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Sample records for production metabolism scaling

  1. Biofuel production: an odyssey from metabolic engineering to fermentation scale-up

    PubMed Central

    Hollinshead, Whitney; He, Lian; Tang, Yinjie J.

    2014-01-01

    Metabolic engineering has developed microbial cell factories that can convert renewable carbon sources into biofuels. Current molecular biology tools can efficiently alter enzyme levels to redirect carbon fluxes toward biofuel production, but low product yield and titer in large bioreactors prevent the fulfillment of cheap biofuels. There are three major roadblocks preventing economical biofuel production. First, carbon fluxes from the substrate dissipate into a complex metabolic network. Besides the desired product, microbial hosts direct carbon flux to synthesize biomass, overflow metabolites, and heterologous enzymes. Second, microbial hosts need to oxidize a large portion of the substrate to generate both ATP and NAD(P)H to power biofuel synthesis. High cell maintenance, triggered by the metabolic burdens from genetic modifications, can significantly affect the ATP supply. Thereby, fermentation of advanced biofuels (such as biodiesel and hydrocarbons) often requires aerobic respiration to resolve the ATP shortage. Third, mass transfer limitations in large bioreactors create heterogeneous growth conditions and micro-environmental fluctuations (such as suboptimal O2 level and pH) that induce metabolic stresses and genetic instability. To overcome these limitations, fermentation engineering should merge with systems metabolic engineering. Modern fermentation engineers need to adopt new metabolic flux analysis tools that integrate kinetics, hydrodynamics, and 13C-proteomics, to reveal the dynamic physiologies of the microbial host under large bioreactor conditions. Based on metabolic analyses, fermentation engineers may employ rational pathway modifications, synthetic biology circuits, and bioreactor control algorithms to optimize large-scale biofuel production. PMID:25071754

  2. Biological stoichiometry of plant production: metabolism, scaling and ecological response to global change.

    PubMed

    Elser, J J; Fagan, W F; Kerkhoff, A J; Swenson, N G; Enquist, B J

    2010-05-01

    Biological stoichiometry theory considers the balance of multiple chemical elements in living systems, whereas metabolic scaling theory considers how size affects metabolic properties from cells to ecosystems. We review recent developments integrating biological stoichiometry and metabolic scaling theories in the context of plant ecology and global change. Although vascular plants exhibit wide variation in foliar carbon:nitrogen:phosphorus ratios, they exhibit a higher degree of 'stoichiometric homeostasis' than previously appreciated. Thus, terrestrial carbon:nitrogen:phosphorus stoichiometry will reflect the effects of adjustment to local growth conditions as well as species' replacements. Plant stoichiometry exhibits size scaling, as foliar nutrient concentration decreases with increasing plant size, especially for phosphorus. Thus, small plants have lower nitrogen:phosphorus ratios. Furthermore, foliar nutrient concentration is reflected in other tissues (root, reproductive, support), permitting the development of empirical models of production that scale from tissue to whole-plant levels. Plant stoichiometry exhibits large-scale macroecological patterns, including stronger latitudinal trends and environmental correlations for phosphorus concentration (relative to nitrogen) and a positive correlation between nutrient concentrations and geographic range size. Given this emerging knowledge of how plant nutrients respond to environmental variables and are connected to size, the effects of global change factors (such as carbon dioxide, temperature, nitrogen deposition) can be better understood. PMID:20298486

  3. Genome-scale metabolic network reconstruction of Saccharopolyspora spinosa for Spinosad Production improvement

    PubMed Central

    2014-01-01

    Background Spinosad is a macrolide antibiotic produced by Saccharopolyspora spinosa with aerobic fermentation. However, the wild strain has a low productivity. In this article, a computational guided engineering approach was adopted in order to improve the yield of spinosad in S. spinosa. Results Firstly, a genome-scale metabolic network reconstruction (GSMR) for S.spinosa based on its genome information, literature data and experimental data was extablished. The model was consists of 1,577 reactions, 1,726 metabolites, and 733 enzymes after manually refined. Then, amino acids supplying experiments were performed in order to test the capabilities of the model, and the results showed a high consistency. Subsequently, transhydrogenase (PntAB, EC 1.6.1.2) was chosen as the potential target for spinosad yield improvement based on the in silico metabolic network models. Furthermore, the target gene was manipulated in the parent strain in order to validate the model predictions. At last, shake flask fermentation was carried out which led to spinosad production of 75.32 mg/L, 86.5% higher than the parent strain (40.39 mg/L). Conclusions Results confirmed the model had a high potential in engineering S. spinosa for spinosad production. It is the first GSMM for S.spinosa, it has significance for a better understanding of the comprehensive metabolism and guiding strain designing of Saccharopolyspora spinosa in the future. PMID:24628959

  4. Toward systems-level analysis of agricultural production from crassulacean acid metabolism (CAM): scaling from cell to commercial production.

    PubMed

    Davis, Sarah C; Ming, Ray; LeBauer, David S; Long, Stephen P

    2015-10-01

    Systems-level analyses have become prominent tools for assessing the yield, viability, economic consequences and environmental impacts of agricultural production. Such analyses are well-developed for many commodity crops that are used for food and biofuel, but have not been developed for agricultural production systems based on drought-tolerant plants that use crassulacean acid metabolism (CAM). We review the components of systems-level evaluations, and identify the information available for completing such analyses for CAM cropping systems. Specific needs for developing systems-level evaluations of CAM agricultural production include: improvement of physiological models; assessment of product processing after leaving the farm gate; and application of newly available genetic tools to the optimization of CAM species for commercial production. PMID:26094655

  5. Genome-scale metabolic modeling and in silico analysis of lipid accumulating yeast Candida tropicalis for dicarboxylic acid production.

    PubMed

    Mishra, Pranjul; Park, Gyu-Yeon; Lakshmanan, Meiyappan; Lee, Hee-Seok; Lee, Hongweon; Chang, Matthew Wook; Ching, Chi Bun; Ahn, Jungoh; Lee, Dong-Yup

    2016-09-01

    Recently, the bio-production of α,ω-dicarboxylic acids (DCAs) has gained significant attention, which potentially leads to the replacement of the conventional petroleum-based products. In this regard, the lipid accumulating yeast Candida tropicalis, has been recognized as a promising microbial host for DCA biosynthesis: it possess the unique ω-oxidation pathway where the terminal carbon of α-fatty acids is oxidized to form DCAs with varying chain lengths. However, despite such industrial importance, its cellular physiology and lipid accumulation capability remain largely uncharacterized. Thus, it is imperative to better understand the metabolic behavior of this lipogenic yeast, which could be achieved by a systems biological approach. To this end, herein, we reconstructed the genome-scale metabolic model of C. tropicalis, iCT646, accounting for 646 unique genes, 945 metabolic reactions, and 712 metabolites. Initially, the comparative network analysis of iCT646 with other yeasts revealed several distinctive metabolic reactions, mainly within the amino acid and lipid metabolism including the ω-oxidation pathway. Constraints-based flux analysis was, then, employed to predict the in silico growth rates of C. tropicalis which are highly consistent with the cellular phenotype observed in glucose and xylose minimal media chemostat cultures. Subsequently, the lipid accumulation capability of C. tropicalis was explored in comparison with Saccharomyces cerevisiae, indicating that the formation of "citrate pyruvate cycle" is essential to the lipid accumulation in oleaginous yeasts. The in silico flux analysis also highlighted the enhanced ability of pentose phosphate pathway as NADPH source rather than malic enzyme during lipogenesis. Finally, iCT646 was successfully utilized to highlight the key directions of C. tropicalis strain design for the whole cell biotransformation application to produce long-chain DCAs from alkanes. Biotechnol. Bioeng. 2016;113: 1993-2004.

  6. In silico method for modelling metabolism and gene product expression at genome scale

    PubMed Central

    Lerman, Joshua A.; Hyduke, Daniel R.; Latif, Haythem; Portnoy, Vasiliy A.; Lewis, nathan E.; Orth, Jeffrey D.; Schrimpe-Rutledge, Alexandra C.; Smith, Richard D.; Adkins, Joshua n.; Zengler, Karsten; Palsson, Bernhard O.

    2013-01-01

    Transcription and translation use raw materials and energy generated metabolically to create the macromolecular machinery responsible for all cellular functions, including metabolism. A biochemically accurate model of molecular biology and metabolism will facilitate comprehensive and quantitative computations of an organism's molecular constitution as a function of genetic and environmental parameters. Here we formulate a model of metabolism and macromolecular expression. Prototyping it using the simple microorganism Thermotoga maritima, we show our model accurately simulates variations in cellular composition and gene expression. Moreover, through in silico comparative transcriptomics, the model allows the discovery of new regulons and improving the genome and transcription unit annotations. Our method presents a framework for investigating molecular biology and cellular physiology in silico and may allow quantitative interpretation of multi-omics data sets in the context of an integrated biochemical description of an organism. PMID:22760628

  7. In silico method for modelling metabolism and gene product expression at genome scale

    SciTech Connect

    Lerman, Joshua A.; Hyduke, Daniel R.; Latif, Haythem; Portnoy, Vasiliy A.; Lewis, Nathan E.; Orth, Jeffrey D.; Rutledge, Alexandra C.; Smith, Richard D.; Adkins, Joshua N.; Zengler, Karsten; Palsson, Bernard O.

    2012-07-03

    Transcription and translation use raw materials and energy generated metabolically to create the macromolecular machinery responsible for all cellular functions, including metabolism. A biochemically accurate model of molecular biology and metabolism will facilitate comprehensive and quantitative computations of an organism's molecular constitution as a function of genetic and environmental parameters. Here we formulate a model of metabolism and macromolecular expression. Prototyping it using the simple microorganism Thermotoga maritima, we show our model accurately simulates variations in cellular composition and gene expression. Moreover, through in silico comparative transcriptomics, the model allows the discovery of new regulons and improving the genome and transcription unit annotations. Our method presents a framework for investigating molecular biology and cellular physiology in silico and may allow quantitative interpretation of multi-omics data sets in the context of an integrated biochemical description of an organism.

  8. Scaling metabolic rate fluctuations.

    PubMed

    Labra, Fabio A; Marquet, Pablo A; Bozinovic, Francisco

    2007-06-26

    Complex ecological and economic systems show fluctuations in macroscopic quantities such as exchange rates, size of companies or populations that follow non-Gaussian tent-shaped probability distributions of growth rates with power-law decay, which suggests that fluctuations in complex systems may be governed by universal mechanisms, independent of particular details and idiosyncrasies. We propose here that metabolic rate within individual organisms may be considered as an example of an emergent property of a complex system and test the hypothesis that the probability distribution of fluctuations in the metabolic rate of individuals has a "universal" form regardless of body size or taxonomic affiliation. We examined data from 71 individuals belonging to 25 vertebrate species (birds, mammals, and lizards). We report three main results. First, for all these individuals and species, the distribution of metabolic rate fluctuations follows a tent-shaped distribution with power-law decay. Second, the standard deviation of metabolic rate fluctuations decays as a power-law function of both average metabolic rate and body mass, with exponents -0.352 and -1/4 respectively. Finally, we find that the distributions of metabolic rate fluctuations for different organisms can all be rescaled to a single parent distribution, supporting the existence of general principles underlying the structure and functioning of individual organisms. PMID:17578913

  9. Form and metabolic scaling in colonial animals.

    PubMed

    Hartikainen, Hanna; Humphries, Stuart; Okamura, Beth

    2014-03-01

    Benthic colonial organisms exhibit a wide variation in size and shape and provide excellent model systems for testing the predictions of models that describe the scaling of metabolic rate with organism size. We tested the hypothesis that colony form will influence metabolic scaling and its derivatives by characterising metabolic and propagule production rates in three species of freshwater bryozoans that vary in morphology and module organisation and which demonstrate two- and three-dimensional growth forms. The results were evaluated with respect to predictions from two models for metabolic scaling. Isometric metabolic scaling in two-dimensional colonies supported predictions of a model based on dynamic energy budget theory (DEB) and not those of a model based on fractally branching supply networks. This metabolic isometry appears to be achieved by equivalent energy budgets of edge and central modules, in one species (Cristatella mucedo) via linear growth and in a second species (Lophopus crystallinus) by colony fission. Allometric scaling characterised colonies of a three-dimensional species (Fredericella sultana), also providing support for the DEB model. Isometric scaling of propagule production rates for C. mucedo and F. sultana suggests that the number of propagules produced in colonies increases in direct proportion with the number of modules within colonies. Feeding currents generated by bryozoans function in both food capture and respiration, thus linking metabolic scaling with dynamics of self-shading and resource capture. Metabolic rates fundamentally dictate organismal performance (e.g. growth, reproduction) and, as we show here, are linked with colony form. Metabolic profiles and associated variation in colony form should therefore influence the outcome of biotic interactions in habitats dominated by colonial animals and may drive patterns of macroevolution. PMID:24265433

  10. Integrating large-scale functional genomics data to dissect metabolic networks for hydrogen production

    SciTech Connect

    Harwood, Caroline S

    2012-12-17

    The goal of this project is to identify gene networks that are critical for efficient biohydrogen production by leveraging variation in gene content and gene expression in independently isolated Rhodopseudomonas palustris strains. Coexpression methods were applied to large data sets that we have collected to define probabilistic causal gene networks. To our knowledge this a first systems level approach that takes advantage of strain-to strain variability to computationally define networks critical for a particular bacterial phenotypic trait.

  11. Allometric scaling laws of metabolism

    NASA Astrophysics Data System (ADS)

    da Silva, Jafferson Kamphorst Leal; Garcia, Guilherme J. M.; Barbosa, Lauro A.

    2006-12-01

    One of the most pervasive laws in biology is the allometric scaling, whereby a biological variable Y is related to the mass M of the organism by a power law, Y=YM, where b is the so-called allometric exponent. The origin of these power laws is still a matter of dispute mainly because biological laws, in general, do not follow from physical ones in a simple manner. In this work, we review the interspecific allometry of metabolic rates, where recent progress in the understanding of the interplay between geometrical, physical and biological constraints has been achieved. For many years, it was a universal belief that the basal metabolic rate (BMR) of all organisms is described by Kleiber's law (allometric exponent b=3/4). A few years ago, a theoretical basis for this law was proposed, based on a resource distribution network common to all organisms. Nevertheless, the 3/4-law has been questioned recently. First, there is an ongoing debate as to whether the empirical value of b is 3/4 or 2/3, or even nonuniversal. Second, some mathematical and conceptual errors were found these network models, weakening the proposed theoretical arguments. Another pertinent observation is that the maximal aerobically sustained metabolic rate of endotherms scales with an exponent larger than that of BMR. Here we present a critical discussion of the theoretical models proposed to explain the scaling of metabolic rates, and compare the predicted exponents with a review of the experimental literature. Our main conclusion is that although there is not a universal exponent, it should be possible to develop a unified theory for the common origin of the allometric scaling laws of metabolism.

  12. Reconstruction and in silico analysis of an Actinoplanes sp. SE50/110 genome-scale metabolic model for acarbose production

    PubMed Central

    Wang, Yali; Xu, Nan; Ye, Chao; Liu, Liming; Shi, Zhongping; Wu, Jing

    2015-01-01

    Actinoplanes sp. SE50/110 produces the α-glucosidase inhibitor acarbose, which is used to treat type 2 diabetes mellitus. To obtain a comprehensive understanding of its cellular metabolism, a genome-scale metabolic model of strain SE50/110, iYLW1028, was reconstructed on the bases of the genome annotation, biochemical databases, and extensive literature mining. Model iYLW1028 comprises 1028 genes, 1128 metabolites, and 1219 reactions. One hundred and twenty-two and eighty one genes were essential for cell growth on acarbose synthesis and sucrose media, respectively, and the acarbose biosynthetic pathway in SE50/110 was expounded completely. Based on model predictions, the addition of arginine and histidine to the media increased acarbose production by 78 and 59%, respectively. Additionally, dissolved oxygen has a great effect on acarbose production based on model predictions. Furthermore, genes to be overexpressed for the overproduction of acarbose were identified, and the deletion of treY eliminated the formation of by-product component C. Model iYLW1028 is a useful platform for optimizing and systems metabolic engineering for acarbose production in Actinoplanes sp. SE50/110. PMID:26161077

  13. Identification of metabolic engineering targets for the enhancement of 1,4-butanediol production in recombinant E. coli using large-scale kinetic models.

    PubMed

    Andreozzi, Stefano; Chakrabarti, Anirikh; Soh, Keng Cher; Burgard, Anthony; Yang, Tae Hoon; Van Dien, Stephen; Miskovic, Ljubisa; Hatzimanikatis, Vassily

    2016-05-01

    Rational metabolic engineering methods are increasingly employed in designing the commercially viable processes for the production of chemicals relevant to pharmaceutical, biotechnology, and food and beverage industries. With the growing availability of omics data and of methodologies capable to integrate the available data into models, mathematical modeling and computational analysis are becoming important in designing recombinant cellular organisms and optimizing cell performance with respect to desired criteria. In this contribution, we used the computational framework ORACLE (Optimization and Risk Analysis of Complex Living Entities) to analyze the physiology of recombinant Escherichia coli producing 1,4-butanediol (BDO) and to identify potential strategies for improved production of BDO. The framework allowed us to integrate data across multiple levels and to construct a population of large-scale kinetic models despite the lack of available information about kinetic properties of every enzyme in the metabolic pathways. We analyzed these models and we found that the enzymes that primarily control the fluxes leading to BDO production are part of central glycolysis, the lower branch of tricarboxylic acid (TCA) cycle and the novel BDO production route. Interestingly, among the enzymes between the glucose uptake and the BDO pathway, the enzymes belonging to the lower branch of TCA cycle have been identified as the most important for improving BDO production and yield. We also quantified the effects of changes of the target enzymes on other intracellular states like energy charge, cofactor levels, redox state, cellular growth, and byproduct formation. Independent earlier experiments on this strain confirmed that the computationally obtained conclusions are consistent with the experimentally tested designs, and the findings of the present studies can provide guidance for future work on strain improvement. Overall, these studies demonstrate the potential and

  14. Supply–demand balance and metabolic scaling

    PubMed Central

    Banavar, Jayanth R.; Damuth, John; Maritan, Amos; Rinaldo, Andrea

    2002-01-01

    It is widely accepted that metabolic rates scale across species approximately as the 3/4 power of mass in most if not all groups of organisms. Metabolic demand per unit mass thus decreases as body mass increases. Metabolic rates reflect both the ability of the organism's transport system to deliver metabolites to the tissues and the rate at which the tissues use them. We show that the ubiquitous 3/4 power law for interspecific metabolic scaling arises from simple, general geometric properties of transportation networks constrained to function in biological organisms. The 3/4 exponent and other observed scaling relationships follow when mass-specific metabolic demands match the changing delivery capacities of the network at different body sizes. Deviation from the 3/4 exponent suggests either inefficiency or compensating physiological mechanisms. Our conclusions are based on general arguments incorporating the minimum of biological detail and should therefore apply to the widest range of organisms. PMID:12149461

  15. Genome-scale modeling for metabolic engineering

    SciTech Connect

    Simeonidis, E; Price, ND

    2015-01-13

    We focus on the application of constraint-based methodologies and, more specifically, flux balance analysis in the field of metabolic engineering, and enumerate recent developments and successes of the field. We also review computational frameworks that have been developed with the express purpose of automatically selecting optimal gene deletions for achieving improved production of a chemical of interest. The application of flux balance analysis methods in rational metabolic engineering requires a metabolic network reconstruction and a corresponding in silico metabolic model for the microorganism in question. For this reason, we additionally present a brief overview of automated reconstruction techniques. Finally, we emphasize the importance of integrating metabolic networks with regulatory information-an area which we expect will become increasingly important for metabolic engineering-and present recent developments in the field of metabolic and regulatory integration.

  16. Characterizing acetogenic metabolism using a genome-scale metabolic reconstruction of Clostridium ljungdahlii

    PubMed Central

    2013-01-01

    Background The metabolic capabilities of acetogens to ferment a wide range of sugars, to grow autotrophically on H2/CO2, and more importantly on synthesis gas (H2/CO/CO2) make them very attractive candidates as production hosts for biofuels and biocommodities. Acetogenic metabolism is considered one of the earliest modes of bacterial metabolism. A thorough understanding of various factors governing the metabolism, in particular energy conservation mechanisms, is critical for metabolic engineering of acetogens for targeted production of desired chemicals. Results Here, we present the genome-scale metabolic network of Clostridium ljungdahlii, the first such model for an acetogen. This genome-scale model (iHN637) consisting of 637 genes, 785 reactions, and 698 metabolites captures all the major central metabolic and biosynthetic pathways, in particular pathways involved in carbon fixation and energy conservation. A combination of metabolic modeling, with physiological and transcriptomic data provided insights into autotrophic metabolism as well as aided the characterization of a nitrate reduction pathway in C. ljungdahlii. Analysis of the iHN637 metabolic model revealed that flavin based electron bifurcation played a key role in energy conservation during autotrophic growth and helped identify genes for some of the critical steps in this mechanism. Conclusions iHN637 represents a predictive model that recapitulates experimental data, and provides valuable insights into the metabolic response of C. ljungdahlii to genetic perturbations under various growth conditions. Thus, the model will be instrumental in guiding metabolic engineering of C. ljungdahlii for the industrial production of biocommodities and biofuels. PMID:24274140

  17. Characterizing acetogenic metabolism using a genome-scale metabolic reconstruction of Clostridium ljungdahlii

    SciTech Connect

    Nagarajan, H; Sahin, M; Nogales, J; Latif, H; Lovley, DR; Ebrahim, A; Zengler, K

    2013-11-25

    Background: The metabolic capabilities of acetogens to ferment a wide range of sugars, to grow autotrophically on H-2/CO2, and more importantly on synthesis gas (H-2/CO/CO2) make them very attractive candidates as production hosts for biofuels and biocommodities. Acetogenic metabolism is considered one of the earliest modes of bacterial metabolism. A thorough understanding of various factors governing the metabolism, in particular energy conservation mechanisms, is critical for metabolic engineering of acetogens for targeted production of desired chemicals. Results: Here, we present the genome-scale metabolic network of Clostridium ljungdahlii, the first such model for an acetogen. This genome-scale model (iHN637) consisting of 637 genes, 785 reactions, and 698 metabolites captures all the major central metabolic and biosynthetic pathways, in particular pathways involved in carbon fixation and energy conservation. A combination of metabolic modeling, with physiological and transcriptomic data provided insights into autotrophic metabolism as well as aided the characterization of a nitrate reduction pathway in C. ljungdahlii. Analysis of the iHN637 metabolic model revealed that flavin based electron bifurcation played a key role in energy conservation during autotrophic growth and helped identify genes for some of the critical steps in this mechanism. Conclusions: iHN637 represents a predictive model that recapitulates experimental data, and provides valuable insights into the metabolic response of C. ljungdahlii to genetic perturbations under various growth conditions. Thus, the model will be instrumental in guiding metabolic engineering of C. ljungdahlii for the industrial production of biocommodities and biofuels.

  18. 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

  19. Production of natural products through metabolic engineering of Saccharomyces cerevisiae.

    PubMed

    Krivoruchko, Anastasia; Nielsen, Jens

    2015-12-01

    Many high-value metabolites are produced in nature by organisms that are not ideal for large-scale production. Therefore, interest exists in expressing the biosynthetic pathways of these compounds in organisms that are more suitable for industrial production. Recent years have seen developments in both the discovery of various biosynthetic pathways, as well as development of metabolic engineering tools that allow reconstruction of complex pathways in microorganisms. In the present review we discuss recent advances in reconstruction of the biosynthetic pathways of various high-value products in the yeast Saccharomyces cerevisiae, a commonly used industrial microorganism. Key achievements in the production of different isoprenoids, aromatics and polyketides are presented and the metabolic engineering strategies underlying these accomplishments are discussed. PMID:25544013

  20. Imaging the time-integrated cerebral metabolic activity with subcellular resolution through nanometer-scale detection of biosynthetic products deriving from (13)C-glucose.

    PubMed

    Takado, Yuhei; Knott, Graham; Humbel, Bruno M; Masoodi, Mojgan; Escrig, Stéphane; Meibom, Anders; Comment, Arnaud

    2015-11-01

    Glucose is the primary source of energy for the brain but also an important source of building blocks for proteins, lipids, and nucleic acids. Little is known about the use of glucose for biosynthesis in tissues at the cellular level. We demonstrate that local cerebral metabolic activity can be mapped in mouse brain tissue by quantitatively imaging the biosynthetic products deriving from [U-(13)C]glucose metabolism using a combination of in situ electron microscopy and secondary ion mass-spectroscopy (NanoSIMS). Images of the (13)C-label incorporated into cerebral ultrastructure with ca. 100 nm resolution allowed us to determine the timescale on which the metabolic products of glucose are incorporated into different cells, their sub-compartments and organelles. These were mapped in astrocytes and neurons in the different layers of the motor cortex. We see evidence for high metabolic activity in neurons via the nucleus (13)C enrichment. We observe that in all the major cell compartments, such as e.g. nucleus and Golgi apparatus, neurons incorporate substantially higher concentrations of (13)C-label than astrocytes. PMID:26409162

  1. Genome-scale thermodynamic analysis of Escherichia coli metabolism.

    PubMed

    Henry, Christopher S; Jankowski, Matthew D; Broadbelt, Linda J; Hatzimanikatis, Vassily

    2006-02-15

    Genome-scale metabolic models are an invaluable tool for analyzing metabolic systems as they provide a more complete picture of the processes of metabolism. We have constructed a genome-scale metabolic model of Escherichia coli based on the iJR904 model developed by the Palsson Laboratory at the University of California at San Diego. Group contribution methods were utilized to estimate the standard Gibbs free energy change of every reaction in the constructed model. Reactions in the model were classified based on the activity of the reactions during optimal growth on glucose in aerobic media. The most thermodynamically unfavorable reactions involved in the production of biomass in E. coli were identified as ATP phosphoribosyltransferase, ATP synthase, methylene-tetra-hydrofolate dehydrogenase, and tryptophanase. The effect of a knockout of these reactions on the production of biomass and the production of individual biomass precursors was analyzed. Changes in the distribution of fluxes in the cell after knockout of these unfavorable reactions were also studied. The methodologies and results discussed can be used to facilitate the refinement of the feasible ranges for cellular parameters such as species concentrations and reaction rate constants. PMID:16299075

  2. Next-generation genome-scale models for metabolic engineering.

    PubMed

    King, Zachary A; Lloyd, Colton J; Feist, Adam M; Palsson, Bernhard O

    2015-12-01

    Constraint-based reconstruction and analysis (COBRA) methods have become widely used tools for metabolic engineering in both academic and industrial laboratories. By employing a genome-scale in silico representation of the metabolic network of a host organism, COBRA methods can be used to predict optimal genetic modifications that improve the rate and yield of chemical production. A new generation of COBRA models and methods is now being developed--encompassing many biological processes and simulation strategies-and next-generation models enable new types of predictions. Here, three key examples of applying COBRA methods to strain optimization are presented and discussed. Then, an outlook is provided on the next generation of COBRA models and the new types of predictions they will enable for systems metabolic engineering. PMID:25575024

  3. Construction of a Genome-Scale Metabolic Model of Arthrospira platensis NIES-39 and Metabolic Design for Cyanobacterial Bioproduction.

