host’s adiposity and metabolism. These observations have paved the way for further assessment of the mechanisms underlying these changes. In this review we summarize the current evidence for possible mechanisms underlying gut microbiota induced obesity. The review addresses some well-known effects of the gut microbiota on energy harvesting and changes in metabolic machinery, on metabolic and immune interactions and on possible changes in brain function and behavior. Although there is limited understanding on the symbiotic relationship between us and our gut microbiome, and how disturbances of this relationship affects our health, there is compelling evidence for an important role of the gut microbiota in the development and perpetuation of obesity. PMID:26029487

Model-based confirmation of alternative substrates of mitochondrial electron transport chain.

PubMed

Kleessen, Sabrina; Araújo, Wagner L; Fernie, Alisdair R; Nikoloski, Zoran

2012-03-30

Discrimination of metabolic models based on high throughput metabolomics data, reflecting various internal and external perturbations, is essential for identifying the components that contribute to the emerging behavior of metabolic processes. Here, we investigate 12 different models of the mitochondrial electron transport chain (ETC) in Arabidopsis thaliana during dark-induced senescence in order to elucidate the alternative substrates to this metabolic pathway. Our findings demonstrate that the coupling of the proposed computational approach, based on dynamic flux balance analysis, with time-resolved metabolomics data results in model-based confirmations of the hypotheses that, during dark-induced senescence in Arabidopsis, (i) under conditions where the main substrate for the ETC are not fully available, isovaleryl-CoA dehydrogenase and 2-hydroxyglutarate dehydrogenase are able to donate electrons to the ETC, (ii) phytanoyl-CoA does not act even as an indirect substrate of the electron transfer flavoprotein/electron-transfer flavoprotein:ubiquinone oxidoreductase complex, and (iii) the mitochondrial γ-aminobutyric acid transporter has functional significance in maintaining mitochondrial metabolism. Our study provides a basic framework for future in silico studies of alternative pathways in mitochondrial metabolism under extended darkness whereby the role of its components can be computationally discriminated based on available molecular profile data.

Effect of UV-A and UV-B irradiation on the metabolic profile of aqueous humor in rabbits analyzed by 1H NMR spectroscopy.

PubMed

Tessem, May-Britt; Bathen, Tone F; Cejková, Jitka; Midelfart, Anna

2005-03-01

This study was conducted to investigate metabolic changes in aqueous humor from rabbit eyes exposed to either UV-A or -B radiation, by using (1)H nuclear magnetic resonance (NMR) spectroscopy and unsupervised pattern recognition methods. Both eyes of adult albino rabbits were irradiated with UV-A (366 nm, 0.589 J/cm(2)) or UV-B (312 nm, 1.667 J/cm(2)) radiation for 8 minutes, once a day for 5 days. Three days after the last irradiation, samples of aqueous humor were aspirated, and the metabolic profiles analyzed with (1)H NMR spectroscopy. The metabolic concentrations in the exposed and control materials were statistically analyzed and compared, with multivariate methods and one-way ANOVA. UV-B radiation caused statistically significant alterations of betaine, glucose, ascorbate, valine, isoleucine, and formate in the rabbit aqueous humor. By using principal component analysis, the UV-B-irradiated samples were clearly separated from the UV-A-irradiated samples and the control group. No significant metabolic changes were detected in UV-A-irradiated samples. This study demonstrates the potential of using unsupervised pattern recognition methods to extract valuable metabolic information from complex (1)H NMR spectra. UV-B irradiation of rabbit eyes led to significant metabolic changes in the aqueous humor detected 3 days after the last exposure.

redGEM: Systematic reduction and analysis of genome-scale metabolic reconstructions for development of consistent core metabolic models

PubMed Central

Ataman, Meric

2017-01-01

Genome-scale metabolic reconstructions have proven to be valuable resources in enhancing our understanding of metabolic networks as they encapsulate all known metabolic capabilities of the organisms from genes to proteins to their functions. However the complexity of these large metabolic networks often hinders their utility in various practical applications. Although reduced models are commonly used for modeling and in integrating experimental data, they are often inconsistent across different studies and laboratories due to different criteria and detail, which can compromise transferability of the findings and also integration of experimental data from different groups. In this study, we have developed a systematic semi-automatic approach to reduce genome-scale models into core models in a consistent and logical manner focusing on the central metabolism or subsystems of interest. The method minimizes the loss of information using an approach that combines graph-based search and optimization methods. The resulting core models are shown to be able to capture key properties of the genome-scale models and preserve consistency in terms of biomass and by-product yields, flux and concentration variability and gene essentiality. The development of these “consistently-reduced” models will help to clarify and facilitate integration of different experimental data to draw new understanding that can be directly extendable to genome-scale models. PMID:28727725

Targeting Metabolic Plasticity in Breast Cancer Cells via Mitochondrial Complex I Modulation

PubMed Central

Xu, Qijin; Biener-Ramanujan, Eva; Yang, Wei; Ramanujan, V Krishnan

2016-01-01

Purpose Heterogeneity commonly observed in clinical tumors stems both from the genetic diversity as well as from the differential metabolic adaptation of multiple cancer types during their struggle to maintain uncontrolled proliferation and invasion in vivo. This study aims to identify a potential metabolic window of such adaptation in aggressive human breast cancer cell lines. Methods With a multidisciplinary approach using high resolution imaging, cell metabolism assays, proteomic profiling and animal models of human tumor xenografts and via clinically-relevant, pharmacological approach for modulating mitochondrial complex I function in human breast cancer cell lines, we report a novel route to target metabolic plasticity in human breast cancer cells. Results By a systematic modulation of mitochondrial function and by mitigating metabolic switch phenotype in aggressive human breast cancer cells, we demonstrate that the resulting metabolic adaptation signatures can predictably decrease tumorigenic potential in vivo. Proteomic profiling of the metabolic adaptation in these cells further revealed novel protein-pathway interactograms highlighting the importance of antioxidant machinery in the observed metabolic adaptation. Conclusions Improved metabolic adaptation potential in aggressive human breast cancer cells contribute to improving mitochondrial function and reducing metabolic switch phenotype –which may be vital for targeting primary tumor growth in vivo. PMID:25677747

Isolation and characterization of a hydrocarbonoclastic bacterial enrichment from total petroleum hydrocarbon contaminated sediments: potential candidates for bioaugmentation in bio-based processes.

PubMed

Di Gregorio, Simona; Siracusa, Giovanna; Becarelli, Simone; Mariotti, Lorenzo; Gentini, Alessandro; Lorenzi, Roberto

2016-06-01

Seven hydrocarbonoclastic new bacterial isolates were isolated from dredged sediments of a river estuary in Italy. The sediments were contaminated by shipyard activities since decades, mainly ascribable to the exploitation of diesel oil as the fuel for recreational and commercial navigation of watercrafts. The bacterial isolates were able to utilize diesel oil as sole carbon source. Their metabolic capacities were evaluated by GC-MS analysis, with reference to the depletion of both the normal and branched alkanes, the nC18 fatty acid methyl ester and the unresolved complex mixture of organic compounds. They were taxonomically identified as different species of Stenotrophomonas and Pseudomonas spp. by the combination of amplified ribosomal DNA restriction analysis (ARDRA) and repetitive sequence-based PCR (REP-PCR) analysis. The metabolic activities of interest were analyzed both in relation to the single bacterial strains and to the combination of the latter as a multibacterial species system. After 6 days of incubation in mineral medium with diesel oil as sole carbon source, the Stenotrophomonas sp. M1 strain depleted 43-46 % of Cn-alkane from C28 up to C30, 70 % of the nC18 fatty acid methyl ester and the 46 % of the unresolved complex mixture of organic compounds. On the other hand, the Pseudomonas sp. NM1 strain depleted the 76 % of the nC18 fatty acid methyl ester, the 50 % of the unresolved complex mixture of organic compounds. The bacterial multispecies system was able to completely deplete Cn-alkane from C28 up to C30 and to deplete the 95 % of the unresolved complex mixture of organic compounds. The isolates, either as single strains and as a bacterial multispecies system, were proposed as candidates for bioaugmentation in bio-based processes for the decontamination of dredged sediments.

Quantitative Analysis of Complex Drug-Drug Interactions Between Repaglinide and Cyclosporin A/Gemfibrozil Using Physiologically Based Pharmacokinetic Models With In Vitro Transporter/Enzyme Inhibition Data.

PubMed

Kim, Soo-Jin; Toshimoto, Kota; Yao, Yoshiaki; Yoshikado, Takashi; Sugiyama, Yuichi

2017-09-01

Quantitative analysis of transporter- and enzyme-mediated complex drug-drug interactions (DDIs) is challenging. Repaglinide (RPG) is transported into the liver by OATP1B1 and then is metabolized by CYP2C8 and CYP3A4. The purpose of this study was to describe the complex DDIs of RPG quantitatively based on unified physiologically based pharmacokinetic (PBPK) models using in vitro K i values for OATP1B1, CYP3A4, and CYP2C8. Cyclosporin A (CsA) or gemfibrozil (GEM) increased the blood concentrations of RPG. The time profiles of RPG and the inhibitors were analyzed by PBPK models, considering the inhibition of OATP1B1 and CYP3A4 by CsA or OATP1B1 inhibition by GEM and its glucuronide and the mechanism-based inhibition of CYP2C8 by GEM glucuronide. RPG-CsA interaction was closely predicted using a reported in vitro K i,OATP1B1 value in the presence of CsA preincubation. RPG-GEM interaction was underestimated compared with observed data, but the simulation was improved with the increase of f m,CYP2C8 . These results based on in vitro K i values for transport and metabolism suggest the possibility of a bottom-up approach with in vitro inhibition data for the prediction of complex DDIs using unified PBPK models and in vitro f m value of a substrate for multiple enzymes should be considered carefully for the prediction. Copyright © 2017 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

Culinary plants and their potential impact on metabolic overload.

PubMed

Kim, Ji Yeon; Kwon, Oran

2011-07-01

Contemporary human behavior has led a large proportion of the population to metabolic overload and obesity. Postprandial hyperlipidemia and hyperglycemia evoke redox imbalance in the short term and lead to complex chronic disease in the long term with repeated occurrence. Complex diseases are best prevented with complex components of plants; thus, current nutrition research has begun to focus on the development of plant-based functional foods and dietary supplements for health and well-being. Furthermore, given the wide range of species, parts, and secondary metabolites, culinary plants can contribute significant variety and complexity to the human diet. Although understanding the health benefits of culinary plants has been one of the great challenges in nutritional science due to their inherent complexity, it is an advantageous pursuit. This review will address the challenges and opportunities relating to studies of the health benefits of culinary plants, with an emphasis on obesity attributed to metabolic overload. © 2011 New York Academy of Sciences.

BiNA: A Visual Analytics Tool for Biological Network Data

PubMed Central

Gerasch, Andreas; Faber, Daniel; Küntzer, Jan; Niermann, Peter; Kohlbacher, Oliver; Lenhof, Hans-Peter; Kaufmann, Michael

2014-01-01

Interactive visual analysis of biological high-throughput data in the context of the underlying networks is an essential task in modern biomedicine with applications ranging from metabolic engineering to personalized medicine. The complexity and heterogeneity of data sets require flexible software architectures for data analysis. Concise and easily readable graphical representation of data and interactive navigation of large data sets are essential in this context. We present BiNA - the Biological Network Analyzer - a flexible open-source software for analyzing and visualizing biological networks. Highly configurable visualization styles for regulatory and metabolic network data offer sophisticated drawings and intuitive navigation and exploration techniques using hierarchical graph concepts. The generic projection and analysis framework provides powerful functionalities for visual analyses of high-throughput omics data in the context of networks, in particular for the differential analysis and the analysis of time series data. A direct interface to an underlying data warehouse provides fast access to a wide range of semantically integrated biological network databases. A plugin system allows simple customization and integration of new analysis algorithms or visual representations. BiNA is available under the 3-clause BSD license at http://bina.unipax.info/. PMID:24551056

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 indispensable technique to study metabolism at the cellular or tissue level. The technique is easy to adopt, provides in-depth, comprehensive and integrated metabolic information and enables rapid quantitative analysis.

Development of Nano/Micro Probes for Femtoliter Volume and Single Cell Measurements

NASA Astrophysics Data System (ADS)

Gao, Yang

Single cell analysis has recently emerged as an important field of biomedical re- search. It is now clear that heterogeneity of cell metabolism functions in complex biological systems is correlated to changes in biological function and disease processes. A variety of nano/micro probes were developed to enable investigation of cells properties such as membrane stiffness, pH value. However, very few designs were focused on single cell metabolic function studies. There is a critical need for technologies that provide analysis of heterogeneity of cell metabolic functions, especially on metabolism. Nevertheless, the few existing approaches suffer from fundamental defects and need to be improved. This work focused on developing nano/micro probes that are suitable for single cell functionality investigation. Both types of probes are designed to measure cell-to-cell/time-to-time heterogeneity in metabolic functions over a long period of time. Lab-made carbon nanoprobes were developed especially for electro-physiological measurement. The unique structure of the carbon nanoprobes makes them suitable for important intracellular applications like trans-membrane potential measurements and various electrochemical measurement for cell function studies. While it is important of have ability to carry out intracellular measure, there are also occasions where the information of a cell as a whole is collected. One of the most important indicator of a cells metabolic functions is cell respiration rate/oxygen consumption rate. A micro-perfusion based multi-functional single cell sensing probe was the developed to carry out measurements on cell as a whole. Formed by a double-barrel theta pipette, the perfusion flow enables the direct measurement of the metabolic flux for example oxygen consumption rate. In conclusion, this work developed nano/micro-probes as novel single cell investigation tools. The data acquired from these tools could provide valuable assistance on applications including cell metabolism studies, cancer diagnoses, and therapy evaluations.

Pathway Activity Profiling (PAPi): from the metabolite profile to the metabolic pathway activity.

PubMed

Aggio, Raphael B M; Ruggiero, Katya; Villas-Bôas, Silas Granato

2010-12-01

Metabolomics is one of the most recent omics-technologies and uses robust analytical techniques to screen low molecular mass metabolites in biological samples. It has evolved very quickly during the last decade. However, metabolomics datasets are considered highly complex when used to relate metabolite levels to metabolic pathway activity. Despite recent developments in bioinformatics, which have improved the quality of metabolomics data, there is still no straightforward method capable of correlating metabolite level to the activity of different metabolic pathways operating within the cells. Thus, this kind of analysis still depends on extremely laborious and time-consuming processes. Here, we present a new algorithm Pathway Activity Profiling (PAPi) with which we are able to compare metabolic pathway activities from metabolite profiles. The applicability and potential of PAPi was demonstrated using a previously published data from the yeast Saccharomyces cerevisiae. PAPi was able to support the biological interpretations of the previously published observations and, in addition, generated new hypotheses in a straightforward manner. However, PAPi is time consuming to perform manually. Thus, we also present here a new R-software package (PAPi) which implements the PAPi algorithm and facilitates its usage to quickly compare metabolic pathways activities between different experimental conditions. Using the identified metabolites and their respective abundances as input, the PAPi package calculates pathways' Activity Scores, which represents the potential metabolic pathways activities and allows their comparison between conditions. PAPi also performs principal components analysis and analysis of variance or t-test to investigate differences in activity level between experimental conditions. In addition, PAPi generates comparative graphs highlighting up- and down-regulated pathway activity. These datasets are available in http://www.4shared.com/file/hTWyndYU/extra.html and http://www.4shared.com/file/VbQIIDeu/intra.html. PAPi package is available in: http://www.4shared.com/file/s0uIYWIg/PAPi_10.html s.villas-boas@auckland.ac.nz Supplementary data are available at Bioinformatics online.

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 in the connection between the multienzymatic complexes, and stably retain these modifications. Here for the first time, we have introduced the general concept of attractor metabolic network, in which this dynamic behavior is observed. PMID:23554883

Consequences of C4 differentiation for chloroplast membrane proteomes in maize mesophyll and bundle sheath cells.

PubMed

Majeran, Wojciech; Zybailov, Boris; Ytterberg, A Jimmy; Dunsmore, Jason; Sun, Qi; van Wijk, Klaas J

2008-09-01

Chloroplasts of maize leaves differentiate into specific bundle sheath (BS) and mesophyll (M) types to accommodate C(4) photosynthesis. Chloroplasts contain thylakoid and envelope membranes that contain the photosynthetic machineries and transporters but also proteins involved in e.g. protein homeostasis. These chloroplast membranes must be specialized within each cell type to accommodate C(4) photosynthesis and regulate metabolic fluxes and activities. This quantitative study determined the differentiated state of BS and M chloroplast thylakoid and envelope membrane proteomes and their oligomeric states using innovative gel-based and mass spectrometry-based protein quantifications. This included native gels, iTRAQ, and label-free quantification using an LTQ-Orbitrap. Subunits of Photosystems I and II, the cytochrome b(6)f, and ATP synthase complexes showed average BS/M accumulation ratios of 1.6, 0.45, 1.0, and 1.33, respectively, whereas ratios for the light-harvesting complex I and II families were 1.72 and 0.68, respectively. A 1000-kDa BS-specific NAD(P)H dehydrogenase complex with associated proteins of unknown function containing more than 15 proteins was observed; we speculate that this novel complex possibly functions in inorganic carbon concentration when carboxylation rates by ribulose-bisphosphate carboxylase/oxygenase are lower than decarboxylation rates by malic enzyme. Differential accumulation of thylakoid proteases (Egy and DegP), state transition kinases (STN7,8), and Photosystem I and II assembly factors was observed, suggesting that cell-specific photosynthetic electron transport depends on post-translational regulatory mechanisms. BS/M ratios for inner envelope transporters phosphoenolpyruvate/P(i) translocator, Dit1, Dit2, and Mex1 were determined and reflect metabolic fluxes in carbon metabolism. A wide variety of hundreds of other proteins showed differential BS/M accumulation. Mass spectral information and functional annotations are available through the Plant Proteome Database. These data are integrated with previous data, resulting in a model for C(4) photosynthesis, thereby providing new rationales for metabolic engineering of C(4) pathways and targeted analysis of genetic networks that coordinate C(4) differentiation.

Using nocturnal cold air drainage flow to monitor ecosystem processes in complex terrain

Treesearch

Thomas G. Pypker; Michael H. Unsworth; Alan C. Mix; William Rugh; Troy Ocheltree; Karrin Alstad; Barbara J. Bond

2007-01-01

This paper presents initial investigations of a new approach to monitor ecosystem processes in complex terrain on large scales. Metabolic processes in mountainous ecosystems are poorly represented in current ecosystem monitoring campaigns because the methods used for monitoring metabolism at the ecosystem scale (e.g., eddy covariance) require flat study sites. Our goal...

Complete genome sequence of Corynebacterium variabile DSM 44702 isolated from the surface of smear-ripened cheeses and insights into cheese ripening and flavor generation

PubMed Central

2011-01-01

Background Corynebacterium variabile is part of the complex microflora on the surface of smear-ripened cheeses and contributes to the development of flavor and textural properties during cheese ripening. Still little is known about the metabolic processes and microbial interactions during the production of smear-ripened cheeses. Therefore, the gene repertoire contributing to the lifestyle of the cheese isolate C. variabile DSM 44702 was deduced from the complete genome sequence to get a better understanding of this industrial process. Results The chromosome of C. variabile DSM 44702 is composed of 3, 433, 007 bp and contains 3, 071 protein-coding regions. A comparative analysis of this gene repertoire with that of other corynebacteria detected 1, 534 predicted genes to be specific for the cheese isolate. These genes might contribute to distinct metabolic capabilities of C. variabile, as several of them are associated with metabolic functions in cheese habitats by playing roles in the utilization of alternative carbon and sulphur sources, in amino acid metabolism, and fatty acid degradation. Relevant C. variabile genes confer the capability to catabolize gluconate, lactate, propionate, taurine, and gamma-aminobutyric acid and to utilize external caseins. In addition, C. variabile is equipped with several siderophore biosynthesis gene clusters for iron acquisition and an exceptional repertoire of AraC-regulated iron uptake systems. Moreover, C. variabile can produce acetoin, butanediol, and methanethiol, which are important flavor compounds in smear-ripened cheeses. Conclusions The genome sequence of C. variabile provides detailed insights into the distinct metabolic features of this bacterium, implying a strong adaption to the iron-depleted cheese surface habitat. By combining in silico data obtained from the genome annotation with previous experimental knowledge, occasional observations on genes that are involved in the complex metabolic capacity of C. variabile were integrated into a global view on the lifestyle of this species. PMID:22053731

Statistical total correlation spectroscopy scaling for enhancement of metabolic information recovery in biological NMR spectra.

PubMed

Maher, Anthony D; Fonville, Judith M; Coen, Muireann; Lindon, John C; Rae, Caroline D; Nicholson, Jeremy K

2012-01-17

The high level of complexity in nuclear magnetic resonance (NMR) metabolic spectroscopic data sets has fueled the development of experimental and mathematical techniques that enhance latent biomarker recovery and improve model interpretability. We previously showed that statistical total correlation spectroscopy (STOCSY) can be used to edit NMR spectra to remove drug metabolite signatures that obscure metabolic variation of diagnostic interest. Here, we extend this "STOCSY editing" concept to a generalized scaling procedure for NMR data that enhances recovery of latent biochemical information and improves biological classification and interpretation. We call this new procedure STOCSY-scaling (STOCSY(S)). STOCSY(S) exploits the fixed proportionality in a set of NMR spectra between resonances from the same molecule to suppress or enhance features correlated with a resonance of interest. We demonstrate this new approach using two exemplar data sets: (a) a streptozotocin rat model (n = 30) of type 1 diabetes and (b) a human epidemiological study utilizing plasma NMR spectra of patients with metabolic syndrome (n = 67). In both cases significant biomarker discovery improvement was observed by using STOCSY(S): the approach successfully suppressed interfering NMR signals from glucose and lactate that otherwise dominate the variation in the streptozotocin study, which then allowed recovery of biomarkers such as glycine, which were otherwise obscured. In the metabolic syndrome study, we used STOCSY(S) to enhance variation from the high-density lipoprotein cholesterol peak, improving the prediction of individuals with metabolic syndrome from controls in orthogonal projections to latent structures discriminant analysis models and facilitating the biological interpretation of the results. Thus, STOCSY(S) is a versatile technique that is applicable in any situation in which variation, either biological or otherwise, dominates a data set at the expense of more interesting or important features. This approach is generally appropriate for many types of NMR-based complex mixture analyses and hence for wider applications in bioanalytical science.

Introduction to fatty acids and lipids.