    PubMed

    Yoshikawa, Katsunori; Aikawa, Shimpei; Kojima, Yuta; Toya, Yoshihiro; Furusawa, Chikara; Kondo, Akihiko; Shimizu, Hiroshi

    2015-01-01

    Arthrospira (Spirulina) platensis is a promising feedstock and host strain for bioproduction because of its high accumulation of glycogen and superior characteristics for industrial production. Metabolic simulation using a genome-scale metabolic model and flux balance analysis is a powerful method that can be used to design metabolic engineering strategies for the improvement of target molecule production. In this study, we constructed a genome-scale metabolic model of A. platensis NIES-39 including 746 metabolic reactions and 673 metabolites, and developed novel strategies to improve the production of valuable metabolites, such as glycogen and ethanol. The simulation results obtained using the metabolic model showed high consistency with experimental results for growth rates under several trophic conditions and growth capabilities on various organic substrates. The metabolic model was further applied to design a metabolic network to improve the autotrophic production of glycogen and ethanol. Decreased flux of reactions related to the TCA cycle and phosphoenolpyruvate reaction were found to improve glycogen production. Furthermore, in silico knockout simulation indicated that deletion of genes related to the respiratory chain, such as NAD(P)H dehydrogenase and cytochrome-c oxidase, could enhance ethanol production by using ammonium as a nitrogen source. PMID:26640947

  4. Construction of a Genome-Scale Metabolic Model of Arthrospira platensis NIES-39 and Metabolic Design for Cyanobacterial Bioproduction

    PubMed Central

    Yoshikawa, Katsunori; Aikawa, Shimpei; Kojima, Yuta; Toya, Yoshihiro; Furusawa, Chikara; Kondo, Akihiko; Shimizu, Hiroshi

    2015-01-01

    Arthrospira (Spirulina) platensis is a promising feedstock and host strain for bioproduction because of its high accumulation of glycogen and superior characteristics for industrial production. Metabolic simulation using a genome-scale metabolic model and flux balance analysis is a powerful method that can be used to design metabolic engineering strategies for the improvement of target molecule production. In this study, we constructed a genome-scale metabolic model of A. platensis NIES-39 including 746 metabolic reactions and 673 metabolites, and developed novel strategies to improve the production of valuable metabolites, such as glycogen and ethanol. The simulation results obtained using the metabolic model showed high consistency with experimental results for growth rates under several trophic conditions and growth capabilities on various organic substrates. The metabolic model was further applied to design a metabolic network to improve the autotrophic production of glycogen and ethanol. Decreased flux of reactions related to the TCA cycle and phosphoenolpyruvate reaction were found to improve glycogen production. Furthermore, in silico knockout simulation indicated that deletion of genes related to the respiratory chain, such as NAD(P)H dehydrogenase and cytochrome-c oxidase, could enhance ethanol production by using ammonium as a nitrogen source. PMID:26640947

  5. Improved Succinate Production by Metabolic Engineering

    PubMed Central

    Cheng, Ke-Ke; Wang, Gen-Yu; Zeng, Jing; Zhang, Jian-An

    2013-01-01

    Succinate is a promising chemical which has wide applications and can be produced by biological route. The history of the biosuccinate production shows that the joint effort of different metabolic engineering approaches brings successful results. In order to enhance the succinate production, multiple metabolical strategies have been sought. In this review, different overproducers for succinate production, including natural succinate overproducers and metabolic engineered overproducers, are examined and the metabolic engineering strategies and performances are discussed. Modification of the mechanism of substrate transportation, knocking-out genes responsible for by-products accumulation, overexpression of the genes directly involved in the pathway, and improvement of internal NADH and ATP formation are some of the strategies applied. Combination of the appropriate genes from homologous and heterologous hosts, extension of substrate, integrated production of succinate, and other high-value-added products are expected to bring a desired objective of producing succinate from renewable resources economically and efficiently. PMID:23691505

  6. Genome scale metabolic modeling of the riboflavin overproducer Ashbya gossypii.

    PubMed

    Ledesma-Amaro, Rodrigo; Kerkhoven, Eduard J; Revuelta, José Luis; Nielsen, Jens

    2014-06-01

    Ashbya gossypii is a filamentous fungus that naturally overproduces riboflavin, or vitamin B2. Advances in genetic and metabolic engineering of A. gossypii have permitted the switch from industrial chemical synthesis to the current biotechnological production of this vitamin. Additionally, A. gossypii is a model organism with one of the smallest eukaryote genomes being phylogenetically close to Saccharomyces cerevisiae. It has therefore been used to study evolutionary aspects of bakers' yeast. We here reconstructed the first genome scale metabolic model of A. gossypii, iRL766. The model was validated by biomass growth, riboflavin production and substrate utilization predictions. Gene essentiality analysis of the A. gossypii model in comparison with the S. cerevisiae model demonstrated how the whole-genome duplication event that separates the two species has led to an even spread of paralogs among all metabolic pathways. Additionally, iRL766 was used to integrate transcriptomics data from two different growth stages of A. gossypii, comparing exponential growth to riboflavin production stages. Both reporter metabolite analysis and in silico identification of transcriptionally regulated enzymes demonstrated the important involvement of beta-oxidation and the glyoxylate cycle in riboflavin production. PMID:24374726

  7. Quantifying the curvilinear metabolic scaling in mammals.

    PubMed

    Packard, Gary C

    2015-10-01

    A perplexing problem confronting students of metabolic allometry concerns the convex curvature that seemingly occurs in log-log plots of basal metabolic rate (BMR) vs. body mass in mammals. This putative curvilinearity has typically been interpreted in the context of a simple power function, Y=a*Xb, on the arithmetic scale, with the allometric exponent, b, supposedly increasing steadily as a dependent function of body size. The relationship can be quantified in arithmetic domain by exponentiating a quadratic equation fitted to logarithmic transformations of the original data, but the resulting model is not in the form of a power function and it is unlikely to describe accurately the pattern in the original distribution. I therefore re-examined a dataset for 636 species of mammal and discovered that the relationship between BMR and body mass is well-described by a power function with an explicit, non-zero intercept and lognormal, heteroscedastic error. The model has an invariant allometric exponent of 0.75, so the appearance in prior investigations of a steadily increasing exponent probably was an aberration resulting from undue reliance on logarithmic transformations to estimate statistical models in arithmetic domain. Theoretical constructs relating BMR to body mass in mammals may need to be modified to accommodate a positive intercept in the statistical model, but they do not need to be revised, or rejected, at present time on grounds that the allometric exponent varies with body size. New data from planned experiments will be needed to confirm any hypothesis based on data currently available. PMID:26173580

  8. Metabolic engineering of yeast for production of fuels and chemicals.

    PubMed

    Nielsen, Jens; Larsson, Christer; van Maris, Antonius; Pronk, Jack

    2013-06-01

    Microbial production of fuels and chemicals from renewable carbohydrate feedstocks offers sustainable and economically attractive alternatives to their petroleum-based production. The yeast Saccharomyces cerevisiae offers many advantages as a platform cell factory for such applications. Already applied on a huge scale for bioethanol production, this yeast is easy to genetically engineer, its physiology, metabolism and genetics have been intensively studied and its robustness enables it to handle harsh industrial conditions. Introduction of novel pathways and optimization of its native cellular processes by metabolic engineering are rapidly expanding its range of cell-factory applications. Here we review recent scientific progress in metabolic engineering of S. cerevisiae for the production of bioethanol, advanced biofuels, and chemicals. PMID:23611565

  9. Development and experimental verification of a genome-scale metabolic model for Corynebacterium glutamicum

    PubMed Central

    Shinfuku, Yohei; Sorpitiporn, Natee; Sono, Masahiro; Furusawa, Chikara; Hirasawa, Takashi; Shimizu, Hiroshi

    2009-01-01

    Background In silico genome-scale metabolic models enable the analysis of the characteristics of metabolic systems of organisms. In this study, we reconstructed a genome-scale metabolic model of Corynebacterium glutamicum on the basis of genome sequence annotation and physiological data. The metabolic characteristics were analyzed using flux balance analysis (FBA), and the results of FBA were validated using data from culture experiments performed at different oxygen uptake rates. Results The reconstructed genome-scale metabolic model of C. glutamicum contains 502 reactions and 423 metabolites. We collected the reactions and biomass components from the database and literatures, and made the model available for the flux balance analysis by filling gaps in the reaction networks and removing inadequate loop reactions. Using the framework of FBA and our genome-scale metabolic model, we first simulated the changes in the metabolic flux profiles that occur on changing the oxygen uptake rate. The predicted production yields of carbon dioxide and organic acids agreed well with the experimental data. The metabolic profiles of amino acid production phases were also investigated. A comprehensive gene deletion study was performed in which the effects of gene deletions on metabolic fluxes were simulated; this helped in the identification of several genes whose deletion resulted in an improvement in organic acid production. Conclusion The genome-scale metabolic model provides useful information for the evaluation of the metabolic capabilities and prediction of the metabolic characteristics of C. glutamicum. This can form a basis for the in silico design of C. glutamicum metabolic networks for improved bioproduction of desirable metabolites. PMID:19646286

  10. Metabolic scaling in animals: methods, empirical results, and theoretical explanations.

    PubMed

    White, Craig R; Kearney, Michael R

    2014-01-01

    Life on earth spans a size range of around 21 orders of magnitude across species and can span a range of more than 6 orders of magnitude within species of animal. The effect of size on physiology is, therefore, enormous and is typically expressed by how physiological phenomena scale with mass(b). When b ≠ 1 a trait does not vary in direct proportion to mass and is said to scale allometrically. The study of allometric scaling goes back to at least the time of Galileo Galilei, and published scaling relationships are now available for hundreds of traits. Here, the methods of scaling analysis are reviewed, using examples for a range of traits with an emphasis on those related to metabolism in animals. Where necessary, new relationships have been generated from published data using modern phylogenetically informed techniques. During recent decades one of the most controversial scaling relationships has been that between metabolic rate and body mass and a number of explanations have been proposed for the scaling of this trait. Examples of these mechanistic explanations for metabolic scaling are reviewed, and suggestions made for comparing between them. Finally, the conceptual links between metabolic scaling and ecological patterns are examined, emphasizing the distinction between (1) the hypothesis that size- and temperature-dependent variation among species and individuals in metabolic rate influences ecological processes at levels of organization from individuals to the biosphere and (2) mechanistic explanations for metabolic rate that may explain the size- and temperature-dependence of this trait. PMID:24692144

  11. Yeast metabolic chassis designs for diverse biotechnological products

    PubMed Central

    Jouhten, Paula; Boruta, Tomasz; Andrejev, Sergej; Pereira, Filipa; Rocha, Isabel; Patil, Kiran Raosaheb

    2016-01-01

    The diversity of industrially important molecules for which microbial production routes have been experimentally demonstrated is rapidly increasing. The development of economically viable producer cells is, however, lagging behind, as it requires substantial engineering of the host metabolism. A chassis strain suitable for production of a range of molecules is therefore highly sought after but remains elusive. Here, we propose a genome-scale metabolic modeling approach to design chassis strains of Saccharomyces cerevisiae – a widely used microbial cell factory. For a group of 29 products covering a broad range of biochemistry and applications, we identified modular metabolic engineering strategies for re-routing carbon flux towards the desired product. We find distinct product families with shared targets forming the basis for the corresponding chassis cells. The design strategies include overexpression targets that group products by similarity in precursor and cofactor requirements, as well as gene deletion strategies for growth-product coupling that lead to non-intuitive product groups. Our results reveal the extent and the nature of flux re-routing necessary for producing a diverse range of products in a widely used cell factory and provide blueprints for constructing pre-optimized chassis strains. PMID:27430744

  12. Yeast metabolic chassis designs for diverse biotechnological products.

    PubMed

    Jouhten, Paula; Boruta, Tomasz; Andrejev, Sergej; Pereira, Filipa; Rocha, Isabel; Patil, Kiran Raosaheb

    2016-01-01

    The diversity of industrially important molecules for which microbial production routes have been experimentally demonstrated is rapidly increasing. The development of economically viable producer cells is, however, lagging behind, as it requires substantial engineering of the host metabolism. A chassis strain suitable for production of a range of molecules is therefore highly sought after but remains elusive. Here, we propose a genome-scale metabolic modeling approach to design chassis strains of Saccharomyces cerevisiae - a widely used microbial cell factory. For a group of 29 products covering a broad range of biochemistry and applications, we identified modular metabolic engineering strategies for re-routing carbon flux towards the desired product. We find distinct product families with shared targets forming the basis for the corresponding chassis cells. The design strategies include overexpression targets that group products by similarity in precursor and cofactor requirements, as well as gene deletion strategies for growth-product coupling that lead to non-intuitive product groups. Our results reveal the extent and the nature of flux re-routing necessary for producing a diverse range of products in a widely used cell factory and provide blueprints for constructing pre-optimized chassis strains. PMID:27430744

  13. Redirection of metabolism for hydrogen production

    SciTech Connect

    Harwood, Caroline S.

    2011-11-28

    This project is to develop and apply techniques in metabolic engineering to improve the biocatalytic potential of the bacterium Rhodopseudomonas palustris for nitrogenase-catalyzed hydrogen gas production. R. palustris, is an ideal platform to develop as a biocatalyst for hydrogen gas production because it is an extremely versatile microbe that produces copious amounts of hydrogen by drawing on abundant natural resources of sunlight and biomass. Anoxygenic photosynthetic bacteria, such as R. palustris, generate hydrogen and ammonia during a process known as biological nitrogen fixation. This reaction is catalyzed by the enzyme nitrogenase and normally consumes nitrogen gas, ATP and electrons. The applied use of nitrogenase for hydrogen production is attractive because hydrogen is an obligatory product of this enzyme and is formed as the only product when nitrogen gas is not supplied. Our challenge is to understand the systems biology of R. palustris sufficiently well to be able to engineer cells to produce hydrogen continuously, as fast as possible and with as high a conversion efficiency as possible of light and electron donating substrates. For many experiments we started with a strain of R. palustris that produces hydrogen constitutively under all growth conditions. We then identified metabolic pathways and enzymes important for removal of electrons from electron-donating organic compounds and for their delivery to nitrogenase in whole R. palustris cells. For this we developed and applied improved techniques in 13C metabolic flux analysis. We identified reactions that are important for generating electrons for nitrogenase and that are yield-limiting for hydrogen production. We then increased hydrogen production by blocking alternative electron-utilizing metabolic pathways by mutagenesis. In addition we found that use of non-growing cells as biocatalysts for hydrogen gas production is an attractive option, because cells divert all resources away from growth and

  14. Northern Florida reef tract benthic metabolism scaled by remote sensing

    USGS Publications Warehouse

    Brock, J.C.; Yates, K.K.; Halley, R.B.; Kuffner, I.B.; Wright, C.W.; Hatcher, B.G.

    2006-01-01

    Holistic rates of excess organic carbon production (E) and calcification for a 0.5 km2 segment of the backreef platform of the northern Florida reef tract (NFRT) were estimated by combining biotope mapping using remote sensing with community metabolic rates determined with a benthic incubation system. The use of ASTER multispectral satellite imaging for the spatial scaling of benthic metabolic processes resulted in errors in E and net calcification (G) of 48 and 431% respectively, relative to estimates obtained using AISA hyperspectral airborne scanning. At 19 and 125%, the E and G errors relative to the AISA-based estimates were less pronounced for an analysis that used IKONOS multispectral satellite imagery to spatially extrapolate the chamber process measurements. Our scaling analysis indicates that the holistic calcification rate of the backreef platform of the northern Florida reef tract is negligible at 0.07 g CaCO3 m-2 d-1. All of the mapped biotopes in this reef zone are net heterotrophic, resulting in an estimated holistic excess production rate of -0.56 g C m-2 d-1, and an overall gross primary production to respiration ratio of 0.85. Based on our finding of ubiquitous heterotrophy, we infer that the backreef platform of the NFRT is a sink for external inputs of suspended particulate organic matter. Further, our results suggest that the inward advection of inorganic nutrients is not a dominant forcing mechanism for benthic biogeochemical function in the NFRT. We suggest that the degradation of the northern Florida reef tract may parallel the community phase shifts documented within other reef systems polluted by organic detritus.

  15. Genome-scale models of bacterial metabolism: reconstruction and applications

    PubMed Central

    Durot, Maxime; Bourguignon, Pierre-Yves; Schachter, Vincent

    2009-01-01

    Genome-scale metabolic models bridge the gap between genome-derived biochemical information and metabolic phenotypes in a principled manner, providing a solid interpretative framework for experimental data related to metabolic states, and enabling simple in silico experiments with whole-cell metabolism. Models have been reconstructed for almost 20 bacterial species, so far mainly through expert curation efforts integrating information from the literature with genome annotation. A wide variety of computational methods exploiting metabolic models have been developed and applied to bacteria, yielding valuable insights into bacterial metabolism and evolution, and providing a sound basis for computer-assisted design in metabolic engineering. Recent advances in computational systems biology and high-throughput experimental technologies pave the way for the systematic reconstruction of metabolic models from genomes of new species, and a corresponding expansion of the scope of their applications. In this review, we provide an introduction to the key ideas of metabolic modeling, survey the methods, and resources that enable model reconstruction and refinement, and chart applications to the investigation of global properties of metabolic systems, the interpretation of experimental results, and the re-engineering of their biochemical capabilities. PMID:19067749

  16. Accelerating the reconstruction of genome-scale metabolic networks

    PubMed Central

    Notebaart, Richard A; van Enckevort, Frank HJ; Francke, Christof; Siezen, Roland J; Teusink, Bas

    2006-01-01

    Background The genomic information of a species allows for the genome-scale reconstruction of its metabolic capacity. Such a metabolic reconstruction gives support to metabolic engineering, but also to integrative bioinformatics and visualization. Sequence-based automatic reconstructions require extensive manual curation, which can be very time-consuming. Therefore, we present a method to accelerate the time-consuming process of network reconstruction for a query species. The method exploits the availability of well-curated metabolic networks and uses high-resolution predictions of gene equivalency between species, allowing the transfer of gene-reaction associations from curated networks. Results We have evaluated the method using Lactococcus lactis IL1403, for which a genome-scale metabolic network was published recently. We recovered most of the gene-reaction associations (i.e. 74 – 85%) which are incorporated in the published network. Moreover, we predicted over 200 additional genes to be associated to reactions, including genes with unknown function, genes for transporters and genes with specific metabolic reactions, which are good candidates for an extension to the previously published network. In a comparison of our developed method with the well-established approach Pathologic, we predicted 186 additional genes to be associated to reactions. We also predicted a relatively high number of complete conserved protein complexes, which are derived from curated metabolic networks, illustrating the potential predictive power of our method for protein complexes. Conclusion We show that our methodology can be applied to accelerate the reconstruction of genome-scale metabolic networks by taking optimal advantage of existing, manually curated networks. As orthology detection is the first step in the method, only the translated open reading frames (ORFs) of a newly sequenced genome are necessary to reconstruct a metabolic network. When more manually curated metabolic

  17. Genome scale metabolic reconstruction of Chlorella variabilis for exploring its metabolic potential for biofuels.

    PubMed

    Juneja, Ankita; Chaplen, Frank W R; Murthy, Ganti S

    2016-08-01

    A compartmentalized genome scale metabolic network was reconstructed for Chlorella variabilis to offer insight into various metabolic potentials from this alga. The model, iAJ526, was reconstructed with 1455 reactions, 1236 metabolites and 526 genes. 21% of the reactions were transport reactions and about 81% of the total reactions were associated with enzymes. Along with gap filling reactions, 2 major sub-pathways were added to the model, chitosan synthesis and rhamnose metabolism. The reconstructed model had reaction participation of 4.3 metabolites per reaction and average lethality fraction of 0.21. The model was effective in capturing the growth of C. variabilis under three light conditions (white, red and red+blue light) with fair agreement. This reconstructed metabolic network will serve an important role in systems biology for further exploration of metabolism for specific target metabolites and enable improved characteristics in the strain through metabolic engineering. PMID:26995318

  18. Metabolic Engineering for the Production of Natural Products

    PubMed Central

    Pickens, Lauren B.; Tang, Yi; Chooi, Yit-Heng

    2014-01-01

    Natural products and natural product derived compounds play an important role in modern healthcare as frontline treatments for many diseases and as inspiration for chemically synthesized therapeutics. With advances in sequencing and recombinant DNA technology, many of the biosynthetic pathways responsible for the production of these chemically complex and pharmaceutically valuable compounds have been elucidated. With an ever expanding toolkit of biosynthetic components, metabolic engineering is an increasingly powerful method to improve natural product titers and generate novel compounds. Heterologous production platforms have enabled access to pathways from difficult to culture strains; systems biology and metabolic modeling tools have resulted in increasing predictive and analytic capabilities; advances in expression systems and regulation have enabled the fine-tuning of pathways for increased efficiency, and characterization of individual pathway components has facilitated the construction of hybrid pathways for the production of new compounds. These advances in the many aspects of metabolic engineering have not only yielded fascinating scientific discoveries but also make it an increasingly viable approach for the optimization of natural product biosynthesis. PMID:22432617

  19. Reconstruction and analysis of the genome-scale metabolic model of Lactobacillus casei LC2W.

    PubMed

    Xu, Nan; Liu, Jie; Ai, Lianzhong; Liu, Liming

    2015-01-10

    Lactobacillus casei LC2W is a recently isolated probiotic lactic acid bacterial strain, which is widely used in the dairy and pharmaceutical industries and in clinical medicine. The first genome-scale metabolic model for L. casei, composed of 846 genes, 969 metabolic reactions, and 785 metabolites, was reconstructed using both manual genome annotation and an automatic SEED model. Then, the iJL846 model was validated by simulating cell growth on 15 reported carbon sources. The iJL846 model explored the metabolism of L. casei on a genome scale: (1) explanation of the genetic codes-metabolic functions of 342 genes were reannotated in this model; (2) characterization of the physiology-10 amino acids and 7 vitamins were identified to be essential nutrients for L. casei LC2W growth; (3) analyses of metabolic pathways-the transport and metabolism of the 17 essential nutrients and exopolysaccharide (EPS) biosynthesis-were performed; (4) exploration of metabolic capacity was conducted-for lactate, the importance of genes in its biosynthetic pathways was evaluated, and the requirements of amino acids were predicted for mixed acid fermentation; for flavor compounds, the effects of oxygen were analyzed, and three new knockout targets were selected for acetoin production; for EPS, 11 types of nutrients in the rich medium and important reactions in the biosynthetic pathway were identified that enhanced EPS production. In conclusion, the iJL846 model serves as a useful tool for understanding and engineering the metabolism of this probiotic strain. PMID:25452194

  20. Investigating Moorella thermoacetica metabolism with a genome-scale constraint-based metabolic model.

    PubMed

    Islam, M Ahsanul; Zengler, Karsten; Edwards, Elizabeth A; Mahadevan, Radhakrishnan; Stephanopoulos, Gregory

    2015-08-01

    Moorella thermoacetica is a strictly anaerobic, endospore-forming, and metabolically versatile acetogenic bacterium capable of conserving energy by both autotrophic (acetogenesis) and heterotrophic (homoacetogenesis) modes of metabolism. Its metabolic diversity and the ability to efficiently convert a wide range of compounds, including syngas (CO + H2) into acetyl-CoA have made this thermophilic bacterium a promising host for industrial biotechnology applications. However, lack of detailed information on M. thermoacetica's metabolism is a major impediment to its use as a microbial cell factory. In order to overcome this issue, a genome-scale constraint-based metabolic model of Moorella thermoacetica, iAI558, has been developed using its genome sequence and physiological data from published literature. The reconstructed metabolic network of M. thermoacetica comprises 558 metabolic genes, 705 biochemical reactions, and 698 metabolites. Of the total 705 model reactions, 680 are gene-associated while the rest are non-gene associated reactions. The model, in addition to simulating both autotrophic and heterotrophic growth of M. thermoacetica, revealed degeneracy in its TCA-cycle, a common characteristic of anaerobic metabolism. Furthermore, the model helped elucidate the poorly understood energy conservation mechanism of M. thermoacetica during autotrophy. Thus, in addition to generating experimentally testable hypotheses regarding its physiology, such a detailed model will facilitate rapid strain designing and metabolic engineering of M. thermoacetica for industrial applications. PMID:25994252

  1. MEMOSys: Bioinformatics platform for genome-scale metabolic models

    PubMed Central

    2011-01-01

    Background Recent advances in genomic sequencing have enabled the use of genome sequencing in standard biological and biotechnological research projects. The challenge is how to integrate the large amount of data in order to gain novel biological insights. One way to leverage sequence data is to use genome-scale metabolic models. We have therefore designed and implemented a bioinformatics platform which supports the development of such metabolic models. Results MEMOSys (MEtabolic MOdel research and development System) is a versatile platform for the management, storage, and development of genome-scale metabolic models. It supports the development of new models by providing a built-in version control system which offers access to the complete developmental history. Moreover, the integrated web board, the authorization system, and the definition of user roles allow collaborations across departments and institutions. Research on existing models is facilitated by a search system, references to external databases, and a feature-rich comparison mechanism. MEMOSys provides customizable data exchange mechanisms using the SBML format to enable analysis in external tools. The web application is based on the Java EE framework and offers an intuitive user interface. It currently contains six annotated microbial metabolic models. Conclusions We have developed a web-based system designed to provide researchers a novel application facilitating the management and development of metabolic models. The system is freely available at http://www.icbi.at/MEMOSys. PMID:21276275

  2. Identifying all moiety conservation laws in genome-scale metabolic networks.

    PubMed

    De Martino, Andrea; De Martino, Daniele; Mulet, Roberto; Pagnani, Andrea

    2014-01-01

    The stoichiometry of a metabolic network gives rise to a set of conservation laws for the aggregate level of specific pools of metabolites, which, on one hand, pose dynamical constraints that cross-link the variations of metabolite concentrations and, on the other, provide key insight into a cell's metabolic production capabilities. When the conserved quantity identifies with a chemical moiety, extracting all such conservation laws from the stoichiometry amounts to finding all non-negative integer solutions of a linear system, a programming problem known to be NP-hard. We present an efficient strategy to compute the complete set of integer conservation laws of a genome-scale stoichiometric matrix, also providing a certificate for correctness and maximality of the solution. Our method is deployed for the analysis of moiety conservation relationships in two large-scale reconstructions of the metabolism of the bacterium E. coli, in six tissue-specific human metabolic networks, and, finally, in the human reactome as a whole, revealing that bacterial metabolism could be evolutionarily designed to cover broader production spectra than human metabolism. Convergence to the full set of moiety conservation laws in each case is achieved in extremely reduced computing times. In addition, we uncover a scaling relation that links the size of the independent pool basis to the number of metabolites, for which we present an analytical explanation. PMID:24988199

  3. Identifying All Moiety Conservation Laws in Genome-Scale Metabolic Networks

    PubMed Central

    2014-01-01

    The stoichiometry of a metabolic network gives rise to a set of conservation laws for the aggregate level of specific pools of metabolites, which, on one hand, pose dynamical constraints that cross-link the variations of metabolite concentrations and, on the other, provide key insight into a cell's metabolic production capabilities. When the conserved quantity identifies with a chemical moiety, extracting all such conservation laws from the stoichiometry amounts to finding all non-negative integer solutions of a linear system, a programming problem known to be NP-hard. We present an efficient strategy to compute the complete set of integer conservation laws of a genome-scale stoichiometric matrix, also providing a certificate for correctness and maximality of the solution. Our method is deployed for the analysis of moiety conservation relationships in two large-scale reconstructions of the metabolism of the bacterium E. coli, in six tissue-specific human metabolic networks, and, finally, in the human reactome as a whole, revealing that bacterial metabolism could be evolutionarily designed to cover broader production spectra than human metabolism. Convergence to the full set of moiety conservation laws in each case is achieved in extremely reduced computing times. In addition, we uncover a scaling relation that links the size of the independent pool basis to the number of metabolites, for which we present an analytical explanation. PMID:24988199

  4. Generation and Evaluation of a Genome-Scale Metabolic Network Model of Synechococcus elongatus PCC7942

    PubMed Central

    Triana, Julián; Montagud†, Arnau; Siurana, Maria; Fuente, David; Urchueguía, Arantxa; Gamermann, Daniel; Torres, Javier; Tena, Jose; de Córdoba, Pedro Fernández; Urchueguía, Javier F.

    2014-01-01

    The reconstruction of genome-scale metabolic models and their applications represent a great advantage of systems biology. Through their use as metabolic flux simulation models, production of industrially-interesting metabolites can be predicted. Due to the growing number of studies of metabolic models driven by the increasing genomic sequencing projects, it is important to conceptualize steps of reconstruction and analysis. We have focused our work in the cyanobacterium Synechococcus elongatus PCC7942, for which several analyses and insights are unveiled. A comprehensive approach has been used, which can be of interest to lead the process of manual curation and genome-scale metabolic analysis. The final model, iSyf715 includes 851 reactions and 838 metabolites. A biomass equation, which encompasses elementary building blocks to allow cell growth, is also included. The applicability of the model is finally demonstrated by simulating autotrophic growth conditions of Synechococcus elongatus PCC7942. PMID:25141288

  5. The evolution of genome-scale models of cancer metabolism

    PubMed Central

    Lewis, Nathan E.; Abdel-Haleem, Alyaa M.

    2013-01-01

    The importance of metabolism in cancer is becoming increasingly apparent with the identification of metabolic enzyme mutations and the growing awareness of the influence of metabolism on signaling, epigenetic markers, and transcription. However, the complexity of these processes has challenged our ability to make sense of the metabolic changes in cancer. Fortunately, constraint-based modeling, a systems biology approach, now enables one to study the entirety of cancer metabolism and simulate basic phenotypes. With the newness of this field, there has been a rapid evolution of both the scope of these models and their applications. Here we review the various constraint-based models built for cancer metabolism and how their predictions are shedding new light on basic cancer phenotypes, elucidating pathway differences between tumors, and dicovering putative anti-cancer targets. As the field continues to evolve, the scope of these genome-scale cancer models must expand beyond central metabolism to address questions related to the diverse processes contributing to tumor development and metastasis. PMID:24027532

  6. A Quantitative System-Scale Characterization of the Metabolism of Clostridium acetobutylicum

    PubMed Central

    Yoo, Minyeong; Bestel-Corre, Gwenaelle; Croux, Christian; Riviere, Antoine; Meynial-Salles, Isabelle

    2015-01-01

    ABSTRACT Engineering industrial microorganisms for ambitious applications, for example, the production of second-generation biofuels such as butanol, is impeded by a lack of knowledge of primary metabolism and its regulation. A quantitative system-scale analysis was applied to the biofuel-producing bacterium Clostridium acetobutylicum, a microorganism used for the industrial production of solvent. An improved genome-scale model, iCac967, was first developed based on thorough biochemical characterizations of 15 key metabolic enzymes and on extensive literature analysis to acquire accurate fluxomic data. In parallel, quantitative transcriptomic and proteomic analyses were performed to assess the number of mRNA molecules per cell for all genes under acidogenic, solventogenic, and alcohologenic steady-state conditions as well as the number of cytosolic protein molecules per cell for approximately 700 genes under at least one of the three steady-state conditions. A complete fluxomic, transcriptomic, and proteomic analysis applied to different metabolic states allowed us to better understand the regulation of primary metabolism. Moreover, this analysis enabled the functional characterization of numerous enzymes involved in primary metabolism, including (i) the enzymes involved in the two different butanol pathways and their cofactor specificities, (ii) the primary hydrogenase and its redox partner, (iii) the major butyryl coenzyme A (butyryl-CoA) dehydrogenase, and (iv) the major glyceraldehyde-3-phosphate dehydrogenase. This study provides important information for further metabolic engineering of C. acetobutylicum to develop a commercial process for the production of n-butanol. PMID:26604256

  7. Multi-scale modeling for sustainable chemical production.

    PubMed

    Zhuang, Kai; Bakshi, Bhavik R; Herrgård, Markus J

    2013-09-01

    With recent advances in metabolic engineering, it is now technically possible to produce a wide portfolio of existing petrochemical products from biomass feedstock. In recent years, a number of modeling approaches have been developed to support the engineering and decision-making processes associated with the development and implementation of a sustainable biochemical industry. The temporal and spatial scales of modeling approaches for sustainable chemical production vary greatly, ranging from metabolic models that aid the design of fermentative microbial strains to material and monetary flow models that explore the ecological impacts of all economic activities. Research efforts that attempt to connect the models at different scales have been limited. Here, we review a number of existing modeling approaches and their applications at the scales of metabolism, bioreactor, overall process, chemical industry, economy, and ecosystem. In addition, we propose a multi-scale approach for integrating the existing models into a cohesive framework. The major benefit of this proposed framework is that the design and decision-making at each scale can be informed, guided, and constrained by simulations and predictions at every other scale. In addition, the development of this multi-scale framework would promote cohesive collaborations across multiple traditionally disconnected modeling disciplines to achieve sustainable chemical production. PMID:23520143

  8. 13C metabolic flux analysis at a genome-scale.

    PubMed

    Gopalakrishnan, Saratram; Maranas, Costas D

    2015-11-01

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

  9. Metabolic stasis in an ancient symbiosis: genome-scale metabolic networks from two Blattabacterium cuenoti strains, primary endosymbionts of cockroaches

    PubMed Central

    2012-01-01

    Background Cockroaches are terrestrial insects that strikingly eliminate waste nitrogen as ammonia instead of uric acid. Blattabacterium cuenoti (Mercier 1906) strains Bge and Pam are the obligate primary endosymbionts of the cockroaches Blattella germanica and Periplaneta americana, respectively. The genomes of both bacterial endosymbionts have recently been sequenced, making possible a genome-scale constraint-based reconstruction of their metabolic networks. The mathematical expression of a metabolic network and the subsequent quantitative studies of phenotypic features by Flux Balance Analysis (FBA) represent an efficient functional approach to these uncultivable bacteria. Results We report the metabolic models of Blattabacterium strains Bge (iCG238) and Pam (iCG230), comprising 296 and 289 biochemical reactions, associated with 238 and 230 genes, and 364 and 358 metabolites, respectively. Both models reflect both the striking similarities and the singularities of these microorganisms. FBA was used to analyze the properties, potential and limits of the models, assuming some environmental constraints such as aerobic conditions and the net production of ammonia from these bacterial systems, as has been experimentally observed. In addition, in silico simulations with the iCG238 model have enabled a set of carbon and nitrogen sources to be defined, which would also support a viable phenotype in terms of biomass production in the strain Pam, which lacks the first three steps of the tricarboxylic acid cycle. FBA reveals a metabolic condition that renders these enzymatic steps dispensable, thus offering a possible evolutionary explanation for their elimination. We also confirm, by computational simulations, the fragility of the metabolic networks and their host dependence. Conclusions The minimized Blattabacterium metabolic networks are surprisingly similar in strains Bge and Pam, after 140 million years of evolution of these endosymbionts in separate cockroach

  10. Synthetic Evolution of Metabolic Productivity Using Biosensors.

    PubMed

    Williams, Thomas C; Pretorius, Isak S; Paulsen, Ian T

    2016-05-01

    Synthetic biology has progressed to the point where genes that encode whole metabolic pathways and even genomes can be manufactured and brought to life. This impressive ability to synthesise and assemble DNA is not yet matched by an ability to predictively engineer biology. These difficulties exist because biological systems are often overwhelmingly complex, having evolved to facilitate growth and survival rather than specific engineering objectives such as the optimisation of biochemical production. A promising and revolutionary solution to this problem is to harness the process of evolution to create microbial strains with desired properties. The tools of systems biology can then be applied to understand the principles of biological design, bringing synthetic biology closer to becoming a predictive engineering discipline. PMID:26948437

  11. Scaling of metabolic rate on body mass in small laboratory mammals

    NASA Technical Reports Server (NTRS)

    Pace, N.; Rahlmann, D. F.; Smith, A. H.

    1980-01-01

    The scaling of metabolic heat production rate on body mass is investigated for five species of small laboratory mammal in order to define selection of animals of metabolic rates and size range appropriate for the measurement of changes in the scaling relationship upon exposure to weightlessness in Shuttle/Spacelab experiment. Metabolic rates were measured according to oxygen consumption and carbon dioxide production for individual male and female Swiss-Webster mice, Syrian hamsters, Simonsen albino rats, Hartley guinea pigs and New Zealand white rabbits, which range in mass from 0.05 to 5 kg mature body size, at ages of 1, 2, 3, 5, 8, 12, 18 and 24 months. The metabolic intensity, defined as the heat produced per hour per kg body mass, is found to decrease dramatically with age until the animals are 6 to 8 months old, with little or no sex difference. When plotted on a logarithmic graph, the relation of metabolic rate to total body mass is found to obey a power law of index 0.676, which differs significantly from the classical value of 0.75. When the values for the mice are removed, however, an index of 0.749 is obtained. It is thus proposed that six male animals, 8 months of age, of each of the four remaining species be used to study the effects of gravitational loading on the metabolic energy requirements of terrestrial animals.

  12. Swimming in Light: A Large-Scale Computational Analysis of the Metabolism of Dinoroseobacter shibae

    PubMed Central

    Rex, Rene; Bill, Nelli; Schmidt-Hohagen, Kerstin; Schomburg, Dietmar

    2013-01-01

    The Roseobacter clade is a ubiquitous group of marine α-proteobacteria. To gain insight into the versatile metabolism of this clade, we took a constraint-based approach and created a genome-scale metabolic model (iDsh827) of Dinoroseobacter shibae DFL12T. Our model is the first accounting for the energy demand of motility, the light-driven ATP generation and experimentally determined specific biomass composition. To cover a large variety of environmental conditions, as well as plasmid and single gene knock-out mutants, we simulated 391,560 different physiological states using flux balance analysis. We analyzed our results with regard to energy metabolism, validated them experimentally, and revealed a pronounced metabolic response to the availability of light. Furthermore, we introduced the energy demand of motility as an important parameter in genome-scale metabolic models. The results of our simulations also gave insight into the changing usage of the two degradation routes for dimethylsulfoniopropionate, an abundant compound in the ocean. A side product of dimethylsulfoniopropionate degradation is dimethyl sulfide, which seeds cloud formation and thus enhances the reflection of sunlight. By our exhaustive simulations, we were able to identify single-gene knock-out mutants, which show an increased production of dimethyl sulfide. In addition to the single-gene knock-out simulations we studied the effect of plasmid loss on the metabolism. Moreover, we explored the possible use of a functioning phosphofructokinase for D. shibae. PMID:24098096

  13. MultiMetEval: Comparative and Multi-Objective Analysis of Genome-Scale Metabolic Models

    PubMed Central

    Gevorgyan, Albert; Kierzek, Andrzej M.; Breitling, Rainer; Takano, Eriko

    2012-01-01

    Comparative metabolic modelling is emerging as a novel field, supported by the development of reliable and standardized approaches for constructing genome-scale metabolic models in high throughput. New software solutions are needed to allow efficient comparative analysis of multiple models in the context of multiple cellular objectives. Here, we present the user-friendly software framework Multi-Metabolic Evaluator (MultiMetEval), built upon SurreyFBA, which allows the user to compose collections of metabolic models that together can be subjected to flux balance analysis. Additionally, MultiMetEval implements functionalities for multi-objective analysis by calculating the Pareto front between two cellular objectives. Using a previously generated dataset of 38 actinobacterial genome-scale metabolic models, we show how these approaches can lead to exciting novel insights. Firstly, after incorporating several pathways for the biosynthesis of natural products into each of these models, comparative flux balance analysis predicted that species like Streptomyces that harbour the highest diversity of secondary metabolite biosynthetic gene clusters in their genomes do not necessarily have the metabolic network topology most suitable for compound overproduction. Secondly, multi-objective analysis of biomass production and natural product biosynthesis in these actinobacteria shows that the well-studied occurrence of discrete metabolic switches during the change of cellular objectives is inherent to their metabolic network architecture. Comparative and multi-objective modelling can lead to insights that could not be obtained by normal flux balance analyses. MultiMetEval provides a powerful platform that makes these analyses straightforward for biologists. Sources and binaries of MultiMetEval are freely available from https://github.com/PiotrZakrzewski/MetEval/downloads. PMID:23272111

  14. Linking genome-scale metabolic modeling and genome annotation

    PubMed Central

    Blais, Edik M.; Chavali, Arvind K.; Papin, Jason A.

    2014-01-01

    Summary Genome-scale metabolic network reconstructions, assembled from annotated genomes, serve as a platform for integrating data from heterogeneous sources and generating hypotheses for further experimental validation. Implementing constraint-based modeling techniques such as Flux Balance Analysis (FBA) on network reconstructions allow for interrogating metabolism at a systems-level, which aids in identifying and rectifying gaps in knowledge. With genome sequences for various organisms from prokaryotes to eukaryotes becoming increasingly available, a significant bottleneck lies in the structural and functional annotation of these sequences. Using topologically-based and biologically-inspired metabolic network refinement, we can better characterize enzymatic functions present in an organism and link annotation of these functions to candidate transcripts, both steps that can be experimentally validated. PMID:23417799

  15. Exploring the role of temperature in the ocean through metabolic scaling.

    PubMed

    Bruno, John F; Carr, Lindsey A; O'Connor, Mary I

    2015-12-01

    Temperature imposes a constraint on the rates and outcomes of ecological processes that determine community- and ecosystem-level patterns. The application of metabolic scaling theory has advanced our understanding of the influence of temperature on pattern and process in marine communities. Metabolic scaling theory uses the fundamental and ubiquitous patterns of temperature-dependent metabolism to predict how environmental temperature influences patterns and processes at higher levels of biological organization. Here, we outline some of these predictions to review recent advances and illustrate how scaling theory might be applied to new challenges. For example, warming can alter species interactions and food-web structure and can also reduce total animal biomass supportable by a given amount of primary production by increasing animal metabolism and energetic demand. Additionally, within a species, larval development is faster in warmer water, potentially influencing dispersal and other demographic processes like population connectivity and gene flow. These predictions can be extended further to address major questions in marine ecology, and present an opportunity for conceptual unification of marine ecological research across levels of biological organization. Drawing on work by ecologists and oceanographers over the last century, a metabolic scaling approach represents a promising way forward for applying ecological understanding to basic questions as well as conservation challenges. PMID:26909420

  16. Large-scale reconstruction and phylogenetic analysis of metabolic environments

    PubMed Central

    Borenstein, Elhanan; Kupiec, Martin; Feldman, Marcus W.; Ruppin, Eytan

    2008-01-01

    The topology of metabolic networks may provide important insights not only into the metabolic capacity of species, but also into the habitats in which they evolved. Here we introduce the concept of a metabolic network's “seed set”—the set of compounds that, based on the network topology, are exogenously acquired—and provide a methodological framework to computationally infer the seed set of a given network. Such seed sets form ecological “interfaces” between metabolic networks and their surroundings, approximating the effective biochemical environment of each species. Analyzing the metabolic networks of 478 species and identifying the seed set of each species, we present a comprehensive large-scale reconstruction of such predicted metabolic environments. The seed sets' composition significantly correlates with several basic properties characterizing the species' environments and agrees with biological observations concerning major adaptations. Species whose environments are highly predictable (e.g., obligate parasites) tend to have smaller seed sets than species living in variable environments. Phylogenetic analysis of the seed sets reveals the complex dynamics governing gain and loss of seeds across the phylogenetic tree and the process of transition between seed and non-seed compounds. Our findings suggest that the seed state is transient and that seeds tend either to be dropped completely from the network or to become non-seed compounds relatively fast. The seed sets also permit a successful reconstruction of a phylogenetic tree of life. The “reverse ecology” approach presented lays the foundations for studying the evolutionary interplay between organisms and their habitats on a large scale. PMID:18787117

  17. Flux Coupling Analysis of Genome-Scale Metabolic Network Reconstructions

    PubMed Central

    Burgard, Anthony P.; Nikolaev, Evgeni V.; Schilling, Christophe H.; Maranas, Costas D.

    2004-01-01

    In this paper, we introduce the Flux Coupling Finder (FCF) framework for elucidating the topological and flux connectivity features of genome-scale metabolic networks. The framework is demonstrated on genome-scale metabolic reconstructions of Helicobacter pylori, Escherichia coli, and Saccharomyces cerevisiae. The analysis allows one to determine whether any two metabolic fluxes, v1 and v2, are (1) directionally coupled, if a non-zero flux for v1 implies a non-zero flux for v2 but not necessarily the reverse; (2) partially coupled, if a non-zero flux for v1 implies a non-zero, though variable, flux for v2 and vice versa; or (3) fully coupled, if a non-zero flux for v1 implies not only a non-zero but also a fixed flux for v2 and vice versa. Flux coupling analysis also enables the global identification of blocked reactions, which are all reactions incapable of carrying flux under a certain condition; equivalent knockouts, defined as the set of all possible reactions whose deletion forces the flux through a particular reaction to zero; and sets of affected reactions denoting all reactions whose fluxes are forced to zero if a particular reaction is deleted. The FCF approach thus provides a novel and versatile tool for aiding metabolic reconstructions and guiding genetic manipulations. PMID:14718379

  18. Metabolic allometric scaling model: combining cellular transportation and heat dissipation constraints.

    PubMed

    Shestopaloff, Yuri K

    2016-08-15

    Living organisms need energy to be 'alive'. Energy is produced by the biochemical processing of nutrients, and the rate of energy production is called the metabolic rate. Metabolism is very important from evolutionary and ecological perspectives, and for organismal development and functioning. It depends on different parameters, of which organism mass is considered to be one of the most important. Simple relationships between the mass of organisms and their metabolic rates were empirically discovered by M. Kleiber in 1932. Such dependence is described by a power function, whose exponent is referred to as the allometric scaling coefficient. With the increase of mass, the metabolic rate usually increases more slowly; if mass increases by two times, the metabolic rate increases less than two times. This fact has far-reaching implications for the organization of life. The fundamental biological and biophysical mechanisms underlying this phenomenon are still not well understood. The present study shows that one such primary mechanism relates to transportation of substances, such as nutrients and waste, at a cellular level. Variations in cell size and associated cellular transportation costs explain the known variance of the allometric exponent. The introduced model also includes heat dissipation constraints. The model agrees with experimental observations and reconciles experimental results across different taxa. It ties metabolic scaling to organismal and environmental characteristics, helps to define perspective directions of future research and allows the prediction of allometric exponents based on characteristics of organisms and the environments they live in. PMID:27284070

  19. Reconstruction and analysis of a genome-scale metabolic network of Corynebacterium glutamicum S9114.

    PubMed

    Mei, Jie; Xu, Nan; Ye, Chao; Liu, Liming; Wu, Jianrong

    2016-01-10

    Corynebacterium glutamicum S9114 is commonly used for industrial glutamate production. Therefore, a comprehensive understanding of the physiological and metabolic characteristics of C. glutamicum is important for developing its potential for industrial production. A genome-scale metabolic model, iJM658, was reconstructed based on genome annotation and literature mining. The model consists of 658 genes, 984 metabolites and 1065 reactions. The model quantitatively predicted C. glutamicum growth on different carbon and nitrogen sources and determined 129 genes to be essential for cell growth. The iJM658 model predicted that C. glutamicum had two glutamate biosynthesis pathways and lacked eight key genes in biotin synthesis. Robustness analysis indicated a relative low oxygen level (1.21mmol/gDW/h) would improve glutamate production rate. Potential metabolic engineering targets for improving γ-aminobutyrate and isoleucine production rate were predicted by in silico deletion or overexpression of some genes. The iJM658 model is a useful tool for understanding and optimizing the metabolism of C. glutamicum and a valuable resource for future metabolic and physiological research. PMID:26392034

  20. iAK692: A genome-scale metabolic model of Spirulina platensis C1

    PubMed Central

    2012-01-01

    Background Spirulina (Arthrospira) platensis is a well-known filamentous cyanobacterium used in the production of many industrial products, including high value compounds, healthy food supplements, animal feeds, pharmaceuticals and cosmetics, for example. It has been increasingly studied around the world for scientific purposes, especially for its genome, biology, physiology, and also for the analysis of its small-scale metabolic network. However, the overall description of the metabolic and biotechnological capabilities of S. platensis requires the development of a whole cellular metabolism model. Recently, the S. platensis C1 (Arthrospira sp. PCC9438) genome sequence has become available, allowing systems-level studies of this commercial cyanobacterium. Results In this work, we present the genome-scale metabolic network analysis of S. platensis C1, iAK692, its topological properties, and its metabolic capabilities and functions. The network was reconstructed from the S. platensis C1 annotated genomic sequence using Pathway Tools software to generate a preliminary network. Then, manual curation was performed based on a collective knowledge base and a combination of genomic, biochemical, and physiological information. The genome-scale metabolic model consists of 692 genes, 837 metabolites, and 875 reactions. We validated iAK692 by conducting fermentation experiments and simulating the model under autotrophic, heterotrophic, and mixotrophic growth conditions using COBRA toolbox. The model predictions under these growth conditions were consistent with the experimental results. The iAK692 model was further used to predict the unique active reactions and essential genes for each growth condition. Additionally, the metabolic states of iAK692 during autotrophic and mixotrophic growths were described by phenotypic phase plane (PhPP) analysis. Conclusions This study proposes the first genome-scale model of S. platensis C1, iAK692, which is a predictive metabolic platform

  1. Engineering strategy of yeast metabolism for higher alcohol production

    PubMed Central

    2011-01-01

    Background While Saccharomyces cerevisiae is a promising host for cost-effective biorefinary processes due to its tolerance to various stresses during fermentation, the metabolically engineered S. cerevisiae strains exhibited rather limited production of higher alcohols than that of Escherichia coli. Since the structure of the central metabolism of S. cerevisiae is distinct from that of E. coli, there might be a problem in the structure of the central metabolism of S. cerevisiae. In this study, the potential production of higher alcohols by S. cerevisiae is compared to that of E. coli by employing metabolic simulation techniques. Based on the simulation results, novel metabolic engineering strategies for improving higher alcohol production by S. cerevisiae were investigated by in silico modifications of the metabolic models of S. cerevisiae. Results The metabolic simulations confirmed that the high production of butanols and propanols by the metabolically engineered E. coli strains is derived from the flexible behavior of their central metabolism. Reducing this flexibility by gene deletion is an effective strategy to restrict the metabolic states for producing target alcohols. In contrast, the lower yield using S. cerevisiae originates from the structurally limited flexibility of its central metabolism in which gene deletions severely reduced cell growth. Conclusions The metabolic simulation demonstrated that the poor productivity of S. cerevisiae was improved by the introduction of E. coli genes to compensate the structural difference. This suggested that gene supplementation is a promising strategy for the metabolic engineering of S. cerevisiae to produce higher alcohols which should be the next challenge for the synthetic bioengineering of S. cerevisiae for the efficient production of higher alcohols. PMID:21902829

  2. Uncinate Process Length in Birds Scales with Resting Metabolic Rate

    PubMed Central

    Tickle, Peter; Nudds, Robert; Codd, Jonathan

    2009-01-01

    A fundamental function of the respiratory system is the supply of oxygen to meet metabolic demand. Morphological constraints on the supply of oxygen, such as the structure of the lung, have previously been studied in birds. Recent research has shown that uncinate processes (UP) are important respiratory structures in birds, facilitating inspiratory and expiratory movements of the ribs and sternum. Uncinate process length (UPL) is important for determining the mechanical advantage for these respiratory movements. Here we report on the relationship between UPL, body size, metabolic demand and locomotor specialisation in birds. UPL was found to scale isometrically with body mass. Process length is greatest in specialist diving birds, shortest in walking birds and intermediate length in all others relative to body size. Examination of the interaction between the length of the UP and metabolic demand indicated that, relative to body size, species with high metabolic rates have corresponding elongated UP. We propose that elongated UP confer an advantage on the supply of oxygen, perhaps by improving the mechanical advantage and reducing the energetic cost of movements of the ribs and sternum. PMID:19479074

  3. Metabolic modeling of endosymbiont genome reduction on a temporal scale.

    PubMed

    Yizhak, Keren; Tuller, Tamir; Papp, Balázs; Ruppin, Eytan

    2011-03-29

    A fundamental challenge in Systems Biology is whether a cell-scale metabolic model can predict patterns of genome evolution by realistically accounting for associated biochemical constraints. Here, we study the order in which genes are lost in an in silico evolutionary process, leading from the metabolic network of Escherichia coli to that of the endosymbiont Buchnera aphidicola. We examine how this order correlates with the order by which the genes were actually lost, as estimated from a phylogenetic reconstruction. By optimizing this correlation across the space of potential growth and biomass conditions, we compute an upper bound estimate on the model's prediction accuracy (R=0.54). The model's network-based predictive ability outperforms predictions obtained using genomic features of individual genes, reflecting the effect of selection imposed by metabolic stoichiometric constraints. Thus, while the timing of gene loss might be expected to be a completely stochastic evolutionary process, remarkably, we find that metabolic considerations, on their own, make a marked 40% contribution to determining when such losses occur. PMID:21451589

  4. Genome-scale metabolic model of Pichia pastoris with native and humanized glycosylation of recombinant proteins.

    PubMed

    Irani, Zahra Azimzadeh; Kerkhoven, Eduard J; Shojaosadati, Seyed Abbas; Nielsen, Jens

    2016-05-01

    Pichia pastoris is used for commercial production of human therapeutic proteins, and genome-scale models of P. pastoris metabolism have been generated in the past to study the metabolism and associated protein production by this yeast. A major challenge with clinical usage of recombinant proteins produced by P. pastoris is the difference in N-glycosylation of proteins produced by humans and this yeast. However, through metabolic engineering, a P. pastoris strain capable of producing humanized N-glycosylated proteins was constructed. The current genome-scale models of P. pastoris do not address native nor humanized N-glycosylation, and we therefore developed ihGlycopastoris, an extension to the iLC915 model with both native and humanized N-glycosylation for recombinant protein production, but also an estimation of N-glycosylation of P. pastoris native proteins. This new model gives a better prediction of protein yield, demonstrates the effect of the different types of N-glycosylation of protein yield, and can be used to predict potential targets for strain improvement. The model represents a step towards a more complete description of protein production in P. pastoris, which is required for using these models to understand and optimize protein production processes. Biotechnol. Bioeng. 2016;113: 961-969. © 2015 Wiley Periodicals, Inc. PMID:26480251

  5. Using a Genome-Scale Metabolic Model of Enterococcus faecalis V583 To Assess Amino Acid Uptake and Its Impact on Central Metabolism

    PubMed Central

    Solheim, Margrete; van Grinsven, Koen W. A.; Olivier, Brett G.; Levering, Jennifer; Grosseholz, Ruth; Hugenholtz, Jeroen; Holo, Helge; Nes, Ingolf; Teusink, Bas; Kummer, Ursula

    2014-01-01

    Increasing antibiotic resistance in pathogenic bacteria necessitates the development of new medication strategies. Interfering with the metabolic network of the pathogen can provide novel drug targets but simultaneously requires a deeper and more detailed organism-specific understanding of the metabolism, which is often surprisingly sparse. In light of this, we reconstructed a genome-scale metabolic model of the pathogen Enterococcus faecalis V583. The manually curated metabolic network comprises 642 metabolites and 706 reactions. We experimentally determined metabolic profiles of E. faecalis grown in chemically defined medium in an anaerobic chemostat setup at different dilution rates and calculated the net uptake and product fluxes to constrain the model. We computed growth-associated energy and maintenance parameters and studied flux distributions through the metabolic network. Amino acid auxotrophies were identified experimentally for model validation and revealed seven essential amino acids. In addition, the important metabolic hub of glutamine/glutamate was altered by constructing a glutamine synthetase knockout mutant. The metabolic profile showed a slight shift in the fermentation pattern toward ethanol production and increased uptake rates of multiple amino acids, especially l-glutamine and l-glutamate. The model was used to understand the altered flux distributions in the mutant and provided an explanation for the experimentally observed redirection of the metabolic flux. We further highlighted the importance of gene-regulatory effects on the redirection of the metabolic fluxes upon perturbation. The genome-scale metabolic model presented here includes gene-protein-reaction associations, allowing a further use for biotechnological applications, for studying essential genes, proteins, or reactions, and the search for novel drug targets. PMID:25527553

  6. Metabolic engineering of cyanobacteria for the synthesis of commodity products.

    PubMed

    Angermayr, S Andreas; Gorchs Rovira, Aleix; Hellingwerf, Klaas J

    2015-06-01

    Through metabolic engineering cyanobacteria can be employed in biotechnology. Combining the capacity for oxygenic photosynthesis and carbon fixation with an engineered metabolic pathway allows carbon-based product formation from CO(2), light, and water directly. Such cyanobacterial 'cell factories' are constructed to produce biofuels, bioplastics, and commodity chemicals. Efforts of metabolic engineers and synthetic biologists allow the modification of the intermediary metabolism at various branching points, expanding the product range. The new biosynthesis routes 'tap' the metabolism ever more efficiently, particularly through the engineering of driving forces and utilization of cofactors generated during the light reactions of photosynthesis, resulting in higher product titers. High rates of carbon rechanneling ultimately allow an almost-complete allocation of fixed carbon to product above biomass. PMID:25908503

  7. Genome-scale metabolic modeling of Mucor circinelloides and comparative analysis with other oleaginous species.

    PubMed

    Vongsangnak, Wanwipa; Klanchui, Amornpan; Tawornsamretkit, Iyarest; Tatiyaborwornchai, Witthawin; Laoteng, Kobkul; Meechai, Asawin

    2016-06-01

    We present a novel genome-scale metabolic model iWV1213 of Mucor circinelloides, which is an oleaginous fungus for industrial applications. The model contains 1213 genes, 1413 metabolites and 1326 metabolic reactions across different compartments. We demonstrate that iWV1213 is able to accurately predict the growth rates of M. circinelloides on various nutrient sources and culture conditions using Flux Balance Analysis and Phenotypic Phase Plane analysis. Comparative analysis of three oleaginous genome-scale models, including M. circinelloides (iWV1213), Mortierella alpina (iCY1106) and Yarrowia lipolytica (iYL619_PCP) revealed that iWV1213 possesses a higher number of genes involved in carbohydrate, amino acid, and lipid metabolisms that might contribute to its versatility in nutrient utilization. Moreover, the identification of unique and common active reactions among the Zygomycetes oleaginous models using Flux Variability Analysis unveiled a set of gene/enzyme candidates as metabolic engineering targets for cellular improvement. Thus, iWV1213 offers a powerful metabolic engineering tool for multi-level omics analysis, enabling strain optimization as a cell factory platform of lipid-based production. PMID:26911256

  8. Kinetic modeling of cell metabolism for microbial production.

    PubMed

    Costa, Rafael S; Hartmann, Andras; Vinga, Susana

    2016-02-10

    Kinetic models of cellular metabolism are important tools for the rational design of metabolic engineering strategies and to explain properties of complex biological systems. The recent developments in high-throughput experimental data are leading to new computational approaches for building kinetic models of metabolism. Herein, we briefly survey the available databases, standards and software tools that can be applied for kinetic models of metabolism. In addition, we give an overview about recently developed ordinary differential equations (ODE)-based kinetic models of metabolism and some of the main applications of such models are illustrated in guiding metabolic engineering design. Finally, we review the kinetic modeling approaches of large-scale networks that are emerging, discussing their main advantages, challenges and limitations. PMID:26724578

  9. Microbial methanol formation: A major end product of pectin metabolism

    SciTech Connect

    Schink, B.; Zeikus, J.G.