PubMed

Burdge, Graham C; Calder, Philip C

2015-01-01

The purpose of this article is to describe the structure, function and metabolism of fatty acids and lipids that are of particular importance in the context of parenteral nutrition. Lipids are a heterogeneous group of molecules that share the common property of hydrophobicity. Lipids range in structure from simple short hydrocarbon chains to more complex molecules, including triacylglycerols, phospholipids and sterols and their esters. Lipids within each class may differ structurally. Fatty acids are common components of complex lipids, and these differ according to chain length and the presence, number and position of double bonds in the hydrocarbon chain. Structural variation among complex lipids and among fatty acids gives rise to functional differences that result in different impacts upon metabolism and upon cell and tissue responses. Fatty acids and complex lipids exhibit a variety of structural variations that influence their metabolism and their functional effects. © 2015 S. Karger AG, Basel.

Decomposition of metabolic network into functional modules based on the global connectivity structure of reaction graph.

PubMed

Ma, Hong-Wu; Zhao, Xue-Ming; Yuan, Ying-Jin; Zeng, An-Ping

2004-08-12

Metabolic networks are organized in a modular, hierarchical manner. Methods for a rational decomposition of the metabolic network into relatively independent functional subsets are essential to better understand the modularity and organization principle of a large-scale, genome-wide network. Network decomposition is also necessary for functional analysis of metabolism by pathway analysis methods that are often hampered by the problem of combinatorial explosion due to the complexity of metabolic network. Decomposition methods proposed in literature are mainly based on the connection degree of metabolites. To obtain a more reasonable decomposition, the global connectivity structure of metabolic networks should be taken into account. In this work, we use a reaction graph representation of a metabolic network for the identification of its global connectivity structure and for decomposition. A bow-tie connectivity structure similar to that previously discovered for metabolite graph is found also to exist in the reaction graph. Based on this bow-tie structure, a new decomposition method is proposed, which uses a distance definition derived from the path length between two reactions. An hierarchical classification tree is first constructed from the distance matrix among the reactions in the giant strong component of the bow-tie structure. These reactions are then grouped into different subsets based on the hierarchical tree. Reactions in the IN and OUT subsets of the bow-tie structure are subsequently placed in the corresponding subsets according to a 'majority rule'. Compared with the decomposition methods proposed in literature, ours is based on combined properties of the global network structure and local reaction connectivity rather than, primarily, on the connection degree of metabolites. The method is applied to decompose the metabolic network of Escherichia coli. Eleven subsets are obtained. More detailed investigations of the subsets show that reactions in the same subset are really functionally related. The rational decomposition of metabolic networks, and subsequent studies of the subsets, make it more amenable to understand the inherent organization and functionality of metabolic networks at the modular level. http://genome.gbf.de/bioinformatics/

Systems metabolic engineering of Escherichia coli for L-threonine production.

PubMed

Lee, Kwang Ho; Park, Jin Hwan; Kim, Tae Yong; Kim, Hyun Uk; Lee, Sang Yup

2007-01-01

Amino-acid producers have traditionally been developed by repeated random mutagenesis owing to the difficulty in rationally engineering the complex and highly regulated metabolic network. Here, we report the development of the genetically defined L-threonine overproducing Escherichia coli strain by systems metabolic engineering. Feedback inhibitions of aspartokinase I and III (encoded by thrA and lysC, respectively) and transcriptional attenuation regulations (located in thrL) were removed. Pathways for Thr degradation were removed by deleting tdh and mutating ilvA. The metA and lysA genes were deleted to make more precursors available for Thr biosynthesis. Further target genes to be engineered were identified by transcriptome profiling combined with in silico flux response analysis, and their expression levels were manipulated accordingly. The final engineered E. coli strain was able to produce Thr with a high yield of 0.393 g per gram of glucose, and 82.4 g/l Thr by fed-batch culture. The systems metabolic engineering strategy reported here may be broadly employed for developing genetically defined organisms for the efficient production of various bioproducts.

Evolutionary engineering of Saccharomyces cerevisiae for efficient conversion of red algal biosugars to bioethanol.

PubMed

Lee, Hye-Jin; Kim, Soo-Jung; Yoon, Jeong-Jun; Kim, Kyoung Heon; Seo, Jin-Ho; Park, Yong-Cheol

2015-09-01

The aim of this work was to apply the evolutionary engineering to construct a mutant Saccharomyces cerevisiae HJ7-14 resistant on 2-deoxy-D-glucose and with an enhanced ability of bioethanol production from galactose, a mono-sugar in red algae. In batch and repeated-batch fermentations, HJ7-14 metabolized 5-fold more galactose and produced ethanol 2.1-fold faster than the parental D452-2 strain. Transcriptional analysis of genes involved in the galactose metabolism revealed that moderate relief from the glucose-mediated repression of the transcription of the GAL genes might enable HJ7-14 to metabolize galactose rapidly. HJ7-14 produced 7.4 g/L ethanol from hydrolysates of the red alga Gelidium amansii within 12 h, which was 1.5-times faster than that observed with D452-2. We demonstrate conclusively that evolutionary engineering is a promising tool to manipulate the complex galactose metabolism in S. cerevisiae to produce bioethanol from red alga. Copyright © 2015 Elsevier Ltd. All rights reserved.

The topology of metabolic isotope labeling networks.

PubMed

Weitzel, Michael; Wiechert, Wolfgang; Nöh, Katharina

2007-08-29

Metabolic Flux Analysis (MFA) based on isotope labeling experiments (ILEs) is a widely established tool for determining fluxes in metabolic pathways. Isotope labeling networks (ILNs) contain all essential information required to describe the flow of labeled material in an ILE. Whereas recent experimental progress paves the way for high-throughput MFA, large network investigations and exact statistical methods, these developments are still limited by the poor performance of computational routines used for the evaluation and design of ILEs. In this context, the global analysis of ILN topology turns out to be a clue for realizing large speedup factors in all required computational procedures. With a strong focus on the speedup of algorithms the topology of ILNs is investigated using graph theoretic concepts and algorithms. A rigorous determination of all cyclic and isomorphic subnetworks, accompanied by the global analysis of ILN connectivity is performed. Particularly, it is proven that ILNs always brake up into a large number of small strongly connected components (SCCs) and, moreover, there are natural isomorphisms between many of these SCCs. All presented techniques are universal, i.e. they do not require special assumptions on the network structure, bidirectionality of fluxes, measurement configuration, or label input. The general results are exemplified with a practically relevant metabolic network which describes the central metabolism of E. coli comprising 10390 isotopomer pools. Exploiting the topological features of ILNs leads to a significant speedup of all universal algorithms for ILE evaluation. It is proven in theory and exemplified with the E. coli example that a speedup factor of about 1000 compared to standard algorithms is achieved. This widely opens the door for new high performance algorithms suitable for high throughput applications and large ILNs. Moreover, for the first time the global topological analysis of ILNs allows to comprehensively describe and understand the general patterns of label flow in complex networks. This is an invaluable tool for the structural design of new experiments and the interpretation of measured data.

Metabolomic and proteomic analysis of D-lactate-producing Lactobacillus delbrueckii under various fermentation conditions.

PubMed

Liang, Shaoxiong; Gao, Dacheng; Liu, Huanhuan; Wang, Cheng; Wen, Jianping

2018-05-28

As an important feedstock monomer for the production of biodegradable stereo-complex poly-lactic acid polymer, D-lactate has attracted much attention. To improve D-lactate production by microorganisms such as Lactobacillus delbrueckii, various fermentation conditions were performed, such as the employment of anaerobic fermentation, the utilization of more suitable neutralizing agents, and exploitation of alternative nitrogen sources. The highest D-lactate titer could reach 133 g/L under the optimally combined fermentation condition, increased by 70.5% compared with the control. To decipher the potential mechanisms of D-lactate overproduction, the time-series response of intracellular metabolism to different fermentation conditions was investigated by GC-MS and LC-MS/MS-based metabolomic analysis. Then the metabolomic datasets were subjected to weighted correlation network analysis (WGCNA), and nine distinct metabolic modules and eight hub metabolites were identified to be specifically associated with D-lactate production. Moreover, a quantitative iTRAQ-LC-MS/MS proteomic approach was employed to further analyze the change of intracellular metabolism under the combined fermentation condition, identifying 97 up-regulated and 42 down-regulated proteins compared with the control. The in-depth analysis elucidated how the key factors exerted influence on D-lactate biosynthesis. The results revealed that glycolysis and pentose phosphate pathways, transport of glucose, amino acids and peptides, amino acid metabolism, peptide hydrolysis, synthesis of nucleotides and proteins, and cell division were all strengthened, while ATP consumption for exporting proton, cell damage, metabolic burden caused by stress response, and bypass of pyruvate were decreased under the combined condition. These might be the main reasons for significantly improved D-lactate production. These findings provide the first omics view of cell growth and D-lactate overproduction in L. delbrueckii, which can be a theoretical basis for further improving the production of D-lactate.

Role of the BAHD1 Chromatin-Repressive Complex in Placental Development and Regulation of Steroid Metabolism

PubMed Central

Lakisic, Goran; Wendling, Olivia; Libertini, Emanuele; Radford, Elizabeth J.; Le Guillou, Morwenna; Champy, Marie-France; Wattenhofer-Donzé, Marie; Soubigou, Guillaume; Ait-Si-Ali, Slimane; Feunteun, Jean; Sorg, Tania; Coppée, Jean-Yves; Ferguson-Smith, Anne C.; Cossart, Pascale; Bierne, Hélène

2016-01-01

BAHD1 is a vertebrate protein that promotes heterochromatin formation and gene repression in association with several epigenetic regulators. However, its physiological roles remain unknown. Here, we demonstrate that ablation of the Bahd1 gene results in hypocholesterolemia, hypoglycemia and decreased body fat in mice. It also causes placental growth restriction with a drop of trophoblast glycogen cells, a reduction of fetal weight and a high neonatal mortality rate. By intersecting transcriptome data from murine Bahd1 knockout (KO) placentas at stages E16.5 and E18.5 of gestation, Bahd1-KO embryonic fibroblasts, and human cells stably expressing BAHD1, we also show that changes in BAHD1 levels alter expression of steroid/lipid metabolism genes. Biochemical analysis of the BAHD1-associated multiprotein complex identifies MIER proteins as novel partners of BAHD1 and suggests that BAHD1-MIER interaction forms a hub for histone deacetylases and methyltransferases, chromatin readers and transcription factors. We further show that overexpression of BAHD1 leads to an increase of MIER1 enrichment on the inactive X chromosome (Xi). In addition, BAHD1 and MIER1/3 repress expression of the steroid hormone receptor genes ESR1 and PGR, both playing important roles in placental development and energy metabolism. Moreover, modulation of BAHD1 expression in HEK293 cells triggers epigenetic changes at the ESR1 locus. Together, these results identify BAHD1 as a core component of a chromatin-repressive complex regulating placental morphogenesis and body fat storage and suggest that its dysfunction may contribute to several human diseases. PMID:26938916

Nonlinear temperature effects on multifractal complexity of metabolic rate of mice

PubMed Central

Bogdanovich, Jose M.; Bozinovic, Francisco

2016-01-01

Complex physiological dynamics have been argued to be a signature of healthy physiological function. Here we test whether the complexity of metabolic rate fluctuations in small endotherms decreases with lower environmental temperatures. To do so, we examine the multifractal temporal scaling properties of the rate of change in oxygen consumption r(VO2), in the laboratory mouse Mus musculus, assessing their long range correlation properties across seven different environmental temperatures, ranging from 0 °C to 30 °C. To do so, we applied multifractal detrended fluctuation analysis (MF-DFA), finding that r(VO2) fluctuations show two scaling regimes. For small time scales below the crossover time (approximately 102 s), either monofractal or weak multifractal dynamics are observed depending on whether Ta < 15 °C or Ta > 15 °C respectively. For larger time scales, r(VO2) fluctuations are characterized by an asymptotic scaling exponent that indicates multifractal anti-persistent or uncorrelated dynamics. For both scaling regimes, a generalization of the multiplicative cascade model provides very good fits for the Renyi exponents τ(q), showing that the infinite number of exponents h(q) can be described by only two independent parameters, a and b. We also show that the long-range correlation structure of r(VO2) time series differs from randomly shuffled series, and may not be explained as an artifact of stochastic sampling of a linear frequency spectrum. These results show that metabolic rate dynamics in a well studied micro-endotherm are consistent with a highly non-linear feedback control system. PMID:27781179

Nonlinear temperature effects on multifractal complexity of metabolic rate of mice.

PubMed

Labra, Fabio A; Bogdanovich, Jose M; Bozinovic, Francisco

2016-01-01

Complex physiological dynamics have been argued to be a signature of healthy physiological function. Here we test whether the complexity of metabolic rate fluctuations in small endotherms decreases with lower environmental temperatures. To do so, we examine the multifractal temporal scaling properties of the rate of change in oxygen consumption r ( VO 2 ), in the laboratory mouse Mus musculus , assessing their long range correlation properties across seven different environmental temperatures, ranging from 0 °C to 30 °C. To do so, we applied multifractal detrended fluctuation analysis (MF-DFA), finding that r(VO 2 ) fluctuations show two scaling regimes. For small time scales below the crossover time (approximately 10 2 s), either monofractal or weak multifractal dynamics are observed depending on whether T a < 15 °C or T a > 15 °C respectively. For larger time scales, r(VO 2 ) fluctuations are characterized by an asymptotic scaling exponent that indicates multifractal anti-persistent or uncorrelated dynamics. For both scaling regimes, a generalization of the multiplicative cascade model provides very good fits for the Renyi exponents τ ( q ), showing that the infinite number of exponents h(q) can be described by only two independent parameters, a and b . We also show that the long-range correlation structure of r(VO 2 ) time series differs from randomly shuffled series, and may not be explained as an artifact of stochastic sampling of a linear frequency spectrum. These results show that metabolic rate dynamics in a well studied micro-endotherm are consistent with a highly non-linear feedback control system.

Using next generation transcriptome sequencing to predict an ectomycorrhizal metablome.

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

Larsen, P. E.; Sreedasyam, A.; Trivedi, G

Mycorrhizae, symbiotic interactions between soil fungi and tree roots, are ubiquitous in terrestrial ecosystems. The fungi contribute phosphorous, nitrogen and mobilized nutrients from organic matter in the soil and in return the fungus receives photosynthetically-derived carbohydrates. This union of plant and fungal metabolisms is the mycorrhizal metabolome. Understanding this symbiotic relationship at a molecular level provides important contributions to the understanding of forest ecosystems and global carbon cycling. We generated next generation short-read transcriptomic sequencing data from fully-formed ectomycorrhizae between Laccaria bicolor and aspen (Populus tremuloides) roots. The transcriptomic data was used to identify statistically significantly expressed gene models usingmore » a bootstrap-style approach, and these expressed genes were mapped to specific metabolic pathways. Integration of expressed genes that code for metabolic enzymes and the set of expressed membrane transporters generates a predictive model of the ectomycorrhizal metabolome. The generated model of mycorrhizal metabolome predicts that the specific compounds glycine, glutamate, and allantoin are synthesized by L. bicolor and that these compounds or their metabolites may be used for the benefit of aspen in exchange for the photosynthetically-derived sugars fructose and glucose. The analysis illustrates an approach to generate testable biological hypotheses to investigate the complex molecular interactions that drive ectomycorrhizal symbiosis. These models are consistent with experimental environmental data and provide insight into the molecular exchange processes for organisms in this complex ecosystem. The method used here for predicting metabolomic models of mycorrhizal systems from deep RNA sequencing data can be generalized and is broadly applicable to transcriptomic data derived from complex systems.« less

Elementary Mode Analysis: A Useful Metabolic Pathway Analysis Tool for Characterizing Cellular Metabolism

PubMed Central

Trinh, Cong T.; Wlaschin, Aaron; Srienc, Friedrich

2010-01-01

Elementary Mode Analysis is a useful Metabolic Pathway Analysis tool to identify the structure of a metabolic network that links the cellular phenotype to the corresponding genotype. The analysis can decompose the intricate metabolic network comprised of highly interconnected reactions into uniquely organized pathways. These pathways consisting of a minimal set of enzymes that can support steady state operation of cellular metabolism represent independent cellular physiological states. Such pathway definition provides a rigorous basis to systematically characterize cellular phenotypes, metabolic network regulation, robustness, and fragility that facilitate understanding of cell physiology and implementation of metabolic engineering strategies. This mini-review aims to overview the development and application of elementary mode analysis as a metabolic pathway analysis tool in studying cell physiology and as a basis of metabolic engineering. PMID:19015845

Characterization of the cellulose-degrading bacterium NCIMB 10462

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

Dees, C.; Scott, T.C.; Phelps, T.J.

The gram-negative cellulase-producing bacterium NCIMB 10462 has been previously named Pseudomonas fluorescens subsp. or var. cellulose. Because of renewed interest in cellulose-degrading bacteria for use in the bioconversion of cellulose to chemical feed stocks and fuels, we re-examined the characteristics of this microorganism to determine its true metabolic potential. Metabolic and physical characterization of NCIMB 10462 revealed that this is an alkalophilic, non-fermentative, gram-negative, oxidase-positive, motile, cellulose-degrading bacterium. The aerobic substrate utilization profile of this bacterium has few characteristics consistent with a classification of P. fluorescens and a very low probability match with the genus Sphingomonas. However, total lipid analysismore » did not reveal that any sphingolipid bases are produced by this bacterium. NCIMB 10462 grows best aerobically, but also grows well in complex media under reducing conditions. NCIMB 10462 grows slowly under anaerobic conditions on complex media, but growth on cellulosic media occurred only under aerobic conditions. Total fatty acid analysis (MIDI) of NCIMB 10462 failed to group this bacterium with a known pseudomonas species. However, fatty acid analysis of the bacteria when grown at temperatures below 37{degrees}C suggest that the organism is a pseudomonad. Since a predominant characteristic of this bacterium is its ability to degrade cellulose, we suggest that it be called Pseudomonas cellulosa.« less

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

iTRAQ-Based Proteomics Analysis and Network Integration for Kernel Tissue Development in Maize

PubMed Central

Dong, Yongbin; Wang, Qilei; Du, Chunguang; Xiong, Wenwei; Li, Xinyu; Zhu, Sailan; Li, Yuling

2017-01-01

Grain weight is one of the most important yield components and a developmentally complex structure comprised of two major compartments (endosperm and pericarp) in maize (Zea mays L.), however, very little is known concerning the coordinated accumulation of the numerous proteins involved. Herein, we used isobaric tags for relative and absolute quantitation (iTRAQ)-based comparative proteomic method to analyze the characteristics of dynamic proteomics for endosperm and pericarp during grain development. Totally, 9539 proteins were identified for both components at four development stages, among which 1401 proteins were non-redundant, 232 proteins were specific in pericarp and 153 proteins were specific in endosperm. A functional annotation of the identified proteins revealed the importance of metabolic and cellular processes, and binding and catalytic activities for the tissue development. Three and 76 proteins involved in 49 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were integrated for the specific endosperm and pericarp proteins, respectively, reflecting their complex metabolic interactions. In addition, four proteins with important functions and different expression levels were chosen for gene cloning and expression analysis. Different concordance between mRNA level and the protein abundance was observed across different proteins, stages, and tissues as in previous research. These results could provide useful message for understanding the developmental mechanisms in grain development in maize. PMID:28837076

Renormalization group approach to power-law modeling of complex metabolic networks.

PubMed

Hernández-Bermejo, Benito

2010-08-07

In the modeling of complex biological systems, and especially in the framework of the description of metabolic pathways, the use of power-law models (such as S-systems and GMA systems) often provides a remarkable accuracy over several orders of magnitude in concentrations, an unusually broad range not fully understood at present. In order to provide additional insight in this sense, this article is devoted to the renormalization group analysis of reactions in fractal or self-similar media. In particular, the renormalization group methodology is applied to the investigation of how rate-laws describing such reactions are transformed when the geometric scale is changed. The precise purpose of such analysis is to investigate whether or not power-law rate-laws present some remarkable features accounting for the successes of power-law modeling. As we shall see, according to the renormalization group point of view the answer is positive, as far as power-laws are the critical solutions of the renormalization group transformation, namely power-law rate-laws are the renormalization group invariant solutions. Moreover, it is shown that these results also imply invariance under the group of concentration scalings, thus accounting for the reported power-law model accuracy over several orders of magnitude in metabolite concentrations. Copyright 2010 Elsevier Ltd. All rights reserved.

Metabolism-based herbicide resistance and cross-resistance in crop weeds: a threat to herbicide sustainability and global crop production.

PubMed

Yu, Qin; Powles, Stephen

2014-11-01

Weedy plant species that have evolved resistance to herbicides due to enhanced metabolic capacity to detoxify herbicides (metabolic resistance) are a major issue. Metabolic herbicide resistance in weedy plant species first became evident in the 1980s in Australia (in Lolium rigidum) and the United Kingdom (in Alopecurus myosuroides) and is now increasingly recognized in several crop-weed species as a looming threat to herbicide sustainability and thus world crop production. Metabolic resistance often confers resistance to herbicides of different chemical groups and sites of action and can extend to new herbicide(s). Cytochrome P450 monooxygenase, glycosyl transferase, and glutathione S-transferase are often implicated in herbicide metabolic resistance. However, precise biochemical and molecular genetic elucidation of metabolic resistance had been stalled until recently. Complex cytochrome P450 superfamilies, high genetic diversity in metabolic resistant weedy plant species (especially cross-pollinated species), and the complexity of genetic control of metabolic resistance have all been barriers to advances in understanding metabolic herbicide resistance. However, next-generation sequencing technologies and transcriptome-wide gene expression profiling are now revealing the genes endowing metabolic herbicide resistance in plants. This Update presents an historical review to current understanding of metabolic herbicide resistance evolution in weedy plant species. © 2014 American Society of Plant Biologists. All Rights Reserved.

The depressed central carbon and energy metabolisms is associated to the acquisition of levofloxacin resistance in Vibrio alginolyticus.

PubMed

Cheng, Zhi-Xue; Yang, Man-Jun; Peng, Bo; Peng, Xuan-Xian; Lin, Xiang-Min; Li, Hui

2018-06-15

The overuse and misuse of antibiotics lead to bacterial antibiotic resistance, challenging human health and intensive cultivation. It is especially required to understand for the mechanism of antibiotic resistance to control antibiotic-resistant pathogens. The present study characterized the differential proteome of levofloxacin-resistant Vibrio alginolyticus with the most advanced iTRAQ quantitative proteomics technology. A total of 160 proteins of differential abundance were identified, where 70 were decreased and 90 were increased. Further analysis demonstrated that crucial metabolic pathways like TCA cycle were significantly down-regulated. qRT-PCR analysis demonstrated the decreased gene expression of glycolysis/gluconeogenesis, the TCA cycle, and fatty acid biosynthesis. Moreover, Na(+)-NQR complex gene expression, membrane potential and the adenylate energy charge ratio were decreased, indicating that the decreased central carbon metabolism is associated to the acquisition of levofloxacin resistance. Therefore, the reduced central carbon and energy metabolisms form a characteristic feature as fitness costs of V. alginolyticus in resistance to levofloxacin. The overuse and misuse of antibiotics lead to bacterial antibiotic resistance, challenging human health and intensive cultivation. Understanding for the antibiotic resistance mechanisms is especially required to control these antibiotic-resistant pathogens. The present study characterized the differential proteome of levofloxacin-resistant Vibrio alginolyticus using the most advanced iTRAQ quantitative proteomics technology. A total of 160 differential abundance of proteins were identified with 70 decreases and 90 increases by liquid chromatography matrix assisted laser desorption ionization mass spectrometry. Most interestingly, crucial metabolic pathways such as the TCA cycle sharply fluctuated. This is the first report that the reduced central carbon and energy metabolisms form a characteristic feature as a mechanism of V. alginolyticus in resistance to levofloxacin. Copyright © 2018 Elsevier B.V. All rights reserved.