    1980-01-01

    Various pectinolytic strains of Clostridium, Erwinia, and Pseudomonas species produced methanol as a major end product during growth on pectin but not on glucose of polygalacturonic acid. Pectin metabolism of Clostridium butyricum strain 4PI correlated with a final product concentration of 16 mM at the end of growth, and a 1:1 stoichiometry for methanol production and percent initial substrate methoxylation. Growth on pectin was associated with high activity of pectin methylesterase and the absence of methanol consumption. The ecological significance of pectin metabolism and the establishment of microbial methylotrophic metabolism in nature is discussed.

  10. Comparative Genome-Scale Reconstruction of Gapless Metabolic Networks for Present and Ancestral Species

    PubMed Central

    Pitkänen, Esa; Jouhten, Paula; Hou, Jian; Syed, Muhammad Fahad; Blomberg, Peter; Kludas, Jana; Oja, Merja; Holm, Liisa; Penttilä, Merja; Rousu, Juho; Arvas, Mikko

    2014-01-01

    We introduce a novel computational approach, CoReCo, for comparative metabolic reconstruction and provide genome-scale metabolic network models for 49 important fungal species. Leveraging on the exponential growth in sequenced genome availability, our method reconstructs genome-scale gapless metabolic networks simultaneously for a large number of species by integrating sequence data in a probabilistic framework. High reconstruction accuracy is demonstrated by comparisons to the well-curated Saccharomyces cerevisiae consensus model and large-scale knock-out experiments. Our comparative approach is particularly useful in scenarios where the quality of available sequence data is lacking, and when reconstructing evolutionary distant species. Moreover, the reconstructed networks are fully carbon mapped, allowing their use in 13C flux analysis. We demonstrate the functionality and usability of the reconstructed fungal models with computational steady-state biomass production experiment, as these fungi include some of the most important production organisms in industrial biotechnology. In contrast to many existing reconstruction techniques, only minimal manual effort is required before the reconstructed models are usable in flux balance experiments. CoReCo is available at http://esaskar.github.io/CoReCo/. PMID:24516375

  11. Production of bulk chemicals via novel metabolic pathways in microorganisms.

    PubMed

    Shin, Jae Ho; Kim, Hyun Uk; Kim, Dong In; Lee, Sang Yup

    2013-11-01

    Metabolic engineering has been playing important roles in developing high performance microorganisms capable of producing various chemicals and materials from renewable biomass in a sustainable manner. Synthetic and systems biology are also contributing significantly to the creation of novel pathways and the whole cell-wide optimization of metabolic performance, respectively. In order to expand the spectrum of chemicals that can be produced biotechnologically, it is necessary to broaden the metabolic capacities of microorganisms. Expanding the metabolic pathways for biosynthesizing the target chemicals requires not only the enumeration of a series of known enzymes, but also the identification of biochemical gaps whose corresponding enzymes might not actually exist in nature; this issue is the focus of this paper. First, pathway prediction tools, effectively combining reactions that lead to the production of a target chemical, are analyzed in terms of logics representing chemical information, and designing and ranking the proposed metabolic pathways. Then, several approaches for potentially filling in the gaps of the novel metabolic pathway are suggested along with relevant examples, including the use of promiscuous enzymes that flexibly utilize different substrates, design of novel enzymes for non-natural reactions, and exploration of hypothetical proteins. Finally, strain optimization by systems metabolic engineering in the context of novel metabolic pathways constructed is briefly described. It is hoped that this review paper will provide logical ways of efficiently utilizing 'big' biological data to design and develop novel metabolic pathways for the production of various bulk chemicals that are currently produced from fossil resources. PMID:23280013

  12. Metabolic Profile and Inflammatory Responses in Dairy Cows with Left Displaced Abomasum Kept under Small-Scaled Farm Conditions

    PubMed Central

    Klevenhusen, Fenja; Humer, Elke; Metzler-Zebeli, Barbara; Podstatzky-Lichtenstein, Leopold; Wittek, Thomas; Zebeli, Qendrim

    2015-01-01

    Simple Summary This research established an association between lactation number and milk production and metabolic and inflammatory responses in high-producing dairy cows affected by left abomasal displacement in small-scaled dairy farms. The study showed metabolic alterations, liver damage, and inflammation in the sick cows, which were further exacerbated with increasing lactation number and milk yield of the cows. Abstract Left displaced abomasum (LDA) is a severe metabolic disease of cattle with a strong negative impact on production efficiency of dairy farms. Metabolic and inflammatory alterations associated with this disease have been reported in earlier studies, conducted mostly in large dairy farms. This research aimed to: (1) evaluate metabolic and inflammatory responses in dairy cows affected by LDA in small-scaled dairy farms; and (2) establish an association between lactation number and milk production with the outcome of metabolic variables. The cows with LDA had lower serum calcium (Ca), but greater concentrations of non-esterified fatty acids (NEFA) and beta-hydroxy-butyrate (BHBA), in particular when lactation number was >2. Cows with LDA showed elevated levels of aspartate aminotransferase, glutamate dehydrogenase, and serum amyloid A (SAA), regardless of lactation number. In addition, this study revealed strong associations between milk yield and the alteration of metabolic profile but not with inflammation in the sick cows. Results indicate metabolic alterations, liver damage, and inflammation in LDA cows kept under small-scale farm conditions. Furthermore, the data suggest exacerbation of metabolic profile and Ca metabolism but not of inflammation and liver health with increasing lactation number and milk yield in cows affected by LDA. PMID:26479481

  13. Metabolic engineering for the production of plant isoquinoline alkaloids.

    PubMed

    Diamond, Andrew; Desgagné-Penix, Isabel

    2016-06-01

    Several plant isoquinoline alkaloids (PIAs) possess powerful pharmaceutical and biotechnological properties. Thus, PIA metabolism and its fascinating molecules, including morphine, colchicine and galanthamine, have attracted the attention of both the industry and researchers involved in plant science, biochemistry, chemical bioengineering and medicine. Currently, access and availability of high-value PIAs [commercialized (e.g. galanthamine) or not (e.g. narciclasine)] is limited by low concentration in nature, lack of cultivation or geographic access, seasonal production and risk of overharvesting wild plant species. Nevertheless, most commercial PIAs are still extracted from plant sources. Efforts to improve the production of PIA have largely been impaired by the lack of knowledge on PIA metabolism. With the development and integration of next-generation sequencing technologies, high-throughput proteomics and metabolomics analyses and bioinformatics, systems biology was used to unravel metabolic pathways allowing the use of metabolic engineering and synthetic biology approaches to increase production of valuable PIAs. Metabolic engineering provides opportunity to overcome issues related to restricted availability, diversification and productivity of plant alkaloids. Engineered plant, plant cells and microbial cell cultures can act as biofactories by offering their metabolic machinery for the purpose of optimizing the conditions and increasing the productivity of a specific alkaloid. In this article, is presented an update on the production of PIA in engineered plant, plant cell cultures and heterologous micro-organisms. PMID:26503307

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

    PubMed

    Unrean, Pornkamol; Srienc, Friedrich

    2011-11-01

    A metabolic network can be described by a set of elementary modes or pathways representing discrete metabolic states that support cell function. We have recently shown that in the most likely metabolic state the usage probability of individual elementary modes is distributed according to the Boltzmann distribution law while complying with the principle of maximum entropy production. To demonstrate that a metabolic network evolves towards such state we have carried out adaptive evolution experiments with Thermoanaerobacterium saccharolyticum operating with a reduced metabolic functionality based on a reduced set of elementary modes. In such reduced metabolic network metabolic fluxes can be conveniently computed from the measured metabolite secretion pattern. Over a time span of 300 generations the specific growth rate of the strain continuously increased together with a continuous increase in the rate of entropy production. We show that the rate of entropy production asymptotically approaches the maximum entropy production rate predicted from the state when the usage probability of individual elementary modes is distributed according to the Boltzmann distribution. Therefore, the outcome of evolution of a complex biological system can be predicted in highly quantitative terms using basic statistical mechanical principles. PMID:21903175

  15. Metabolic Profile and Inflammatory Responses in Dairy Cows with Left Displaced Abomasum Kept under Small-Scaled Farm Conditions.

    PubMed

    Klevenhusen, Fenja; Humer, Elke; Metzler-Zebeli, Barbara; Podstatzky-Lichtenstein, Leopold; Wittek, Thomas; Zebeli, Qendrim

    2015-01-01

    Left displaced abomasum (LDA) is a severe metabolic disease of cattle with a strong negative impact on production efficiency of dairy farms. Metabolic and inflammatory alterations associated with this disease have been reported in earlier studies, conducted mostly in large dairy farms. This research aimed to: (1) evaluate metabolic and inflammatory responses in dairy cows affected by LDA in small-scaled dairy farms; and (2) establish an Animals 2015, 5 1022 association between lactation number and milk production with the outcome of metabolic variables. The cows with LDA had lower serum calcium (Ca), but greater concentrations of non-esterified fatty acids (NEFA) and beta-hydroxy-butyrate (BHBA), in particular when lactation number was >2. Cows with LDA showed elevated levels of aspartate aminotransferase, glutamate dehydrogenase, and serum amyloid A (SAA), regardless of lactation number. In addition, this study revealed strong associations between milk yield and the alteration of metabolic profile but not with inflammation in the sick cows. Results indicate metabolic alterations, liver damage, and inflammation in LDA cows kept under small-scale farm conditions. Furthermore, the data suggest exacerbation of metabolic profile and Ca metabolism but not of inflammation and liver health with increasing lactation number and milk yield in cows affected by LDA. PMID:26479481

  16. Investigating host-pathogen behavior and their interaction using genome-scale metabolic network models.

    PubMed

    Sadhukhan, Priyanka P; Raghunathan, Anu

    2014-01-01

    Genome Scale Metabolic Modeling methods represent one way to compute whole cell function starting from the genome sequence of an organism and contribute towards understanding and predicting the genotype-phenotype relationship. About 80 models spanning all the kingdoms of life from archaea to eukaryotes have been built till date and used to interrogate cell phenotype under varying conditions. These models have been used to not only understand the flux distribution in evolutionary conserved pathways like glycolysis and the Krebs cycle but also in applications ranging from value added product formation in Escherichia coli to predicting inborn errors of Homo sapiens metabolism. This chapter describes a protocol that delineates the process of genome scale metabolic modeling for analysing host-pathogen behavior and interaction using flux balance analysis (FBA). The steps discussed in the process include (1) reconstruction of a metabolic network from the genome sequence, (2) its representation in a precise mathematical framework, (3) its translation to a model, and (4) the analysis using linear algebra and optimization. The methods for biological interpretations of computed cell phenotypes in the context of individual host and pathogen models and their integration are also discussed. PMID:25048144

  17. Genome Scale Reconstruction of a Salmonella Metabolic Model

    PubMed Central

    AbuOun, Manal; Suthers, Patrick F.; Jones, Gareth I.; Carter, Ben R.; Saunders, Mark P.; Maranas, Costas D.; Woodward, Martin J.; Anjum, Muna F.

    2009-01-01

    Salmonella are closely related to commensal Escherichia coli but have gained virulence factors enabling them to behave as enteric pathogens. Less well studied are the similarities and differences that exist between the metabolic properties of these organisms that may contribute toward niche adaptation of Salmonella pathogens. To address this, we have constructed a genome scale Salmonella metabolic model (iMA945). The model comprises 945 open reading frames or genes, 1964 reactions, and 1036 metabolites. There was significant overlap with genes present in E. coli MG1655 model iAF1260. In silico growth predictions were simulated using the model on different carbon, nitrogen, phosphorous, and sulfur sources. These were compared with substrate utilization data gathered from high throughput phenotyping microarrays revealing good agreement. Of the compounds tested, the majority were utilizable by both Salmonella and E. coli. Nevertheless a number of differences were identified both between Salmonella and E. coli and also within the Salmonella strains included. These differences provide valuable insight into differences between a commensal and a closely related pathogen and within different pathogenic strains opening new avenues for future explorations. PMID:19690172

  18. The scaling of maximum and basal metabolic rates of mammals and birds

    NASA Astrophysics Data System (ADS)

    Barbosa, Lauro A.; Garcia, Guilherme J. M.; da Silva, Jafferson K. L.

    2006-01-01

    Allometric scaling is one of the most pervasive laws in biology. Its origin, however, is still a matter of dispute. Recent studies have established that maximum metabolic rate scales with an exponent larger than that found for basal metabolism. This unpredicted result sets a challenge that can decide which of the concurrent hypotheses is the correct theory. Here, we show that both scaling laws can be deduced from a single network model. Besides the 3/4-law for basal metabolism, the model predicts that maximum metabolic rate scales as M, maximum heart rate as M, and muscular capillary density as M, in agreement with data.

  19. Scaling of standard metabolic rate in estuarine crocodiles Crocodylus porosus.

    PubMed

    Seymour, Roger S; Gienger, C M; Brien, Matthew L; Tracy, Christopher R; Charlie Manolis, S; Webb, Grahame J W; Christian, Keith A

    2013-05-01

    Standard metabolic rate (SMR, ml O2 min(-1)) of captive Crocodylus porosus at 30 °C scales with body mass (kg) according to the equation, SMR = 1.01 M(0.829), in animals ranging in body mass of 3.3 orders of magnitude (0.19-389 kg). The exponent is significantly higher than 0.75, so does not conform to quarter-power scaling theory, but rather is likely an emergent property with no single explanation. SMR at 1 kg body mass is similar to the literature for C. porosus and for alligators. The high exponent is not related to feeding, growth, or obesity of captive animals. The log-transformed data appear slightly curved, mainly because SMR is somewhat low in many of the largest animals (291-389 kg). A 3-parameter model is scarcely different from the linear one, but reveals a declining exponent between 0.862 and 0.798. A non-linear model on arithmetic axes overestimates SMR in 70% of the smallest animals and does not satisfactorily represent the data. PMID:23233168

  20. Genome-scale metabolic flux analysis of Streptomyces lividans growing on a complex medium.

    PubMed

    D'Huys, Pieter-Jan; Lule, Ivan; Vercammen, Dominique; Anné, Jozef; Van Impe, Jan F; Bernaerts, Kristel

    2012-09-15

    Constraint-based metabolic modeling comprises various excellent tools to assess experimentally observed phenotypic behavior of micro-organisms in terms of intracellular metabolic fluxes. In combination with genome-scale metabolic networks, micro-organisms can be investigated in much more detail and under more complex environmental conditions. Although complex media are ubiquitously applied in industrial fermentations and are often a prerequisite for high protein secretion yields, such multi-component conditions are seldom investigated using genome-scale flux analysis. In this paper, a systematic and integrative approach is presented to determine metabolic fluxes in Streptomyces lividans TK24 grown on a nutritious and complex medium. Genome-scale flux balance analysis and randomized sampling of the solution space are combined to extract maximum information from exometabolome profiles. It is shown that biomass maximization cannot predict the observed metabolite production pattern as such. Although this cellular objective commonly applies to batch fermentation data, both input and output constraints are required to reproduce the measured biomass production rate. Rich media hence not necessarily lead to maximum biomass growth. To eventually identify a unique intracellular flux vector, a hierarchical optimization of cellular objectives is adopted. Out of various tested secondary objectives, maximization of the ATP yield per flux unit returns the closest agreement with the maximum frequency in flux histograms. This unique flux estimation is hence considered as a reasonable approximation for the biological fluxes. Flux maps for different growth phases show no active oxidative part of the pentose phosphate pathway, but NADPH generation in the TCA cycle and NADPH transdehydrogenase activity are most important in fulfilling the NADPH balance. Amino acids contribute to biomass growth by augmenting the pool of available amino acids and by boosting the TCA cycle, particularly

  1. Cardiac Metabolism in Heart Failure - Implications beyond ATP production

    PubMed Central

    Doenst, Torsten; Nguyen, T. Dung; Abel, E. Dale

    2013-01-01

    The heart has a high rate of ATP production and turnover which is required to maintain its continuous mechanical work. Perturbations in ATP generating processes may therefore affect contractile function directly. Characterizing cardiac metabolism in heart failure revealed several metabolic alterations termed metabolic remodeling, ranging from changes in substrate utilization to mitochondrial dysfunction, ultimately resulting in ATP deficiency and impaired contractility. However, ATP depletion is not the only relevant consequence of metabolic remodeling during heart failure. By providing cellular building blocks and signaling molecules, metabolic pathways control essential processes such as cell growth and regeneration. Thus, alterations in cardiac metabolism may also affect the progression to heart failure by mechanisms beyond ATP supply. Our aim is therefore to highlight that metabolic remodeling in heart failure not only results in impaired cardiac energetics, but also induces other processes implicated in the development of heart failure such as structural remodeling and oxidative stress. Accordingly, modulating cardiac metabolism in heart failure may have significant therapeutic relevance that goes beyond the energetic aspect. PMID:23989714

  2. Classifying forest productivity at different scales

    SciTech Connect

    Graham, R.L.

    1991-01-01

    Spatial scale is an important consideration when evaluating, using, or constructing forest productivity classifications. First, the factors which dominate spatial variability in forest productivity are scale dependent. For example, within a stand, spatial variability in productivity is dominated by microsite differences; within a national forest such as the Cherokee National Forest, spatial variability is dominated by topography and land-use history (e.g., years since harvest); within a large region such as the southeast, spatial variability is dominated by climatic patterns. Second, classifications developed at different spatial scales are often used for different purposes. For example, stand-level classifications are often keys or rules used in the field to judge the quality or potential of a site. National-forest classifications are often presented as maps or tables and may be used in forest land planning. Regional classifications may be maps or tables and may be used to quantify or predict resource availability. These scale-related differences in controlling factors and purposes will affect both the methods and the data used to develop classifications. In this paper, I will illustrate these points by describing and comparing three forest productivity classifications, each developed for a specific purpose at a specific scale. My objective is not to argue for or against any of these particular classifications but rather to heighten awareness of the critical role that spatial scale plays in the use and development of forest productivity classifications. 8 refs., 2 figs., 1 tab.

  3. Genome-scale reconstruction of Salinispora tropica CNB-440 metabolism to study strain-specific adaptation.

    PubMed

    Contador, C A; Rodríguez, V; Andrews, B A; Asenjo, J A

    2015-11-01

    The first manually curated genome-scale metabolic model for Salinispora tropica strain CNB-440 was constructed. The reconstruction enables characterization of the metabolic capabilities for understanding and modeling the cellular physiology of this actinobacterium. The iCC908 model was based on physiological and biochemical information of primary and specialised metabolism pathways. The reconstructed stoichiometric matrix consists of 1169 biochemical conversions, 204 transport reactions and 1317 metabolites. A total of 908 structural open reading frames (ORFs) were included in the reconstructed network. The number of gene functions included in the reconstructed network corresponds to 20% of all characterized ORFs in the S. tropica genome. The genome-scale metabolic model was used to study strain-specific capabilities in defined minimal media. iCC908 was used to analyze growth capabilities in 41 different minimal growth-supporting environments. These nutrient sources were evaluated experimentally to assess the accuracy of in silico growth simulations. The model predicted no auxotrophies for essential amino acids, which was corroborated experimentally. The strain is able to use 21 different carbon sources, 8 nitrogen sources and 4 sulfur sources from the nutrient sources tested. Experimental observation suggests that the cells may be able to store sulfur. False predictions provided opportunities to gain new insights into the physiology of this species, and to gap fill the missing knowledge. The incorporation of modifications led to increased accuracy in predicting the outcome of growth/no growth experiments from 76 to 93%. iCC908 can thus be used to define the metabolic capabilities of S. tropica and guide and enhance the production of specialised metabolites. PMID:26459337

  4. Metabolic Engineering of Microalgal Based Biofuel Production: Prospects and Challenges

    PubMed Central

    Banerjee, Chiranjib; Dubey, Kashyap K.; Shukla, Pratyoosh

    2016-01-01

    The current scenario in renewable energy is focused on development of alternate and sustainable energy sources, amongst which microalgae stands as one of the promising feedstock for biofuel production. It is well known that microalgae generate much larger amounts of biofuels in a shorter time than other sources based on plant seeds. However, the greatest challenge in a transition to algae-based biofuel production is the various other complications involved in microalgal cultivation, its harvesting, concentration, drying and lipid extraction. Several green microalgae accumulate lipids, especially triacylglycerols (TAGs), which are main precursors in the production of lipid. The various aspects on metabolic pathway analysis of an oleaginous microalgae i.e., Chlamydomonas reinhardtii have elucidated some novel metabolically important genes and this enhances the lipid production in this microalgae. Adding to it, various other aspects in metabolic engineering using OptFlux and effectual bioprocess design also gives an interactive snapshot of enhancing lipid production which ultimately improvises the oil yield. This article reviews the current status of microalgal based technologies for biofuel production, bioreactor process design, flux analysis and it also provides various strategies to increase lipids accumulation via metabolic engineering. PMID:27065986

  5. Metabolic Engineering of Microalgal Based Biofuel Production: Prospects and Challenges.

    PubMed

    Banerjee, Chiranjib; Dubey, Kashyap K; Shukla, Pratyoosh

    2016-01-01

    The current scenario in renewable energy is focused on development of alternate and sustainable energy sources, amongst which microalgae stands as one of the promising feedstock for biofuel production. It is well known that microalgae generate much larger amounts of biofuels in a shorter time than other sources based on plant seeds. However, the greatest challenge in a transition to algae-based biofuel production is the various other complications involved in microalgal cultivation, its harvesting, concentration, drying and lipid extraction. Several green microalgae accumulate lipids, especially triacylglycerols (TAGs), which are main precursors in the production of lipid. The various aspects on metabolic pathway analysis of an oleaginous microalgae i.e., Chlamydomonas reinhardtii have elucidated some novel metabolically important genes and this enhances the lipid production in this microalgae. Adding to it, various other aspects in metabolic engineering using OptFlux and effectual bioprocess design also gives an interactive snapshot of enhancing lipid production which ultimately improvises the oil yield. This article reviews the current status of microalgal based technologies for biofuel production, bioreactor process design, flux analysis and it also provides various strategies to increase lipids accumulation via metabolic engineering. PMID:27065986

  6. Advances in Metabolic Engineering of Cyanobacteria for Photosynthetic Biochemical Production.

    PubMed

    Lai, Martin C; Lan, Ethan I

    2015-01-01

    Engineering cyanobacteria into photosynthetic microbial cell factories for the production of biochemicals and biofuels is a promising approach toward sustainability. Cyanobacteria naturally grow on light and carbon dioxide, bypassing the need of fermentable plant biomass and arable land. By tapping into the central metabolism and rerouting carbon flux towards desirable compound production, cyanobacteria are engineered to directly convert CO₂ into various chemicals. This review discusses the diversity of bioproducts synthesized by engineered cyanobacteria, the metabolic pathways used, and the current engineering strategies used for increasing their titers. PMID:26516923

  7. Advances in Metabolic Engineering of Cyanobacteria for Photosynthetic Biochemical Production

    PubMed Central

    Lai, Martin C.; Lan, Ethan I.

    2015-01-01

    Engineering cyanobacteria into photosynthetic microbial cell factories for the production of biochemicals and biofuels is a promising approach toward sustainability. Cyanobacteria naturally grow on light and carbon dioxide, bypassing the need of fermentable plant biomass and arable land. By tapping into the central metabolism and rerouting carbon flux towards desirable compound production, cyanobacteria are engineered to directly convert CO2 into various chemicals. This review discusses the diversity of bioproducts synthesized by engineered cyanobacteria, the metabolic pathways used, and the current engineering strategies used for increasing their titers. PMID:26516923

  8. A genome-scale metabolic network reconstruction of tomato (Solanum lycopersicum L.) and its application to photorespiratory metabolism.

    PubMed

    Yuan, Huili; Cheung, C Y Maurice; Poolman, Mark G; Hilbers, Peter A J; van Riel, Natal A W

    2016-01-01

    Tomato (Solanum lycopersicum L.) has been studied extensively due to its high economic value in the market, and high content in health-promoting antioxidant compounds. Tomato is also considered as an excellent model organism for studying the development and metabolism of fleshy fruits. However, the growth, yield and fruit quality of tomatoes can be affected by drought stress, a common abiotic stress for tomato. To investigate the potential metabolic response of tomato plants to drought, we reconstructed iHY3410, a genome-scale metabolic model of tomato leaf, and used this metabolic network to simulate tomato leaf metabolism. The resulting model includes 3410 genes and 2143 biochemical and transport reactions distributed across five intracellular organelles including cytosol, plastid, mitochondrion, peroxisome and vacuole. The model successfully described the known metabolic behaviour of tomato leaf under heterotrophic and phototrophic conditions. The in silico investigation of the metabolic characteristics for photorespiration and other relevant metabolic processes under drought stress suggested that: (i) the flux distributions through the mevalonate (MVA) pathway under drought were distinct from that under normal conditions; and (ii) the changes in fluxes through core metabolic pathways with varying flux ratio of RubisCO carboxylase to oxygenase may contribute to the adaptive stress response of plants. In addition, we improved on previous studies of reaction essentiality analysis for leaf metabolism by including potential alternative routes for compensating reaction knockouts. Altogether, the genome-scale model provides a sound framework for investigating tomato metabolism and gives valuable insights into the functional consequences of abiotic stresses. PMID:26576489

  9. Understanding the Causes and Implications of Endothelial Metabolic Variation in Cardiovascular Disease through Genome-Scale Metabolic Modeling

    PubMed Central

    McGarrity, Sarah; Halldórsson, Haraldur; Palsson, Sirus; Johansson, Pär I.; Rolfsson, Óttar

    2016-01-01

    High-throughput biochemical profiling has led to a requirement for advanced data interpretation techniques capable of integrating the analysis of gene, protein, and metabolic profiles to shed light on genotype–phenotype relationships. Herein, we consider the current state of knowledge of endothelial cell (EC) metabolism and its connections to cardiovascular disease (CVD) and explore the use of genome-scale metabolic models (GEMs) for integrating metabolic and genomic data. GEMs combine gene expression and metabolic data acting as frameworks for their analysis and, ultimately, afford mechanistic understanding of how genetic variation impacts metabolism. We demonstrate how GEMs can be used to investigate CVD-related genetic variation, drug resistance mechanisms, and novel metabolic pathways in ECs. The application of GEMs in personalized medicine is also highlighted. Particularly, we focus on the potential of GEMs to identify metabolic biomarkers of endothelial dysfunction and to discover methods of stratifying treatments for CVDs based on individual genetic markers. Recent advances in systems biology methodology, and how these methodologies can be applied to understand EC metabolism in both health and disease, are thus highlighted. PMID:27148541

  10. Understanding the Causes and Implications of Endothelial Metabolic Variation in Cardiovascular Disease through Genome-Scale Metabolic Modeling.