Combined Inhibition of the Renin-Angiotensin System and Neprilysin Positively Influences Complex Mitochondrial Adaptations in Progressive Experimental Heart Failure

PubMed Central

Reinders, Jörg; Schröder, Josef; Dietl, Alexander; Schmid, Peter M.; Jungbauer, Carsten; Resch, Markus; Maier, Lars S.; Luchner, Andreas; Birner, Christoph

2017-01-01

Background Inhibitors of the renin angiotensin system and neprilysin (RAS-/NEP-inhibitors) proved to be extraordinarily beneficial in systolic heart failure. Furthermore, compelling evidence exists that impaired mitochondrial pathways are causatively involved in progressive left ventricular (LV) dysfunction. Consequently, we aimed to assess whether RAS-/NEP-inhibition can attenuate mitochondrial adaptations in experimental heart failure (HF). Methods and Results By progressive right ventricular pacing, distinct HF stages were induced in 15 rabbits, and 6 animals served as controls (CTRL). Six animals with manifest HF (CHF) were treated with the RAS-/NEP-inhibitor omapatrilat. Echocardiographic studies and invasive blood pressure measurements were undertaken during HF progression. Mitochondria were isolated from LV tissue, respectively, and further worked up for proteomic analysis using the SWATH technique. Enzymatic activities of citrate synthase and the electron transfer chain (ETC) complexes I, II, and IV were assessed. Ultrastructural analyses were performed by transmission electron microscopy. During progression to overt HF, intricate expression changes were mainly detected for proteins belonging to the tricarboxylic acid cycle, glucose and fat metabolism, and the ETC complexes, even though ETC complex I, II, or IV enzymatic activities were not significantly influenced. Treatment with a RAS-/NEP-inhibitor then reversed some maladaptive metabolic adaptations, positively influenced the decline of citrate synthase activity, and altered the composition of each respiratory chain complex, even though this was again not accompanied by altered ETC complex enzymatic activities. Finally, ultrastructural evidence pointed to a reduction of autophagolytic and degenerative processes with omapatrilat-treatment. Conclusions This study describes complex adaptations of the mitochondrial proteome in experimental tachycardia-induced heart failure and shows that a combined RAS-/NEP-inhibition can beneficially influence mitochondrial key pathways. PMID:28076404

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.

A complex web of risks for metabolic syndrome: race/ethnicity, economics, and gender.

PubMed

Salsberry, Pamela J; Corwin, Elizabeth; Reagan, Patricia B

2007-08-01

Metabolic syndrome is a recognizable clinical cluster of risks known to be associated in combination and independently with an increased risk for cardiovascular disease (CVD). Identifying and treating metabolic syndrome is one promising strategy to reduce CVD. The intersection of race/ethnicity, gender, and economic status complicates our understanding of who is at risk for metabolic syndrome, but understanding this social patterning is important for the development of targeted interventions. This study examines the relationship between metabolic syndrome (and the underlying contributing risk factors) and race/ethnicity, economic status, and gender. National Health and Nutrition Examination Survey data collected from 1999 through 2002 were used; analysis was completed in 2006-2007. Metabolic syndrome was defined using the Adult Treatment Panel III definition. Economic status was measured using income as a percentage of the poverty level. Prevalence of metabolic syndrome and each of its contributing risk factors were determined by race/ethnicity and economic group. Logistic regressions were estimated. All analyses were stratified by gender. Economic effects were seen for women, but not men. Women in the lowest economic group were more likely to be at risk in four of the five risk categories when compared with women in the highest economic group. Differences in the contributing risk profiles for metabolic syndrome were seen by race/ethnicity. Strategies to reduce CVD must be built on a clear understanding of the differences in contributing risk factors for metabolic syndrome across subgroups. The findings from this study provide further information to guide the targeting of these strategies.

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...

Turning Biochemistry Inside Out: A New Approach to Teaching Metabolism in the Post-Genomic Era

ERIC Educational Resources Information Center

Gerrard, Juliet A.; Sparrow, Ashley D.

2002-01-01

This article describes a new approach to teaching metabolic pathways, designed to engage students with the material, and its complexities. Based on a novel way of presenting metabolic pathways, in which the focus is placed on proteins rather than metabolites, simple tutorial-based exercises and mini-projects are described, bringing metabolism to…

Gender differences in the prevalence and development of metabolic syndrome in Chinese population with abdominal obesity.

PubMed

Xu, Shaoyong; Gao, Bin; Xing, Ying; Ming, Jie; Bao, Junxiang; Zhang, Qiang; Wan, Yi; Ji, Qiuhe

2013-01-01

Not all the people with metabolic syndrome (MS) have abdominal obesity (AO). The study aimed to investigate gender differences in the prevalence and development of MS in Chinese population with abdominal obesity, which has rarely been reported. Data were obtained from the 2007-08 China National Diabetes and Metabolic Disorders Study, and participants were divided into two samples for analysis. Sample 1 consisted of 19,046 people with abdominal obesity, while sample 2 included 2,124 people meeting pre-specified requirements. Survival analysis was used to analyze the development of MS. The age-standardized prevalence of MS in Chinese population with AO was 49.5%. The prevalence in males (73.7%) was significantly higher than that in females (36.9%). Males had significantly higher proportions of combinations of three or four MS components than females (36.4% vs. 30.2% and 18.4% vs. 5%, respectively). MS developed quick at first and became slow down later. Half of the participants with AO developed to MS after 3.9 years (95% CI: 3.7-4.1) from the initial metabolic abnormal component, whereas 75% developed to MS after 7.7 years (95% CI: 7.5-7.9). Compared with females, Chinese males with AO should receive more attention because of their higher prevalence of MS and its components, more complex and risky combinations of abnormal components, and faster development of MS.

Identification of differentially accumulated proteins associated with embryogenic and non-embryogenic calli in saffron (Crocus sativus L.)

PubMed Central

2012-01-01

Background Somatic embryogenesis (SE) is a complex biological process that occurs under inductive conditions and causes fully differentiated cells to be reprogrammed to an embryo like state. In order to get a better insight about molecular basis of the SE in Crocus sativus L. and to characterize differentially accumulated proteins during the process, a proteomic study based on two-dimensional gel electrophoresis and matrix-assisted laser desorption/ionization time of flight mass spectrometry has been carried out. Results We have compared proteome profiles of non-embryogenic and embryogenic calli with native corm explants. Total soluble proteins were phenol-extracted and loaded on 18 cm IPG strips for the first dimension and 11.5% sodium dodecyl sulfate-polyacrylamide gels for the second dimension. Fifty spots with more than 1.5-fold change in abundance were subjected to mass spectrometry analysis for further characterization. Among them 36 proteins could be identified, which are classified into defense and stress response, protein synthesis and processing, carbohydrate and energy metabolism, secondary metabolism, and nitrogen metabolism. Conclusion Our results showed that diverse cellular and molecular processes were affected during somatic to embryogenic transition. Differential proteomic analysis suggests a key role for ascorbate metabolism during early stage of SE, and points to the possible role of ascorbate-glutathione cycle in establishing somatic embryos. PMID:22243837

Lipoic acid metabolism and mitochondrial redox regulation.

PubMed

Solmonson, Ashley D; DeBerardinis, Ralph J

2017-11-30

Lipoic acid is an essential cofactor for mitochondrial metabolism and is synthesized de novo using intermediates from mitochondrial fatty acid synthesis type II, S-adenosylmethionine and iron-sulfur clusters. This cofactor is required for catalysis by multiple mitochondrial 2-ketoacid dehydrogenase complexes, including pyruvate dehydrogenase, alpha-ketoglutarate dehydrogenase, and branched-chain ketoacid dehydrogenase. Lipoic acid also plays a critical role in stabilizing and regulating these multi-enzyme complexes.  Many of these dehydrogenases are regulated by reactive oxygen species, mediated through the disulfide bond of the prosthetic lipoyl moiety.  Collectively, its functions explain why lipoic acid is required for cell growth, mitochondrial activity and coordination of fuel metabolism. Lipoic acid is an essential cofactor for mitochondrial metabolism and is synthesized de novo using intermediates from mitochondrial fatty acid synthesis type II, S-adenosylmethionine and iron-sulfur clusters. This cofactor is required for catalysis by multiple mitochondrial 2-ketoacid dehydrogenase complexes, including pyruvate dehydrogenase, alpha-ketoglutarate dehydrogenase, and branched-chain ketoacid dehydrogenase. Lipoic acid also plays a critical role in stabilizing and regulating these multi-enzyme complexes.  Many of these dehydrogenases are regulated by reactive oxygen species, mediated through the disulfide bond of the prosthetic lipoyl moiety.  Collectively, its functions explain why lipoic acid is required for cell growth, mitochondrial activity and coordination of fuel metabolism. Copyright © 2017, The American Society for Biochemistry and Molecular Biology.

Bioorthogonal chemical imaging of metabolic activities in live mammalian hippocampal tissues with stimulated Raman scattering

NASA Astrophysics Data System (ADS)

Hu, Fanghao; Lamprecht, Michael R.; Wei, Lu; Morrison, Barclay; Min, Wei

2016-12-01

Brain is an immensely complex system displaying dynamic and heterogeneous metabolic activities. Visualizing cellular metabolism of nucleic acids, proteins, and lipids in brain with chemical specificity has been a long-standing challenge. Recent development in metabolic labeling of small biomolecules allows the study of these metabolisms at the global level. However, these techniques generally require nonphysiological sample preparation for either destructive mass spectrometry imaging or secondary labeling with relatively bulky fluorescent labels. In this study, we have demonstrated bioorthogonal chemical imaging of DNA, RNA, protein and lipid metabolism in live rat brain hippocampal tissues by coupling stimulated Raman scattering microscopy with integrated deuterium and alkyne labeling. Heterogeneous metabolic incorporations for different molecular species and neurogenesis with newly-incorporated DNA were observed in the dentate gyrus of hippocampus at the single cell level. We further applied this platform to study metabolic responses to traumatic brain injury in hippocampal slice cultures, and observed marked upregulation of protein and lipid metabolism particularly in the hilus region of the hippocampus within days of mechanical injury. Thus, our method paves the way for the study of complex metabolic profiles in live brain tissue under both physiological and pathological conditions with single-cell resolution and minimal perturbation.

Regulation of Fatty Acid Oxidation in Mouse Cumulus-Oocyte Complexes during Maturation and Modulation by PPAR Agonists

PubMed Central

Dunning, Kylie R.; Anastasi, Marie R.; Zhang, Voueleng J.; Russell, Darryl L.; Robker, Rebecca L.

2014-01-01

Fatty acid oxidation is an important energy source for the oocyte; however, little is known about how this metabolic pathway is regulated in cumulus-oocyte complexes. Analysis of genes involved in fatty acid oxidation showed that many are regulated by the luteinizing hormone surge during in vivo maturation, including acyl-CoA synthetases, carnitine transporters, acyl-CoA dehydrogenases and acetyl-CoA transferase, but that many are dysregulated when cumulus-oocyte complexes are matured under in vitro maturation conditions using follicle stimulating hormone and epidermal growth factor. Fatty acid oxidation, measured as production of 3H2O from [3H]palmitic acid, occurs in mouse cumulus-oocyte complexes in response to the luteinizing hormone surge but is significantly reduced in cumulus-oocyte complexes matured in vitro. Thus we sought to determine whether fatty acid oxidation in cumulus-oocyte complexes could be modulated during in vitro maturation by lipid metabolism regulators, namely peroxisome proliferator activated receptor (PPAR) agonists bezafibrate and rosiglitazone. Bezafibrate showed no effect with increasing dose, while rosiglitazone dose dependently inhibited fatty acid oxidation in cumulus-oocyte complexes during in vitro maturation. To determine the impact of rosiglitazone on oocyte developmental competence, cumulus-oocyte complexes were treated with rosiglitazone during in vitro maturation and gene expression, oocyte mitochondrial activity and embryo development following in vitro fertilization were assessed. Rosiglitazone restored Acsl1, Cpt1b and Acaa2 levels in cumulus-oocyte complexes and increased oocyte mitochondrial membrane potential yet resulted in significantly fewer embryos reaching the morula and hatching blastocyst stages. Thus fatty acid oxidation is increased in cumulus-oocyte complexes matured in vivo and deficient during in vitro maturation, a known model of poor oocyte quality. That rosiglitazone further decreased fatty acid oxidation during in vitro maturation and resulted in poor embryo development points to the developmental importance of fatty acid oxidation and the need for it to be optimized during in vitro maturation to improve this reproductive technology. PMID:24505284

A broad investigation of the HBV-mediated changes to primary hepatocyte physiology reveals HBV significantly alters metabolic pathways.

PubMed

Lamontagne, R Jason; Casciano, Jessica C; Bouchard, Michael J

2018-06-01

As the leading risk factor for the development of liver cancer, chronic infection with hepatitis B virus (HBV) represents a significant global health concern. Although an effective HBV vaccine exists, at least 240 million people are chronically infected with HBV worldwide. Therapeutic options for the treatment of chronic HBV remain limited, and none achieve an absolute cure. To develop novel therapeutic targets, a better understanding of the complex network of virus-host interactions is needed. Because of the central metabolic role of the liver, we assessed the metabolic impact of HBV infection as a means to identify viral dependency factors and metabolic pathways that could serve as novel points of therapeutic intervention. Primary rat hepatocytes were infected with a control adenovirus, an adenovirus expressing a greater-than-unit-length copy of the HBV genome, or an adenovirus expressing the HBV X protein (HBx). A panel of 369 metabolites was analyzed for HBV- or HBx-induced changes 24 and 48 h post infection. Pathway analysis was used to identify key metabolic pathways altered in the presence of HBV or HBx expression, and these findings were further supported through integration of publically available gene expression data. We observed distinct changes to multiple metabolites in the context of HBV replication or HBx expression. Interestingly, a panel of 7 metabolites (maltotriose, maltose, myristate [14:0], arachidate [20:0], 3-hydroxybutyrate [BHBA], myo-inositol, and 2-palmitoylglycerol [16,0]) were altered by both HBV and HBx at both time points. In addition, incorporation of data from a transcriptome-based dataset allowed us to identify metabolic pathways, including long chain fatty acid metabolism, glycolysis, and glycogen metabolism, that were significantly altered by HBV and HBx. Because the liver is a central regulator of metabolic processes, it is important to understand how HBV replication and HBV protein expression affects the metabolic function of hepatocytes. Through analysis of a broad panel of metabolites we investigated this metabolic impact. The results of these studies have defined metabolic consequences of an HBV infection of hepatocytes and will help to lay the groundwork for novel research directions and, potentially, development of novel anti-HBV therapeutics. Copyright © 2018. Published by Elsevier Inc.

Nuclear factor-kappaB bioluminescence imaging-guided transcriptomic analysis for the assessment of host-biomaterial interaction in vivo.

PubMed

Hsiang, Chien-Yun; Chen, Yueh-Sheng; Ho, Tin-Yun

2009-06-01

Establishment of a comprehensive platform for the assessment of host-biomaterial interaction in vivo is an important issue. Nuclear factor-kappaB (NF-kappaB) is an inducible transcription factor that is activated by numerous stimuli. Therefore, NF-kappaB-dependent luminescent signal in transgenic mice carrying the luciferase genes was used as the guide to monitor the biomaterials-affected organs, and transcriptomic analysis was further applied to evaluate the complex host responses in affected organs in this study. In vivo imaging showed that genipin-cross-linked gelatin conduit (GGC) implantation evoked the strong NF-kappaB activity at 6h in the implanted region, and transcriptomic analysis showed that the expressions of interleukin-6 (IL-6), IL-24, and IL-1 family were up-regulated. A strong luminescent signal was observed in spleen on 14 d, suggesting that GGC implantation might elicit the biological events in spleen. Transcriptomic analysis of spleen showed that 13 Kyoto Encyclopedia of Genes and Genomes pathways belonging to cell cycles, immune responses, and metabolism were significantly altered by GGC implants. Connectivity Map analysis suggested that the gene signatures of GGC were similar to those of compounds that affect lipid or glucose metabolism. GeneSetTest analysis further showed that host responses to GGC implants might be related to diseases states, especially the metabolic and cardiovascular diseases. In conclusion, our data provided a concept of molecular imaging-guided transcriptomic platform for the evaluation and the prediction of host-biomaterial interaction in vivo.

Sequential Metabolism of Secondary Alkyl Amines to Metabolic-Intermediate Complexes: Opposing Roles for the Secondary Hydroxylamine and Primary Amine Metabolites of Desipramine, (S)-Fluoxetine, and N-Desmethyldiltiazem

PubMed Central

Hanson, Kelsey L.; VandenBrink, Brooke M.; Babu, Kantipudi N.; Allen, Kyle E.; Nelson, Wendel L.

2010-01-01

Three secondary amines desipramine (DES), (S)-fluoxetine [(S)-FLX], and N-desmethyldiltiazem (MA) undergo N-hydroxylation to the corresponding secondary hydroxylamines [N-hydroxydesipramine, (S)-N-hydroxyfluoxetine, and N-hydroxy-N-desmethyldiltiazem] by cytochromes P450 2C11, 2C19, and 3A4, respectively. The expected primary amine products, N-desmethyldesipramine, (S)-norfluoxetine, and N,N-didesmethyldiltiazem, are also observed. The formation of metabolic-intermediate (MI) complexes from these substrates and metabolites was examined. In each example, the initial rates of MI complex accumulation followed the order secondary hydroxylamine > secondary amine ≫ primary amine, suggesting that the primary amine metabolites do not contribute to formation of MI complexes from these secondary amines. Furthermore, the primary amine metabolites, which accumulate in incubations of the secondary amines, inhibit MI complex formation. Mass balance studies provided estimates of the product ratios of N-dealkylation to N-hydroxylation. The ratios were 2.9 (DES-CYP2C11), 3.6 [(S)-FLX-CYP2C19], and 0.8 (MA-CYP3A4), indicating that secondary hydroxylamines are significant metabolites of the P450-mediated metabolism of secondary alkyl amines. Parallel studies with N-methyl-d3-desipramine and CYP2C11 demonstrated significant isotopically sensitive switching from N-demethylation to N-hydroxylation. These findings demonstrate that the major pathway to MI complex formation from these secondary amines arises from N-hydroxylation rather than N-dealkylation and that the primary amines are significant competitive inhibitors of MI complex formation. PMID:20200233

Sequential metabolism of secondary alkyl amines to metabolic-intermediate complexes: opposing roles for the secondary hydroxylamine and primary amine metabolites of desipramine, (s)-fluoxetine, and N-desmethyldiltiazem.

PubMed

Hanson, Kelsey L; VandenBrink, Brooke M; Babu, Kantipudi N; Allen, Kyle E; Nelson, Wendel L; Kunze, Kent L

2010-06-01

Three secondary amines desipramine (DES), (S)-fluoxetine [(S)-FLX], and N-desmethyldiltiazem (MA) undergo N-hydroxylation to the corresponding secondary hydroxylamines [N-hydroxydesipramine, (S)-N-hydroxyfluoxetine, and N-hydroxy-N-desmethyldiltiazem] by cytochromes P450 2C11, 2C19, and 3A4, respectively. The expected primary amine products, N-desmethyldesipramine, (S)-norfluoxetine, and N,N-didesmethyldiltiazem, are also observed. The formation of metabolic-intermediate (MI) complexes from these substrates and metabolites was examined. In each example, the initial rates of MI complex accumulation followed the order secondary hydroxylamine > secondary amine > primary amine, suggesting that the primary amine metabolites do not contribute to formation of MI complexes from these secondary amines. Furthermore, the primary amine metabolites, which accumulate in incubations of the secondary amines, inhibit MI complex formation. Mass balance studies provided estimates of the product ratios of N-dealkylation to N-hydroxylation. The ratios were 2.9 (DES-CYP2C11), 3.6 [(S)-FLX-CYP2C19], and 0.8 (MA-CYP3A4), indicating that secondary hydroxylamines are significant metabolites of the P450-mediated metabolism of secondary alkyl amines. Parallel studies with N-methyl-d(3)-desipramine and CYP2C11 demonstrated significant isotopically sensitive switching from N-demethylation to N-hydroxylation. These findings demonstrate that the major pathway to MI complex formation from these secondary amines arises from N-hydroxylation rather than N-dealkylation and that the primary amines are significant competitive inhibitors of MI complex formation.

Rectified Brownian movement in molecular and cell biology

NASA Astrophysics Data System (ADS)

Fox, Ronald F.

1998-02-01

A unified model is presented for rectified Brownian movement as the mechanism for a variety of putatively chemomechanical energy conversions in molecular and cell biology. The model is established by a detailed analysis of ubiquinone transport in electron transport chains and of allosteric conformation changes in proteins. It is applied to P-type ATPase ion transporters and to a variety of rotary arm enzyme complexes. It provides a basis for the dynamics of actin-myosin cross-bridges in muscle fibers. In this model, metabolic free energy does no work directly, but instead biases boundary conditions for thermal diffusion. All work is done by thermal energy, which is harnessed at the expense of metabolic free energy through the establishment of the asymmetric boundary conditions.

Development of a proteomic approach to monitor protein synthesis in mycotoxin producing moulds.

PubMed

Milles, J; Krämer, J; Prange, A

2007-12-01

In general, proteome studies compare different states of metabolism to investigate external or internal influences on protein expression. In the context of mycotoxin production the method could open another view on this complex and could be helpful to gain knowledge about proteins which are involved in metabolism (enzymes, transporters). In this short technical report, we describe a new protocol suitable for protein preparation for whole proteome analysis ofFusarium graminearum. Cell lysis was performed by grinding the mycelium with liquid nitrogen. Proteins were extracted with TCA/acetone and then cleaned; the isolated proteins were separated in a 2D-gel electrophoresis system (BioRad) using different pH gradients. The protocol established seems also generally applicable for other mycotoxin producing fungi.

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.

Anti-cancer analogues ME-143 and ME-344 exert toxicity by directly inhibiting mitochondrial NADH: ubiquinone oxidoreductase (Complex I).