    PubMed

    McGarrity, Sarah; Halldórsson, Haraldur; Palsson, Sirus; Johansson, Pär I; Rolfsson, Óttar

    2016-01-01

    High-throughput biochemical profiling has led to a requirement for advanced data interpretation techniques capable of integrating the analysis of gene, protein, and metabolic profiles to shed light on genotype-phenotype relationships. Herein, we consider the current state of knowledge of endothelial cell (EC) metabolism and its connections to cardiovascular disease (CVD) and explore the use of genome-scale metabolic models (GEMs) for integrating metabolic and genomic data. GEMs combine gene expression and metabolic data acting as frameworks for their analysis and, ultimately, afford mechanistic understanding of how genetic variation impacts metabolism. We demonstrate how GEMs can be used to investigate CVD-related genetic variation, drug resistance mechanisms, and novel metabolic pathways in ECs. The application of GEMs in personalized medicine is also highlighted. Particularly, we focus on the potential of GEMs to identify metabolic biomarkers of endothelial dysfunction and to discover methods of stratifying treatments for CVDs based on individual genetic markers. Recent advances in systems biology methodology, and how these methodologies can be applied to understand EC metabolism in both health and disease, are thus highlighted. PMID:27148541

  11. Metabolic Profiling of Geobacter sulfurreducens during Industrial Bioprocess Scale-Up

    PubMed Central

    Muhamadali, Howbeer; Xu, Yun; Ellis, David I.; Allwood, J. William; Rattray, Nicholas J. W.; Correa, Elon; Alrabiah, Haitham

    2015-01-01

    During the industrial scale-up of bioprocesses it is important to establish that the biological system has not changed significantly when moving from small laboratory-scale shake flasks or culturing bottles to an industrially relevant production level. Therefore, during upscaling of biomass production for a range of metal transformations, including the production of biogenic magnetite nanoparticles by Geobacter sulfurreducens, from 100-ml bench-scale to 5-liter fermentors, we applied Fourier transform infrared (FTIR) spectroscopy as a metabolic fingerprinting approach followed by the analysis of bacterial cell extracts by gas chromatography-mass spectrometry (GC-MS) for metabolic profiling. FTIR results clearly differentiated between the phenotypic changes associated with different growth phases as well as the two culturing conditions. Furthermore, the clustering patterns displayed by multivariate analysis were in agreement with the turbidimetric measurements, which displayed an extended lag phase for cells grown in a 5-liter bioreactor (24 h) compared to those grown in 100-ml serum bottles (6 h). GC-MS analysis of the cell extracts demonstrated an overall accumulation of fumarate during the lag phase under both culturing conditions, coinciding with the detected concentrations of oxaloacetate, pyruvate, nicotinamide, and glycerol-3-phosphate being at their lowest levels compared to other growth phases. These metabolites were overlaid onto a metabolic network of G. sulfurreducens, and taking into account the levels of these metabolites throughout the fermentation process, the limited availability of oxaloacetate and nicotinamide would seem to be the main metabolic bottleneck resulting from this scale-up process. Additional metabolite-feeding experiments were carried out to validate the above hypothesis. Nicotinamide supplementation (1 mM) did not display any significant effects on the lag phase of G. sulfurreducens cells grown in the 100-ml serum bottles. However

  12. Metabolic Profiling of Geobacter sulfurreducens during Industrial Bioprocess Scale-Up.

    PubMed

    Muhamadali, Howbeer; Xu, Yun; Ellis, David I; Allwood, J William; Rattray, Nicholas J W; Correa, Elon; Alrabiah, Haitham; Lloyd, Jonathan R; Goodacre, Royston

    2015-05-15

    During the industrial scale-up of bioprocesses it is important to establish that the biological system has not changed significantly when moving from small laboratory-scale shake flasks or culturing bottles to an industrially relevant production level. Therefore, during upscaling of biomass production for a range of metal transformations, including the production of biogenic magnetite nanoparticles by Geobacter sulfurreducens, from 100-ml bench-scale to 5-liter fermentors, we applied Fourier transform infrared (FTIR) spectroscopy as a metabolic fingerprinting approach followed by the analysis of bacterial cell extracts by gas chromatography-mass spectrometry (GC-MS) for metabolic profiling. FTIR results clearly differentiated between the phenotypic changes associated with different growth phases as well as the two culturing conditions. Furthermore, the clustering patterns displayed by multivariate analysis were in agreement with the turbidimetric measurements, which displayed an extended lag phase for cells grown in a 5-liter bioreactor (24 h) compared to those grown in 100-ml serum bottles (6 h). GC-MS analysis of the cell extracts demonstrated an overall accumulation of fumarate during the lag phase under both culturing conditions, coinciding with the detected concentrations of oxaloacetate, pyruvate, nicotinamide, and glycerol-3-phosphate being at their lowest levels compared to other growth phases. These metabolites were overlaid onto a metabolic network of G. sulfurreducens, and taking into account the levels of these metabolites throughout the fermentation process, the limited availability of oxaloacetate and nicotinamide would seem to be the main metabolic bottleneck resulting from this scale-up process. Additional metabolite-feeding experiments were carried out to validate the above hypothesis. Nicotinamide supplementation (1 mM) did not display any significant effects on the lag phase of G. sulfurreducens cells grown in the 100-ml serum bottles. However

  13. Intramolecular stable isotope distributions detect plant metabolic responses on century time scales

    NASA Astrophysics Data System (ADS)

    Schleucher, Jürgen; Ehlers, Ina; Augusti, Angela; Betson, Tatiana

    2014-05-01

    Plants respond to environmental changes on a vast range of time scales, and plant gas exchanges constitute important feedback mechanisms in the global C cycle. Responses on time scales of decades to centuries are most important for climate models, for prediction of crop productivity, and for adaptation to climate change. Unfortunately, responses on these timescale are least understood. We argue that the knowledge gap on intermediate time scales is due to a lack of adequate methods that can bridge between short-term manipulative experiments (e.g. FACE) and paleo research. Manipulative experiments in plant ecophysiology give information on metabolism on time scales up to years. However, this information cannot be linked to results from retrospective studies in paleo research, because little metabolic information can be derived from paleo archives. Stable isotopes are prominent tools in plant ecophysiology, biogeochemistry and in paleo research, but in all applications to date, isotope ratios of whole molecules are measured. However, it is well established that stable isotope abundance varies among intramolecular groups of biochemical metabolites, that is each so-called "isotopomer" has a distinct abundance. This intramolecular variation carries information on metabolic regulation, which can even be traced to individual enzymes (Schleucher et al., Plant, Cell Environ 1999). Here, we apply intramolecular isotope distributions to study the metabolic response of plants to increasing atmospheric [CO2] during the past century. Greenhouse experiments show that the deuterium abundance among the two positions in the C6H2 group of photosynthetic glucose depends on [CO2] during growth. This is observed for all plants using C3 photosynthesis, and reflects the metabolic flux ratio between photorespiration and photosynthesis. Photorespiration is a major C flux that limits assimilation in C3 plants, which encompass the overwhelming fraction of terrestrial photosynthesis and the

  14. Major evolutionary transitions of life, metabolic scaling and the number and size of mitochondria and chloroplasts.

    PubMed

    Okie, Jordan G; Smith, Val H; Martin-Cereceda, Mercedes

    2016-05-25

    We investigate the effects of trophic lifestyle and two types of major evolutionary transitions in individuality-the endosymbiotic acquisition of organelles and development of multicellularity-on organellar and cellular metabolism and allometry. We develop a quantitative framework linking the size and metabolic scaling of eukaryotic cells to the abundance, size and metabolic scaling of mitochondria and chloroplasts and analyse a newly compiled, unprecedented database representing unicellular and multicellular cells covering diverse phyla and tissues. Irrespective of cellularity, numbers and total volumes of mitochondria scale linearly with cell volume, whereas chloroplasts scale sublinearly and sizes of both organelles remain largely invariant with cell size. Our framework allows us to estimate the metabolic scaling exponents of organelles and cells. Photoautotrophic cells and organelles exhibit photosynthetic scaling exponents always less than one, whereas chemoheterotrophic cells and organelles have steeper respiratory scaling exponents close to one. Multicellularity has no discernible effect on the metabolic scaling of organelles and cells. In contrast, trophic lifestyle has a profound and uniform effect, and our results suggest that endosymbiosis fundamentally altered the metabolic scaling of free-living bacterial ancestors of mitochondria and chloroplasts, from steep ancestral scaling to a shallower scaling in their endosymbiotic descendants. PMID:27194700

  15. Metabolic engineering of bacteria for ethanol production

    SciTech Connect

    Ingram, L.O.; Gomez, P.F.; Lai, X.; Moniruzzaman, M.; Wood, B.E.; Yomano, L.P.; York, S.W.

    1998-04-20

    Technologies are available which will allow the conversion of lignocellulose into fuel ethanol using genetically engineered bacteria. Assembling these into a cost-effective process remains a challenge. The authors` work has focused primarily on the genetic engineering of enteric bacteria using a portable ethanol production pathway. Genes encoding Zymomonas mobilis pyruvate decarboxylase and alcohol dehydrogenase have been integrated into the chromosome of Escherichia coli B to produce strain KO11 for the fermentation of hemicellulose-derived syrups. This organism can efficiently ferment all hexose and pentose sugars present in the polymers of hemicellulose. Klebsiella oxytoca M5A1 has been genetically engineered in a similar manner to produce strain P2 for ethanol production from cellulose. This organism has the native ability to ferment cellobiose and cellotriose, eliminating the need for one class of cellulase enzymes. The optimal pH for cellulose fermentation with this organism is near that of fungal cellulases. The general approach for the genetic engineering of new biocatalysts has been most successful with enteric bacteria thus far. However, this approach may also prove useful with gram-positive bacteria which have other important traits for lignocellulose conversion. Many opportunities remain for further improvements in the biomass to ethanol processes.

  16. RPC Production at General Tecnica: a mass scale production

    NASA Astrophysics Data System (ADS)

    della Volpe, D.; Morganti, S.

    2006-08-01

    The construction of LHC has deeply changed the RPC production. The enormous amount of detector needed and the strong requirements on gas volume quality had a deep impact on the production chain and on the QC and QA at the production site. This basically has brought the RPC from an almost hand-crafted detector to a medium scale mass product. The most critical aspects of the production chain have been modified and/or improved introducing new and more rigorous QC and QA procedures to guarantee the detector quality and improve the management of storage and the procurement on materials. Here it will be presented the work carried on in the last four year at the production site to improve and check the quality and the results achieved. Something like 10000 RPC were produced between 2002 and 2005. Also a preliminary and rough analysis on the efficiencies of the various phases in the chain production based on ATLAS production will be presented.

  17. Production of L-carnitine by secondary metabolism of bacteria

    PubMed Central

    Bernal, Vicente; Sevilla, Ángel; Cánovas, Manuel; Iborra, José L

    2007-01-01

    The increasing commercial demand for L-carnitine has led to a multiplication of efforts to improve its production with bacteria. The use of different cell environments, such as growing, resting, permeabilized, dried, osmotically stressed, freely suspended and immobilized cells, to maintain enzymes sufficiently active for L-carnitine production is discussed in the text. The different cell states of enterobacteria, such as Escherichia coli and Proteus sp., which can be used to produce L-carnitine from crotonobetaine or D-carnitine as substrate, are analyzed. Moreover, the combined application of both bioprocess and metabolic engineering has allowed a deeper understanding of the main factors controlling the production process, such as energy depletion and the alteration of the acetyl-CoA/CoA ratio which are coupled to the end of the biotransformation. Furthermore, the profiles of key central metabolic activities such as the TCA cycle, the glyoxylate shunt and the acetate metabolism are seen to be closely interrelated and affect the biotransformation efficiency. Although genetically modified strains have been obtained, new strain improvement strategies are still needed, especially in Escherichia coli as a model organism for molecular biology studies. This review aims to summarize and update the state of the art in L-carnitine production using E. coli and Proteus sp, emphasizing the importance of proper reactor design and operation strategies, together with metabolic engineering aspects and the need for feed-back between wet and in silico work to optimize this biotransformation. PMID:17910757

  18. Metabolic Design and Control for Production in Prokaryotes

    SciTech Connect

    Chhabra, Swapnil R.; Keasling, J.D.

    2010-11-10

    Prokaryotic life on earth is manifested by its diversity and omnipresence. These microbes serve as natural sources of a large variety of compounds with the potential to serve the ever growing, medicinal, chemical and transportation needs of the human population. However, commercially viable production of these compounds can be realized only through significant improvement of the native production capacity of natural isolates. The most favorable way to achieve this goal is through the genetic manipulation of metabolic pathways that direct the production of these molecules. While random mutagenesis and screening have dominated the industrial production of such compounds in the past our increased understanding of microbial physiology over the last five decades has shifted this trend towards rational approaches for metabolic design. Major drivers of this trend include recombinant DNA technology, high throughput characterization of macromolecular cellular components, quantitative modeling for metabolic engine ring, targeted combinatorial engineering and synthetic biology. In this chapter we track the evolution of microbial engineering technologies from the black box era of random mutagenesis to the science and engineering-driven era of metabolic design.

  19. Metabolic differences in cattle with excitable temperaments can influence productivity

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Temperament can negatively affect various production traits, including live weight, ADG, DMI, conception rates, and carcass weight. Three research studies are summarized which indicate the potential influence of temperament on metabolism. In Brahman heifers, (n=12) the 6 most temperamental and 6 mos...

  20. Model based engineering of Pichia pastoris central metabolism enhances recombinant protein production

    PubMed Central

    Nocon, Justyna; Steiger, Matthias G.; Pfeffer, Martin; Sohn, Seung Bum; Kim, Tae Yong; Maurer, Michael; Rußmayer, Hannes; Pflügl, Stefan; Ask, Magnus; Haberhauer-Troyer, Christina; Ortmayr, Karin; Hann, Stephan; Koellensperger, Gunda; Gasser, Brigitte; Lee, Sang Yup; Mattanovich, Diethard

    2014-01-01

    The production of recombinant proteins is frequently enhanced at the levels of transcription, codon usage, protein folding and secretion. Overproduction of heterologous proteins, however, also directly affects the primary metabolism of the producing cells. By incorporation of the production of a heterologous protein into a genome scale metabolic model of the yeast Pichia pastoris, the effects of overproduction were simulated and gene targets for deletion or overexpression for enhanced productivity were predicted. Overexpression targets were localized in the pentose phosphate pathway and the TCA cycle, while knockout targets were found in several branch points of glycolysis. Five out of 9 tested targets led to an enhanced production of cytosolic human superoxide dismutase (hSOD). Expression of bacterial β-glucuronidase could be enhanced as well by most of the same genetic modifications. Beneficial mutations were mainly related to reduction of the NADP/H pool and the deletion of fermentative pathways. Overexpression of the hSOD gene itself had a strong impact on intracellular fluxes, most of which changed in the same direction as predicted by the model. In vivo fluxes changed in the same direction as predicted to improve hSOD production. Genome scale metabolic modeling is shown to predict overexpression and deletion mutants which enhance recombinant protein production with high accuracy. PMID:24853352

  1. Biofilm Formation Mechanisms of Pseudomonas aeruginosa Predicted via Genome-Scale Kinetic Models of Bacterial Metabolism

    PubMed Central

    Vital-Lopez, Francisco G.; Reifman, Jaques; Wallqvist, Anders

    2015-01-01

    A hallmark of Pseudomonas aeruginosa is its ability to establish biofilm-based infections that are difficult to eradicate. Biofilms are less susceptible to host inflammatory and immune responses and have higher antibiotic tolerance than free-living planktonic cells. Developing treatments against biofilms requires an understanding of bacterial biofilm-specific physiological traits. Research efforts have started to elucidate the intricate mechanisms underlying biofilm development. However, many aspects of these mechanisms are still poorly understood. Here, we addressed questions regarding biofilm metabolism using a genome-scale kinetic model of the P. aeruginosa metabolic network and gene expression profiles. Specifically, we computed metabolite concentration differences between known mutants with altered biofilm formation and the wild-type strain to predict drug targets against P. aeruginosa biofilms. We also simulated the altered metabolism driven by gene expression changes between biofilm and stationary growth-phase planktonic cultures. Our analysis suggests that the synthesis of important biofilm-related molecules, such as the quorum-sensing molecule Pseudomonas quinolone signal and the exopolysaccharide Psl, is regulated not only through the expression of genes in their own synthesis pathway, but also through the biofilm-specific expression of genes in pathways competing for precursors to these molecules. Finally, we investigated why mutants defective in anthranilate degradation have an impaired ability to form biofilms. Alternative to a previous hypothesis that this biofilm reduction is caused by a decrease in energy production, we proposed that the dysregulation of the synthesis of secondary metabolites derived from anthranilate and chorismate is what impaired the biofilms of these mutants. Notably, these insights generated through our kinetic model-based approach are not accessible from previous constraint-based model analyses of P. aeruginosa biofilm

  2. Toxicity of polyamines and their metabolic products.

    PubMed

    Pegg, Anthony E

    2013-12-16

    Polyamines are ubiquitous and essential components of mammalian cells. They have multiple functions including critical roles in nucleic acid and protein synthesis, gene expression, protein function, protection from oxidative damage, the regulation of ion channels, and maintenance of the structure of cellular macromolecules. It is essential to maintain a correct level of polyamines, and this amount is tightly regulated at the levels of transport, synthesis, and degradation. Catabolic pathways generate reactive aldehydes including acrolein and hydrogen peroxide via a number of oxidases. These metabolites, particularly those from spermine, can cause significant toxicity with damage to proteins, DNA, and other cellular components. Their production can be increased as a result of infection or cell damage that releases free polyamines and activates the oxidative catabolic pathways. Since polyamines also have an important physiological role in protection from oxidative damage, the reduction in polyamine content may exacerbate the toxic potential of these agents. Increases in polyamine catabolism have been implicated in the development of diseases including stroke, other neurological diseases, renal failure, liver disease, and cancer. These results provide new opportunities for the early diagnosis, prevention, and treatment of disease. PMID:24224555

  3. Shift in metabolism towards ethanol production in Saccharomyces cerevisiae by addition of metabolic inhibitors

    SciTech Connect

    Hahn-Haegerdal, B.; Mattiasson, B.

    1982-01-01

    The future exploitation of fermentation processes for the production of bulk chemicals will very much depend on whether product yield and product concentration can be improved. At the present time the cost for the raw material and the product upgrading limits the competitiveness of fermentation processes in relation to petrochemical processes. Much effort is put into selecting microbial strains with higher product yields as well as improved tolerance towards increased product concentrations. This approach is rather laborious and time-consuming and the overall goal will be beneficial if it is complemented with other techniques. This investigation will describe how productivity migh be improved by addition of a specific metabolic inhibitor, sodium azide, which inhibits the cytochrome oxidase of the respiratory chain. As a model for these studies Saccaromyces cerevisiae fermenting glucose to ethanol was chosen.

  4. Metabolic transit and toxicity of Maillard reaction products.

    PubMed

    Finot, P A; Furniss, D E

    1989-01-01

    The feeding of Maillard reaction products (MRP) has been reported to lead to a variety of effects on metabolism which may be classed as "anti-nutritional" or "anti-physiological", depending on whether they are due to the loss of essential nutrients or to the presence of the MRP per se. This paper describes the sensitivity of essential nutrients in the "early" and "advanced" stages of the Maillard reaction, the metabolic transit of Amadori compounds, premelanoidins, melanoidins, hydroxymethyl-furfural, carboxymethyl-lysine, as well as the effects of MRP on pancreatic amylase and on urinary zinc excretion. PMID:2506565

  5. Fumaric Acid Production in Saccharomyces cerevisiae by In Silico Aided Metabolic Engineering

    PubMed Central

    Xu, Guoqiang; Zou, Wei; Chen, Xiulai; Xu, Nan; Liu, Liming; Chen, Jian

    2012-01-01

    Fumaric acid (FA) is a promising biomass-derived building-block chemical. Bio-based FA production from renewable feedstock is a promising and sustainable alternative to petroleum-based chemical synthesis. Here we report on FA production by direct fermentation using metabolically engineered Saccharomyces cerevisiae with the aid of in silico analysis of a genome-scale metabolic model. First, FUM1 was selected as the target gene on the basis of extensive literature mining. Flux balance analysis (FBA) revealed that FUM1 deletion can lead to FA production and slightly lower growth of S. cerevisiae. The engineered S. cerevisiae strain obtained by deleting FUM1 can produce FA up to a concentration of 610±31 mg L–1 without any apparent change in growth in fed-batch culture. FT-IR and 1H and 13C NMR spectra confirmed that FA was synthesized by the engineered S. cerevisiae strain. FBA identified pyruvate carboxylase as one of the factors limiting higher FA production. When the RoPYC gene was introduced, S. cerevisiae produced 1134±48 mg L–1 FA. Furthermore, the final engineered S. cerevisiae strain was able to produce 1675±52 mg L–1 FA in batch culture when the SFC1 gene encoding a succinate–fumarate transporter was introduced. These results demonstrate that the model shows great predictive capability for metabolic engineering. Moreover, FA production in S. cerevisiae can be efficiently developed with the aid of in silico metabolic engineering. PMID:23300594

  6. Metabolic Engineering of Microorganisms for the Production of Higher Alcohols

    PubMed Central

    Choi, Yong Jun; Lee, Joungmin; Jang, Yu-Sin

    2014-01-01

    ABSTRACT Due to the increasing concerns about limited fossil resources and environmental problems, there has been much interest in developing biofuels from renewable biomass. Ethanol is currently used as a major biofuel, as it can be easily produced by existing fermentation technology, but it is not the best biofuel due to its low energy density, high vapor pressure, hygroscopy, and incompatibility with current infrastructure. Higher alcohols, including 1-propanol, 1-butanol, isobutanol, 2-methyl-1-butanol, and 3-methyl-1-butanol, which possess fuel properties more similar to those of petroleum-based fuel, have attracted particular interest as alternatives to ethanol. Since microorganisms isolated from nature do not allow production of these alcohols at high enough efficiencies, metabolic engineering has been employed to enhance their production. Here, we review recent advances in metabolic engineering of microorganisms for the production of higher alcohols. PMID:25182323

  7. Scaling metabolism from individuals to reef-fish communities at broad spatial scales.

    PubMed

    Barneche, D R; Kulbicki, M; Floeter, S R; Friedlander, A M; Maina, J; Allen, A P

    2014-09-01

    Fishes contribute substantially to energy and nutrient fluxes in reef ecosystems, but quantifying these roles is challenging. Here, we do so by synthesising a large compilation of fish metabolic-rate data with a comprehensive database on reef-fish community abundance and biomass. Individual-level analyses support predictions of Metabolic Theory after accounting for significant family-level variation, and indicate that some tropical reef fishes may already be experiencing thermal regimes at or near their temperature optima. Community-level analyses indicate that total estimated respiratory fluxes of reef-fish communities increase on average ~2-fold from 22 to 28 °C. Comparisons of estimated fluxes among trophic groups highlight striking differences in resource use by communities in different regions, perhaps partly reflecting distinct evolutionary histories, and support the hypothesis that piscivores receive substantial energy subsidies from outside reefs. Our study demonstrates one approach to synthesising individual- and community-level data to establish broad-scale trends in contributions of biota to ecosystem dynamics. PMID:24943721

  8. Metabolic network analysis of lysine producing Corynebacterium glutamicum at a miniaturized scale.

    PubMed

    Wittmann, Christoph; Kim, Hyung Min; Heinzle, Elmar

    2004-07-01

    We present a straightforward approach comprising (13)C tracer experiments at 200-microL volume in 96-well microtiter plates with on-line measurement of dissolved oxygen for quantitative high-throughput metabolic network analysis at a miniaturized scale. This method was successfully applied for cultivation and (13)C metabolic flux analysis of two mutants of lysine producing Corynebacterium glutamicum (ATCC 13287 and ATCC 21543). Microtiter-plate cultivations showed excellent accordance in kinetics and stoichiometry of growth and product formation as well as in intracellular flux distributions as compared with parallel shake-flask experiments. These cultivations further allowed clear identification of strain-specific flux differences such as increased flux toward lysine, increased flux through the pentose phosphate pathway (PPP), decreased flux through the tricarboxylic (TCA) cycle, and increased dihydroxyacetone formation in C. glutamicum ATCC 21543 compared with ATCC 13287. The present approach has strong potential for broad quantitative screening of metabolic network activities, especially those involving high-cost tracer substrates. PMID:15211482

  9. Universal scaling of production rates across mammalian lineages

    PubMed Central

    Hamilton, Marcus J.; Davidson, Ana D.; Sibly, Richard M.; Brown, James H.

    2011-01-01

    Over many millions of years of independent evolution, placental, marsupial and monotreme mammals have diverged conspicuously in physiology, life history and reproductive ecology. The differences in life histories are particularly striking. Compared with placentals, marsupials exhibit shorter pregnancy, smaller size of offspring at birth and longer period of lactation in the pouch. Monotremes also exhibit short pregnancy, but incubate embryos in eggs, followed by a long period of post-hatching lactation. Using a large sample of mammalian species, we show that, remarkably, despite their very different life histories, the scaling of production rates is statistically indistinguishable across mammalian lineages. Apparently all mammals are subject to the same fundamental metabolic constraints on productivity, because they share similar body designs, vascular systems and costs of producing new tissue. PMID:20798111

  10. Patterns of metabolite changes identified from large-scale gene perturbations in Arabidopsis using a genome-scale metabolic network.

    PubMed

    Kim, Taehyong; Dreher, Kate; Nilo-Poyanco, Ricardo; Lee, Insuk; Fiehn, Oliver; Lange, Bernd Markus; Nikolau, Basil J; Sumner, Lloyd; Welti, Ruth; Wurtele, Eve S; Rhee, Seung Y

    2015-04-01

    Metabolomics enables quantitative evaluation of metabolic changes caused by genetic or environmental perturbations. However, little is known about how perturbing a single gene changes the metabolic system as a whole and which network and functional properties are involved in this response. To answer this question, we investigated the metabolite profiles from 136 mutants with single gene perturbations of functionally diverse Arabidopsis (Arabidopsis thaliana) genes. Fewer than 10 metabolites were changed significantly relative to the wild type in most of the mutants, indicating that the metabolic network was robust to perturbations of single metabolic genes. These changed metabolites were closer to each other in a genome-scale metabolic network than expected by chance, supporting the notion that the genetic perturbations changed the network more locally than globally. Surprisingly, the changed metabolites were close to the perturbed reactions in only 30% of the mutants of the well-characterized genes. To determine the factors that contributed to the distance between the observed metabolic changes and the perturbation site in the network, we examined nine network and functional properties of the perturbed genes. Only the isozyme number affected the distance between the perturbed reactions and changed metabolites. This study revealed patterns of metabolic changes from large-scale gene perturbations and relationships between characteristics of the perturbed genes and metabolic changes. PMID:25670818

  11. Biobased organic acids production by metabolically engineered microorganisms.

    PubMed

    Chen, Yun; Nielsen, Jens

    2016-02-01

    Bio-based production of organic acids via microbial fermentation has been traditionally used in food industry. With the recent desire to develop more sustainable bioprocesses for production of fuels, chemicals and materials, the market for microbial production of organic acids has been further expanded as organic acids constitute a key group among top building block chemicals that can be produced from renewable resources. Here we review the current status for production of citric acid and lactic acid, and we highlight the use of modern metabolic engineering technologies to develop high performance microbes for production of succinic acid and 3-hydroxypropionic acid. Also, the key limitations and challenges in microbial organic acids production are discussed. PMID:26748037

  12. Metabolic engineering for the production of 1,3-propanediol

    SciTech Connect

    Cameron, D.C.; Tong, I.T., Skraly, F.A.

    1993-12-31

    Metabolic engineering involves the use of recombinant DNA techniques for the modification of intermediary metabolic pathways. Microorganisms have recently been engineered to produce compounds such as indigo, ethanol, fatty acids and polyhydroxyalkanoates. As a model system for research in metabolic engineering, the authors have constructed a strain of the bacterium Escherichia coli, that is able to produce 1,3-propanediol (1,3-PD) from glycerol. This strain contains the genes for the glycerol deydratase and the 1,3-PD oxidoreductase from Klebsiella pneumoniae. The authors have also investigated genetic and environmental strategies for improving the yield and productivity of 1,3-PD by the engineered organism. In addition to being a useful model system, 1,3-PD production is of current practical interest. First 1,3-PD (also known as trimethylene glycol) and 1,4-butanediol, the more readily available diols. Second, the volume of feedstock (glycerol) is expected to grow, as it is a by-product of the production of polyglycoside surfactants and biodiesel fluids.