PubMed

Lim, Sze Chern; Carey, Kirstyn T; McKenzie, Matthew

2015-01-01

Isoflavonoids have been shown to inhibit tumor proliferation and metastasis by activating cell death pathways. As such, they have been widely studied as potential therapies for cancer prevention. The second generation synthetic isoflavan analogues ME-143 and ME-344 also exhibit anti-cancer effects, however their specific molecular targets have not been completely defined. To identify these targets, we examined the effects of ME-143 and ME-344 on cellular metabolism and found that they are potent inhibitors of mitochondrial oxidative phosphorylation (OXPHOS) complex I (NADH: ubiquinone oxidoreductase) activity. In isolated HEK293T mitochondria, ME-143 and ME-344 reduced complex I activity to 14.3% and 28.6% of control values respectively. In addition to the inhibition of complex I, ME-344 also significantly inhibited mitochondrial complex III (ubiquinol: ferricytochrome-c oxidoreductase) activity by 10.8%. This inhibition of complex I activity (and to a lesser extent complex III activity) was associated with a reduction in mitochondrial oxygen consumption. In permeabilized HEK293T cells, ME-143 and ME-344 significantly reduced the maximum ADP-stimulated respiration rate to 62.3% and 70.0% of control levels respectively in the presence of complex I-linked substrates. Conversely, complex II-linked respiration was unaffected by either drug. We also observed that the inhibition of complex I-linked respiration caused the dissipation of the mitochondrial membrane potential (ΔΨm). Blue native (BN-PAGE) analysis revealed that prolonged loss of ΔΨm results in the destabilization of the native OXPHOS complexes. In particular, treatment of 143B osteosarcoma, HeLa and HEK293T human embryonic kidney cells with ME-344 for 4 h resulted in reduced steady-state levels of mature complex I. Degradation of the complex I subunit NDUFA9, as well as the complex IV (ferrocytochrome c: oxygen oxidoreductase) subunit COXIV, was also evident. The identification of OXPHOS complex I as a target of ME-143 and ME-344 advances our understanding of how these drugs induce cell death by disrupting mitochondrial metabolism, and will direct future work to maximize the anti-cancer capacity of these and other isoflavone-based compounds.

Fast and automated characterization of major constituents in rat biofluid after oral administration of Abelmoschus manihot extract using ultra-performance liquid chromatography/quadrupole time-of-flight mass spectrometry and MetaboLynx.

PubMed

Guo, Jianming; Shang, Er-Xin; Duan, Jin-Ao; Tang, Yuping; Qian, Dawei; Su, Shulan

2010-02-01

In drug metabolism research, the setting up of a complex series of mass spectrometry experiments and the subsequent analysis of the large amounts of data produced are often time-consuming. In this paper, we describe a strategy using ultra-performance liquid chromatography/quadrupole time-of-flight mass spectrometry (UPLC/QTOFMS) with automated data analysis software (MetaboLynx) for fast analysis of the metabolic profile of flavonoids in Abelmoschus manihot. Rat plasma and urine samples collected 1 h and 0-12 h after oral administration of Abelmoschus manihot were analyzed by UPLC/QTOFMS within 15 min. The post-acquisition data were processed using MetaboLynx. With key parameters carefully set, MetaboLynx is able to show the presence of a wide range of metabolites with only a limited requirement for manual intervention and data interpretation time. A total of 16 and 38 metabolites were identified in plasma and urine compared with blank samples. The results indicated that methylation and glucuronidation after deglycosylation were the major metabolic pathways of flavonoid glycosides in Abelmoschus manihot. The present study provided important information about the metabolism of flavonoid glycosides in Abelmoschus manihot which will be helpful for fully understanding the mechanism of action of this herb. Furthermore, this work demonstrated the potential of the UPLC/QTOFMS approach using MetaboLynx for fast and automated identification of metabolites from Chinese herbal medicines. Copyright (c) 2010 John Wiley & Sons, Ltd.

Characterization of the pharmacokinetics of gasoline using PBPK modeling with a complex mixtures chemical lumping approach.

PubMed

Dennison, James E; Andersen, Melvin E; Yang, Raymond S H

2003-09-01

Gasoline consists of a few toxicologically significant components and a large number of other hydrocarbons in a complex mixture. By using an integrated, physiologically based pharmacokinetic (PBPK) modeling and lumping approach, we have developed a method for characterizing the pharmacokinetics (PKs) of gasoline in rats. The PBPK model tracks selected target components (benzene, toluene, ethylbenzene, o-xylene [BTEX], and n-hexane) and a lumped chemical group representing all nontarget components, with competitive metabolic inhibition between all target compounds and the lumped chemical. PK data was acquired by performing gas uptake PK studies with male F344 rats in a closed chamber. Chamber air samples were analyzed every 10-20 min by gas chromatography/flame ionization detection and all nontarget chemicals were co-integrated. A four-compartment PBPK model with metabolic interactions was constructed using the BTEX, n-hexane, and lumped chemical data. Target chemical kinetic parameters were refined by studies with either the single chemical alone or with all five chemicals together. o-Xylene, at high concentrations, decreased alveolar ventilation, consistent with respiratory irritation. A six-chemical interaction model with the lumped chemical group was used to estimate lumped chemical partitioning and metabolic parameters for a winter blend of gasoline with methyl t-butyl ether and a summer blend without any oxygenate. Computer simulation results from this model matched well with experimental data from single chemical, five-chemical mixture, and the two blends of gasoline. The PBPK model analysis indicated that metabolism of individual components was inhibited up to 27% during the 6-h gas uptake experiments of gasoline exposures.

Hepatic Steatosis as a Marker of Metabolic Dysfunction

PubMed Central

Fabbrini, Elisa; Magkos, Faidon

2015-01-01

Nonalcoholic fatty liver disease (NAFLD) is the liver manifestation of the complex metabolic derangements associated with obesity. NAFLD is characterized by excessive deposition of fat in the liver (steatosis) and develops when hepatic fatty acid availability from plasma and de novo synthesis exceeds hepatic fatty acid disposal by oxidation and triglyceride export. Hepatic steatosis is therefore the biochemical result of an imbalance between complex pathways of lipid metabolism, and is associated with an array of adverse changes in glucose, fatty acid, and lipoprotein metabolism across all tissues of the body. Intrahepatic triglyceride (IHTG) content is therefore a very good marker (and in some cases may be the cause) of the presence and the degree of multiple-organ metabolic dysfunction. These metabolic abnormalities are likely responsible for many cardiometabolic risk factors associated with NAFLD, such as insulin resistance, type 2 diabetes mellitus, and dyslipidemia. Understanding the factors involved in the pathogenesis and pathophysiology of NAFLD will lead to a better understanding of the mechanisms responsible for the metabolic complications of obesity, and hopefully to the discovery of novel effective treatments for their reversal. PMID:26102213

Contribution of Inhibitor of DNA Binding/Differentiation-3 and Endocrine Disrupting Chemicals to Pathophysiological Aspects of Chronic Disease

PubMed Central

2017-01-01

The overwhelming increase in the global incidence of obesity and its associated complications such as insulin resistance, atherosclerosis, pulmonary disease, and degenerative disorders including dementia constitutes a serious public health problem. The Inhibitor of DNA Binding/Differentiation-3 (ID3), a member of the ID family of transcriptional regulators, has been shown to play a role in adipogenesis and therefore ID3 may influence obesity and metabolic health in response to environmental factors. This review will highlight the current understanding of how ID3 may contribute to complex chronic diseases via metabolic perturbations. Based on the increasing number of reports that suggest chronic exposure to and accumulation of endocrine disrupting chemicals (EDCs) within the human body are associated with metabolic disorders, we will also consider the impact of these chemicals on ID3. Improved understanding of the ID3 pathways by which exposure to EDCs can potentiate complex chronic diseases in populations with metabolic disorders (obesity, metabolic syndrome, and glucose intolerance) will likely provide useful knowledge in the prevention and control of complex chronic diseases associated with exposure to environmental pollutants. PMID:28785583

Megadalton Complexes in the Chloroplast Stroma of Arabidopsis thaliana Characterized by Size Exclusion Chromatography, Mass Spectrometry, and Hierarchical Clustering*

PubMed Central

Olinares, Paul Dominic B.; Ponnala, Lalit; van Wijk, Klaas J.

2010-01-01

To characterize MDa-sized macromolecular chloroplast stroma protein assemblies and to extend coverage of the chloroplast stroma proteome, we fractionated soluble chloroplast stroma in the non-denatured state by size exclusion chromatography with a size separation range up to ∼5 MDa. To maximize protein complex stability and resolution of megadalton complexes, ionic strength and composition were optimized. Subsequent high accuracy tandem mass spectrometry analysis (LTQ-Orbitrap) identified 1081 proteins across the complete native mass range. Protein complexes and assembly states above 0.8 MDa were resolved using hierarchical clustering, and protein heat maps were generated from normalized protein spectral counts for each of the size exclusion chromatography fractions; this complemented previous analysis of stromal complexes up to 0.8 MDa (Peltier, J. B., Cai, Y., Sun, Q., Zabrouskov, V., Giacomelli, L., Rudella, A., Ytterberg, A. J., Rutschow, H., and van Wijk, K. J. (2006) The oligomeric stromal proteome of Arabidopsis thaliana chloroplasts. Mol. Cell. Proteomics 5, 114–133). This combined experimental and bioinformatics analyses resolved chloroplast ribosomes in different assembly and functional states (e.g. 30, 50, and 70 S), which enabled the identification of plastid homologues of prokaryotic ribosome assembly factors as well as proteins involved in co-translational modifications, targeting, and folding. The roles of these ribosome-associating proteins will be discussed. Known RNA splice factors (e.g. CAF1/WTF1/RNC1) as well as uncharacterized proteins with RNA-binding domains (pentatricopeptide repeat, RNA recognition motif, and chloroplast ribosome maturation), RNases, and DEAD box helicases were found in various sized complexes. Chloroplast DNA (>3 MDa) was found in association with the complete heteromeric plastid-encoded DNA polymerase complex, and a dozen other DNA-binding proteins, e.g. DNA gyrase, topoisomerase, and various DNA repair enzymes. The heteromeric ≥5-MDa pyruvate dehydrogenase complex and the 0.8–1-MDa acetyl-CoA carboxylase complex associated with uncharacterized biotin carboxyl carrier domain proteins constitute the entry point to fatty acid metabolism in leaves; we suggest that their large size relates to the need for metabolic channeling. Protein annotations and identification data are available through the Plant Proteomics Database, and mass spectrometry data are available through Proteomics Identifications database. PMID:20423899

BioLayout(Java): versatile network visualisation of structural and functional relationships.

PubMed

Goldovsky, Leon; Cases, Ildefonso; Enright, Anton J; Ouzounis, Christos A

2005-01-01

Visualisation of biological networks is becoming a common task for the analysis of high-throughput data. These networks correspond to a wide variety of biological relationships, such as sequence similarity, metabolic pathways, gene regulatory cascades and protein interactions. We present a general approach for the representation and analysis of networks of variable type, size and complexity. The application is based on the original BioLayout program (C-language implementation of the Fruchterman-Rheingold layout algorithm), entirely re-written in Java to guarantee portability across platforms. BioLayout(Java) provides broader functionality, various analysis techniques, extensions for better visualisation and a new user interface. Examples of analysis of biological networks using BioLayout(Java) are presented.

The transcriptional activator GaaR of Aspergillus niger is required for release and utilization of d- galacturonic acid from pectin

DOE PAGES

Alazi, Ebru; Niu, Jing; Kowalczyk, Joanna E.; ...

2016-05-13

We identified the d-galacturonic acid (GA)-responsive transcriptional activator GaaR of the saprotrophic fungus, Aspergillus niger, which was found to be essential for growth on GA and polygalacturonic acid (PGA). Growth of the ΔgaaR strain was reduced on complex pectins. Genome-wide expression analysis showed that GaaR is required for the expression of genes necessary to release GA from PGA and more complex pectins, to transport GA into the cell, and to induce the GA catabolic pathway. Residual growth of ΔgaaR on complex pectins is likely due to the expression of pectinases acting on rhamnogalacturonan and subsequent metabolism of the monosaccharides othermore » than GA.« less

Unravelling the molecular basis for light modulated cellulase gene expression - the role of photoreceptors in Neurospora crassa

PubMed Central

2012-01-01

Background Light represents an important environmental cue, which exerts considerable influence on the metabolism of fungi. Studies with the biotechnological fungal workhorse Trichoderma reesei (Hypocrea jecorina) have revealed an interconnection between transcriptional regulation of cellulolytic enzymes and the light response. Neurospora crassa has been used as a model organism to study light and circadian rhythm biology. We therefore investigated whether light also regulates transcriptional regulation of cellulolytic enzymes in N. crassa. Results We show that the N. crassa photoreceptor genes wc-1, wc-2 and vvd are involved in regulation of cellulase gene expression, indicating that this phenomenon is conserved among filamentous fungi. The negative effect of VVD on production of cellulolytic enzymes is thereby accomplished by its role in photoadaptation and hence its function in White collar complex (WCC) formation. In contrast, the induction of vvd expression by the WCC does not seem to be crucial in this process. Additionally, we found that WC-1 and WC-2 not only act as a complex, but also have individual functions upon growth on cellulose. Conclusions Genome wide transcriptome analysis of photoreceptor mutants and evaluation of results by analysis of mutant strains identified several candidate genes likely to play a role in light modulated cellulase gene expression. Genes with functions in amino acid metabolism, glycogen metabolism, energy supply and protein folding are enriched among genes with decreased expression levels in the wc-1 and wc-2 mutants. The ability to properly respond to amino acid starvation, i. e. up-regulation of the cross pathway control protein cpc-1, was found to be beneficial for cellulase gene expression. Our results further suggest a contribution of oxidative depolymerization of cellulose to plant cell wall degradation in N. crassa. PMID:22462823

Comparative ultrastructure of fruit plastids in three genetically diverse genotypes of apple (Malus × domestica Borkh.) during development.

PubMed

Schaeffer, Scott M; Christian, Ryan; Castro-Velasquez, Nohely; Hyden, Brennan; Lynch-Holm, Valerie; Dhingra, Amit

2017-10-01

Comparative ultrastructural developmental time-course analysis has identified discrete stages at which the fruit plastids undergo structural and consequently functional transitions to facilitate subsequent development-guided understanding of the complex plastid biology. Plastids are the defining organelle for a plant cell and are critical for myriad metabolic functions. The role of leaf plastid, chloroplast, is extensively documented; however, fruit plastids-chromoplasts-are poorly understood, especially in the context of the diverse metabolic processes operating in these diverse plant organs. Recently, in a comparative study of the predicted plastid-targeted proteomes across seven plant species, we reported that each plant species is predicted to harbor a unique set of plastid-targeted proteins. However, the temporal and developmental context of these processes remains unknown. In this study, an ultrastructural analysis approach was used to characterize fruit plastids in the epidermal and collenchymal cell layers at 11 developmental timepoints in three genotypes of apple (Malus × domestica Borkh.): chlorophyll-predominant 'Granny Smith', carotenoid-predominant 'Golden Delicious', and anthocyanin-predominant 'Top Red Delicious'. Plastids transitioned from a proplastid-like plastid to a chromoplast-like plastid in epidermis cells, while in the collenchyma cells, they transitioned from a chloroplast-like plastid to a chloro-chromo-amyloplast plastid. Plastids in the collenchyma cells of the three genotypes demonstrated a diverse array of structures and features. This study enabled the identification of discrete developmental stages during which specific functions are most likely being performed by the plastids as indicated by accumulation of plastoglobuli, starch granules, and other sub-organeller structures. Information regarding the metabolically active developmental stages is expected to facilitate biologically relevant omics studies to unravel the complex biochemistry of plastids in perennial non-model systems.

Metabolism. Part III: Lipids.

ERIC Educational Resources Information Center

Bodner, George M.

1986-01-01

Describes the metabolic processes of complex lipids, including saponification, activation and transport, and the beta-oxidation spiral. Discusses fatty acid degradation in regard to biochemical energy and ketone bodies. (TW)

Identification of the Mitochondrial Heme Metabolism Complex

PubMed Central

Medlock, Amy E.; Shiferaw, Mesafint T.; Marcero, Jason R.; Vashisht, Ajay A.; Wohlschlegel, James A.; Phillips, John D.; Dailey, Harry A.

2015-01-01

Heme is an essential cofactor for most organisms and all metazoans. While the individual enzymes involved in synthesis and utilization of heme are fairly well known, less is known about the intracellular trafficking of porphyrins and heme, or regulation of heme biosynthesis via protein complexes. To better understand this process we have undertaken a study of macromolecular assemblies associated with heme synthesis. Herein we have utilized mass spectrometry with coimmunoprecipitation of tagged enzymes of the heme biosynthetic pathway in a developing erythroid cell culture model to identify putative protein partners. The validity of these data obtained in the tagged protein system is confirmed by normal porphyrin/heme production by the engineered cells. Data obtained are consistent with the presence of a mitochondrial heme metabolism complex which minimally consists of ferrochelatase, protoporphyrinogen oxidase and aminolevulinic acid synthase-2. Additional proteins involved in iron and intermediary metabolism as well as mitochondrial transporters were identified as potential partners in this complex. The data are consistent with the known location of protein components and support a model of transient protein-protein interactions within a dynamic protein complex. PMID:26287972

Clustering of Genetically Defined Allele Classes in the Caenorhabditis elegans DAF-2 Insulin/IGF-1 Receptor

PubMed Central

Patel, Dhaval S.; Garza-Garcia, Acely; Nanji, Manoj; McElwee, Joshua J.; Ackerman, Daniel; Driscoll, Paul C.; Gems, David

2008-01-01

The DAF-2 insulin/IGF-1 receptor regulates development, metabolism, and aging in the nematode Caenorhabditis elegans. However, complex differences among daf-2 alleles complicate analysis of this gene. We have employed epistasis analysis, transcript profile analysis, mutant sequence analysis, and homology modeling of mutant receptors to understand this complexity. We define an allelic series of nonconditional daf-2 mutants, including nonsense and deletion alleles, and a putative null allele, m65. The most severe daf-2 alleles show incomplete suppression by daf-18(0) and daf-16(0) and have a range of effects on early development. Among weaker daf-2 alleles there exist distinct mutant classes that differ in epistatic interactions with mutations in other genes. Mutant sequence analysis (including 11 newly sequenced alleles) reveals that class 1 mutant lesions lie only in certain extracellular regions of the receptor, while class 2 (pleiotropic) and nonconditional missense mutants have lesions only in the ligand-binding pocket of the receptor ectodomain or the tyrosine kinase domain. Effects of equivalent mutations on the human insulin receptor suggest an altered balance of intracellular signaling in class 2 alleles. These studies consolidate and extend our understanding of the complex genetics of daf-2 and its underlying molecular biology. PMID:18245374

A global approach to analysis and interpretation of metabolic data for plant natural product discovery.

PubMed

Hur, Manhoi; Campbell, Alexis Ann; Almeida-de-Macedo, Marcia; Li, Ling; Ransom, Nick; Jose, Adarsh; Crispin, Matt; Nikolau, Basil J; Wurtele, Eve Syrkin

2013-04-01

Discovering molecular components and their functionality is key to the development of hypotheses concerning the organization and regulation of metabolic networks. The iterative experimental testing of such hypotheses is the trajectory that can ultimately enable accurate computational modelling and prediction of metabolic outcomes. This information can be particularly important for understanding the biology of natural products, whose metabolism itself is often only poorly defined. Here, we describe factors that must be in place to optimize the use of metabolomics in predictive biology. A key to achieving this vision is a collection of accurate time-resolved and spatially defined metabolite abundance data and associated metadata. One formidable challenge associated with metabolite profiling is the complexity and analytical limits associated with comprehensively determining the metabolome of an organism. Further, for metabolomics data to be efficiently used by the research community, it must be curated in publicly available metabolomics databases. Such databases require clear, consistent formats, easy access to data and metadata, data download, and accessible computational tools to integrate genome system-scale datasets. Although transcriptomics and proteomics integrate the linear predictive power of the genome, the metabolome represents the nonlinear, final biochemical products of the genome, which results from the intricate system(s) that regulate genome expression. For example, the relationship of metabolomics data to the metabolic network is confounded by redundant connections between metabolites and gene-products. However, connections among metabolites are predictable through the rules of chemistry. Therefore, enhancing the ability to integrate the metabolome with anchor-points in the transcriptome and proteome will enhance the predictive power of genomics data. We detail a public database repository for metabolomics, tools and approaches for statistical analysis of metabolomics data, and methods for integrating these datasets with transcriptomic data to create hypotheses concerning specialized metabolisms that generate the diversity in natural product chemistry. We discuss the importance of close collaborations among biologists, chemists, computer scientists and statisticians throughout the development of such integrated metabolism-centric databases and software.

A global approach to analysis and interpretation of metabolic data for plant natural product discovery†

PubMed Central

Hur, Manhoi; Campbell, Alexis Ann; Almeida-de-Macedo, Marcia; Li, Ling; Ransom, Nick; Jose, Adarsh; Crispin, Matt; Nikolau, Basil J.

2013-01-01

Discovering molecular components and their functionality is key to the development of hypotheses concerning the organization and regulation of metabolic networks. The iterative experimental testing of such hypotheses is the trajectory that can ultimately enable accurate computational modelling and prediction of metabolic outcomes. This information can be particularly important for understanding the biology of natural products, whose metabolism itself is often only poorly defined. Here, we describe factors that must be in place to optimize the use of metabolomics in predictive biology. A key to achieving this vision is a collection of accurate time-resolved and spatially defined metabolite abundance data and associated metadata. One formidable challenge associated with metabolite profiling is the complexity and analytical limits associated with comprehensively determining the metabolome of an organism. Further, for metabolomics data to be efficiently used by the research community, it must be curated in publically available metabolomics databases. Such databases require clear, consistent formats, easy access to data and metadata, data download, and accessible computational tools to integrate genome system-scale datasets. Although transcriptomics and proteomics integrate the linear predictive power of the genome, the metabolome represents the nonlinear, final biochemical products of the genome, which results from the intricate system(s) that regulate genome expression. For example, the relationship of metabolomics data to the metabolic network is confounded by redundant connections between metabolites and gene-products. However, connections among metabolites are predictable through the rules of chemistry. Therefore, enhancing the ability to integrate the metabolome with anchor-points in the transcriptome and proteome will enhance the predictive power of genomics data. We detail a public database repository for metabolomics, tools and approaches for statistical analysis of metabolomics data, and methods for integrating these dataset with transcriptomic data to create hypotheses concerning specialized metabolism that generates the diversity in natural product chemistry. We discuss the importance of close collaborations among biologists, chemists, computer scientists and statisticians throughout the development of such integrated metabolism-centric databases and software. PMID:23447050

Integrated, systems metabolic picture of acetone-butanol-ethanol fermentation by Clostridium acetobutylicum.

PubMed

Liao, Chen; Seo, Seung-Oh; Celik, Venhar; Liu, Huaiwei; Kong, Wentao; Wang, Yi; Blaschek, Hans; Jin, Yong-Su; Lu, Ting

2015-07-07

Microbial metabolism involves complex, system-level processes implemented via the orchestration of metabolic reactions, gene regulation, and environmental cues. One canonical example of such processes is acetone-butanol-ethanol (ABE) fermentation by Clostridium acetobutylicum, during which cells convert carbon sources to organic acids that are later reassimilated to produce solvents as a strategy for cellular survival. The complexity and systems nature of the process have been largely underappreciated, rendering challenges in understanding and optimizing solvent production. Here, we present a system-level computational framework for ABE fermentation that combines metabolic reactions, gene regulation, and environmental cues. We developed the framework by decomposing the entire system into three modules, building each module separately, and then assembling them back into an integrated system. During the model construction, a bottom-up approach was used to link molecular events at the single-cell level into the events at the population level. The integrated model was able to successfully reproduce ABE fermentations of the WT C. acetobutylicum (ATCC 824), as well as its mutants, using data obtained from our own experiments and from literature. Furthermore, the model confers successful predictions of the fermentations with various network perturbations across metabolic, genetic, and environmental aspects. From foundation to applications, the framework advances our understanding of complex clostridial metabolism and physiology and also facilitates the development of systems engineering strategies for the production of advanced biofuels.

Integrated, systems metabolic picture of acetone-butanol-ethanol fermentation by Clostridium acetobutylicum

PubMed Central

Liao, Chen; Seo, Seung-Oh; Celik, Venhar; Liu, Huaiwei; Kong, Wentao; Wang, Yi; Blaschek, Hans; Jin, Yong-Su; Lu, Ting

2015-01-01

Microbial metabolism involves complex, system-level processes implemented via the orchestration of metabolic reactions, gene regulation, and environmental cues. One canonical example of such processes is acetone-butanol-ethanol (ABE) fermentation by Clostridium acetobutylicum, during which cells convert carbon sources to organic acids that are later reassimilated to produce solvents as a strategy for cellular survival. The complexity and systems nature of the process have been largely underappreciated, rendering challenges in understanding and optimizing solvent production. Here, we present a system-level computational framework for ABE fermentation that combines metabolic reactions, gene regulation, and environmental cues. We developed the framework by decomposing the entire system into three modules, building each module separately, and then assembling them back into an integrated system. During the model construction, a bottom-up approach was used to link molecular events at the single-cell level into the events at the population level. The integrated model was able to successfully reproduce ABE fermentations of the WT C. acetobutylicum (ATCC 824), as well as its mutants, using data obtained from our own experiments and from literature. Furthermore, the model confers successful predictions of the fermentations with various network perturbations across metabolic, genetic, and environmental aspects. From foundation to applications, the framework advances our understanding of complex clostridial metabolism and physiology and also facilitates the development of systems engineering strategies for the production of advanced biofuels. PMID:26100881

A structured approach to the study of metabolic control principles in intact and impaired mitochondria.

PubMed

Huber, Heinrich J; Connolly, Niamh M C; Dussmann, Heiko; Prehn, Jochen H M

2012-03-01

We devised an approach to extract control principles of cellular bioenergetics for intact and impaired mitochondria from ODE-based models and applied it to a recently established bioenergetic model of cancer cells. The approach used two methods for varying ODE model parameters to determine those model components that, either alone or in combination with other components, most decisively regulated bioenergetic state variables. We found that, while polarisation of the mitochondrial membrane potential (ΔΨ(m)) and, therefore, the protomotive force were critically determined by respiratory complex I activity in healthy mitochondria, complex III activity was dominant for ΔΨ(m) during conditions of cytochrome-c deficiency. As a further important result, cellular bioenergetics in healthy, ATP-producing mitochondria was regulated by three parameter clusters that describe (1) mitochondrial respiration, (2) ATP production and consumption and (3) coupling of ATP-production and respiration. These parameter clusters resembled metabolic blocks and their intermediaries from top-down control analyses. However, parameter clusters changed significantly when cells changed from low to high ATP levels or when mitochondria were considered to be impaired by loss of cytochrome-c. This change suggests that the assumption of static metabolic blocks by conventional top-down control analyses is not valid under these conditions. Our approach is complementary to both ODE and top-down control analysis approaches and allows a better insight into cellular bioenergetics and its pathological alterations.

[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.

Twenty novel mutations in BCKDHA, BCKDHB and DBT genes in a cohort of 52 Saudi Arabian patients with maple syrup urine disease.

PubMed

Imtiaz, Faiqa; Al-Mostafa, Abeer; Allam, Rabab; Ramzan, Khushnooda; Al-Tassan, Nada; Tahir, Asma I; Al-Numair, Nouf S; Al-Hamed, Mohamed H; Al-Hassnan, Zuhair; Al-Owain, Mohammad; Al-Zaidan, Hamad; Al-Amoudi, Mohammad; Qari, Alya; Balobaid, Ameera; Al-Sayed, Moeenaldeen

2017-06-01

Maple syrup urine disease (MSUD), an autosomal recessive inborn error of metabolism due to defects in the branched-chain α-ketoacid dehydrogenase (BCKD) complex, is commonly observed among other inherited metabolic disorders in the kingdom of Saudi Arabia. This report presents the results of mutation analysis of three of the four genes encoding the BCKD complex in 52 biochemically diagnosed MSUD patients originating from Saudi Arabia. The 25 mutations (20 novel) detected spanned across the entire coding regions of the BCKHDA , BCKDHB and DBT genes. There were no mutations found in the DLD gene in this cohort of patients. Prediction effects, conservation and modelling of novel mutations demonstrated that all were predicted to be disease-causing. All mutations presented in a homozygous form and we did not detect the presence of a "founder" mutation in any of three genes. In addition, prenatal molecular genetic testing was successfully carried out on chorionic villus samples or amniocenteses in 10 expectant mothers with affected children with MSUD, molecularly characterized by this study.

In silico metabolic engineering of Clostridium ljungdahlii for synthesis gas fermentation.

PubMed

Chen, Jin; Henson, Michael A

2016-11-01

Synthesis gas fermentation is one of the most promising routes to convert synthesis gas (syngas; mainly comprised of H 2 and CO) to renewable liquid fuels and chemicals by specialized bacteria. The most commonly studied syngas fermenting bacterium is Clostridium ljungdahlii, which produces acetate and ethanol as its primary metabolic byproducts. Engineering of C. ljungdahlii metabolism to overproduce ethanol, enhance the synthesize of the native byproducts lactate and 2,3-butanediol, and introduce the synthesis of non-native products such as butanol and butyrate has substantial commercial value. We performed in silico metabolic engineering studies using a genome-scale reconstruction of C. ljungdahlii metabolism and the OptKnock computational framework to identify gene knockouts that were predicted to enhance the synthesis of these native products and non-native products, introduced through insertion of the necessary heterologous pathways. The OptKnock derived strategies were often difficult to assess because increase product synthesis was invariably accompanied by decreased growth. Therefore, the OptKnock strategies were further evaluated using a spatiotemporal metabolic model of a syngas bubble column reactor, a popular technology for large-scale gas fermentation. Unlike flux balance analysis, the bubble column model accounted for the complex tradeoffs between increased product synthesis and reduced growth rates of engineered mutants within the spatially varying column environment. The two-stage methodology for deriving and evaluating metabolic engineering strategies was shown to yield new C. ljungdahlii gene targets that offer the potential for increased product synthesis under realistic syngas fermentation conditions. Copyright © 2016 International Metabolic Engineering Society. Published by Elsevier Inc. All rights reserved.

Community composition, diversity, and metabolism of intestinal microbiota in cultivated European eel (Anguilla anguilla).

PubMed

Huang, Wei; Cheng, Zhiqiang; Lei, Shaonan; Liu, Lanying; Lv, Xin; Chen, Lihua; Wu, Miaohong; Wang, Chao; Tian, Baoyu; Song, Yongkang

2018-05-01

The intestinal tract, which harbours tremendous numbers of bacteria, plays a pivotal role in the digestion and absorption of nutrients. Here, high-throughput sequencing technology was used to determine the community composition and complexity of the intestinal microbiota in cultivated European eels during three stages of their lifecycle, after which the metabolic potentials of their intestinal microbial communities were assessed. The results demonstrated that European eel intestinal microbiota were dominated by bacteria in the phyla Proteobacteria and Fusobacteria. Statistical analyses revealed that the three cultured European eel life stages (elver, yellow eel, and silver eel) shared core microbiota dominated by Aeromonas. Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) predictions of metagenome function revealed that the European eel intestinal microbiota might play significant roles in host nutrient metabolism. Biolog AN MicroPlate™ analysis and extracellular enzyme assays of culturable intestinal bacteria showed that the intestinal microbiota have a marked advantage in the metabolism of starch, which is the main carbohydrate component in European eel formulated feed. Understanding the ecology and functions of the intestinal microbiota during different developmental stages will help us improve the effects of fish-based bacteria on the composition and metabolic capacity of nutrients in European eels.

Effect of Prolonged Simulated Microgravity on Metabolic Proteins in Rat Hippocampus: Steps toward Safe Space Travel.

PubMed

Wang, Yun; Javed, Iqbal; Liu, Yahui; Lu, Song; Peng, Guang; Zhang, Yongqian; Qing, Hong; Deng, Yulin

2016-01-04

Mitochondria are not only the main source of energy in cells but also produce reactive oxygen species (ROS), which result in oxidative stress when in space. This oxidative stress is responsible for energy imbalances and cellular damage. In this study, a rat tail suspension model was used in individual experiments for 7 and 21 days to explore the effect of simulated microgravity (SM) on metabolic proteins in the hippocampus, a vital brain region involved in learning, memory, and navigation. A comparative (18)O-labeled quantitative proteomic strategy was used to observe the differential expression of metabolic proteins. Forty-two and sixty-seven mitochondrial metabolic proteins were differentially expressed after 21 and 7 days of SM, respectively. Mitochondrial Complex I, III, and IV, isocitrate dehydrogenase and malate dehydrogenase were down-regulated. Moreover, DJ-1 and peroxiredoxin 6, which defend against oxidative damage, were up-regulated in the hippocampus. Western blot analysis of proteins DJ-1 and COX 5A confirmed the mass spectrometry results. Despite these changes in mitochondrial protein expression, no obvious cell apoptosis was observed after 21 days of SM. The results of this study indicate that the oxidative stress induced by SM has profound effects on metabolic proteins.

Requirement for the Mitochondrial Pyruvate Carrier in Mammalian Development Revealed by a Hypomorphic Allelic Series

PubMed Central

Bowman, Caitlyn E.; Hartung, Thomas

2016-01-01

Glucose and oxygen are two of the most important molecules transferred from mother to fetus during eutherian pregnancy, and the metabolic fates of these nutrients converge at the transport and metabolism of pyruvate in mitochondria. Pyruvate enters the mitochondrial matrix through the mitochondrial pyruvate carrier (MPC), a complex in the inner mitochondrial membrane that consists of two essential components, MPC1 and MPC2. Here, we define the requirement for mitochondrial pyruvate metabolism during development with a progressive allelic series of Mpc1 deficiency in mouse. Mpc1 deletion was homozygous lethal in midgestation, but Mpc1 hypomorphs and tissue-specific deletion of Mpc1 presented as early perinatal lethality. The allelic series demonstrated that graded suppression of MPC resulted in dose-dependent metabolic and transcriptional changes. Steady-state metabolomics analysis of brain and liver from Mpc1 hypomorphic embryos identified compensatory changes in amino acid and lipid metabolism. Flux assays in Mpc1-deficient embryonic fibroblasts also reflected these changes, including a dramatic increase in mitochondrial alanine utilization. The mitochondrial alanine transaminase GPT2 was found to be necessary and sufficient for increased alanine flux upon MPC inhibition. These data show that impaired mitochondrial pyruvate transport results in biosynthetic deficiencies that can be mitigated in part by alternative anaplerotic substrates in utero. PMID:27215380

Model-based Confirmation of Alternative Substrates of Mitochondrial Electron Transport Chain

PubMed Central

Kleessen, Sabrina; Araújo, Wagner L.; Fernie, Alisdair R.; Nikoloski, Zoran

2012-01-01

Discrimination of metabolic models based on high throughput metabolomics data, reflecting various internal and external perturbations, is essential for identifying the components that contribute to the emerging behavior of metabolic processes. Here, we investigate 12 different models of the mitochondrial electron transport chain (ETC) in Arabidopsis thaliana during dark-induced senescence in order to elucidate the alternative substrates to this metabolic pathway. Our findings demonstrate that the coupling of the proposed computational approach, based on dynamic flux balance analysis, with time-resolved metabolomics data results in model-based confirmations of the hypotheses that, during dark-induced senescence in Arabidopsis, (i) under conditions where the main substrate for the ETC are not fully available, isovaleryl-CoA dehydrogenase and 2-hydroxyglutarate dehydrogenase are able to donate electrons to the ETC, (ii) phytanoyl-CoA does not act even as an indirect substrate of the electron transfer flavoprotein/electron-transfer flavoprotein:ubiquinone oxidoreductase complex, and (iii) the mitochondrial γ-aminobutyric acid transporter has functional significance in maintaining mitochondrial metabolism. Our study provides a basic framework for future in silico studies of alternative pathways in mitochondrial metabolism under extended darkness whereby the role of its components can be computationally discriminated based on available molecular profile data. PMID:22334689

Metabolome analysis of biosynthetic mutants reveals a diversity of metabolic changes and allows identification of a large number of new compounds in Arabidopsis.

PubMed

Böttcher, Christoph; von Roepenack-Lahaye, Edda; Schmidt, Jürgen; Schmotz, Constanze; Neumann, Steffen; Scheel, Dierk; Clemens, Stephan

2008-08-01

Metabolomics is facing a major challenge: the lack of knowledge about metabolites present in a given biological system. Thus, large-scale discovery of metabolites is considered an essential step toward a better understanding of plant metabolism. We show here that the application of a metabolomics approach generating structural information for the analysis of Arabidopsis (Arabidopsis thaliana) mutants allows the efficient cataloging of metabolites. Fifty-six percent of the features that showed significant differences in abundance between seeds of wild-type, transparent testa4, and transparent testa5 plants could be annotated. Seventy-five compounds were structurally characterized, 21 of which could be identified. About 40 compounds had not been known from Arabidopsis before. Also, the high-resolution analysis revealed an unanticipated expansion of metabolic conversions upstream of biosynthetic blocks. Deficiency in chalcone synthase results in the increased seed-specific biosynthesis of a range of phenolic choline esters. Similarly, a lack of chalcone isomerase activity leads to the accumulation of various naringenin chalcone derivatives. Furthermore, our data provide insight into the connection between p-coumaroyl-coenzyme A-dependent pathways. Lack of flavonoid biosynthesis results in elevated synthesis not only of p-coumarate-derived choline esters but also of sinapate-derived metabolites. However, sinapoylcholine is not the only accumulating end product. Instead, we observed specific and sophisticated changes in the complex pattern of sinapate derivatives.

The investigation of immunoprotective and sedative hypnotic effect of total polysaccharide from Suanzaoren decoction by serum metabonomics approach.

PubMed

Niu, Xiaoyi; He, Bosai; Du, Yiyang; Sui, Zhenyu; Rong, Weiwei; Wang, Xiaotong; Li, Qing; Bi, Kaishun

2018-06-01

Suanzaoren decoction, as one of the traditional Chinese medicine prescriptions, has been most commonly used in Asian countries and reported to inhibit the process of immunodeficiency insomnia. Polysaccharide is important component which also contributes to the role of immunoprotective and sedative hypnotic effects. This study was aimed to explore the immunoprotective and sedative hypnotic mechanisms of polysaccharide from Suanzaoren decoction by serum metabonomics approach. With this purpose, complex physical and chemical immunodeficiency insomnia models were firstly established according to its multi-target property. Serum samples were analyzed using UHPLC/Q-TOF-MS spectrometry approach to determine endogenous metabolites. Then, principal component analysis was used to distinguish the groups, and partial least squares discriminate analysis was carried out to confirm the important variables. The serum metabolic profiling was identified and pathway analysis was performed after the total polysaccharide administration. The twenty-one potential biomarkers were screened, and the levels were all reversed to different degrees in the total polysaccharide treated groups. These potential biomarkers were mainly related to vitamin, sphingolipid, bile acid, phospholipid and acylcarnitine metabolisms. The result has indicated that total polysaccharide could inhibit insomnia triggered by immunodeficiency stimulation through regulating those metabolic pathways. This study provides a useful approach for exploring the mechanism and evaluating the efficacy of total polysaccharide from Suanzaoren decoction. Copyright © 2018 Elsevier B.V. All rights reserved.

Deletion of nfnAB in Thermoanaerobacterium saccharolyticum and Its Effect on Metabolism

DOE PAGES

Lo, Jonathan; Zheng, Tianyong; Olson, Daniel G.; ...

2015-06-29

NfnAB catalyzes the reversible transfer of electrons from reduced ferredoxin and NADH to 2 NADP +. The NfnAB complex has been hypothesized to be the main enzyme for ferredoxin oxidization in strains of Thermoanaerobacterium saccharolyticum engineered for increased ethanol production. NfnAB complex activity was detectable in crude cell extracts of T. saccharolyticum. In this paper, activity was also detected using activity staining of native PAGE gels. The nfnAB gene was deleted in different strains of T. saccharolyticum to determine its effect on end product formation. In wild-type T. saccharolyticum, deletion of nfnAB resulted in a 46% increase in H 2more » formation but otherwise little change in other fermentation products. In two engineered strains with 80% theoretical ethanol yield, loss of nfnAB caused two different responses: in one strain, ethanol yield decreased to about 30% of the theoretical value, while another strain had no change in ethanol yield. Biochemical analysis of cell extracts showed that the ΔnfnAB strain with decreased ethanol yield had NADPH-linked alcohol dehydrogenase (ADH) activity, while the ΔnfnAB strain with unchanged ethanol yield had NADH-linked ADH activity. Deletion of nfnAB caused loss of NADPH-linked ferredoxin oxidoreductase activity in all cell extracts. Significant NADH-linked ferredoxin oxidoreductase activity was seen in all cell extracts, including those that had lost nfnAB. This suggests that there is an unidentified NADH:ferredoxin oxidoreductase (distinct from nfnAB) playing a role in ethanol formation. The NfnAB complex plays a key role in generating NADPH in a strain that had become reliant on NADPH-ADH activity. Importance: Thermophilic anaerobes that can convert biomass-derived sugars into ethanol have been investigated as candidates for biofuel formation. Many anaerobes have been genetically engineered to increase biofuel formation; however, key aspects of metabolism remain unknown and poorly understood. One example is the mechanism for ferredoxin oxidation and transfer of electrons to NAD(P) +. The electron-bifurcating enzyme complex NfnAB is known to catalyze the reversible transfer of electrons from reduced ferredoxin and NADH to 2 NADP + and is thought to play key roles linking NAD(P)(H) metabolism with ferredoxin metabolism. Finally, we report the first deletion of nfnAB and demonstrate a role for NfnAB in metabolism and ethanol formation in Thermoanaerobacterium saccharolyticum and show that this may be an important feature among other thermophilic ethanologenic anaerobes.« less

Gene expression profiles of Drosophila melanogaster exposed to an insecticidal extract of Piper nigrum.

PubMed

Jensen, Helen R; Scott, Ian M; Sims, Steve; Trudeau, Vance L; Arnason, John Thor

2006-02-22

Black pepper, Piper nigrum L. (Piperaceae), has insecticidal properties and could potentially be utilized as an alternative to synthetic insecticides. Piperine extracted from P. nigrum has a biphasic effect upon cytochrome P450 monooxygenase activity with an initial suppression followed by induction. In this study, an ethyl acetate extract of P. nigrum seeds was tested for insecticidal activity toward adult Musca domestica and Drosophila melanogaster. The effect of this same P. nigrum extract upon differential gene expression in D. melanogaster was investigated using cDNA microarray analysis of 7380 genes. Treatment of D. melanogaster with P. nigrum extract led to a greater than 2-fold upregulation of transcription of the cytochrome P450 phase I metabolism genes Cyp 6a8, Cyp 9b2, and Cyp 12d1 as well as the glutathione-S-transferase phase II metabolism gene Gst-S1. These data suggests a complex effect of P. nigrum upon toxin metabolism.

Constraint-based stoichiometric modelling from single organisms to microbial communities

PubMed Central

Olivier, Brett G.; Bruggeman, Frank J.; Teusink, Bas

2016-01-01

Microbial communities are ubiquitously found in Nature and have direct implications for the environment, human health and biotechnology. The species composition and overall function of microbial communities are largely shaped by metabolic interactions such as competition for resources and cross-feeding. Although considerable scientific progress has been made towards mapping and modelling species-level metabolism, elucidating the metabolic exchanges between microorganisms and steering the community dynamics remain an enormous scientific challenge. In view of the complexity, computational models of microbial communities are essential to obtain systems-level understanding of ecosystem functioning. This review discusses the applications and limitations of constraint-based stoichiometric modelling tools, and in particular flux balance analysis (FBA). We explain this approach from first principles and identify the challenges one faces when extending it to communities, and discuss the approaches used in the field in view of these challenges. We distinguish between steady-state and dynamic FBA approaches extended to communities. We conclude that much progress has been made, but many of the challenges are still open. PMID:28334697

Characterizing Strain Variation in Engineered E. coli Using a Multi-Omics-Based Workflow

DOE PAGES

Brunk, Elizabeth; George, Kevin W.; Alonso-Gutierrez, Jorge; ...

2016-05-19

Understanding the complex interactions that occur between heterologous and native biochemical pathways represents a major challenge in metabolic engineering and synthetic biology. We present a workflow that integrates metabolomics, proteomics, and genome-scale models of Escherichia coli metabolism to study the effects of introducing a heterologous pathway into a microbial host. This workflow incorporates complementary approaches from computational systems biology, metabolic engineering, and synthetic biology; provides molecular insight into how the host organism microenvironment changes due to pathway engineering; and demonstrates how biological mechanisms underlying strain variation can be exploited as an engineering strategy to increase product yield. As a proofmore » of concept, we present the analysis of eight engineered strains producing three biofuels: isopentenol, limonene, and bisabolene. Application of this workflow identified the roles of candidate genes, pathways, and biochemical reactions in observed experimental phenomena and facilitated the construction of a mutant strain with improved productivity. The contributed workflow is available as an open-source tool in the form of iPython notebooks.« less

Energy and time determine scaling in biological and computer designs

PubMed Central

Bezerra, George; Edwards, Benjamin; Brown, James; Forrest, Stephanie

2016-01-01

Metabolic rate in animals and power consumption in computers are analogous quantities that scale similarly with size. We analyse vascular systems of mammals and on-chip networks of microprocessors, where natural selection and human engineering, respectively, have produced systems that minimize both energy dissipation and delivery times. Using a simple network model that simultaneously minimizes energy and time, our analysis explains empirically observed trends in the scaling of metabolic rate in mammals and power consumption and performance in microprocessors across several orders of magnitude in size. Just as the evolutionary transitions from unicellular to multicellular animals in biology are associated with shifts in metabolic scaling, our model suggests that the scaling of power and performance will change as computer designs transition to decentralized multi-core and distributed cyber-physical systems. More generally, a single energy–time minimization principle may govern the design of many complex systems that process energy, materials and information. This article is part of the themed issue ‘The major synthetic evolutionary transitions’. PMID:27431524

Energy and time determine scaling in biological and computer designs.