  13. Evaluation of endogenous acidic metabolic products associated with carbohydrate metabolism in tumor cells.

    PubMed

    Mazzio, Elizabeth A; Smith, Bruce; Soliman, Karam F A

    2010-06-01

    Tumor cells have a high tolerance for acidic and hypoxic microenvironments, also producing abundant lactic acid through accelerated glycolysis in the presence or absence of O(2). While the accumulation of lactate is thought to be a major contributor to the reduction of pH-circumscribing aggressive tumors, it is not known if other endogenous metabolic products contribute this acidity. Furthermore, anaerobic metabolism in cancer cells bears similarity to homo-fermentative lactic acid bacteria, however very little is known about an alternative pathway that may drive adenosine triphosphate (ATP) production independent of glycolysis. In this study, we quantify over 40 end-products (amines, acids, alcohols, aldehydes, or ketones) produced by malignant neuroblastoma under accelerated glycolysis (+glucose (GLU) supply 1-10 mM) +/- mitochondrial toxin; 1-methyl-4-phenylpyridinium (MPP(+)) to abate aerobic respiration to delineate differences between anaerobic vs. aerobic cell required metabolic pathways. The data show that an acceleration of anaerobic glycolysis prompts an expected reduction in extracellular pH (pH(ex)) from neutral to 6.7 +/- 0.006. Diverse metabolic acids associated with this drop in acidity were quantified by ionic exchange liquid chromatography (LC), showing concomitant rise in lactate (Ctrls 7.5 +/- 0.5 mM; +GLU 12.35 +/- 1.3 mM; +GLU + MPP 18.1 +/- 1.8 mM), acetate (Ctrl 0.84 +/- 0.13 mM: +GLU 1.3 +/- 0.15 mM; +GLU + MPP 2.7 +/- 0.4 mM), fumarate, and a-ketoglutarate (<10 microM) while a range of other metabolic organic acids remained undetected. Amino acids quantified by o-phthalaldehyde precolumn derivatization/electrochemical detection-LC show accumulation of L: -alanine (1.6 +/- .052 mM), L: -glutamate (285 +/- 9.7 microM), L: -asparagine (202 +/- 2.1 microM), and L: -aspartate (84.2 +/- 4.9 microM) produced during routine metabolism, while other amino acids remain undetected. In contrast, the data show no evidence for accumulation of acetaldehyde

  14. Metabolically engineered Escherichia coli for efficient production of glycosylated natural products

    PubMed Central

    Peirú, Salvador; Rodríguez, Eduardo; Menzella, Hugo G.; Carney, John R.; Gramajo, Hugo

    2008-01-01

    Summary Significant achievements in polyketide gene expression have made Escherichia coli one of the most promising hosts for the heterologous production of pharmacologically important polyketides. However, attempts to produce glycosylated polyketides, by the expression of heterologous sugar pathways, have been hampered until now by the low levels of glycosylated compounds produced by the recombinant hosts. By carrying out metabolic engineering of three endogenous pathways that lead to the synthesis of TDP sugars in E. coli, we have greatly improved the intracellular levels of the common deoxysugar intermediate TDP‐4‐keto‐6‐deoxyglucose resulting in increased production of the heterologous sugars TDP‐L‐mycarose and TDP‐d‐desosamine, both components of medically important polyketides. Bioconversion experiments carried out by feeding 6‐deoxyerythronolide B (6‐dEB) or 3‐α‐mycarosylerythronolide B (MEB) demonstrated that the genetically modified E. coli B strain was able to produce 60‐ and 25‐fold more erythromycin D (EryD) than the original strain K207‐3, respectively. Moreover, the additional knockout of the multidrug efflux pump AcrAB further improved the ability of the engineered strain to produce these glycosylated compounds. These results open the possibility of using E. coli as a generic host for the industrial scale production of glycosylated polyketides, and to combine the polyketide and deoxysugar combinatorial approaches with suitable glycosyltransferases to yield massive libraries of novel compounds with variations in both the aglycone and the tailoring sugars. PMID:21261868

  15. Unit Price Scaling Trends for Chemical Products

    SciTech Connect

    Qi, Wei; Sathre, Roger; William R. Morrow, III; Shehabi, Arman

    2015-08-01

    To facilitate early-stage life-cycle techno-economic modeling of emerging technologies, here we identify scaling relations between unit price and sales quantity for a variety of chemical products of three categories - metal salts, organic compounds, and solvents. We collect price quotations for lab-scale and bulk purchases of chemicals from both U.S. and Chinese suppliers. We apply a log-log linear regression model to estimate the price discount effect. Using the median discount factor of each category, one can infer bulk prices of products for which only lab-scale prices are available. We conduct out-of-sample tests showing that most of the price proxies deviate from their actual reference prices by a factor less than ten. We also apply the bootstrap method to determine if a sample median discount factor should be accepted for price approximation. We find that appropriate discount factors for metal salts and for solvents are both -0.56, while that for organic compounds is -0.67 and is less representative due to greater extent of product heterogeneity within this category.

  16. Genome-Scale Reconstruction and Analysis of the Pseudomonas putida KT2440 Metabolic Network Facilitates Applications in Biotechnology

    PubMed Central

    Godinho, Miguel; Bielecka, Agata; Regenhardt, Daniela; Timmis, Kenneth N.

    2008-01-01

    A cornerstone of biotechnology is the use of microorganisms for the efficient production of chemicals and the elimination of harmful waste. Pseudomonas putida is an archetype of such microbes due to its metabolic versatility, stress resistance, amenability to genetic modifications, and vast potential for environmental and industrial applications. To address both the elucidation of the metabolic wiring in P. putida and its uses in biocatalysis, in particular for the production of non-growth-related biochemicals, we developed and present here a genome-scale constraint-based model of the metabolism of P. putida KT2440. Network reconstruction and flux balance analysis (FBA) enabled definition of the structure of the metabolic network, identification of knowledge gaps, and pin-pointing of essential metabolic functions, facilitating thereby the refinement of gene annotations. FBA and flux variability analysis were used to analyze the properties, potential, and limits of the model. These analyses allowed identification, under various conditions, of key features of metabolism such as growth yield, resource distribution, network robustness, and gene essentiality. The model was validated with data from continuous cell cultures, high-throughput phenotyping data, 13C-measurement of internal flux distributions, and specifically generated knock-out mutants. Auxotrophy was correctly predicted in 75% of the cases. These systematic analyses revealed that the metabolic network structure is the main factor determining the accuracy of predictions, whereas biomass composition has negligible influence. Finally, we drew on the model to devise metabolic engineering strategies to improve production of polyhydroxyalkanoates, a class of biotechnologically useful compounds whose synthesis is not coupled to cell survival. The solidly validated model yields valuable insights into genotype–phenotype relationships and provides a sound framework to explore this versatile bacterium and to

  17. Rhamnolipids in perspective: gene regulatory pathways, metabolic engineering, production and technological forecasting.

    PubMed

    Dobler, Leticia; Vilela, Leonardo F; Almeida, Rodrigo V; Neves, Bianca C

    2016-01-25

    Rhamnolipids have emerged as a very promising class of biosurfactants in the last decades, exhibiting properties of great interest in several industrial applications, and have represented a suitable alternative to chemically-synthesized surfactants. This class of biosurfactants has been extensively studied in recent years, aiming at their large-scale production based on renewable resources, which still require high financial costs. Development of non-pathogenic, high-producing strains has been the focus of a number of studies involving heterologous microbial hosts as platforms. However, the intricate gene regulation network controlling rhamnolipid biosynthesis represents a challenge to metabolic engineering and remains to be further understood and explored. This article provides an overview of the biosynthetic pathways and the main gene regulatory factors involved in rhamnolipid production within Pseudomonas aeruginosa, the prototypal producing species. In addition, we provide a perspective view into the main strategies applied to metabolic engineering and biotechnological production. PMID:26409933

  18. A Caenorhabditis elegans Genome-Scale Metabolic Network Model.

    PubMed

    Yilmaz, L Safak; Walhout, Albertha J M

    2016-05-25

    Caenorhabditis elegans is a powerful model to study metabolism and how it relates to nutrition, gene expression, and life history traits. However, while numerous experimental techniques that enable perturbation of its diet and gene function are available, a high-quality metabolic network model has been lacking. Here, we reconstruct an initial version of the C. elegans metabolic network. This network model contains 1,273 genes, 623 enzymes, and 1,985 metabolic reactions and is referred to as iCEL1273. Using flux balance analysis, we show that iCEL1273 is capable of representing the conversion of bacterial biomass into C. elegans biomass during growth and enables the predictions of gene essentiality and other phenotypes. In addition, we demonstrate that gene expression data can be integrated with the model by comparing metabolic rewiring in dauer animals versus growing larvae. iCEL1273 is available at a dedicated website (wormflux.umassmed.edu) and will enable the unraveling of the mechanisms by which different macro- and micronutrients contribute to the animal's physiology. PMID:27211857

  19. Shape shifting predicts ontogenetic changes in metabolic scaling in diverse aquatic invertebrates

    PubMed Central

    Glazier, Douglas S.; Hirst, Andrew G.; Atkinson, David

    2015-01-01

    Metabolism fuels all biological activities, and thus understanding its variation is fundamentally important. Much of this variation is related to body size, which is commonly believed to follow a 3/4-power scaling law. However, during ontogeny, many kinds of animals and plants show marked shifts in metabolic scaling that deviate from 3/4-power scaling predicted by general models. Here, we show that in diverse aquatic invertebrates, ontogenetic shifts in the scaling of routine metabolic rate from near isometry (bR = scaling exponent approx. 1) to negative allometry (bR < 1), or the reverse, are associated with significant changes in body shape (indexed by bL = the scaling exponent of the relationship between body mass and body length). The observed inverse correlations between bR and bL are predicted by metabolic scaling theory that emphasizes resource/waste fluxes across external body surfaces, but contradict theory that emphasizes resource transport through internal networks. Geometric estimates of the scaling of surface area (SA) with body mass (bA) further show that ontogenetic shifts in bR and bA are positively correlated. These results support new metabolic scaling theory based on SA influences that may be applied to ontogenetic shifts in bR shown by many kinds of animals and plants. PMID:25652833

  20. Metabolic modeling of fumaric acid production by Rhizopus arrhizus

    SciTech Connect

    Gangl, I.C.; Weigand, W.W.; Keller, F.A.

    1991-12-31

    A metabolic model is developed for fumaric acid production by Rhizopus arrhizus. The model describes the reaction network and the extents of reaction in terms of the concentrations of the measurable species. The proposed pathway consists of the Embden-Meyerhof pathway and two pathways to FA production, both of which require CO{sub 2} fixation (the forward and the reverse TCA cycles). Relationships among the measurable quantities, in addition to those obtainable by a macroscopic mass balance, are found by invoking a pseudo-steady-state assumption on the nonaccumulating species in the pathway. Applications of the metabolic model, such as verifying the proposed pathway, obtaining the theoretical yield and selectivity, and detecting experimental errors, are discussed.

  1. Engineering metabolic systems for production of advanced fuels.

    PubMed

    Yan, Yajun; Liao, James C

    2009-04-01

    The depleting petroleum storage and increasing environmental deterioration are threatening the sustainable development of human societies. As such, biofuels and chemical feedstocks generated from renewable sources are becoming increasingly important. Although previous efforts led to great success in bio-ethanol production, higher alcohols, fatty acid derivatives including biodiesels, alkanes, and alkenes offer additional advantages because of their compatibility with existing infrastructure. In addition, some of these compounds are useful chemical feedstocks. Since native organisms do not naturally produce these compounds in high quantities, metabolic engineering becomes essential in constructing producing organisms. In this article, we briefly review the four major metabolic systems, the coenzyme-A mediated pathways, the keto acid pathways, the fatty acid pathway, and the isoprenoid pathways, that allow production of these fuel-grade chemicals. PMID:19198907

  2. Intraspecific Scaling of the Resting and Maximum Metabolic Rates of the Crucian Carp (Carassius auratus)

    PubMed Central

    Huang, Qingda; Zhang, Yurong; Liu, Shuting; Wang, Wen; Luo, Yiping

    2013-01-01

    The question of how the scaling of metabolic rate with body mass (M) is achieved in animals is unresolved. Here, we tested the cell metabolism hypothesis and the organ size hypothesis by assessing the mass scaling of the resting metabolic rate (RMR), maximum metabolic rate (MMR), erythrocyte size, and the masses of metabolically active organs in the crucian carp (Carassius auratus). The M of the crucian carp ranged from 4.5 to 323.9 g, representing an approximately 72-fold difference. The RMR and MMR increased with M according to the allometric equations RMR = 0.212M0.776 and MMR = 0.753M0.785. The scaling exponents for RMR (br) and MMR (bm) obtained in crucian carp were close to each other. Thus, the factorial aerobic scope remained almost constant with increasing M. Although erythrocyte size was negatively correlated with both mass-specific RMR and absolute RMR adjusted to M, it and all other hematological parameters showed no significant relationship with M. These data demonstrate that the cell metabolism hypothesis does not describe metabolic scaling in the crucian carp, suggesting that erythrocyte size may not represent the general size of other cell types in this fish and the metabolic activity of cells may decrease as fish grows. The mass scaling exponents of active organs was lower than 1 while that of inactive organs was greater than 1, which suggests that the mass scaling of the RMR can be partly due to variance in the proportion of active/inactive organs in crucian carp. Furthermore, our results provide additional evidence supporting the correlation between locomotor capacity and metabolic scaling. PMID:24376588

  3. 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

  4. MapMaker and PathTracer for tracking carbon in genome-scale metabolic models.

    PubMed

    Tervo, Christopher J; Reed, Jennifer L

    2016-05-01

    Constraint-based reconstruction and analysis (COBRA) modeling results can be difficult to interpret given the large numbers of reactions in genome-scale models. While paths in metabolic networks can be found, existing methods are not easily combined with constraint-based approaches. To address this limitation, two tools (MapMaker and PathTracer) were developed to find paths (including cycles) between metabolites, where each step transfers carbon from reactant to product. MapMaker predicts carbon transfer maps (CTMs) between metabolites using only information on molecular formulae and reaction stoichiometry, effectively determining which reactants and products share carbon atoms. MapMaker correctly assigned CTMs for over 97% of the 2,251 reactions in an Escherichia coli metabolic model (iJO1366). Using CTMs as inputs, PathTracer finds paths between two metabolites. PathTracer was applied to iJO1366 to investigate the importance of using CTMs and COBRA constraints when enumerating paths, to find active and high flux paths in flux balance analysis (FBA) solutions, to identify paths for putrescine utilization, and to elucidate a potential CO2 fixation pathway in E. coli. These results illustrate how MapMaker and PathTracer can be used in combination with constraint-based models to identify feasible, active, and high flux paths between metabolites. PMID:26771089

  5. [Improving 3-dehydroshikimate production by metabolically engineered Escherichia coli].

    PubMed

    Yuan, Fei; Chen, Wujiu; Jia, Shiru; Wang, Qinhong

    2014-10-01

    In the aromatic amino acid biosynthetic pathway 3-dehydroshikimate (DHS) is a key intermediate. As a potent antioxidant and important feedstock for producing a variety of important industrial chemicals, such as adipate and vanillin, DHS is of great commercial value. Here, in this study, we investigated the effect of the co-expression of aroFFBR (3-deoxy-D-arabino-heptulosonate 7-phosphate synthase mutant with tyrosine feedback-inhibition resistance) and tktA (Transketolase A) at different copy number on the production of DHS. The increased copy number of aroFFBR and tktA would enhance the production of DHS by the fold of 2.93. In order to further improve the production of DHS, we disrupted the key genes in by-product pathways of the parent strain Escherichia coli AB2834. The triple knockout strain of ldhA, ackA-pta and adhE would further increase the production of DHS. The titer of DHS in shake flask reached 1.83 g/L, 5.7-fold higher than that of the parent strain E. coli AB2834. In 5-L fed-batch fermentation, the metabolically engineered strain produced 25.48 g/L DHS after 62 h. Metabolically engineered E. coli has the potential to further improve the production of DHS. PMID:25726580

  6. Computational evaluation of Synechococcus sp. PCC 7002 metabolism for chemical production

    SciTech Connect

    Vu, Trang; Hill, Eric A.; Kucek, Leo A.; Konopka, Allan; Beliaev, Alex S.; Reed, Jennifer L.

    2013-05-24

    Cyanobacteria are ideal metabolic engineering platforms for carbon-neutral biotechnology because they directly convert CO2 to a range of valuable products. In this study, we present a computational assessment of biochemical production in Synechococcus sp. PCC 7002 (Synechococcus 7002), a fast growing cyanobacterium whose genome has been sequenced, and for which genetic modification methods have been developed. We evaluated the maximum theoretical yields (mol product per mol CO2 or mol photon) of producing various chemicals under photoautotrophic and dark conditions using a genome-scale metabolic model of Synechococcus 7002. We found that the yields were lower under dark conditions, compared to photoautotrophic conditions, due to the limited amount of energy and reductant generated from glycogen. We also examined the effects of photon and CO2 limitations on chemical production under photoautotrophic conditions. In addition, using various computational methods such as MOMA, RELATCH, and OptORF, we identified gene-knockout mutants that are predicted to improve chemical production under photoautotrophic and/or dark anoxic conditions. These computational results are useful for metabolic engineering of cyanobacteria to synthesize valueadded products.

  7. A Common Scaling Rule for Abundance, Energetics, and Production of Parasitic and Free-Living Species

    PubMed Central

    Hechinger, Ryan F.; Lafferty, Kevin D.; Dobson, Andy P.; Brown, James H.; Kuris, Armand M.

    2011-01-01

    The metabolic theory of ecology uses the scaling of metabolism with body size and temperature to explain the causes and consequences of species abundance. However, the theory and its empirical tests have never simultaneously examined parasites alongside free-living species. This is unfortunate because parasites represent at least half of species diversity. We show that metabolic scaling theory could not account for the abundance of parasitic or free-living species in three estuarine food webs until accounting for trophic dynamics. Analyses then revealed that the abundance of all species uniformly scaled with body mass to the −¾ power. This result indicates “production equivalence,” where biomass production within trophic levels is invariant of body size across all species and functional groups: invertebrate or vertebrate, ectothermic or endothermic, and free-living or parasitic. PMID:21778398

  8. A common scaling rule for abundance, energetics, and production of parasitic and free-living species

    USGS Publications Warehouse

    Hechinger, Ryan F.; Lafferty, Kevin D.; Dobson, Andy P.; Brown, James H.; Kuris, Armand M.

    2011-01-01

    The metabolic theory of ecology uses the scaling of metabolism with body size and temperature to explain the causes and consequences of species abundance. However, the theory and its empirical tests have never simultaneously examined parasites alongside free-living species. This is unfortunate because parasites represent at least half of species diversity. We show that metabolic scaling theory could not account for the abundance of parasitic or free-living species in three estuarine food webs until accounting for trophic dynamics. Analyses then revealed that the abundance of all species uniformly scaled with body mass to the - 3/4 power. This result indicates "production equivalence," where biomass production within trophic levels is invariant of body size across all species and functional groups: invertebrate or vertebrate, ectothermic or endothermic, and free-living or parasitic.

  9. Metabolic reconstruction, constraint-based analysis and game theory to probe genome-scale metabolic networks.

    PubMed

    Ruppin, Eytan; Papin, Jason A; de Figueiredo, Luis F; Schuster, Stefan

    2010-08-01

    With the advent of modern omics technologies, it has become feasible to reconstruct (quasi-) whole-cell metabolic networks and characterize them in more and more detail. Computer simulations of the dynamic behavior of such networks are difficult due to a lack of kinetic data and to computational limitations. In contrast, network analysis based on appropriate constraints such as the steady-state condition (constraint-based analysis) is feasible and allows one to derive conclusions about the system's metabolic capabilities. Here, we review methods for the reconstruction of metabolic networks, modeling techniques such as flux balance analysis and elementary flux modes and current progress in their development and applications. Game-theoretical methods for studying metabolic networks are discussed as well. PMID:20692823

  10. Genome-Scale Metabolic Reconstructions and Theoretical Investigation of Methane Conversion in Methylomicrobium buryatense Strain 5G(B1)

    SciTech Connect

    de la Torre, Andrea; Metivier, Aisha; Chu, Frances; Laurens, Lieve M. L.; Beck, David A. C.; Pienkos, Philip T.; Lidstrom, Mary E.; Kalyuzhnaya, Marina G.

    2015-11-25

    Methane-utilizing bacteria (methanotrophs) are capable of growth on methane and are attractive systems for bio-catalysis. However, the application of natural methanotrophic strains to large-scale production of value-added chemicals/biofuels requires a number of physiological and genetic alterations. An accurate metabolic model coupled with flux balance analysis can provide a solid interpretative framework for experimental data analyses and integration.

  11. From DNA to FBA: How to Build Your Own Genome-Scale Metabolic Model

    PubMed Central

    Cuevas, Daniel A.; Edirisinghe, Janaka; Henry, Chris S.; Overbeek, Ross; O’Connell, Taylor G.; Edwards, Robert A.

    2016-01-01

    Microbiological studies are increasingly relying on in silico methods to perform exploration and rapid analysis of genomic data, and functional genomics studies are supplemented by the new perspectives that genome-scale metabolic models offer. A mathematical model consisting of a microbe’s entire metabolic map can be rapidly determined from whole-genome sequencing and annotating the genomic material encoded in its DNA. Flux-balance analysis (FBA), a linear programming technique that uses metabolic models to predict the phenotypic responses imposed by environmental elements and factors, is the leading method to simulate and manipulate cellular growth in silico. However, the process of creating an accurate model to use in FBA consists of a series of steps involving a multitude of connections between bioinformatics databases, enzyme resources, and metabolic pathways. We present the methodology and procedure to obtain a metabolic model using PyFBA, an extensible Python-based open-source software package aimed to provide a platform where functional annotations are used to build metabolic models (http://linsalrob.github.io/PyFBA). Backed by the Model SEED biochemistry database, PyFBA contains methods to reconstruct a microbe’s metabolic map, run FBA upon different media conditions, and gap-fill its metabolism. The extensibility of PyFBA facilitates novel techniques in creating accurate genome-scale metabolic models. PMID:27379044

  12. From DNA to FBA: How to Build Your Own Genome-Scale Metabolic Model.

    PubMed

    Cuevas, Daniel A; Edirisinghe, Janaka; Henry, Chris S; Overbeek, Ross; O'Connell, Taylor G; Edwards, Robert A

    2016-01-01

    Microbiological studies are increasingly relying on in silico methods to perform exploration and rapid analysis of genomic data, and functional genomics studies are supplemented by the new perspectives that genome-scale metabolic models offer. A mathematical model consisting of a microbe's entire metabolic map can be rapidly determined from whole-genome sequencing and annotating the genomic material encoded in its DNA. Flux-balance analysis (FBA), a linear programming technique that uses metabolic models to predict the phenotypic responses imposed by environmental elements and factors, is the leading method to simulate and manipulate cellular growth in silico. However, the process of creating an accurate model to use in FBA consists of a series of steps involving a multitude of connections between bioinformatics databases, enzyme resources, and metabolic pathways. We present the methodology and procedure to obtain a metabolic model using PyFBA, an extensible Python-based open-source software package aimed to provide a platform where functional annotations are used to build metabolic models (http://linsalrob.github.io/PyFBA). Backed by the Model SEED biochemistry database, PyFBA contains methods to reconstruct a microbe's metabolic map, run FBA upon different media conditions, and gap-fill its metabolism. The extensibility of PyFBA facilitates novel techniques in creating accurate genome-scale metabolic models. PMID:27379044

  13. The RAVEN Toolbox and Its Use for Generating a Genome-scale Metabolic Model for Penicillium chrysogenum

    PubMed Central

    Agren, Rasmus; Liu, Liming; Shoaie, Saeed; Vongsangnak, Wanwipa; Nookaew, Intawat; Nielsen, Jens

    2013-01-01

    We present the RAVEN (Reconstruction, Analysis and Visualization of Metabolic Networks) Toolbox: a software suite that allows for semi-automated reconstruction of genome-scale models. It makes use of published models and/or the KEGG database, coupled with extensive gap-filling and quality control features. The software suite also contains methods for visualizing simulation results and omics data, as well as a range of methods for performing simulations and analyzing the results. The software is a useful tool for system-wide data analysis in a metabolic context and for streamlined reconstruction of metabolic networks based on protein homology. The RAVEN Toolbox workflow was applied in order to reconstruct a genome-scale metabolic model for the important microbial cell factory Penicillium chrysogenum Wisconsin54-1255. The model was validated in a bibliomic study of in total 440 references, and it comprises 1471 unique biochemical reactions and 1006 ORFs. It was then used to study the roles of ATP and NADPH in the biosynthesis of penicillin, and to identify potential metabolic engineering targets for maximization of penicillin production. PMID:23555215

  14. Genome-scale reconstruction of the Streptococcus pyogenes M49 metabolic network reveals growth requirements and indicates potential drug targets.

    PubMed

    Levering, Jennifer; Fiedler, Tomas; Sieg, Antje; van Grinsven, Koen W A; Hering, Silvio; Veith, Nadine; Olivier, Brett G; Klett, Lara; Hugenholtz, Jeroen; Teusink, Bas; Kreikemeyer, Bernd; Kummer, Ursula

    2016-08-20

    Genome-scale metabolic models comprise stoichiometric relations between metabolites, as well as associations between genes and metabolic reactions and facilitate the analysis of metabolism. We computationally reconstructed the metabolic network of the lactic acid bacterium Streptococcus pyogenes M49. Initially, we based the reconstruction on genome annotations and already existing and curated metabolic networks of Bacillus subtilis, Escherichia coli, Lactobacillus plantarum and Lactococcus lactis. This initial draft was manually curated with the final reconstruction accounting for 480 genes associated with 576 reactions and 558 metabolites. In order to constrain the model further, we performed growth experiments of wild type and arcA deletion strains of S. pyogenes M49 in a chemically defined medium and calculated nutrient uptake and production fluxes. We additionally performed amino acid auxotrophy experiments to test the consistency of the model. The established genome-scale model can be used to understand the growth requirements of the human pathogen S. pyogenes and define optimal and suboptimal conditions, but also to describe differences and similarities between S. pyogenes and related lactic acid bacteria such as L. lactis in order to find strategies to reduce the growth of the pathogen and propose drug targets. PMID:26970054

  15. BHP may scale up methanol production

    SciTech Connect

    Alperowicz, N.

    1993-06-23

    Broken Hill Pty. (BHP: Melbourne) says otherwise uneconomic gas reserves in the Timor Sea off northwest Australia could be developed if the company`s plans to commercialize a novel gas-to-methanol technology prove to be viable. BHP is building an A$70-million ($50 million) research unit in Victoria using ICI`s Leading Concept Methanol gas-to-methanol process. If this unit proves viable, it could be put on a vessel and taken to Timor Sea where BHP has oil exploration and production interests. Timor gas is not economically viable because of lack of nearby markets. The 54,000-m.t./year research plant, located at Werrbee near Melbourne, is scheduled to start production in the second half of 1994, according to BHP manager Joe Evon. The plant is being built by Davy/John Brown. Provided the economic climate is right, BHP is expected to build a world-scale methanol plant offshore.

  16. High-throughput generation, optimization and analysis of genome-scale metabolic models.

    SciTech Connect

    Henry, C. S.; DeJongh, M.; Best, A. A.; Frybarger, P. M.; Linsay, B.; Stevens, R. L.

    2010-09-01

    Genome-scale metabolic models have proven to be valuable for predicting organism phenotypes from genotypes. Yet efforts to develop new models are failing to keep pace with genome sequencing. To address this problem, we introduce the Model SEED, a web-based resource for high-throughput generation, optimization and analysis of genome-scale metabolic models. The Model SEED integrates existing methods and introduces techniques to automate nearly every step of this process, taking {approx}48 h to reconstruct a metabolic model from an assembled genome sequence. We apply this resource to generate 130 genome-scale metabolic models representing a taxonomically diverse set of bacteria. Twenty-two of the models were validated against available gene essentiality and Biolog data, with the average model accuracy determined to be 66% before optimization and 87% after optimization.

  17. Metabolic engineering of Saccharomyces cerevisiae to improve 1-hexadecanol production.

    PubMed

    Feng, Xueyang; Lian, Jiazhang; Zhao, Huimin

    2015-01-01

    Fatty alcohols are important components of a vast array of surfactants, lubricants, detergents, pharmaceuticals and cosmetics. We have engineered Saccharomyces cerevisiae to produce 1-hexadecanol by expressing a fatty acyl-CoA reductase (FAR) from barn owl (Tyto alba). In order to improve fatty alcohol production, we have manipulated both the structural genes and the regulatory genes in yeast lipid metabolism. The acetyl-CoA carboxylase gene (ACC1) was over-expressed, which improved 1-hexadecanol production by 56% (from 45mg/L to 71mg/L). Knocking out the negative regulator of the INO1 gene in phospholipid metabolism, RPD3, further enhanced 1-hexadecanol production by 98% (from 71mg/L to 140mg/L). The cytosolic acetyl-CoA supply was next engineered by expressing a heterologous ATP-dependent citrate lyase, which increased the production of 1-hexadecanol by an additional 136% (from 140mg/L to 330mg/L). Through fed-batch fermentation using resting cells, over 1.1g/L 1-hexadecanol can be produced in glucose minimal medium, which represents the highest titer reported in yeast to date. PMID:25466225

  18. Metabolic Engineering of Candida glabrata for Diacetyl Production

    PubMed Central

    Gao, Xiang; Xu, Nan; Li, Shubo; Liu, Liming

    2014-01-01

    In this study, Candida glabrata, an efficient pyruvate-producing strain, was metabolically engineered for the production of the food ingredient diacetyl. A diacetyl biosynthetic pathway was reconstructed based on genetic modifications and medium optimization. The former included (i) channeling carbon flux into the diacetyl biosynthetic pathway by amplification of acetolactate synthase, (ii) elimination of the branched pathway of α-acetolactate by deleting the ILV5 gene, and (iii) restriction of diacetyl degradation by deleting the BDH gene. The resultant strain showed an almost 1∶1 co-production of α-acetolactate and diacetyl (0.95 g L−1). Furthermore, addition of Fe3+ to the medium enhanced the conversion of α-acetolactate to diacetyl and resulted in a two-fold increase in diacetyl production (2.1 g L−1). In addition, increased carbon flux was further channeled into diacetyl biosynthetic pathway and a titer of 4.7 g L−1 of diacetyl was achieved by altering the vitamin level in the flask culture. Thus, this study illustrates that C. glabrata could be tailored as an attractive platform for enhanced biosynthesis of beneficial products from pyruvate by metabolic engineering strategies. PMID:24614328

  19. Genome-Scale Metabolic Modeling in the Simulation of Field-Scale Uranium Bioremediation

    NASA Astrophysics Data System (ADS)

    Yabusaki, S.; Wilkins, M.; Fang, Y.; Williams, K. H.; Waichler, S.; Long, P. E.