PubMed

Moses, Melanie; Bezerra, George; Edwards, Benjamin; Brown, James; Forrest, Stephanie

2016-08-19

Metabolic rate in animals and power consumption in computers are analogous quantities that scale similarly with size. We analyse vascular systems of mammals and on-chip networks of microprocessors, where natural selection and human engineering, respectively, have produced systems that minimize both energy dissipation and delivery times. Using a simple network model that simultaneously minimizes energy and time, our analysis explains empirically observed trends in the scaling of metabolic rate in mammals and power consumption and performance in microprocessors across several orders of magnitude in size. Just as the evolutionary transitions from unicellular to multicellular animals in biology are associated with shifts in metabolic scaling, our model suggests that the scaling of power and performance will change as computer designs transition to decentralized multi-core and distributed cyber-physical systems. More generally, a single energy-time minimization principle may govern the design of many complex systems that process energy, materials and information.This article is part of the themed issue 'The major synthetic evolutionary transitions'. © 2016 The Author(s).

From Network Analysis to Functional Metabolic Modeling of the Human Gut Microbiota.

PubMed

Bauer, Eugen; Thiele, Ines

2018-01-01

An important hallmark of the human gut microbiota is its species diversity and complexity. Various diseases have been associated with a decreased diversity leading to reduced metabolic functionalities. Common approaches to investigate the human microbiota include high-throughput sequencing with subsequent correlative analyses. However, to understand the ecology of the human gut microbiota and consequently design novel treatments for diseases, it is important to represent the different interactions between microbes with their associated metabolites. Computational systems biology approaches can give further mechanistic insights by constructing data- or knowledge-driven networks that represent microbe interactions. In this minireview, we will discuss current approaches in systems biology to analyze the human gut microbiota, with a particular focus on constraint-based modeling. We will discuss various community modeling techniques with their advantages and differences, as well as their application to predict the metabolic mechanisms of intestinal microbial communities. Finally, we will discuss future perspectives and current challenges of simulating realistic and comprehensive models of the human gut microbiota.

Evidence for the involvement of the anthranilate degradation pathway in Pseudomonas aeruginosa biofilm formation

PubMed Central

Costaglioli, Patricia; Barthe, Christophe; Claverol, Stephane; Brözel, Volker S; Perrot, Michel; Crouzet, Marc; Bonneu, Marc; Garbay, Bertrand; Vilain, Sebastien

2012-01-01

Bacterial biofilms are complex cell communities found attached to surfaces and surrounded by an extracellular matrix composed of exopolysaccharides, DNA, and proteins. We investigated the whole-genome expression profile of Pseudomonas aeruginosa sessile cells (SCs) present in biofilms developed on a glass wool substratum. The transcriptome and proteome of SCs were compared with those of planktonic cell cultures. Principal component analysis revealed a biofilm-specific gene expression profile. Our study highlighted the overexpression of genes controlling the anthranilate degradation pathway in the SCs grown on glass wool for 24 h. In this condition, the metabolic pathway that uses anthranilate for Pseudomonas quinolone signal production was not activated, which suggested that anthranilate was primarily being consumed for energy metabolism. Transposon mutants defective for anthranilate degradation were analyzed in a simple assay of biofilm formation. The phenotypic analyses confirmed that P. aeruginosa biofilm formation partially depended on the activity of the anthranilate degradation pathway. This work points to a new feature concerning anthranilate metabolism in P. aeruginosa SCs. PMID:23170231

Metabolic resource allocation in individual microbes determines ecosystem interactions and spatial dynamics

PubMed Central

Harcombe, William R.; Riehl, William J.; Dukovski, Ilija; Granger, Brian R.; Betts, Alex; Lang, Alex H.; Bonilla, Gracia; Kar, Amrita; Leiby, Nicholas; Mehta, Pankaj; Marx, Christopher J.; Segrè, Daniel

2014-01-01

Summary The inter-species exchange of metabolites plays a key role in the spatio-temporal dynamics of microbial communities. This raises the question whether ecosystem-level behavior of structured communities can be predicted using genome-scale models of metabolism for multiple organisms. We developed a modeling framework that integrates dynamic flux balance analysis with diffusion on a lattice, and applied it to engineered consortia. First, we predicted, and experimentally confirmed, the species-ratio to which a 2-species mutualistic consortium converges, and the equilibrium composition of a newly engineered 3-member community. We next identified a specific spatial arrangement of colonies, which gives rise to what we term the “eclipse dilemma”: does a competitor placed between a colony and its cross-feeding partner benefit or hurt growth of the original colony? Our experimentally validated finding, that the net outcome is beneficial, highlights the complex nature of metabolic interactions in microbial communities, while at the same time demonstrating their predictability. PMID:24794435

beta-Methyl-15-p-iodophenylpentadecanoic acid metabolism and kinetics in the isolated rat heart.

PubMed

DeGrado, T R; Holden, J E; Ng, C K; Raffel, D M; Gatley, S J

1989-01-01

The use of 15-p-iodophenyl-beta-methyl-pentadecanoic acid (beta Me-IPPA) as an indicator of long chain fatty acid (LCFA) utilization in nuclear medicine studies was evaluated in the isolated, perfused, working rat heart. Time courses of radioactivity (residue curves) were obtained following bolus injections of both beta Me-IPPA and its straight chain counterpart 15-p-iodophenyl-pentadecanoic acid (IPPA). IPPA kinetics clearly indicated flow independent impairment of fatty acid oxidation caused by the carnitine palmitoyltransferase I inhibitor 2[5(4-chlorophenyl)pentyl]oxirane-2-carboxylate (POCA). In contrast, beta Me-IPPA kinetics were insensitive to changes in fatty acid oxidation rate and net utilization of long chain fatty acid. Analysis of radiolabeled species in coronary effluent and heart homogenates showed the methylated fatty acid to be readily incorporated into complex lipids but a poor substrate for oxidation. POCA did not significantly alter metabolism of the tracer, suggesting that the tracer is poorly metabolized beyond beta Me-IPPA-CoA in the oxidative pathway.

Optical spectroscopy in turbid media utilizing an integrating sphere: mitochondrial chromophore analysis during metabolic transitions

PubMed Central

Chess, David J.; Billings, Eric; Covian, Raúl; Glancy, Brian; French, Stephanie; Taylor, Joni; de Bari, Heather; Murphy, Elizabeth; Balaban, Robert S.

2013-01-01

Recent evidence suggests that the activity of mitochondrial oxidative phosphorylation Complexes (MOPC) is modulated at multiple sites. Herein, a method of optically monitoring electron distribution within and between MOPC is described using a center-mounted sample in an integrating sphere (to minimize scattering effects) with a rapid-scanning spectrometer. The redox-sensitive MOPC absorbances (~465 to 630 nm) were modeled using linear least squares analysis with individual chromophore spectra. Classical mitochondrial activity transitions (e.g., ADP-induced increase in oxygen consumption) were used to characterize this approach. Most notable in these studies was the observation that intermediates of the catalytic cycle of cytochrome oxidase are dynamically modulated with metabolic state. The MOPC redox state, along with measurements of oxygen consumption and mitochondrial membrane potential, was used to evaluate the conductances of different sections of the electron transport chain. This analysis then was applied to mitochondria isolated from rabbit hearts subjected to ischemia-reperfusion (I/R). Surprisingly, I/R resulted in an inhibition of all measured MOPC conductances, suggesting a coordinated down-regulation of mitochondrial activity with this well-established cardiac perturbation. PMID:23665273

Global metabolic profiling procedures for urine using UPLC-MS.

PubMed

Want, Elizabeth J; Wilson, Ian D; Gika, Helen; Theodoridis, Georgios; Plumb, Robert S; Shockcor, John; Holmes, Elaine; Nicholson, Jeremy K

2010-06-01

The production of 'global' metabolite profiles involves measuring low molecular-weight metabolites (<1 kDa) in complex biofluids/tissues to study perturbations in response to physiological challenges, toxic insults or disease processes. Information-rich analytical platforms, such as mass spectrometry (MS), are needed. Here we describe the application of ultra-performance liquid chromatography-MS (UPLC-MS) to urinary metabolite profiling, including sample preparation, stability/storage and the selection of chromatographic conditions that balance metabolome coverage, chromatographic resolution and throughput. We discuss quality control and metabolite identification, as well as provide details of multivariate data analysis approaches for analyzing such MS data. Using this protocol, the analysis of a sample set in 96-well plate format, would take ca. 30 h, including 1 h for system setup, 1-2 h for sample preparation, 24 h for UPLC-MS analysis and 1-2 h for initial data processing. The use of UPLC-MS for metabolic profiling in this way is not faster than the conventional HPLC-based methods but, because of improved chromatographic performance, provides superior metabolome coverage.

Is metabolic syndrome related with coronary artery disease severity and complexity: An observational study about IDF and AHA/NHLBI metabolic syndrome definitions.

PubMed

Aykan, Ahmet Çağrı; Gül, İlker; Kalaycıoğlu, Ezgi; Gökdeniz, Tayyar; Hatem, Engin; Menteşe, Ümit; Yıldız, Banu Şahin; Yıldız, Mustafa

2014-01-01

The aim of the present study was to assess the relation between metabolic syndrome (MS) and coronary artery disease (CAD) complexity, assessed by Syntax score (SS), and severity in non-diabetic patients with stable CAD who underwent coronary angiography, and to evaluate whether the MS defined by different definitions, including International Diabetes Federation (IDF) and American Heart Association/National Heart Lung Blood Institute (AHA/NHLBI) guidelines, similarly correlated with SS. The present study is cross sectional and observational with prospective inclusion of 248 consecutive patients (157 male) who underwent coronary angiography due to stable CAD. The prevalence of MS was 54.4% according to IDF definition and 50.4% according to AHA/NHLBI definition. MS score according to IDF definitions (r = 0.446, p < 0.001), MS score according to AHA/NHLBI definitions (r = 0.341, p < 0.001) were moderately correlated with SS. In Fisher r to z transformation test the correlations of the presence of MS according to IDF and AHA/NHLBI definitions with SS were not statistically significant (p = 0.168, z = -1.38). The systolic blood pressure (p < 0.001, B = 0.354, 95% CI = -0.308 to 0.228), diastolic blood pressure (p = 0.006, B = -0.194, 95% CI = -0.333 to -0.056), age (p = 0.014, B = 0.147, 95% CI = 0.029 to 0.264), left ventricular ejection fraction (p = 0.031, B = -0.150, 95% CI= -0.286 to -0.014), waist/hip circumference (p < 0.001, B = 45.713, 95% CI = 23.235 to 68.1919) and log10 high density lipoprotein (p < 0.001, B = -22.209, 95% CI = -33.298 to-11.119) were the independent predictors of SS in linear regression analysis. MS is associated with the presence and complexity of CAD. Besides the presence of discrepancy in the limits of waist circumference, both IDF and AHA/NHLBI criteria were similarly correlated with CAD complexity.

Temperature variability analysis using wavelets and multiscale entropy in patients with systemic inflammatory response syndrome, sepsis, and septic shock.

PubMed

Papaioannou, Vasilios E; Chouvarda, Ioanna G; Maglaveras, Nikos K; Pneumatikos, Ioannis A

2012-12-12

Even though temperature is a continuous quantitative variable, its measurement has been considered a snapshot of a process, indicating whether a patient is febrile or afebrile. Recently, other diagnostic techniques have been proposed for the association between different properties of the temperature curve with severity of illness in the Intensive Care Unit (ICU), based on complexity analysis of continuously monitored body temperature. In this study, we tried to assess temperature complexity in patients with systemic inflammation during a suspected ICU-acquired infection, by using wavelets transformation and multiscale entropy of temperature signals, in a cohort of mixed critically ill patients. Twenty-two patients were enrolled in the study. In five, systemic inflammatory response syndrome (SIRS, group 1) developed, 10 had sepsis (group 2), and seven had septic shock (group 3). All temperature curves were studied during the first 24 hours of an inflammatory state. A wavelet transformation was applied, decomposing the signal in different frequency components (scales) that have been found to reflect neurogenic and metabolic inputs on temperature oscillations. Wavelet energy and entropy per different scales associated with complexity in specific frequency bands and multiscale entropy of the whole signal were calculated. Moreover, a clustering technique and a linear discriminant analysis (LDA) were applied for permitting pattern recognition in data sets and assessing diagnostic accuracy of different wavelet features among the three classes of patients. Statistically significant differences were found in wavelet entropy between patients with SIRS and groups 2 and 3, and in specific ultradian bands between SIRS and group 3, with decreased entropy in sepsis. Cluster analysis using wavelet features in specific bands revealed concrete clusters closely related with the groups in focus. LDA after wrapper-based feature selection was able to classify with an accuracy of more than 80% SIRS from the two sepsis groups, based on multiparametric patterns of entropy values in the very low frequencies and indicating reduced metabolic inputs on local thermoregulation, probably associated with extensive vasodilatation. We suggest that complexity analysis of temperature signals can assess inherent thermoregulatory dynamics during systemic inflammation and has increased discriminating value in patients with infectious versus noninfectious conditions, probably associated with severity of illness.

Temperature variability analysis using wavelets and multiscale entropy in patients with systemic inflammatory response syndrome, sepsis, and septic shock

PubMed Central

2012-01-01

Background Even though temperature is a continuous quantitative variable, its measurement has been considered a snapshot of a process, indicating whether a patient is febrile or afebrile. Recently, other diagnostic techniques have been proposed for the association between different properties of the temperature curve with severity of illness in the Intensive Care Unit (ICU), based on complexity analysis of continuously monitored body temperature. In this study, we tried to assess temperature complexity in patients with systemic inflammation during a suspected ICU-acquired infection, by using wavelets transformation and multiscale entropy of temperature signals, in a cohort of mixed critically ill patients. Methods Twenty-two patients were enrolled in the study. In five, systemic inflammatory response syndrome (SIRS, group 1) developed, 10 had sepsis (group 2), and seven had septic shock (group 3). All temperature curves were studied during the first 24 hours of an inflammatory state. A wavelet transformation was applied, decomposing the signal in different frequency components (scales) that have been found to reflect neurogenic and metabolic inputs on temperature oscillations. Wavelet energy and entropy per different scales associated with complexity in specific frequency bands and multiscale entropy of the whole signal were calculated. Moreover, a clustering technique and a linear discriminant analysis (LDA) were applied for permitting pattern recognition in data sets and assessing diagnostic accuracy of different wavelet features among the three classes of patients. Results Statistically significant differences were found in wavelet entropy between patients with SIRS and groups 2 and 3, and in specific ultradian bands between SIRS and group 3, with decreased entropy in sepsis. Cluster analysis using wavelet features in specific bands revealed concrete clusters closely related with the groups in focus. LDA after wrapper-based feature selection was able to classify with an accuracy of more than 80% SIRS from the two sepsis groups, based on multiparametric patterns of entropy values in the very low frequencies and indicating reduced metabolic inputs on local thermoregulation, probably associated with extensive vasodilatation. Conclusions We suggest that complexity analysis of temperature signals can assess inherent thermoregulatory dynamics during systemic inflammation and has increased discriminating value in patients with infectious versus noninfectious conditions, probably associated with severity of illness. PMID:22424316

Dynamic subcellular localization of a respiratory complex controls bacterial respiration

PubMed Central

Alberge, François; Espinosa, Leon; Seduk, Farida; Sylvi, Léa; Toci, René; Walburger, Anne; Magalon, Axel

2015-01-01

Respiration, an essential process for most organisms, has to optimally respond to changes in the metabolic demand or the environmental conditions. The branched character of their respiratory chains allows bacteria to do so by providing a great metabolic and regulatory flexibility. Here, we show that the native localization of the nitrate reductase, a major respiratory complex under anaerobiosis in Escherichia coli, is submitted to tight spatiotemporal regulation in response to metabolic conditions via a mechanism using the transmembrane proton gradient as a cue for polar localization. These dynamics are critical for controlling the activity of nitrate reductase, as the formation of polar assemblies potentiates the electron flux through the complex. Thus, dynamic subcellular localization emerges as a critical factor in the control of respiration in bacteria. DOI: http://dx.doi.org/10.7554/eLife.05357.001 PMID:26077726

The Zinc-Schiff Base-Novicidin Complex as a Potential Prostate Cancer Therapy

PubMed Central

Milosavljevic, Vedran; Haddad, Yazan; Merlos Rodrigo, Miguel Angel; Moulick, Amitava; Polanska, Hana; Hynek, David; Heger, Zbynek; Kopel, Pavel; Adam, Vojtech

2016-01-01

Prostate cancer cells control energy metabolism by chelating intracellular zinc. Thus, zinc delivery has been a popular therapeutic approach for prostate cancer. Here, we propose the use of the membrane-penetrating peptide Novicidin connected to zinc-Schiff base as a carrier vehicle for the delivery of zinc to prostate cells. Mass spectrometry, electrochemistry and spectrophotometry confirmed the formation/stability of this complex and provided insight regarding the availability of zinc for complex interactions. This delivery system showed minor toxicity in normal PNT1A cells and high potency towards PC3 tumor cells. The complex preferentially penetrated PC3 tumor cells in contrast to confinement to the membranes of PNT1A. Furthermore, zinc uptake was confirmed in both cell lines. Molecular analysis was used to confirm the activation of zinc stress (e.g., ZnT-1) and apoptosis (e.g., CASP-1). Our results strongly suggest that the zinc-Schiff base-Novicidin complex has great potential as a novel anticancer drug. PMID:27727290

Characterizing steady states of genome-scale metabolic networks in continuous cell cultures.

PubMed

Fernandez-de-Cossio-Diaz, Jorge; Leon, Kalet; Mulet, Roberto

2017-11-01

In the continuous mode of cell culture, a constant flow carrying fresh media replaces culture fluid, cells, nutrients and secreted metabolites. Here we present a model for continuous cell culture coupling intra-cellular metabolism to extracellular variables describing the state of the bioreactor, taking into account the growth capacity of the cell and the impact of toxic byproduct accumulation. We provide a method to determine the steady states of this system that is tractable for metabolic networks of arbitrary complexity. We demonstrate our approach in a toy model first, and then in a genome-scale metabolic network of the Chinese hamster ovary cell line, obtaining results that are in qualitative agreement with experimental observations. We derive a number of consequences from the model that are independent of parameter values. The ratio between cell density and dilution rate is an ideal control parameter to fix a steady state with desired metabolic properties. This conclusion is robust even in the presence of multi-stability, which is explained in our model by a negative feedback loop due to toxic byproduct accumulation. A complex landscape of steady states emerges from our simulations, including multiple metabolic switches, which also explain why cell-line and media benchmarks carried out in batch culture cannot be extrapolated to perfusion. On the other hand, we predict invariance laws between continuous cell cultures with different parameters. A practical consequence is that the chemostat is an ideal experimental model for large-scale high-density perfusion cultures, where the complex landscape of metabolic transitions is faithfully reproduced.

Association of Family Composition and Metabolic Syndrome in Korean Adults Aged over 45 Years Old.

PubMed

Kim, Young-Ju

2015-12-01

This study investigated the relationship between family composition and the prevalence of metabolic syndrome by gender in Korean adults aged 45 years and older. The sample consisted of 11,291 participants in the Korea National Health and Nutrition Examination Survey from 2010 to 2012. We used complex sample analyses, including strata, cluster, and sample weighting, to allow generalization to the Korean population. Complex samples crosstabs and chi-square tests were conducted to compare the percentage of sociodemographic characteristics to the prevalence of metabolic syndrome and its components by gender and family composition. Next, a complex sample logistic regression was performed to examine the association between family composition and the prevalence of metabolic syndrome by gender. The percentage of adults living alone was 5.6% for men and 13.9% for women. Slightly more women (14.0%) than men (10.1%) reported living with three generations. The percentage of metabolic syndrome in Korean adults aged 45 years and older was 53.2% for men and 35.7% for women. For women, we found that living with one or three generations was significantly associated with a higher risk of metabolic syndrome, blood pressure, and triglyceride abnormality after adjusting for age, education, household income, smoking, physical activity, and body mass index, when compared to living alone. No significant relationships were found for men. A national strategy, tailored on gender and family composition, needs to be developed in order to prevent the increase of metabolic syndrome in Korean women over middle age. Copyright © 2015. Published by Elsevier B.V.

Characterizing steady states of genome-scale metabolic networks in continuous cell cultures

PubMed Central

Leon, Kalet; Mulet, Roberto

2017-01-01

In the continuous mode of cell culture, a constant flow carrying fresh media replaces culture fluid, cells, nutrients and secreted metabolites. Here we present a model for continuous cell culture coupling intra-cellular metabolism to extracellular variables describing the state of the bioreactor, taking into account the growth capacity of the cell and the impact of toxic byproduct accumulation. We provide a method to determine the steady states of this system that is tractable for metabolic networks of arbitrary complexity. We demonstrate our approach in a toy model first, and then in a genome-scale metabolic network of the Chinese hamster ovary cell line, obtaining results that are in qualitative agreement with experimental observations. We derive a number of consequences from the model that are independent of parameter values. The ratio between cell density and dilution rate is an ideal control parameter to fix a steady state with desired metabolic properties. This conclusion is robust even in the presence of multi-stability, which is explained in our model by a negative feedback loop due to toxic byproduct accumulation. A complex landscape of steady states emerges from our simulations, including multiple metabolic switches, which also explain why cell-line and media benchmarks carried out in batch culture cannot be extrapolated to perfusion. On the other hand, we predict invariance laws between continuous cell cultures with different parameters. A practical consequence is that the chemostat is an ideal experimental model for large-scale high-density perfusion cultures, where the complex landscape of metabolic transitions is faithfully reproduced. PMID:29131817

Metabolic control analysis is helpful for informed genetic manipulation of oilseed rape (Brassica napus) to increase seed oil content

PubMed Central

Weselake, Randall J.; Shah, Saleh; Tang, Mingguo; Quant, Patti A.; Snyder, Crystal L.; Furukawa-Stoffer, Tara L.; Zhu, Weiming; Taylor, David C.; Zou, Jitao; Kumar, Arvind; Hall, Linda; Laroche, Andre; Rakow, Gerhard; Raney, Phillip; Moloney, Maurice M.; Harwood, John L.