    2015-12-01

    Coupled variably saturated flow and biogeochemical reactive transport modeling is used to improve understanding of the processes, properties, and conditions controlling uranium bio-immobilization in a field experiment where uranium-contaminated groundwater was amended with acetate and bicarbonate. The acetate stimulates indigenous microorganisms that catalyze metal reduction, including the conversion of aqueous U(VI) to solid-phase U(IV), which effectively removes uranium from solution. The initiation of the bicarbonate amendment prior to biostimulation was designed to promote U(VI) desorption that would increase the aqueous U(VI) available for bioreduction. The three-dimensional simulations were able to largely reproduce the timing and magnitude of the physical, chemical and biological responses to the acetate and bicarbonate amendment in the context of changing water table elevation and gradient. A time series of groundwater proteomic samples exhibited correlations between the most abundant Geobacter metallireducens proteins and the genome-scale metabolic model-predicted fluxes of intra-cellular reactions associated with each of those proteins. The desorption of U(VI) induced by the bicarbonate amendment led to initially higher rates of bioreduction compared to locations with minimal bicarbonate exposure. After bicarbonate amendment ceased, bioreduction continued at these locations whereas U(VI) sorption was the dominant removal mechanism at the bicarbonate-impacted sites.

  20. Membrane transporters in a human genome-scale metabolic knowledgebase and their implications for disease

    PubMed Central

    Sahoo, Swagatika; Aurich, Maike K.; Jonsson, Jon J.; Thiele, Ines

    2014-01-01

    Membrane transporters enable efficient cellular metabolism, aid in nutrient sensing, and have been associated with various diseases, such as obesity and cancer. Genome-scale metabolic network reconstructions capture genomic, physiological, and biochemical knowledge of a target organism, along with a detailed representation of the cellular metabolite transport mechanisms. Since the first reconstruction of human metabolism, Recon 1, published in 2007, progress has been made in the field of metabolite transport. Recently, we published an updated reconstruction, Recon 2, which significantly improved the metabolic coverage and functionality. Human metabolic reconstructions have been used to investigate the role of metabolism in disease and to predict biomarkers and drug targets. Given the importance of cellular transport systems in understanding human metabolism in health and disease, we analyzed the coverage of transport systems for various metabolite classes in Recon 2. We will review the current knowledge on transporters (i.e., their preferred substrates, transport mechanisms, metabolic relevance, and disease association for each metabolite class). We will assess missing coverage and propose modifications and additions through a transport module that is functional when combined with Recon 2. This information will be valuable for further refinements. These data will also provide starting points for further experiments by highlighting areas of incomplete knowledge. This review represents the first comprehensive overview of the transporters involved in central metabolism and their transport mechanisms, thus serving as a compendium of metabolite transporters specific for human metabolic reconstructions. PMID:24653705

  1. Metabolic engineering for isoprenoid-based biofuel production.

    PubMed

    Gupta, P; Phulara, S C

    2015-09-01

    Sustainable economic and industrial growth is the need of the hour and it requires renewable energy resources having better performance and compatibility with existing fuel infrastructure from biological routes. Isoprenoids (C ≥ 5) can be a potential alternative due to their diverse nature and physiochemical properties similar to that of petroleum based fuels. In the past decade, extensive research has been done to utilize metabolic engineering strategies in micro-organisms primarily, (i) to overcome the limitations associated with their natural and non-natural production and (ii) to develop commercially competent microbial strain for isoprenoid-based biofuel production. This review briefly describes the engineered isoprenoid biosynthetic pathways in well-characterized microbial systems for the production of several isoprenoid-based biofuels and fuel precursors. PMID:26095690

  2. Metabolic engineering strategies for improving xylitol production from hemicellulosic sugars.

    PubMed

    Su, Buli; Wu, Mianbin; Lin, Jianping; Yang, Lirong

    2013-11-01

    Xylitol is a five-carbon sugar alcohol with potential for use as a sweetener. Industrially, xylitol is currently produced by chemical hydrogenation of D-xylose using Raney nickel catalysts and this requires expensive separation and purification steps as well as high pressure and temperature that lead to environmental pollution. Highly efficient biotechnological production of xylitol using microorganisms is gaining more attention and has been proposed as an alternative process. Although the biotechnological method has not yet surpassed the advantages of chemical reduction in terms of yield and cost, various strategies offer promise for the biotechnological production of xylitol. In this review, the focus is on the most recent developments of the main metabolic engineering strategies for improving the production of xylitol. PMID:23881318

  3. Genome-scale reconstruction of the metabolic network in Yersinia pestis CO92

    NASA Astrophysics Data System (ADS)

    Navid, Ali; Almaas, Eivind

    2007-03-01

    The gram-negative bacterium Yersinia pestis is the causative agent of bubonic plague. Using publicly available genomic, biochemical and physiological data, we have developed a constraint-based flux balance model of metabolism in the CO92 strain (biovar Orientalis) of this organism. The metabolic reactions were appropriately compartmentalized, and the model accounts for the exchange of metabolites, as well as the import of nutrients and export of waste products. We have characterized the metabolic capabilities and phenotypes of this organism, after comparing the model predictions with available experimental observations to evaluate accuracy and completeness. We have also begun preliminary studies into how cellular metabolism affects virulence.

  4. Size matters: plasticity in metabolic scaling shows body-size may modulate responses to climate change.

    PubMed

    Carey, Nicholas; Sigwart, Julia D

    2014-08-01

    Variability in metabolic scaling in animals, the relationship between metabolic rate ( R: ) and body mass ( M: ), has been a source of debate and controversy for decades. R: is proportional to MB: , the precise value of B: much debated, but historically considered equal in all organisms. Recent metabolic theory, however, predicts B: to vary among species with ecology and metabolic level, and may also vary within species under different abiotic conditions. Under climate change, most species will experience increased temperatures, and marine organisms will experience the additional stressor of decreased seawater pH ('ocean acidification'). Responses to these environmental changes are modulated by myriad species-specific factors. Body-size is a fundamental biological parameter, but its modulating role is relatively unexplored. Here, we show that changes to metabolic scaling reveal asymmetric responses to stressors across body-size ranges; B: is systematically decreased under increasing temperature in three grazing molluscs, indicating smaller individuals were more responsive to warming. Larger individuals were, however, more responsive to reduced seawater pH in low temperatures. These alterations to the allometry of metabolism highlight abiotic control of metabolic scaling, and indicate that responses to climate warming and ocean acidification may be modulated by body-size. PMID:25122741

  5. Integration and Validation of the Genome-Scale Metabolic Models of Pichia pastoris: A Comprehensive Update of Protein Glycosylation Pathways, Lipid and Energy Metabolism

    PubMed Central

    Tomàs-Gamisans, Màrius; Ferrer, Pau; Albiol, Joan

    2016-01-01

    Motivation Genome-scale metabolic models (GEMs) are tools that allow predicting a phenotype from a genotype under certain environmental conditions. GEMs have been developed in the last ten years for a broad range of organisms, and are used for multiple purposes such as discovering new properties of metabolic networks, predicting new targets for metabolic engineering, as well as optimizing the cultivation conditions for biochemicals or recombinant protein production. Pichia pastoris is one of the most widely used organisms for heterologous protein expression. There are different GEMs for this methylotrophic yeast of which the most relevant and complete in the published literature are iPP668, PpaMBEL1254 and iLC915. However, these three models differ regarding certain pathways, terminology for metabolites and reactions and annotations. Moreover, GEMs for some species are typically built based on the reconstructed models of related model organisms. In these cases, some organism-specific pathways could be missing or misrepresented. Results In order to provide an updated and more comprehensive GEM for P. pastoris, we have reconstructed and validated a consensus model integrating and merging all three existing models. In this step a comprehensive review and integration of the metabolic pathways included in each one of these three versions was performed. In addition, the resulting iMT1026 model includes a new description of some metabolic processes. Particularly new information described in recently published literature is included, mainly related to fatty acid and sphingolipid metabolism, glycosylation and cell energetics. Finally the reconstructed model was tested and validated, by comparing the results of the simulations with available empirical physiological datasets results obtained from a wide range of experimental conditions, such as different carbon sources, distinct oxygen availability conditions, as well as producing of two different recombinant proteins. In

  6. A genome-scale metabolic reconstruction of Pseudomonas putida KT2440: iJN746 as a cell factory

    PubMed Central

    Nogales, Juan; Palsson, Bernhard Ø; Thiele, Ines

    2008-01-01

    Background Pseudomonas putida is the best studied pollutant degradative bacteria and is harnessed by industrial biotechnology to synthesize fine chemicals. Since the publication of P. putida KT2440's genome, some in silico analyses of its metabolic and biotechnology capacities have been published. However, global understanding of the capabilities of P. putida KT2440 requires the construction of a metabolic model that enables the integration of classical experimental data along with genomic and high-throughput data. The constraint-based reconstruction and analysis (COBRA) approach has been successfully used to build and analyze in silico genome-scale metabolic reconstructions. Results We present a genome-scale reconstruction of P. putida KT2440's metabolism, iJN746, which was constructed based on genomic, biochemical, and physiological information. This manually-curated reconstruction accounts for 746 genes, 950 reactions, and 911 metabolites. iJN746 captures biotechnologically relevant pathways, including polyhydroxyalkanoate synthesis and catabolic pathways of aromatic compounds (e.g., toluene, benzoate, phenylacetate, nicotinate), not described in other metabolic reconstructions or biochemical databases. The predictive potential of iJN746 was validated using experimental data including growth performance and gene deletion studies. Furthermore, in silico growth on toluene was found to be oxygen-limited, suggesting the existence of oxygen-efficient pathways not yet annotated in P. putida's genome. Moreover, we evaluated the production efficiency of polyhydroxyalkanoates from various carbon sources and found fatty acids as the most prominent candidates, as expected. Conclusion Here we presented the first genome-scale reconstruction of P. putida, a biotechnologically interesting all-surrounder. Taken together, this work illustrates the utility of iJN746 as i) a knowledge-base, ii) a discovery tool, and iii) an engineering platform to explore P. putida's potential in

  7. Highly selective production of succinic acid by metabolically engineered Mannheimia succiniciproducens and its efficient purification.

    PubMed

    Choi, Sol; Song, Hyohak; Lim, Sung Won; Kim, Tae Yong; Ahn, Jung Ho; Lee, Jeong Wook; Lee, Moon-Hee; Lee, Sang Yup

    2016-10-01

    Succinic acid (SA) is one of the fermentative products of anaerobic metabolism, and an important industrial chemical that has been much studied for its bio-based production. The key to the economically viable bio-based SA production is to develop an SA producer capable of producing SA with high yield and productivity without byproducts. Mannheimia succiniciproducens is a capnophilic rumen bacterium capable of efficiently producing SA. In this study, in silico genome-scale metabolic simulations were performed to identify gene targets to be engineered, and the PALK strain (ΔldhA and Δpta-ackA) was constructed. Fed-batch culture of PALK on glucose and glycerol as carbon sources resulted in the production of 66.14 g/L of SA with the yield and overall productivity of 1.34 mol/mol glucose equivalent and 3.39 g/L/h, respectively. SA production could be further increased to 90.68 g/L with the yield and overall productivity of 1.15 mol/mol glucose equivalent and 3.49 g/L/h, respectively, by utilizing a mixture of magnesium hydroxide and ammonia solution as a pH controlling solution. Furthermore, formation of byproducts was drastically reduced, resulting in almost homo-fermentative SA production. This allowed the recovery and purification of SA to a high purity (99.997%) with a high recovery yield (74.65%) through simple downstream processes composed of decolorization, vacuum distillation, and crystallization. The SA producer and processes developed in this study will allow economical production of SA in an industrial-scale. Biotechnol. Bioeng. 2016;113: 2168-2177. © 2016 Wiley Periodicals, Inc. PMID:27070659

  8. A protocol for generating a high-quality genome-scale metabolic reconstruction

    PubMed Central

    Thiele, Ines; Palsson, Bernhard Ø.

    2011-01-01

    Network reconstructions are a common denominator in systems biology. Bottom-up metabolic network reconstructions have developed over the past 10 years. These reconstructions represent structured knowledge-bases that abstract pertinent information on the biochemical transformations taking place within specific target organisms. The conversion of a reconstruction into a mathematical format facilitates myriad computational biological studies including evaluation of network content, hypothesis testing and generation, analysis of phenotypic characteristics, and metabolic engineering. To date, genome-scale metabolic reconstructions for more than 30 organisms have been published and this number is expected to increase rapidly. However, these reconstructions differ in quality and coverage that may minimize their predictive potential and use as knowledge-bases. Here, we present a comprehensive protocol describing each step necessary to build a high-quality genome-scale metabolic reconstruction as well as common trials and tribulations. Therefore, this protocol provides a helpful manual for all stages of the reconstruction process. PMID:20057383

  9. A Systems Approach to Predict Oncometabolites via Context-Specific Genome-Scale Metabolic Networks

    PubMed Central

    Nam, Hojung; Campodonico, Miguel; Bordbar, Aarash; Hyduke, Daniel R.; Kim, Sangwoo; Zielinski, Daniel C.; Palsson, Bernhard O.

    2014-01-01

    Altered metabolism in cancer cells has been viewed as a passive response required for a malignant transformation. However, this view has changed through the recently described metabolic oncogenic factors: mutated isocitrate dehydrogenases (IDH), succinate dehydrogenase (SDH), and fumarate hydratase (FH) that produce oncometabolites that competitively inhibit epigenetic regulation. In this study, we demonstrate in silico predictions of oncometabolites that have the potential to dysregulate epigenetic controls in nine types of cancer by incorporating massive scale genetic mutation information (collected from more than 1,700 cancer genomes), expression profiling data, and deploying Recon 2 to reconstruct context-specific genome-scale metabolic models. Our analysis predicted 15 compounds and 24 substructures of potential oncometabolites that could result from the loss-of-function and gain-of-function mutations of metabolic enzymes, respectively. These results suggest a substantial potential for discovering unidentified oncometabolites in various forms of cancers. PMID:25232952

  10. Slow swimming, fast strikes: effects of feeding behavior on scaling of anaerobic metabolism in epipelagic squid.

    PubMed

    Trueblood, Lloyd A; Seibel, Brad A

    2014-08-01

    Many pelagic fishes engage prey at high speeds supported by high metabolic rates and anaerobic metabolic capacity. Epipelagic squids are reported to have among the highest metabolic rates in the oceans as a result of demanding foraging strategies and the use of jet propulsion, which is inherently inefficient. This study examined enzymatic proxies of anaerobic metabolism in two species of pelagic squid, Dosidicus gigas and Doryteuthis pealeii (Lesueur 1821), over a size range of six orders of magnitude. We hypothesized that activity of the anaerobically poised enzymes would be high and increase with size as in ecologically similar fishes. In contrast, we demonstrate that anaerobic metabolic capacity in these organisms scales negatively with body mass. We explored several cephalopod-specific traits, such as the use of tentacles to capture prey, body morphology and reduced relative prey size of adult squids, that may create a diminished reliance on anaerobically fueled burst activity during prey capture in large animals. PMID:25079893

  11. Metabolic engineering of Saccharomyces cerevisiae for itaconic acid production.

    PubMed

    Blazeck, John; Miller, Jarrett; Pan, Anny; Gengler, Jon; Holden, Clinton; Jamoussi, Mariam; Alper, Hal S

    2014-10-01

    Renewable alternatives for petroleum-derived chemicals are achievable through biosynthetic production. Here, we utilize Saccharomyces cerevisiae to enable the synthesis of itaconic acid, a molecule with diverse applications as a petrochemical replacement. We first optimize pathway expression within S. cerevisiae through the use of a hybrid promoter. Next, we utilize sequential, in silico computational genome-scanning to identify beneficial genetic perturbations that are metabolically distant from the itaconic acid synthesis pathway. In this manner, we successfully identify three non-obvious genetic targets (∆ade3 ∆bna2 ∆tes1) that successively improve itaconic acid titer. We establish that focused manipulations of upstream pathway enzymes (localized refactoring) and enzyme re-localization to both mitochondria and cytosol fail to improve itaconic acid titers. Finally, we establish a higher cell density fermentation that ultimately achieves itaconic acid titer of 168 mg/L, a sevenfold improvement over initial conditions. This work represents an attempt to increase itaconic acid production in yeast and demonstrates the successful utilization of computationally guided genetic manipulation to increase metabolic capacity. PMID:24997118

  12. The components of crop productivity: measuring and modeling plant metabolism

    NASA Technical Reports Server (NTRS)

    Bugbee, B.

    1995-01-01

    Several investigators in the CELSS program have demonstrated that crop plants can be remarkably productive in optimal environments where plants are limited only by incident radiation. Radiation use efficiencies of 0.4 to 0.7 g biomass per mol of incident photons have been measured for crops in several laboratories. Some early published values for radiation use efficiency (1 g mol-1) were inflated due to the effect of side lighting. Sealed chambers are the basic research module for crop studies for space. Such chambers allow the measurement of radiation and CO2 fluxes, thus providing values for three determinants of plant growth: radiation absorption, photosynthetic efficiency (quantum yield), and respiration efficiency (carbon use efficiency). Continuous measurement of each of these parameters over the plant life cycle has provided a blueprint for daily growth rates, and is the basis for modeling crop productivity based on component metabolic processes. Much of what has been interpreted as low photosynthetic efficiency is really the result of reduced leaf expansion and poor radiation absorption. Measurements and models of short-term (minutes to hours) and long-term (days to weeks) plant metabolic rates have enormously improved our understanding of plant environment interactions in ground-based growth chambers and are critical to understanding plant responses to the space environment.

  13. Phenoloxidase production and vanillic acid metabolism by Zygomycetes.

    PubMed

    Seigle-Murandi, F; Guiraud, P; Steiman, R; Benoit-Guyod, J L

    1992-04-01

    The ability of 23 strains of Zygomycetes to produce extracellular phenoloxidases was examined on solid media by using 10 different reagents. The results varied depending on the reagent and indicated that most of the strains were devoid of phenoloxidase activity. The production of inducible phenoloxidases was demonstrated by the Bavendamm reaction. The study of the biotransformation of vanillic acid in synthetic medium indicated that the reaction most often obtained was the reduction of vanillic acid to vanillyl alcohol. Helicostylum piriforme and Rhizopus microsporus var. chinensis completely metabolized vanillic acid while good transformation was obtained with Absidia spinosa, Cunninghamella bainieri, Mucor bacilliformis, Mucor plumbeus, Rhizopus arrhizus, Rhizopus stolonifer, Syncephalastrum racemosum and Zygorhynchus moelleri. Other strains did not degrade or poorly degraded vanillic acid. Decarboxylation and demethoxylation of this compound was independent of the production of phenoloxidases as in the case of white-rot fungi. Other enzymatic systems might be implicated in this phenomenon. PMID:1602986

  14. Bioenergetic scaling: metabolic design and body-size constraints in mammals.

    PubMed

    Dobson, G P; Headrick, J P

    1995-08-01

    The cytosolic phosphorylation ratio ([ATP]/[ADP][P(i)]) in the mammalian heart was found to be inversely related to body mass with an exponent of -0.30 (r = 0.999). This exponent is similar to -0.25 calculated for the mass-specific O2 consumption. The inverse of cytosolic free [ADP], the Gibbs energy of ATP hydrolysis (delta G'ATP), and the efficiency of ATP production (energy captured in forming 3 mol of ATP per cycle along the mitochondrial respiratory chain from NADH to 1/2 O2) were all found to scale with body mass with a negative exponent. On the basis of scaling of the phosphorylation ratio and free cytosolic [ADP], we propose that the myocardium and other tissues of small mammals represent a metabolic system with a higher driving potential (a higher delta G'ATP from the higher [ATP]/[ADP][P(i)]) and a higher kinetic gain [(delta V/Vmax)/delta [ADP

  15. Effect of metabolic inhibitors on growth and carotenoid production in Dunaliella bardawil.

    PubMed

    Mysore Doddaiah, Kavitha; Narayan, Anila; Gokare Aswathanarayana, Ravishankar; Ravi, Sarada

    2013-12-01

    Dunaliella bardawil, a green alga accumulates high amount of β-carotene under stress conditions. This organism has been exploited for β-carotene at industrial scale. In the present work, various metabolic inhibitors like diphenylamine (DPA), nicotine, basta, glyphosate, DCMU [3-(3',4'-dichlophenyl)-1,1-dimethylurea] and caffeine were used in autotrophic medium, to understand their influence on carotenoid biosynthesis. The results indicated that these metabolic inhibitors influenced the production of carotenoids like wise, DPA and basta increased the contents of β-carotene (1.7 fold), glyphosate and DCMU for lutein (2.4 and 2 fold) caffeine for biomass yields (1.1 fold), while nicotine decreased the biomass yield (3.6 fold), β-carotene (2 fold) and lutein (10.5 fold). PMID:24426025

  16. Solar photocatalytic oxidation of recalcitrant natural metabolic by-products of amoxicillin biodegradation.

    PubMed

    Pereira, João H O S; Reis, Ana C; Homem, Vera; Silva, José A; Alves, Arminda; Borges, Maria T; Boaventura, Rui A R; Vilar, Vítor J P; Nunes, Olga C

    2014-11-15

    The contamination of the aquatic environment by non-metabolized and metabolized antibiotic residues has brought the necessity of alternative treatment steps to current water decontamination technologies. This work assessed the feasibility of using a multistage treatment system for amoxicillin (AMX) spiked solutions combining: i) a biological treatment process using an enriched culture to metabolize AMX, with ii) a solar photocatalytic system to achieve the removal of the metabolized transformation products (TPs) identified via LC-MS, recalcitrant to further biological degradation. Firstly, a mixed culture (MC) was obtained through the enrichment of an activated sludge sample collected in an urban wastewater treatment plant (WWTP). Secondly, different aqueous matrices spiked with AMX were treated with the MC and the metabolic transformation products were identified. Thirdly, the efficiency of two solar assisted photocatalytic processes (TiO2/UV or Fe(3+)/Oxalate/H2O2/UV-Vis) was assessed in the degradation of the obtained TPs using a lab-scale prototype photoreactor equipped with a compound parabolic collector (CPC). Highest AMX specific biodegradation rates were obtained in buffer and urban wastewater (WW) media (0.10 ± 0.01 and 0.13 ± 0.07 g(AMX) g(biomass)(-1) h(-1), respectively). The resulting TPs, which no longer presented antibacterial activity, were identified as amoxicilloic acid (m/z = 384). The performance of the Fe(3+)/Oxalate/H2O2/UV-Vis system in the removal of the TPs from WW medium was superior to the TiO2/UV process (TPs no longer detected after 40 min (QUV = 2.6 kJ L(-1)), against incomplete TPs removal after 240 min (QUV = 14.9 kJ L(-1)), respectively). PMID:25150518

  17. Metabolic engineering of itaconate production in Escherichia coli.

    PubMed

    Vuoristo, Kiira S; Mars, Astrid E; Sangra, Jose Vidal; Springer, Jan; Eggink, Gerrit; Sanders, Johan P M; Weusthuis, Ruud A

    2015-01-01

    Interest in sustainable development has led to efforts to replace petrochemical-based monomers with biomass-based ones. Itaconic acid, a C5-dicarboxylic acid, is a potential monomer for the chemical industry with many prospective applications. cis-aconitate decarboxylase (CadA) is the key enzyme of itaconate production, converting the citric acid cycle intermediate cis-aconitate into itaconate. Heterologous expression of cadA from Aspergillus terreus in Escherichia coli resulted in low CadA activities and production of trace amounts of itaconate on Luria-Bertani (LB) medium (<10 mg/L). CadA was primarily present as inclusion bodies, explaining the low activity. The activity was significantly improved by using lower cultivation temperatures and mineral medium, and this resulted in enhanced itaconate titres (240 mg/L). The itaconate titre was further increased by introducing citrate synthase and aconitase from Corynebacterium glutamicum and by deleting the genes encoding phosphate acetyltransferase and lactate dehydrogenase. These deletions in E. coli's central metabolism resulted in the accumulation of pyruvate, which is a precursor for itaconate biosynthesis. As a result, itaconate production in aerobic bioreactor cultures was increased up to 690 mg/L. The maximum yield obtained was 0.09 mol itaconate/mol glucose. Strategies for a further improvement of itaconate production are discussed. PMID:25277412

  18. Metabolic engineering of Yarrowia lipolytica for itaconic acid production.

    PubMed

    Blazeck, John; Hill, Andrew; Jamoussi, Mariam; Pan, Anny; Miller, Jarrett; Alper, Hal S

    2015-11-01

    Itaconic acid is a naturally produced organic acid with diverse applications as a replacement for petroleum derived products. However, its industrial viability as a bio-replacement has been restricted due to limitations with native producers. In this light, Yarrowia lipolytica is an excellent potential candidate for itaconic acid production due to its innate capacity to accumulate citric acid cycle intermediates and tolerance to lower pH. Here, we demonstrate the capacity to produce itaconic acid in Y. lipolytica through heterologous expression of the itaconic acid synthesis enzyme, resulting in an initial titer of 33 mg/L. Further optimizations of this strain via metabolic pathway engineering, enzyme localization, and media optimization strategies enabled 4.6g/L of itaconic acid to be produced in bioreactors, representing a 140-fold improvement over initial titer. Moreover, these fermentation conditions did not require additional nutrient supplementation and utilized a low pH condition that enabled the acid form of itaconic acid to be produced. Overall yields (0.058 g/g yield from glucose) and maximum productivity of 0.045 g/L/h still provide areas for future strain improvement. Nevertheless, this work demonstrates that Y. lipolytica has the potential to serve as an industrially relevant platform for itaconic acid production. PMID:26384571

  19. Metabolic engineering of biocatalysts for carboxylic acids production

    PubMed Central

    Liu, Ping; Jarboe, Laura R.

    2012-01-01

    Fermentation of renewable feedstocks by microbes to produce sustainable fuels and chemicals has the potential to replace petrochemical-based production. For example, carboxylic acids produced by microbial fermentation can be used to generate primary building blocks of industrial chemicals by either enzymatic or chemical catalysis. In order to achieve the titer, yield and productivity values required for economically viable processes, the carboxylic acid-producing microbes need to be robust and well-performing. Traditional strain development methods based on mutagenesis have proven useful in the selection of desirable microbial behavior, such as robustness and carboxylic acid production. On the other hand, rationally-based metabolic engineering, like genetic manipulation for pathway design, has becoming increasingly important to this field and has been used for the production of several organic acids, such as succinic acid, malic acid and lactic acid. This review investigates recent works on Saccharomyces cerevisiae and Escherichia coli, as well as the strategies to improve tolerance towards these chemicals. PMID:24688671

  20. Production of riboflavin by metabolically engineered Corynebacterium ammoniagenes.

    PubMed

    Koizumi, S; Yonetani, Y; Maruyama, A; Teshiba, S

    2000-06-01

    Improved strains for the production of riboflavin (vitamin B2) were constructed through metabolic engineering using recombinant DNA techniques in Corynebacterium ammoniagenes. A C. ammoniagenes strain harboring a plasmid containing its riboflavin biosynthetic genes accumulated 17-fold as much riboflavin as the host strain. In order to increase the expression of the biosynthetic genes, we isolated DNA fragments that had promoter activities in C. ammoniagenes. When the DNA fragment (P54-6) showing the strongest promoter activity in minimum medium was introduced into the upstream region of the riboflavin biosynthetic genes, the accumulation of riboflavin was 3-fold elevated. In that strain, the activity of guanosine 5'-triphosphate (GTP) cyclohydrolase II, the first enzyme in riboflavin biosynthesis, was 2.4-fold elevated whereas that of riboflavin synthase, the last enzyme in the biosynthesis, was 44.1-fold elevated. Changing the sequence containing the putative ribosome-binding sequence of 3,4-dihydroxy-2-butanone 4-phosphate synthase/GTP cyclohydrolase II gene led to higher GTP cyclohydrolase II activity and strong enhancement of riboflavin production. Throughout the strain improvement, the activity of GTP cyclohydrolase II correlated with the productivity of riboflavin. In the highest producer strain, riboflavin was produced at the level of 15.3 g l(-1) for 72 h in a 5-l jar fermentor without any end product inhibition. PMID:10919325

  1. Metabolic engineering of Dunaliella salina for production of ketocarotenoids.

    PubMed

    Anila, N; Simon, Daris P; Chandrashekar, Arun; Ravishankar, G A; Sarada, R

    2016-03-01

    Dunaliella is a commercially important marine alga producing high amount of β-carotene. The use of Dunaliella as a potential transgenic system for the production of recombinant proteins has been recently recognized. The present study reports for the first time the metabolic engineering of carotenoid biosynthesis in Dunaliella salina for ketocarotenoid production. The pathway modification included the introduction of a bkt gene from H. pluvialis encoding β-carotene ketolase (4,4'β-oxygenase) along with chloroplast targeting for the production of ketocarotenoids. The bkt under the control of Dunaliella Rubisco smaller subunit promoter along with its transit peptide sequence was introduced into the alga through standardized Agrobacterium-mediated transformation procedure. The selected transformants were confirmed using GFP and GUS expression, PCR and southern blot analysis. A notable upregulation of the endogenous hydroxylase level of transformants was observed where the BKT expression was higher in nutrient-limiting conditions. Carotenoid analysis of the transformants through HPLC and MS analysis showed the presence of astaxanthin and canthaxanthin with maximum content of 3.5 and 1.9 µg/g DW, respectively. The present study reports the feasibility of using D. salina for the production of ketocarotenoids including astaxanthin. PMID:26334599

  2. High Production of 3-Hydroxypropionic Acid in Klebsiella pneumoniae by Systematic Optimization of Glycerol Metabolism

    PubMed Central

    Li, Ying; Wang, Xi; Ge, Xizhen; Tian, Pingfang

    2016-01-01

    3-Hydroxypropionic acid (3-HP) is an important platform chemical proposed by the United States Department of Energy. 3-HP can be converted to a series of bulk chemicals. Biological production of 3-HP has made great progress in recent years. However, low yield of 3-HP restricts its commercialization. In this study, systematic optimization was conducted towards high-yield production of 3-HP in Klebsiella pneumoniae. We first investigated appropriate promoters for the key enzyme (aldehyde dehydrogenase, ALDH) in 3-HP biosynthesis, and found that IPTG-inducible tac promoter enabled overexpression of an endogenous ALDH (PuuC) in K. pneumoniae. We optimized the metabolic flux and found that blocking the synthesis of lactic acid and acetic acid significantly increased the production of 3-HP. Additionally, fermentation conditions were optimized and scaled-up cultivation were investigated. The highest 3-HP titer was observed at 83.8 g/L with a high conversion ratio of 54% on substrate glycerol. Furthermore, a flux distribution model of glycerol metabolism in K. pneumoniae was proposed based on in silico analysis. To our knowledge, this is the highest 3-HP production in K. pneumoniae. This work has significantly advanced biological production of 3-HP from renewable carbon sources. PMID:27230116

  3. High Production of 3-Hydroxypropionic Acid in Klebsiella pneumoniae by Systematic Optimization of Glycerol Metabolism.