2008-01-01

Top–down control analysis (TDCA) is a useful tool for quantifying constraints on metabolic pathways that might be overcome by biotechnological approaches. Previous studies on lipid accumulation in oilseed rape have suggested that diacylglycerol acyltransferase (DGAT), which catalyses the final step in seed oil biosynthesis, might be an effective target for enhancing seed oil content. Here, increased seed oil content, increased DGAT activity, and reduced substrate:product ratio are demonstrated, as well as reduced flux control by complex lipid assembly, as determined by TDCA in Brassica napus (canola) lines which overexpress the gene encoding type-1 DGAT. Lines overexpressing DGAT1 also exhibited considerably enhanced seed oil content under drought conditions. These results support the use of TDCA in guiding the rational selection of molecular targets for oilseed modification. The most effective lines had a seed oil increase of 14%. Moreover, overexpression of DGAT1 under drought conditions reduced this environmental penalty on seed oil content. PMID:18703491

Functional and structural characterization of a β-glucosidase involved in saponin metabolism from intestinal bacteria.

PubMed

Yan, Shan; Wei, Peng-Cheng; Chen, Qiao; Chen, Xin; Wang, Shi-Cheng; Li, Jia-Ru; Gao, Chuan

2018-02-19

Saponins are natural glycosides widely used in medicine and the food industry. Although saponin metabolism in human is dependent on intestinal microbes, few involving bacteria enzymes have been identified. We cloned BlBG3, a GH3 β-glucosidase from Bifidobacterium longum, from human stool. We found that BlBG3 catalyzes the hydrolysis of glycoside furostanol and ginsenoside Rb1 at higher efficiency than other microbial β-glucosidases. Structural analysis of BlBG3 in complex with d-glucose revealed its three unique loops, which form a deep pocket and participate in substrate binding. To understand how substrate is bound to the pocket, molecular docking was performed and the binding interactions of protobioside with BlBG3 were revealed. Mutational study suggested that R484 and H642 are critical for enzymatic activity. Our study presents the first structural and functional analysis of a saponin-processing enzyme from human microbiota. Copyright © 2018 Elsevier Inc. All rights reserved.

Genome analysis of crude oil degrading Franconibacter pulveris strain DJ34 revealed its genetic basis for hydrocarbon degradation and survival in oil contaminated environment.

PubMed

Pal, Siddhartha; Kundu, Anirban; Banerjee, Tirtha Das; Mohapatra, Balaram; Roy, Ajoy; Manna, Riddha; Sar, Pinaki; Kazy, Sufia K

2017-10-01

Franconibacter pulveris strain DJ34, isolated from Duliajan oil fields, Assam, was characterized in terms of its taxonomic, metabolic and genomic properties. The bacterium showed utilization of diverse petroleum hydrocarbons and electron acceptors, metal resistance, and biosurfactant production. The genome (4,856,096bp) of this strain contained different genes related to the degradation of various petroleum hydrocarbons, metal transport and resistance, dissimilatory nitrate, nitrite and sulfite reduction, chemotaxy, biosurfactant synthesis, etc. Genomic comparison with other Franconibacter spp. revealed higher abundance of genes for cell motility, lipid transport and metabolism, transcription and translation in DJ34 genome. Detailed COG analysis provides deeper insights into the genomic potential of this organism for degradation and survival in oil-contaminated complex habitat. This is the first report on ecophysiology and genomic inventory of Franconibacter sp. inhabiting crude oil rich environment, which might be useful for designing the strategy for bioremediation of oil contaminated environment. Copyright © 2017 Elsevier Inc. All rights reserved.

Metabolic control analysis is helpful for informed genetic manipulation of oilseed rape (Brassica napus) to increase seed oil content.

PubMed

Weselake, Randall J; Shah, Saleh; Tang, Mingguo; Quant, Patti A; Snyder, Crystal L; Furukawa-Stoffer, Tara L; Zhu, Weiming; Taylor, David C; Zou, Jitao; Kumar, Arvind; Hall, Linda; Laroche, Andre; Rakow, Gerhard; Raney, Phillip; Moloney, Maurice M; Harwood, John L

2008-01-01

Top-down control analysis (TDCA) is a useful tool for quantifying constraints on metabolic pathways that might be overcome by biotechnological approaches. Previous studies on lipid accumulation in oilseed rape have suggested that diacylglycerol acyltransferase (DGAT), which catalyses the final step in seed oil biosynthesis, might be an effective target for enhancing seed oil content. Here, increased seed oil content, increased DGAT activity, and reduced substrate:product ratio are demonstrated, as well as reduced flux control by complex lipid assembly, as determined by TDCA in Brassica napus (canola) lines which overexpress the gene encoding type-1 DGAT. Lines overexpressing DGAT1 also exhibited considerably enhanced seed oil content under drought conditions. These results support the use of TDCA in guiding the rational selection of molecular targets for oilseed modification. The most effective lines had a seed oil increase of 14%. Moreover, overexpression of DGAT1 under drought conditions reduced this environmental penalty on seed oil content.

Nutrition and the science of disease prevention: a systems approach to support metabolic health

PubMed Central

Bennett, Brian J.; Hall, Kevin D.; Hu, Frank B.; McCartney, Anne L.; Roberto, Christina

2017-01-01

Progress in nutritional science, genetics, computer science, and behavioral economics can be leveraged to address the challenge of noncommunicable disease. This report highlights the connection between nutrition and the complex science of preventing disease and discusses the promotion of optimal metabolic health, building on input from several complementary disciplines. The discussion focuses on (1) the basic science of optimal metabolic health, including data from gene–diet interactions, microbiome, and epidemiological research in nutrition, with the goal of defining better targets and interventions, and (2) how nutrition, from pharma to lifestyle, can build on systems science to address complex issues. PMID:26415028

Combinatorial function of velvet and AreA in transcriptional regulation of nitrate utilization and secondary metabolism.

PubMed

López-Berges, Manuel S; Schäfer, Katja; Hera, Concepción; Di Pietro, Antonio

2014-01-01

Velvet is a conserved protein complex that functions as a regulator of fungal development and secondary metabolism. In the soil-inhabiting pathogen Fusarium oxysporum, velvet governs mycotoxin production and virulence on plant and mammalian hosts. Here we report a previously unrecognized role of the velvet complex in regulation of nitrate metabolism. F. oxysporum mutants lacking VeA or LaeA, two key components of the complex, were impaired in growth on the non-preferred nitrogen sources nitrate and nitrite. Both velvet and the general nitrogen response GATA factor AreA were required for transcriptional activation of nitrate (nit1) and nitrite (nii1) reductase genes under de-repressing conditions, as well as for the nitrate-triggered increase in chromatin accessibility at the nit1 locus. AreA also contributed to chromatin accessibility and expression of two velvet-regulated gene clusters, encoding biosynthesis of the mycotoxin beauvericin and of the siderophore ferricrocin. Thus, velvet and AreA coordinately orchestrate primary and secondary metabolism as well as virulence functions in F. oxysporum. Copyright © 2013 Elsevier Inc. All rights reserved.

Perspectives on the metabolic management of epilepsy through dietary reduction of glucose and elevation of ketone bodies.

PubMed

Greene, Amanda E; Todorova, Mariana T; Seyfried, Thomas N

2003-08-01

Brain cells are metabolically flexible because they can derive energy from both glucose and ketone bodies (acetoacetate and beta-hydroxybutyrate). Metabolic control theory applies principles of bioenergetics and genome flexibility to the management of complex phenotypic traits. Epilepsy is a complex brain disorder involving excessive, synchronous, abnormal electrical firing patterns of neurons. We propose that many epilepsies with varied etiologies may ultimately involve disruptions of brain energy homeostasis and are potentially manageable through principles of metabolic control theory. This control involves moderate shifts in the availability of brain energy metabolites (glucose and ketone bodies) that alter energy metabolism through glycolysis and the tricarboxylic acid cycle, respectively. These shifts produce adjustments in gene-linked metabolic networks that manage or control the seizure disorder despite the continued presence of the inherited or acquired factors responsible for the epilepsy. This hypothesis is supported by information on the management of seizures with diets including fasting, the ketogenic diet and caloric restriction. A better understanding of the compensatory genetic and neurochemical networks of brain energy metabolism may produce novel antiepileptic therapies that are more effective and biologically friendly than those currently available.

Regulation of metabolism by the Mediator complex.

PubMed

Youn, Dou Yeon; Xiaoli, Alus M; Pessin, Jeffrey E; Yang, Fajun

2016-01-01

The Mediator complex was originally discovered in yeast, but it is conserved in all eukaryotes. Its best-known function is to regulate RNA polymerase II-dependent gene transcription. Although the mechanisms by which the Mediator complex regulates transcription are often complicated by the context-dependent regulation, this transcription cofactor complex plays a pivotal role in numerous biological pathways. Biochemical, molecular, and physiological studies using cancer cell lines or model organisms have established the current paradigm of the Mediator functions. However, the physiological roles of the mammalian Mediator complex remain poorly defined, but have attracted a great interest in recent years. In this short review, we will summarize some of the reported functions of selective Mediator subunits in the regulation of metabolism. These intriguing findings suggest that the Mediator complex may be an important player in nutrient sensing and energy balance in mammals.

Muscle as a “Mediator“ of Systemic Metabolism

PubMed Central

Baskin, Kedryn K.; Winders, Benjamin R.; Olson, Eric N.

2015-01-01

Skeletal and cardiac muscles play key roles in the regulation of systemic energy homeostasis and display remarkable plasticity in their metabolic responses to caloric availability and physical activity. In this Perspective we discuss recent studies highlighting transcriptional mechanisms that govern systemic metabolism by striated muscles. We focus on the participation of the Mediator complex in this process, and suggest that tissue-specific regulation of Mediator subunits impacts metabolic homeostasis. PMID:25651178

Mitochondrial NDUFS3 regulates the ROS-mediated onset of metabolic switch in transformed cells

PubMed Central

Suhane, Sonal; Kanzaki, Hirotaka; Arumugaswami, Vaithilingaraja; Murali, Ramachandran; Ramanujan, V. Krishnan

2013-01-01

Summary Aerobic glycolysis in transformed cells is an unique metabolic phenotype characterized by a hyperactivated glycolytic pathway even in the presence of oxygen. It is not clear if the onset of aerobic glycolysis is regulated by mitochondrial dysfunction and, if so, what the metabolic windows of opportunity available to control this metabolic switch (mitochondrial to glycolytic) landscape are in transformed cells. Here we report a genetically-defined model system based on the gene-silencing of a mitochondrial complex I subunit, NDUFS3, where we demonstrate the onset of metabolic switch in isogenic human embryonic kidney cells by differential expression of NDUFS3. By means of extensive metabolic characterization, we demonstrate that NDUFS3 gene silencing systematically introduces mitochondrial dysfunction thereby leading to the onset of aerobic glycolysis in a manner dependent on NDUFS3 protein levels. Furthermore, we show that the sustained imbalance in free radical dynamics is a necessary condition to sustain the observed metabolic switch in cell lines with the most severe NDUFS3 suppression. Together, our data reveal a novel role for mitochondrial complex I subunit NDUFS3 in regulating the degree of mitochondrial dysfunction in living cells, thereby setting a “metabolic threshold” for the observation of aerobic glycolysis phenotype within the confines of mitochondrial dysfunction. PMID:23519235

Unique plasma metabolomic signatures of individuals with inherited disorders of long-chain fatty acid oxidation

PubMed Central

McCoin, Colin S.; Piccolo, Brian D.; Knotts, Trina A.; Matern, Dietrich; Vockley, Jerry; Gillingham, Melanie B.; Adams, Sean H.

2016-01-01

Blood and urine acylcarnitine profiles are commonly used to diagnose long-chain fatty acid oxidation disorders (FAOD: i.e., long-chain hydroxy-acyl-CoA dehydrogenase [LCHAD] and carnitine palmitoyltransferase 2 [CPT2] deficiency), but the global metabolic impact of long-chain FAOD has not been reported. We utilized untargeted metabolomics to characterize plasma metabolites in 12 overnight-fasted individuals with FAOD (10 LCHAD, 2 CPT2) and 11 healthy age-, sex-, and body mass index (BMI)-matched controls, with the caveat that individuals with FAOD consume a low-fat diet supplemented with medium-chain triglycerides (MCT) while matched controls consume a typical American diet. 832 metabolites were identified in plasma, and partial least squared-discriminant analysis (PLS-DA) identified 114 non-acylcarnitine variables that discriminated FAOD subjects and controls. FAOD individuals had significantly higher triglycerides and lower specific phosphatidylethanolamines, ceramides and sphingomyelins. Differences in phosphatidylcholines were also found but the directionality differed by species. Further, there were few differences in non-lipid metabolites indicating the metabolic impact of FAOD specifically on lipid pathways. This analysis provides evidence that LCHAD/CPT2 deficiency significantly alters complex lipid pathway flux. This metabolic signature may provide powerful clinical tools capable of confirming or diagnosing FAOD, even in subjects with a mild phenotype, and provide clues regarding the biochemical and metabolic impact of FAOD that could be relevant to the etiology of FAOD symptoms. PMID:26907176

A mixed-integer linear programming approach to the reduction of genome-scale metabolic networks.

PubMed

Röhl, Annika; Bockmayr, Alexander

2017-01-03

Constraint-based analysis has become a widely used method to study metabolic networks. While some of the associated algorithms can be applied to genome-scale network reconstructions with several thousands of reactions, others are limited to small or medium-sized models. In 2015, Erdrich et al. introduced a method called NetworkReducer, which reduces large metabolic networks to smaller subnetworks, while preserving a set of biological requirements that can be specified by the user. Already in 2001, Burgard et al. developed a mixed-integer linear programming (MILP) approach for computing minimal reaction sets under a given growth requirement. Here we present an MILP approach for computing minimum subnetworks with the given properties. The minimality (with respect to the number of active reactions) is not guaranteed by NetworkReducer, while the method by Burgard et al. does not allow specifying the different biological requirements. Our procedure is about 5-10 times faster than NetworkReducer and can enumerate all minimum subnetworks in case there exist several ones. This allows identifying common reactions that are present in all subnetworks, and reactions appearing in alternative pathways. Applying complex analysis methods to genome-scale metabolic networks is often not possible in practice. Thus it may become necessary to reduce the size of the network while keeping important functionalities. We propose a MILP solution to this problem. Compared to previous work, our approach is more efficient and allows computing not only one, but even all minimum subnetworks satisfying the required properties.

Biochemist-Tree: Using Modular Origami to Understand the Integration of Intermediary Metabolism

ERIC Educational Resources Information Center

Sharp, Duncan

2013-01-01

Intermediary metabolism can be a complex area to study due to the inherent modularity of the catabolic biochemical processes. This article outlines a novel, cost-effective, and universally applicable teaching activity to enhance students understanding of the inter-relationship between the key processes of intermediary metabolism. A simple origami…

Relationships between gut microbiota, plasma metabolites, and metabolic syndrome traits in the METSIM cohort.

PubMed

Org, Elin; Blum, Yuna; Kasela, Silva; Mehrabian, Margarete; Kuusisto, Johanna; Kangas, Antti J; Soininen, Pasi; Wang, Zeneng; Ala-Korpela, Mika; Hazen, Stanley L; Laakso, Markku; Lusis, Aldons J

2017-04-13

The gut microbiome is a complex and metabolically active community that directly influences host phenotypes. In this study, we profile gut microbiota using 16S rRNA gene sequencing in 531 well-phenotyped Finnish men from the Metabolic Syndrome In Men (METSIM) study. We investigate gut microbiota relationships with a variety of factors that have an impact on the development of metabolic and cardiovascular traits. We identify novel associations between gut microbiota and fasting serum levels of a number of metabolites, including fatty acids, amino acids, lipids, and glucose. In particular, we detect associations with fasting plasma trimethylamine N-oxide (TMAO) levels, a gut microbiota-dependent metabolite associated with coronary artery disease and stroke. We further investigate the gut microbiota composition and microbiota-metabolite relationships in subjects with different body mass index and individuals with normal or altered oral glucose tolerance. Finally, we perform microbiota co-occurrence network analysis, which shows that certain metabolites strongly correlate with microbial community structure and that some of these correlations are specific for the pre-diabetic state. Our study identifies novel relationships between the composition of the gut microbiota and circulating metabolites and provides a resource for future studies to understand host-gut microbiota relationships.

AMPK Is Essential to Balance Glycolysis and Mitochondrial Metabolism to Control T-ALL Cell Stress and Survival.

PubMed

Kishton, Rigel J; Barnes, Carson E; Nichols, Amanda G; Cohen, Sivan; Gerriets, Valerie A; Siska, Peter J; Macintyre, Andrew N; Goraksha-Hicks, Pankuri; de Cubas, Aguirre A; Liu, Tingyu; Warmoes, Marc O; Abel, E Dale; Yeoh, Allen Eng Juh; Gershon, Timothy R; Rathmell, W Kimryn; Richards, Kristy L; Locasale, Jason W; Rathmell, Jeffrey C

2016-04-12

T cell acute lymphoblastic leukemia (T-ALL) is an aggressive malignancy associated with Notch pathway mutations. While both normal activated and leukemic T cells can utilize aerobic glycolysis to support proliferation, it is unclear to what extent these cell populations are metabolically similar and if differences reveal T-ALL vulnerabilities. Here we show that aerobic glycolysis is surprisingly less active in T-ALL cells than proliferating normal T cells and that T-ALL cells are metabolically distinct. Oncogenic Notch promoted glycolysis but also induced metabolic stress that activated 5' AMP-activated kinase (AMPK). Unlike stimulated T cells, AMPK actively restrained aerobic glycolysis in T-ALL cells through inhibition of mTORC1 while promoting oxidative metabolism and mitochondrial Complex I activity. Importantly, AMPK deficiency or inhibition of Complex I led to T-ALL cell death and reduced disease burden. Thus, AMPK simultaneously inhibits anabolic growth signaling and is essential to promote mitochondrial pathways that mitigate metabolic stress and apoptosis in T-ALL. Copyright © 2016 Elsevier Inc. All rights reserved.

Obesity and Altered Sleep: A Pathway to Metabolic Derangements in Children?

PubMed Central

Hakim, Fahed; Kheirandish-Gozal, Leila; Gozal, David

2015-01-01

Obstructive sleep apnea (OSA) is a frequent disorder in children and is primarily associated with adenotonsillar hypertrophy., The prominent increases in childhood overweight and obesity rates in the world even among youngest of children have translated into parallel increases in the prevalence of OSA, and such trends will undoubtedly be associated with deleterious global health outcomes and life expectancy. Even an obesity phenotype in childhood OSA, more close to the adult type, has been recently proposed. Reciprocal interactions between sleep in general, OSA, obesity, and disruptions of metabolic homeostasis have emerged in recent years. These associations have suggested the a priori involvement of complex sets of metabolic and inflammatory pathways all of which may underlie increased risk for increased orexigenic behaviors and dysfunctional satiety, hyperlipidemia, and insulin resistance that ultimately favor the emergence of metabolic syndrome. Here, we will review some of the critical evidence supporting the proposed associations between sleep disruption and the metabolism-obesity complex. In addition, we will describe the more recent evidence linking the potential interactive roles of OSA and obesity on metabolic phenotype. PMID:26072337

Consequences of gas flux model choice on the interpretation of metabolic balance across 15 lakes

USGS Publications Warehouse

Dugan, Hilary; Woolway, R. Iestyn; Santoso, Arianto; Corman, Jessica; Jaimes, Aline; Nodine, Emily; Patil, Vijay; Zwart, Jacob A.; Brentrup, Jennifer A.; Hetherington, Amy; Oliver, Samantha K.; Read, Jordan S.; Winters, Kirsten; Hanson, Paul; Read, Emily; Winslow, Luke; Weathers, Kathleen

2016-01-01

Ecosystem metabolism and the contribution of carbon dioxide from lakes to the atmosphere can be estimated from free-water gas measurements through the use of mass balance models, which rely on a gas transfer coefficient (k) to model gas exchange with the atmosphere. Theoretical and empirically based models of krange in complexity from wind-driven power functions to complex surface renewal models; however, model choice is rarely considered in most studies of lake metabolism. This study used high-frequency data from 15 lakes provided by the Global Lake Ecological Observatory Network (GLEON) to study how model choice of kinfluenced estimates of lake metabolism and gas exchange with the atmosphere. We tested 6 models of k on lakes chosen to span broad gradients in surface area and trophic states; a metabolism model was then fit to all 6 outputs of k data. We found that hourly values for k were substantially different between models and, at an annual scale, resulted in significantly different estimates of lake metabolism and gas exchange with the atmosphere.

Dietary lipids and blood cholesterol: quantitative meta-analysis of metabolic ward studies.

PubMed Central

Clarke, R.; Frost, C.; Collins, R.; Appleby, P.; Peto, R.

1997-01-01

OBJECTIVE: To determine the quantitative importance of dietary fatty acids and dietary cholesterol to blood concentrations of total, low density lipoprotein, and high density lipoprotein cholesterol. DESIGN: Meta-analysis of metabolic ward studies of solid food diets in healthy volunteers. SUBJECTS: 395 dietary experiments (median duration 1 month) among 129 groups of individuals. RESULTS: Isocaloric replacement of saturated fats by complex carbohydrates for 10% of dietary calories resulted in blood total cholesterol falling by 0.52 (SE 0.03) mmol/l and low density lipoprotein cholesterol falling by 0.36 (0.05) mmol/l. Isocaloric replacement of complex carbohydrates by polyunsaturated fats for 5% of dietary calories resulted in total cholesterol falling by a further 0.13 (0.02) mmol/l and low density lipoprotein cholesterol falling by 0.11 (0.02) mmol/l. Similar replacement of carbohydrates by monounsaturated fats produced no significant effect on total or low density lipoprotein cholesterol. Avoiding 200 mg/day dietary cholesterol further decreased blood total cholesterol by 0.13 (0.02) mmol/l and low density lipoprotein cholesterol by 0.10 (0.02) mmol/l. CONCLUSIONS: In typical British diets replacing 60% of saturated fats by other fats and avoiding 60% of dietary cholesterol would reduce blood total cholesterol by about 0.8 mmol/l (that is, by 10-15%), with four fifths of this reduction being in low density lipoprotein cholesterol. PMID:9006469

Metabolomics and In-Silico Analysis Reveal Critical Energy Deregulations in Animal Models of Parkinson’s Disease

PubMed Central

Poliquin, Pierre O.; Chen, Jingkui; Cloutier, Mathieu; Trudeau, Louis-Éric; Jolicoeur, Mario

2013-01-01

Parkinson’s disease (PD) is a multifactorial disease known to result from a variety of factors. Although age is the principal risk factor, other etiological mechanisms have been identified, including gene mutations and exposure to toxins. Deregulation of energy metabolism, mostly through the loss of complex I efficiency, is involved in disease progression in both the genetic and sporadic forms of the disease. In this study, we investigated energy deregulation in the cerebral tissue of animal models (genetic and toxin induced) of PD using an approach that combines metabolomics and mathematical modelling. In a first step, quantitative measurements of energy-related metabolites in mouse brain slices revealed most affected pathways. A genetic model of PD, the Park2 knockout, was compared to the effect of CCCP, a complex I blocker. Model simulated and experimental results revealed a significant and sustained decrease in ATP after CCCP exposure, but not in the genetic mice model. In support to data analysis, a mathematical model of the relevant metabolic pathways was developed and calibrated onto experimental data. In this work, we show that a short-term stress response in nucleotide scavenging is most probably induced by the toxin exposure. In turn, the robustness of energy-related pathways in the model explains how genetic perturbations, at least in young animals, are not sufficient to induce significant changes at the metabolite level. PMID:23935941

Sugar Lego: gene composition of bacterial carbohydrate metabolism genomic loci.

PubMed

Kaznadzey, Anna; Shelyakin, Pavel; Gelfand, Mikhail S

2017-11-25

Bacterial carbohydrate metabolism is extremely diverse, since carbohydrates serve as a major energy source and are involved in a variety of cellular processes. Bacterial genes belonging to same metabolic pathway are often co-localized in the chromosome, but it is not a strict rule. Gene co-localization in linked to co-evolution and co-regulation. This study focuses on a large-scale analysis of bacterial genomic loci related to the carbohydrate metabolism. We demonstrate that only 53% of 148,000 studied genes from over six hundred bacterial genomes are co-localized in bacterial genomes with other carbohydrate metabolism genes, which points to a significant role of singleton genes. Co-localized genes form cassettes, ranging in size from two to fifteen genes. Two major factors influencing the cassette-forming tendency are gene function and bacterial phylogeny. We have obtained a comprehensive picture of co-localization preferences of genes for nineteen major carbohydrate metabolism functional classes, over two hundred gene orthologous clusters, and thirty bacterial classes, and characterized the cassette variety in size and content among different species, highlighting a significant role of short cassettes. The preference towards co-localization of carbohydrate metabolism genes varies between 40 and 76% for bacterial taxa. Analysis of frequently co-localized genes yielded forty-five significant pairwise links between genes belonging to different functional classes. The number of such links per class range from zero to eight, demonstrating varying preferences of respective genes towards a specific chromosomal neighborhood. Genes from eleven functional classes tend to co-localize with genes from the same class, indicating an important role of clustering of genes with similar functions. At that, in most cases such co-localization does not originate from local duplication events. Overall, we describe a complex web formed by evolutionary relationships of bacterial carbohydrate metabolism genes, manifested as co-localization patterns. This article was reviewed by Daria V. Dibrova (A.N. Belozersky Institute of Physico-Chemical Biology, Lomonosov Moscow State University, Moscow, Russia), nominated by Armen Mulkidjanian (University of Osnabrück, Germany), Igor Rogozin (NCBI, NLM, NIH, USA) and Yuri Wolf (NCBI, NLM, NIH, USA).

Butenolides from Streptomyces albus J1074 Act as External Signals To Stimulate Avermectin Production in Streptomyces avermitilis.

PubMed

Nguyen, Thao Bich; Kitani, Shigeru; Shimma, Shuichi; Nihira, Takuya

2018-05-01

In streptomycetes, autoregulators are important signaling compounds that trigger secondary metabolism, and they are regarded as Streptomyces hormones based on their extremely low effective concentrations (nM) and the involvement of specific receptor proteins. Our previous distribution study revealed that butenolide-type Streptomyces hormones, including avenolide, are a general class of signaling molecules in streptomycetes and that Streptomyces albus strain J1074 may produce butenolide-type Streptomyces hormones. Here, we describe metabolite profiling of a disruptant of the S. albus aco gene, which encodes a key biosynthetic enzyme for butenolide-type Streptomyces hormones, and identify four butenolide compounds from S. albus J1074 that show avenolide activity. The compounds structurally resemble avenolide and show different levels of avenolide activity. A dual-culture assay with imaging mass spectrometry (IMS) analysis for in vivo metabolic profiling demonstrated that the butenolide compounds of S. albus J1074 stimulate avermectin production in another Streptomyces species, Streptomyces avermitilis , illustrating the complex chemical interactions through interspecies signals in streptomycetes. IMPORTANCE Microorganisms produce external and internal signaling molecules to control their complex physiological traits. In actinomycetes, Streptomyces hormones are low-molecular-weight signals that are key to our understanding of the regulatory mechanisms of Streptomyces secondary metabolism. This study reveals that acyl coenzyme A (acyl-CoA) oxidase is a common and essential biosynthetic enzyme for butenolide-type Streptomyces hormones. Moreover, the diffusible butenolide compounds from a donor Streptomyces strain were recognized by the recipient Streptomyces strain of a different species, resulting in the initiation of secondary metabolism in the recipient. This is an interesting report on the chemical interaction between two different streptomycetes via Streptomyces hormones. Information on the metabolite network may provide useful hints not only to clarification of the regulatory mechanism of secondary metabolism, but also to understanding of the chemical communication among streptomycetes to control their physiological traits. Copyright © 2018 American Society for Microbiology.

Rates of insulin secretion in INS-1 cells are enhanced by coupling to anaplerosis and Kreb's cycle flux independent of ATP synthesis.

PubMed

Cline, Gary W; Pongratz, Rebecca L; Zhao, Xiaojian; Papas, Klearchos K

2011-11-11

Mechanistic models of glucose stimulated insulin secretion (GSIS) established in minimal media in vitro, may not accurately describe the complexity of coupling metabolism with insulin secretion that occurs in vivo. As a first approximation, we have evaluated metabolic pathways in a typical growth media, DMEM as a surrogate in vivo medium, for comparison to metabolic fluxes observed under the typical experimental conditions using the simple salt-buffer of KRB. Changes in metabolism in response to glucose and amino acids and coupling to insulin secretion were measured in INS-1 832/13 cells. Media effects on mitochondrial function and the coupling efficiency of oxidative phosphorylation were determined by fluorometrically measured oxygen consumption rates (OCRs) combined with (31)P NMR measured rates of ATP synthesis. Substrate preferences and pathways into the TCA cycle, and the synthesis of mitochondrial 2nd messengers by anaplerosis were determined by (13)C NMR isotopomer analysis of the fate of [U-(13)C] glucose metabolism. Despite similar incremental increases in insulin secretion, the changes of OCR in response to increasing glucose from 2.5 to 15mM were blunted in DMEM relative to KRB. Basal and stimulated rates of insulin secretion rates were consistently higher in DMEM, while ATP synthesis rates were identical in both DMEM and KRB, suggesting greater mitochondrial uncoupling in DMEM. The relative rates of anaplerosis, and hence synthesis and export of 2nd messengers from the mitochondria were found to be similar in DMEM to those in KRB. And, the correlation of total PC flux with insulin secretion rates in DMEM was found to be congruous with the correlation in KRB. Together, these results suggest that signaling mechanisms associated with both TCA cycle flux and with anaplerotic flux, but not ATP production, may be responsible for the enhanced rates of insulin secretion in more complex, and physiologically-relevant media. Copyright © 2011 Elsevier Inc. All rights reserved.

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

Saxer, Gerda; Krepps, Michael D.; Merkley, Eric D.

Adaptation to ecologically complex environments can provide insights into the evolutionary dynamics and functional constraints encountered by organisms during natural selection. Unlike adaptation to a single limiting resource, adaptation to a new environment with abundant and varied resources can be difficult to achieve by small incremental changes since many mutations are required to achieve even modest gains in fitness. Since changing complex environments are quite common in nature, we investigated how such an epistatic bottleneck can be avoided to allow rapid adaptation. We show that adaptive mutations arise repeatedly in independently evolved populations in the context of greatly increased geneticmore » and phenotypic diversity. We go on to show that weak selection requiring substantial metabolic reprogramming can be readily achieved by mutations in the global response regulator arcA and the stress response regulator rpoS. We identified 46 unique single-nucleotide variants of arcA and 18 mutations in rpoS, nine of which resulted in stop codons or large deletions, suggesting that a subtle modulation of ArcA function and knockouts of rpoS are largely responsible for the metabolic shifts leading to adaptation. These mutations allow a higher order “metabolic selection” that eliminates epistatic bottlenecks, which could occur when many changes would be required. Proteomic and carbohydrate analysis of adapting E. coli populations revealed an up-regulation of enzymes associated with the TCA cycle and amino acid metabolism and an increase in the secretion of putrescine. The overall effect of adaptation across populations is to redirect and efficiently utilize uptake and catabolism of abundant amino acids. Concomitantly, there is a pronounced spread of more ecologically limited strains that results from specialization through metabolic erosion. Remarkably, the global regulators arcA and rpoS can provide a “one-step” mechanism of adaptation to a novel environment, which highlights the importance of global resource management as a powerful strategy to adaptation.« less

A new level of regulation in gluconeogenesis: metabolic state modulates the intracellular localization of aldolase B and its interaction with liver fructose-1,6-bisphosphatase.

PubMed

Droppelmann, Cristian A; Sáez, Doris E; Asenjo, Joel L; Yáñez, Alejandro J; García-Rocha, Mar; Concha, Ilona I; Grez, Manuel; Guinovart, Joan J; Slebe, Juan C

2015-12-01

Understanding how glucose metabolism is finely regulated at molecular and cellular levels in the liver is critical for knowing its relationship to related pathologies, such as diabetes. In order to gain insight into the regulation of glucose metabolism, we studied the liver-expressed isoforms aldolase B and fructose-1,6-bisphosphatase-1 (FBPase-1), key enzymes in gluconeogenesis, analysing their cellular localization in hepatocytes under different metabolic conditions and their protein-protein interaction in vitro and in vivo. We observed that glucose, insulin, glucagon and adrenaline differentially modulate the intracellular distribution of aldolase B and FBPase-1. Interestingly, the in vitro protein-protein interaction analysis between aldolase B and FBPase-1 showed a specific and regulable interaction between them, whereas aldolase A (muscle isozyme) and FBPase-1 showed no interaction. The affinity of the aldolase B and FBPase-1 complex was modulated by intermediate metabolites, but only in the presence of K(+). We observed a decreased association constant in the presence of adenosine monophosphate, fructose-2,6-bisphosphate, fructose-6-phosphate and inhibitory concentrations of fructose-1,6-bisphosphate. Conversely, the association constant of the complex increased in the presence of dihydroxyacetone phosphate (DHAP) and non-inhibitory concentrations of fructose-1,6-bisphosphate. Notably, in vivo FRET studies confirmed the interaction between aldolase B and FBPase-1. Also, the co-expression of aldolase B and FBPase-1 in cultured cells suggested that FBPase-1 guides the cellular localization of aldolase B. Our results provide further evidence that metabolic conditions modulate aldolase B and FBPase-1 activity at the cellular level through the regulation of their interaction, suggesting that their association confers a catalytic advantage for both enzymes. © 2015 Authors; published by Portland Press Limited.

Chemometrics Methods for Specificity, Authenticity and Traceability Analysis of Olive Oils: Principles, Classifications and Applications.

PubMed

Messai, Habib; Farman, Muhammad; Sarraj-Laabidi, Abir; Hammami-Semmar, Asma; Semmar, Nabil

2016-11-17

Olive oils (OOs) show high chemical variability due to several factors of genetic, environmental and anthropic types. Genetic and environmental factors are responsible for natural compositions and polymorphic diversification resulting in different varietal patterns and phenotypes. Anthropic factors, however, are at the origin of different blends' preparation leading to normative, labelled or adulterated commercial products. Control of complex OO samples requires their (i) characterization by specific markers; (ii) authentication by fingerprint patterns; and (iii) monitoring by traceability analysis. These quality control and management aims require the use of several multivariate statistical tools: specificity highlighting requires ordination methods; authentication checking calls for classification and pattern recognition methods; traceability analysis implies the use of network-based approaches able to separate or extract mixed information and memorized signals from complex matrices. This chapter presents a review of different chemometrics methods applied for the control of OO variability from metabolic and physical-chemical measured characteristics. The different chemometrics methods are illustrated by different study cases on monovarietal and blended OO originated from different countries. Chemometrics tools offer multiple ways for quantitative evaluations and qualitative control of complex chemical variability of OO in relation to several intrinsic and extrinsic factors.

Roles of mitochondrial energy dissipation systems in plant development and acclimation to stress.

PubMed

Pu, Xiaojun; Lv, Xin; Tan, Tinghong; Fu, Faqiong; Qin, Gongwei; Lin, Honghui

2015-09-01

Plants are sessile organisms that have the ability to integrate external cues into metabolic and developmental signals. The cues initiate specific signal cascades that can enhance the tolerance of plants to stress, and these mechanisms are crucial to the survival and fitness of plants. The adaption of plants to stresses is a complex process that involves decoding stress inputs as energy-deficiency signals. The process functions through vast metabolic and/or transcriptional reprogramming to re-establish the cellular energy balance. Members of the mitochondrial energy dissipation pathway (MEDP), alternative oxidases (AOXs) and uncoupling proteins (UCPs), act as energy mediators and might play crucial roles in the adaption of plants to stresses. However, their roles in plant growth and development have been relatively less explored. This review summarizes current knowledge about the role of members of the MEDP in plant development as well as recent advances in identifying molecular components that regulate the expression of AOXs and UCPs. Highlighted in particular is a comparative analysis of the expression, regulation and stress responses between AOXs and UCPs when plants are exposed to stresses, and a possible signal cross-talk that orchestrates the MEDP, reactive oxygen species (ROS), calcium signalling and hormone signalling. The MEDP might act as a cellular energy/metabolic mediator that integrates ROS signalling, energy signalling and hormone signalling with plant development and stress accumulation. However, the regulation of MEDP members is complex and occurs at transcriptional, translational, post-translational and metabolic levels. How this regulation is linked to actual fluxes through the AOX/UCP in vivo remains elusive. © The Author 2015. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

A link between central kynurenine metabolism and bone strength in rats with chronic kidney disease

PubMed Central

Pawlak, Krystyna; Oksztulska-Kolanek, Ewa; Domaniewski, Tomasz; Znorko, Beata; Karbowska, Malgorzata; Citkowska, Aleksandra; Rogalska, Joanna; Roszczenko, Alicja; Brzoska, Malgorzata M.; Pawlak, Dariusz

2017-01-01

Background Disturbances in mineral and bone metabolism represent one of the most complex complications of chronic kidney disease (CKD). Serotonin, a monoamine synthesized from tryptophan, may play a potential role in bone metabolism. Brain-derived serotonin exerts a positive effect on the bone structure by limiting bone resorption and enhancing bone formation. Tryptophan is the precursor not only to the serotonin but also and primarily to kynurenine metabolites. The ultimate aim of the present study was to determine the association between central kynurenine metabolism and biomechanical as well as geometrical properties of bone in the experimental model of the early stage of CKD. Methods Thirty-three Wistar rats were randomly divided into two groups (sham-operated and subtotal nephrectomized animals). Three months after surgery, serum samples were obtained for the determination of biochemical parameters, bone turnover biomarkers, and kynurenine pathway metabolites; tibias were collected for bone biomechanical, bone geometrical, and bone mass density analysis; brains were removed and divided into five regions for the determination of kynurenine pathway metabolites. Results Subtotal nephrectomized rats presented higher serum concentrations of creatinine, urea nitrogen, and parathyroid hormone, and developed hypocalcemia. Several biomechanical and geometrical parameters were significantly elevated in rats with experimentally induced CKD. Subtotal nephrectomized rats presented significantly higher kynurenine concentrations and kynurenine/tryptophan ratio and significantly lower tryptophan levels in all studied parts of the brain. Kynurenine in the frontal cortex and tryptophan in the hypothalamus and striatum correlated positively with the main parameters of bone biomechanics and bone geometry. Discussion In addition to the complex mineral, hormone, and metabolite changes, intensified central kynurenine turnover may play an important role in the development of bone changes in the course of CKD. PMID:28439468

Proteomic analysis of proteins related to rice grain chalkiness using iTRAQ and a novel comparison system based on a notched-belly mutant with white-belly

PubMed Central

2014-01-01

Background Grain chalkiness is a complex trait adversely affecting appearance and milling quality, and therefore has been one of principal targets for rice improvement. Eliminating chalkiness from rice has been a daunting task due to the complex interaction between genotype and environment and the lack of molecular markers. In addition, the molecular mechanisms underlying grain chalkiness formation are still imperfectly understood. Results We identified a notched-belly mutant (DY1102) with high percentage of white-belly, which only occurs in the bottom part proximal to the embryo. Using this mutant, a novel comparison system that can minimize the effect of genetic background and growing environment was developed. An iTRAQ-based comparative display of the proteins between the bottom chalky part and the upper translucent part of grains of DY1102 was performed. A total of 113 proteins responsible for chalkiness formation was identified. Among them, 70 proteins are up-regulated and 43 down-regulated. Approximately half of these differentially expressed proteins involved in central metabolic or regulatory pathways including carbohydrate metabolism (especially cell wall synthesis) and protein synthesis, folding and degradation, providing proteomic confirmation of the notion that chalkiness formation involves diverse but delicately regulated pathways. Protein metabolism was the most abundant category, accounting for 27.4% of the total differentially expressed proteins. In addition, down regulation of PDIL 2–3 and BiP was detected in the chalky tissue, indicating the important role of protein metabolism in grain chalkiness formation. Conclusions Using this novel comparison system, our comprehensive survey of endosperm proteomics in the notched-belly mutant provides a valuable proteomic resource for the characterization of pathways contributing to chalkiness formation at molecular and biochemical levels. PMID:24924297

Platform for systems medicine research and diagnostic applications in psychotic disorders-The METSY project.

PubMed

Frank, Elisabeth; Maier, Dieter; Pajula, Juha; Suvitaival, Tommi; Borgan, Faith; Butz-Ostendorf, Markus; Fischer, Alexander; Hietala, Jarmo; Howes, Oliver; Hyötyläinen, Tuulia; Janssen, Joost; Laurikainen, Heikki; Moreno, Carmen; Suvisaari, Jaana; Van Gils, Mark; Orešič, Matej

2018-04-01

Psychotic disorders are associated with metabolic abnormalities including alterations in glucose and lipid metabolism. A major challenge in the treatment of psychosis is to identify patients with vulnerable metabolic profiles who may be at risk of developing cardiometabolic co-morbidities. It is established that both central and peripheral metabolic organs use lipids to control energy balance and regulate peripheral insulin sensitivity. The endocannabinoid system, implicated in the regulation of glucose and lipid metabolism, has been shown to be dysregulated in psychosis. It is currently unclear how these endocannabinoid abnormalities relate to metabolic changes in psychosis. Here we review recent research in the field of metabolic co-morbidities in psychotic disorders as well as the methods to study them and potential links to the endocannabinoid system. We also describe the bioinformatics platforms developed in the EU project METSY for the investigations of the biological etiology in patients at risk of psychosis and in first episode psychosis patients. The METSY project was established with the aim to identify and evaluate multi-modal peripheral and neuroimaging markers that may be able to predict the onset and prognosis of psychiatric and metabolic symptoms in patients at risk of developing psychosis and first episode psychosis patients. Given the intrinsic complexity and widespread role of lipid metabolism, a systems biology approach which combines molecular, structural and functional neuroimaging methods with detailed metabolic characterisation and multi-variate network analysis is essential in order to identify how lipid dysregulation may contribute to psychotic disorders. A decision support system, integrating clinical, neuropsychological and neuroimaging data, was also developed in order to aid clinical decision making in psychosis. Knowledge of common and specific mechanisms may aid the etiopathogenic understanding of psychotic and metabolic disorders, facilitate early disease detection, aid treatment selection and elucidate new targets for pharmacological treatments. Copyright © 2017. Published by Elsevier Masson SAS.

Mammalian gravity receptors: Structure and metabolism

NASA Technical Reports Server (NTRS)

Ross, M.

1984-01-01

High performance liquid chromatography (HPLC) instrumentation was used for amino acid analysis of rat otoconial complexes. The amino acids of otoconial complexes pooled by origin from only 10 rats were analyzed. It is indicated that it should be possible to analyze complexes from only three rats, and perhaps fewer, which means that the method should be applicable to material from space flow rats. It is suggested that the organic otoconial phase is comparable in its complement of acidic amino acids to other calcium carbonate containing materials such as fish otoliths and certain mollusk shells. The organic material is high in acidic amino acids; and the relative proportions of aspirate, glutamate, threonine and serine appear to be similar to those found in neogastropod shells. Its significance to the evolution of biomineralization processes occurring in the animal kingdom is emphasized.

Identification of differentially-expressed genes potentially implicated in drought response in pitaya (Hylocereus undatus) by suppression subtractive hybridization and cDNA microarray analysis.

PubMed

Fan, Qing-Jie; Yan, Feng-Xia; Qiao, Guang; Zhang, Bing-Xue; Wen, Xiao-Peng

2014-01-01

Drought is one of the most severe threats to the growth, development and yield of plant. In order to unravel the molecular basis underlying the high tolerance of pitaya (Hylocereus undatus) to drought stress, suppression subtractive hybridization (SSH) and cDNA microarray approaches were firstly combined to identify the potential important or novel genes involved in the plant responses to drought stress. The forward (drought over drought-free) and reverse (drought-free over drought) suppression subtractive cDNA libraries were constructed using in vitro shoots of cultivar 'Zihonglong' exposed to drought stress and drought-free (control). A total of 2112 clones, among which half were from either forward or reverse SSH library, were randomly picked up to construct a pitaya cDNA microarray. Microarray analysis was carried out to verify the expression fluctuations of this set of clones upon drought treatment compared with the controls. A total of 309 expressed sequence tags (ESTs), 153 from forward library and 156 from reverse library, were obtained, and 138 unique ESTs were identified after sequencing by clustering and blast analyses, which included genes that had been previously reported as responsive to water stress as well as some functionally unknown genes. Thirty six genes were mapped to 47 KEGG pathways, including carbohydrate metabolism, lipid metabolism, energy metabolism, nucleotide metabolism, and amino acid metabolism of pitaya. Expression analysis of the selected ESTs by reverse transcriptase polymerase chain reaction (RT-PCR) corroborated the results of differential screening. Moreover, time-course expression patterns of these selected ESTs further confirmed that they were closely responsive to drought treatment. Among the differentially expressed genes (DEGs), many are related to stress tolerances including drought tolerance. Thereby, the mechanism of drought tolerance of this pitaya genotype is a very complex physiological and biochemical process, in which multiple metabolism pathways and many genes were implicated. The data gained herein provide an insight into the mechanism underlying the drought stress tolerance of pitaya, as well as may facilitate the screening of candidate genes for drought tolerance. © 2013 Elsevier B.V. All rights reserved.