    PubMed

    Li, Ying; Wang, Xi; Ge, Xizhen; Tian, Pingfang

    2016-01-01

    3-Hydroxypropionic acid (3-HP) is an important platform chemical proposed by the United States Department of Energy. 3-HP can be converted to a series of bulk chemicals. Biological production of 3-HP has made great progress in recent years. However, low yield of 3-HP restricts its commercialization. In this study, systematic optimization was conducted towards high-yield production of 3-HP in Klebsiella pneumoniae. We first investigated appropriate promoters for the key enzyme (aldehyde dehydrogenase, ALDH) in 3-HP biosynthesis, and found that IPTG-inducible tac promoter enabled overexpression of an endogenous ALDH (PuuC) in K. pneumoniae. We optimized the metabolic flux and found that blocking the synthesis of lactic acid and acetic acid significantly increased the production of 3-HP. Additionally, fermentation conditions were optimized and scaled-up cultivation were investigated. The highest 3-HP titer was observed at 83.8 g/L with a high conversion ratio of 54% on substrate glycerol. Furthermore, a flux distribution model of glycerol metabolism in K. pneumoniae was proposed based on in silico analysis. To our knowledge, this is the highest 3-HP production in K. pneumoniae. This work has significantly advanced biological production of 3-HP from renewable carbon sources. PMID:27230116

  4. Metabolic engineering of higher plants and algae for isoprenoid production.

    PubMed

    Kempinski, Chase; Jiang, Zuodong; Bell, Stephen; Chappell, Joe

    2015-01-01

    Isoprenoids are a class of compounds derived from the five carbon precursors, dimethylallyl diphosphate, and isopentenyl diphosphate. These molecules present incredible natural chemical diversity, which can be valuable for humans in many aspects such as cosmetics, agriculture, and medicine. However, many terpenoids are only produced in small quantities by their natural hosts and can be difficult to generate synthetically. Therefore, much interest and effort has been directed toward capturing the genetic blueprint for their biochemistry and engineering it into alternative hosts such as plants and algae. These autotrophic organisms are attractive when compared to traditional microbial platforms because of their ability to utilize atmospheric CO2 as a carbon substrate instead of supplied carbon sources like glucose. This chapter will summarize important techniques and strategies for engineering the accumulation of isoprenoid metabolites into higher plants and algae by choosing the correct host, avoiding endogenous regulatory mechanisms, and optimizing potential flux into the target compound. Future endeavors will build on these efforts by fine-tuning product accumulation levels via the vast amount of available "-omic" data and devising metabolic engineering schemes that integrate this into a whole-organism approach. With the development of high-throughput transformation protocols and synthetic biology molecular tools, we have only begun to harness the power and utility of plant and algae metabolic engineering. PMID:25636485

  5. Multiscale Metabolic Modeling of C4 Plants: Connecting Nonlinear Genome-Scale Models to Leaf-Scale Metabolism in Developing Maize Leaves

    PubMed Central

    Bogart, Eli; Myers, Christopher R.

    2016-01-01

    C4 plants, such as maize, concentrate carbon dioxide in a specialized compartment surrounding the veins of their leaves to improve the efficiency of carbon dioxide assimilation. Nonlinear relationships between carbon dioxide and oxygen levels and reaction rates are key to their physiology but cannot be handled with standard techniques of constraint-based metabolic modeling. We demonstrate that incorporating these relationships as constraints on reaction rates and solving the resulting nonlinear optimization problem yields realistic predictions of the response of C4 systems to environmental and biochemical perturbations. Using a new genome-scale reconstruction of maize metabolism, we build an 18000-reaction, nonlinearly constrained model describing mesophyll and bundle sheath cells in 15 segments of the developing maize leaf, interacting via metabolite exchange, and use RNA-seq and enzyme activity measurements to predict spatial variation in metabolic state by a novel method that optimizes correlation between fluxes and expression data. Though such correlations are known to be weak in general, we suggest that developmental gradients may be particularly suited to the inference of metabolic fluxes from expression data, and we demonstrate that our method predicts fluxes that achieve high correlation with the data, successfully capture the experimentally observed base-to-tip transition between carbon-importing tissue and carbon-exporting tissue, and include a nonzero growth rate, in contrast to prior results from similar methods in other systems. PMID:26990967

  6. Metabolic engineering of Escherichia coli for the production of riboflavin

    PubMed Central

    2014-01-01

    Background Riboflavin (vitamin B2), the precursor of the flavin cofactors flavin mononucleotide (FMN) and flavin adenine dinucleotide (FAD), is used commercially as an animal feed supplement and food colorant. E. coli is a robust host for various genetic manipulations and has been employed for efficient production of biofuels, polymers, amino acids, and bulk chemicals. Thus, the aim of this study was to understand the metabolic capacity of E. coli for the riboflavin production by modification of central metabolism, riboflavin biosynthesis pathway and optimization of the fermentation conditions. Results The basic producer RF01S, in which the riboflavin biosynthesis genes ribABDEC from E. coli were overexpressed under the control of the inducible trc promoter, could accumulate 229.1 mg/L of riboflavin. Further engineering was performed by examining the impact of expression of zwf (encodes glucose 6-phosphate dehydrogenase) and gnd (encodes 6-phosphogluconate dehydrogenase) from Corynebacterium glutamicum and pgl (encodes 6-phosphogluconolactonase) from E. coli on riboflavin production. Deleting pgi (encodes glucose-6-phosphate isomerase) and genes of Entner-Doudoroff (ED) pathway successfully redirected the carbon flux into the oxidative pentose phosphate pathway, and overexpressing the acs (encodes acetyl-CoA synthetase) reduced the acetate accumulation. These modifications increased riboflavin production to 585.2 mg/L. By further modulating the expression of ribF (encodes riboflavin kinase) for reducing the conversion of riboflavin to FMN in RF05S, the final engineering strain RF05S-M40 could produce 1036.1 mg/L riboflavin in LB medium at 37°C. After optimizing the fermentation conditions, strain RF05S-M40 produced 2702.8 mg/L riboflavin in the optimized semi-defined medium, which was a value nearly 12-fold higher than that of RF01S, with a yield of 137.5 mg riboflavin/g glucose. Conclusions The engineered strain RF05S-M40 has the highest yield among all

  7. Precursors and metabolic pathway for guaiacol production by Alicyclobacillus acidoterrestris.

    PubMed

    Cai, Rui; Yuan, Yahong; Wang, Zhouli; Guo, Chunfeng; Liu, Bin; Liu, Laping; Wang, Yutang; Yue, Tianli

    2015-12-01

    Alicyclobacillus acidoterrestris has recently received much attention due to its implication in the spoilage of pasteurized fruit juices, which was manifested by the production of guaiacol. Vanillic acid and vanillin have been accepted as the biochemical precursors of guaiacol in fruit juices. The purpose of this study was to try to find other precursors and elucidate details about the conversion of vanillic acid and vanillin to guaiacol by A. acidoterrestris. Four potential substrates including ferulic acid, catechol, phenylalanine and tyrosine were analyzed, but they could not be metabolized to guaiacol by all the thirty A. acidoterrestris strains tested. Resting cell studies and enzyme assays demonstrated that vanillin was reduced to vanillyl alcohol by NADPH-dependent vanillin reductase and oxidized to vanillic acid by NAD(P)(+)-dependent vanillin dehydrogenases in A. acidoterrestris DSM 3923. Vanillic acid underwent a nonoxidative decarboxylation to guaiacol. The reversible vanillic acid decarboxylase involved was oxygen insensitive and pyridine nucleotide-independent. PMID:26241489

  8. Both respiration and photosynthesis determine the scaling of plankton metabolism in the oligotrophic ocean

    PubMed Central

    Serret, Pablo; Robinson, Carol; Aranguren-Gassis, María; García-Martín, Enma Elena; Gist, Niki; Kitidis, Vassilis; Lozano, José; Stephens, John; Harris, Carolyn; Thomas, Rob

    2015-01-01

    Despite its importance to ocean–climate interactions, the metabolic state of the oligotrophic ocean has remained controversial for >15 years. Positions in the debate are that it is either hetero- or autotrophic, which suggests either substantial unaccounted for organic matter inputs, or that all available photosynthesis (P) estimations (including 14C) are biased. Here we show the existence of systematic differences in the metabolic state of the North (heterotrophic) and South (autotrophic) Atlantic oligotrophic gyres, resulting from differences in both P and respiration (R). The oligotrophic ocean is neither auto- nor heterotrophic, but functionally diverse. Our results show that the scaling of plankton metabolism by generalized P:R relationships that has sustained the debate is biased, and indicate that the variability of R, and not only of P, needs to be considered in regional estimations of the ocean's metabolic state. PMID:25908109

  9. Metabolic engineering of Corynebacterium glutamicum for the production of itaconate.

    PubMed

    Otten, Andreas; Brocker, Melanie; Bott, Michael

    2015-07-01

    The capability of Corynebacterium glutamicum for glucose-based synthesis of itaconate was explored, which can serve as building block for production of polymers, chemicals, and fuels. C. glutamicum was highly tolerant to itaconate and did not metabolize it. Expression of the Aspergillus terreus CAD1 gene encoding cis-aconitate decarboxylase (CAD) in strain ATCC13032 led to the production of 1.4mM itaconate in the stationary growth phase. Fusion of CAD with the Escherichia coli maltose-binding protein increased its activity and the itaconate titer more than two-fold. Nitrogen-limited growth conditions boosted CAD activity and itaconate titer about 10-fold to values of 1440 mU mg(-1) and 30 mM. Reduction of isocitrate dehydrogenase activity via exchange of the ATG start codon to GTG or TTG resulted in maximal itaconate titers of 60 mM (7.8 g l(-1)), a molar yield of 0.4 mol mol(-1), and a volumetric productivity of 2.1 mmol l(-1) h(-1). PMID:26100077

  10. Metabolic scaling theory in plant biology and the three oxygen paradoxa of aerobic life.

    PubMed

    Kutschera, Ulrich; Niklas, Karl J

    2013-12-01

    Alfred Russell Wallace was a field naturalist with a strong interest in general physiology. In this vein, he wrote that oxygen (O2), produced by green plants, is "the food of protoplasm, without which it cannot continue to live". Here we summarize current models relating body size to respiration rates (in the context of the metabolic scaling theory) and show that oxygen-uptake activities, measured at 21 vol.% O2, correlate closely with growth patterns at the level of specific organs within the same plant. Thus, whole plant respiration can change ontogenetically, corresponding to alterations in the volume fractions of different tissues. Then, we describe the evolution of cyanobacterial photosynthesis during the Paleoarchean, which changed the world forever. By slowly converting what was once a reducing atmosphere to an oxidizing one, microbes capable of O2-producing photosynthesis modified the chemical nature and distribution of the element iron (Fe), slowly drove some of the most ancient prokaryotes to extinction, created the ozone (O3) layer that subsequently shielded the first terrestrial plants and animals from harmful UV radiation, but also made it possible for Earth's forest to burn, sometimes with catastrophic consequences. Yet another paradox is that the most abundant protein (i.e., the enzyme Rubisco, Ribulose-1,5-biphosphate carboxylase/oxygenase) has a greater affinity for oxygen than for carbon dioxide (CO2), even though its function is to bind with the latter rather than the former. We evaluate this second "oxygen paradox" within the context of photorespiratory carbon loss and crop yield reduction in C3 vs. C4 plants (rye vs. maize). Finally, we analyze the occurrence of reactive oxygen species (ROS) as destructive by-products of cellular metabolism, and discuss the three "O2-paradoxa" with reference to A. R. Wallace's speculations on "design in nature". PMID:23982798

  11. Thermoneutral zone and scaling of metabolic rate on body mass in small mammals

    NASA Technical Reports Server (NTRS)

    Pace, N.; Rahlmann, D. F.

    1983-01-01

    A 4-species animal model suitable for experimental study of the effect of change in gravitational loading on the scale relationship between metabolic rate and total body mass is used to study the effect of temperature on metabolic rate in six male animals, 8-10 months of age, of each of the four species in the ambient temperature range 20-36 C. The measurements taken permitted partitioning of total body heat output into sensible heat loss by radiation, conduction and convection, and into latent heat loss by evaporation of water from the body surface. It is shown that the condition of thermoneutrality is important for metabolic scale effect studies, and that the thermoneutral zone for the species considered here is a narrow one.

  12. Little left in the tank: metabolic scaling in marine teleosts and its implications for aerobic scope

    PubMed Central

    Killen, Shaun S; Costa, Isabel; Brown, Joseph A; Gamperl, A. Kurt

    2006-01-01

    Fish larvae are the world's smallest vertebrates, and their high rates of mortality may be partially owing to a very limited aerobic scope. Unfortunately, however, no complete empirical dataset exists on the relationship between minimal and maximal metabolism (and thus aerobic scope) for any fish species throughout ontogeny, and thus such an association is hard to delineate. We measured standard and maximal metabolism in three marine fish species over their entire life history, and show that while aerobic scope depends greatly on body size and developmental trajectory, it is extremely small during the early life stages (factorial aerobic scope≤1.5). Our findings strongly suggest that limited scope for aerobic activity early in life is likely to constrain physiological function and ultimately impact behaviour and possibly survival. Furthermore, our results have important implications for ecological models that incorporate metabolic scaling, and provide additional evidence against the existence of ‘universal’ scaling exponents. PMID:17164208

  13. Generation of 2,000 breast cancer metabolic landscapes reveals a poor prognosis group with active serotonin production

    PubMed Central

    Leoncikas, Vytautas; Wu, Huihai; Ward, Lara T.; Kierzek, Andrzej M.; Plant, Nick J.

    2016-01-01

    A major roadblock in the effective treatment of cancers is their heterogeneity, whereby multiple molecular landscapes are classified as a single disease. To explore the contribution of cellular metabolism to cancer heterogeneity, we analyse the Metabric dataset, a landmark genomic and transcriptomic study of 2,000 individual breast tumours, in the context of the human genome-scale metabolic network. We create personalized metabolic landscapes for each tumour by exploring sets of active reactions that satisfy constraints derived from human biochemistry and maximize congruency with the Metabric transcriptome data. Classification of the personalized landscapes derived from 997 tumour samples within the Metabric discovery dataset reveals a novel poor prognosis cluster, reproducible in the 995-sample validation dataset. We experimentally follow mechanistic hypotheses resulting from the computational study and establish that active serotonin production is a major metabolic feature of the poor prognosis group. These data support the reconsideration of concomitant serotonin-specific uptake inhibitors treatment during breast cancer chemotherapy. PMID:26813959

  14. Improved evidence-based genome-scale metabolic models for maize leaf, embryo, and endosperm

    DOE PAGESBeta

    Seaver, Samuel M.D.; Bradbury, Louis M.T.; Frelin, Océane; Zarecki, Raphy; Ruppin, Eytan; Hanson, Andrew D.; Henry, Christopher S.

    2015-03-10

    There is a growing demand for genome-scale metabolic reconstructions for plants, fueled by the need to understand the metabolic basis of crop yield and by progress in genome and transcriptome sequencing. Methods are also required to enable the interpretation of plant transcriptome data to study how cellular metabolic activity varies under different growth conditions or even within different organs, tissues, and developmental stages. Such methods depend extensively on the accuracy with which genes have been mapped to the biochemical reactions in the plant metabolic pathways. Errors in these mappings lead to metabolic reconstructions with an inflated number of reactions andmore » possible generation of unreliable metabolic phenotype predictions. Here we introduce a new evidence-based genome-scale metabolic reconstruction of maize, with significant improvements in the quality of the gene-reaction associations included within our model. We also present a new approach for applying our model to predict active metabolic genes based on transcriptome data. This method includes a minimal set of reactions associated with low expression genes to enable activity of a maximum number of reactions associated with high expression genes. We apply this method to construct an organ-specific model for the maize leaf, and tissue specific models for maize embryo and endosperm cells. We validate our models using fluxomics data for the endosperm and embryo, demonstrating an improved capacity of our models to fit the available fluxomics data. All models are publicly available via the DOE Systems Biology Knowledgebase and PlantSEED, and our new method is generally applicable for analysis transcript profiles from any plant, paving the way for further in silico studies with a wide variety of plant genomes.« less

  15. Improved evidence-based genome-scale metabolic models for maize leaf, embryo, and endosperm

    SciTech Connect

    Seaver, Samuel M.D.; Bradbury, Louis M.T.; Frelin, Océane; Zarecki, Raphy; Ruppin, Eytan; Hanson, Andrew D.; Henry, Christopher S.

    2015-03-10

    There is a growing demand for genome-scale metabolic reconstructions for plants, fueled by the need to understand the metabolic basis of crop yield and by progress in genome and transcriptome sequencing. Methods are also required to enable the interpretation of plant transcriptome data to study how cellular metabolic activity varies under different growth conditions or even within different organs, tissues, and developmental stages. Such methods depend extensively on the accuracy with which genes have been mapped to the biochemical reactions in the plant metabolic pathways. Errors in these mappings lead to metabolic reconstructions with an inflated number of reactions and possible generation of unreliable metabolic phenotype predictions. Here we introduce a new evidence-based genome-scale metabolic reconstruction of maize, with significant improvements in the quality of the gene-reaction associations included within our model. We also present a new approach for applying our model to predict active metabolic genes based on transcriptome data. This method includes a minimal set of reactions associated with low expression genes to enable activity of a maximum number of reactions associated with high expression genes. We apply this method to construct an organ-specific model for the maize leaf, and tissue specific models for maize embryo and endosperm cells. We validate our models using fluxomics data for the endosperm and embryo, demonstrating an improved capacity of our models to fit the available fluxomics data. All models are publicly available via the DOE Systems Biology Knowledgebase and PlantSEED, and our new method is generally applicable for analysis transcript profiles from any plant, paving the way for further in silico studies with a wide variety of plant genomes.

  16. Improved evidence-based genome-scale metabolic models for maize leaf, embryo, and endosperm

    PubMed Central

    Seaver, Samuel M. D.; Bradbury, Louis M. T.; Frelin, Océane; Zarecki, Raphy; Ruppin, Eytan; Hanson, Andrew D.; Henry, Christopher S.

    2015-01-01

    There is a growing demand for genome-scale metabolic reconstructions for plants, fueled by the need to understand the metabolic basis of crop yield and by progress in genome and transcriptome sequencing. Methods are also required to enable the interpretation of plant transcriptome data to study how cellular metabolic activity varies under different growth conditions or even within different organs, tissues, and developmental stages. Such methods depend extensively on the accuracy with which genes have been mapped to the biochemical reactions in the plant metabolic pathways. Errors in these mappings lead to metabolic reconstructions with an inflated number of reactions and possible generation of unreliable metabolic phenotype predictions. Here we introduce a new evidence-based genome-scale metabolic reconstruction of maize, with significant improvements in the quality of the gene-reaction associations included within our model. We also present a new approach for applying our model to predict active metabolic genes based on transcriptome data. This method includes a minimal set of reactions associated with low expression genes to enable activity of a maximum number of reactions associated with high expression genes. We apply this method to construct an organ-specific model for the maize leaf, and tissue specific models for maize embryo and endosperm cells. We validate our models using fluxomics data for the endosperm and embryo, demonstrating an improved capacity of our models to fit the available fluxomics data. All models are publicly available via the DOE Systems Biology Knowledgebase and PlantSEED, and our new method is generally applicable for analysis transcript profiles from any plant, paving the way for further in silico studies with a wide variety of plant genomes. PMID:25806041

  17. Pore-scale simulation of microbial growth using a genome-scale metabolic model: Implications for Darcy-scale reactive transport

    SciTech Connect

    Tartakovsky, Guzel D.; Tartakovsky, Alexandre M.; Scheibe, Timothy D.; Fang, Yilin; Mahadevan, Radhakrishnan; Lovley, Derek R.

    2013-09-07

    Recent advances in microbiology have enabled the quantitative simulation of microbial metabolism and growth based on genome-scale characterization of metabolic pathways and fluxes. We have incorporated a genome-scale metabolic model of the iron-reducing bacteria Geobacter sulfurreducens into a pore-scale simulation of microbial growth based on coupling of iron reduction to oxidation of a soluble electron donor (acetate). In our model, fluid flow and solute transport is governed by a combination of the Navier-Stokes and advection-diffusion-reaction equations. Microbial growth occurs only on the surface of soil grains where solid-phase mineral iron oxides are available. Mass fluxes of chemical species associated with microbial growth are described by the genome-scale microbial model, implemented using a constraint-based metabolic model, and provide the Robin-type boundary condition for the advection-diffusion equation at soil grain surfaces. Conventional models of microbially-mediated subsurface reactions use a lumped reaction model that does not consider individual microbial reaction pathways, and describe reactions rates using empirically-derived rate formulations such as the Monod-type kinetics. We have used our pore-scale model to explore the relationship between genome-scale metabolic models and Monod-type formulations, and to assess the manifestation of pore-scale variability (microenvironments) in terms of apparent Darcy-scale microbial reaction rates. The genome-scale model predicted lower biomass yield, and different stoichiometry for iron consumption, in comparisonto prior Monod formulations based on energetics considerations. We were able to fit an equivalent Monod model, by modifying the reaction stoichiometry and biomass yield coefficient, that could effectively match results of the genome-scale simulation of microbial behaviors under excess nutrient conditions, but predictions of the fitted Monod model deviated from those of the genome-scale model under

  18. Pore-scale simulation of microbial growth using a genome-scale metabolic model: Implications for Darcy-scale reactive transport

    NASA Astrophysics Data System (ADS)

    Scheibe, T. D.; Tartakovsky, G.; Tartakovsky, A. M.; Fang, Y.; Mahadevan, R.; Lovley, D. R.

    2012-12-01

    Recent advances in microbiology have enabled the quantitative simulation of microbial metabolism and growth based on genome-scale characterization of metabolic pathways and fluxes. We have incorporated a genome-scale metabolic model of the iron-reducing bacteria Geobacter sulfurreducens into a pore-scale simulation of microbial growth based on coupling of iron reduction to oxidation of a soluble electron donor (acetate). In our model, fluid flow and solute transport is governed by a combination of the Navier-Stokes and advection-diffusion-reaction equations. Microbial growth occurs only on the surface of soil grains where solid-phase mineral iron oxides are available. Mass fluxes of chemical species associated with microbial growth are described by the genome-scale microbial model, implemented using a constraint-based metabolic model, and provide the Robin-type boundary condition for the advection-diffusion equation at soil grain surfaces. Conventional models of microbially-mediated subsurface reactions use a lumped reaction model that does not consider individual microbial reaction pathways, and describe reactions rates using empirically-derived rate formulations such as the Monod-type kinetics. We have used our pore-scale model to explore the relationship between genome-scale metabolic models and Monod-type formulations, and to assess the manifestation of pore-scale variability (microenvironments) in terms of apparent Darcy-scale microbial reaction rates. The genome-scale model predicted lower biomass yield, and different stoichiometry for iron consumption, in comparison to prior Monod formulations based on energetics considerations. We were able to fit an equivalent Monod model, by modifying the reaction stoichiometry and biomass yield coefficient, that could effectively match results of the genome-scale simulation of microbial behaviors under excess nutrient conditions, but predictions of the fitted Monod model deviated from those of the genome-scale model

  19. Response of white peach scale to metabolic stress disinfection and disinfestation (MSDD) treatment

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Metabolic stress disinfection and disinfestation (MSDD) is a postharvest treatment that combines short periods of low pressure (vacuum) and high CO2 with ethanol vapor to control pathogens and arthropod pests on commodities. The system was tested against white peach scale, Pseudaulacaspis pentagona ...

  20. Consistency Analysis of Genome-Scale Models of Bacterial Metabolism: A Metamodel Approach

    PubMed Central

    Ponce-de-Leon, Miguel; Calle-Espinosa, Jorge; Peretó, Juli; Montero, Francisco

    2015-01-01

    Genome-scale metabolic models usually contain inconsistencies that manifest as blocked reactions and gap metabolites. With the purpose to detect recurrent inconsistencies in metabolic models, a large-scale analysis was performed using a previously published dataset of 130 genome-scale models. The results showed that a large number of reactions (~22%) are blocked in all the models where they are present. To unravel the nature of such inconsistencies a metamodel was construed by joining the 130 models in a single network. This metamodel was manually curated using the unconnected modules approach, and then, it was used as a reference network to perform a gap-filling on each individual genome-scale model. Finally, a set of 36 models that had not been considered during the construction of the metamodel was used, as a proof of concept, to extend the metamodel with new biochemical information, and to assess its impact on gap-filling results. The analysis performed on the metamodel allowed to conclude: 1) the recurrent inconsistencies found in the models were already present in the metabolic database used during the reconstructions process; 2) the presence of inconsistencies in a metabolic database can be propagated to the reconstructed models; 3) there are reactions not manifested as blocked which are active as a consequence of some classes of artifacts, and; 4) the results of an automatic gap-filling are highly dependent on the consistency and completeness of the metamodel or metabolic database used as the reference network. In conclusion the consistency analysis should be applied to metabolic databases in order to detect and fill gaps as well as to detect and remove artifacts and redundant information. PMID:26629901

  1. Critical time scale of coarse-graining entropy production

    NASA Astrophysics Data System (ADS)

    Sohn, Jang-il

    2016-04-01

    We study coarse-grained entropy production in an asymmetric random walk system on a periodic one-dimensional lattice. In coarse-grained systems, the original dynamics are unavoidably destroyed, but the coarse-grained entropy production is not hidden below the critical time-scale separation. The hidden entropy production is rapidly increasing near the critical time-scale separation.

  2. Metabolic Engineering and Modeling of Metabolic Pathways to Improve Hydrogen Production by Photosynthetic Bacteria

    SciTech Connect

    Jiao, Y.; Navid, A.

    2014-12-19

    traits act as the biocatalysts of the process designed to both enhance the system efficiency of CO2 fixation and the net hydrogen production rate. Additionally we applied metabolic engineering approaches guided by computational modeling for the chosen model microorganisms to enable efficient hydrogen production.

  3. Synechocystis sp. PCC6803 metabolic models for the enhanced production of hydrogen.

    PubMed

    Montagud, Arnau; Gamermann, Daniel; Fernández de Córdoba, Pedro; Urchueguía, Javier F

    2015-06-01

    In the present economy, difficulties to access energy sources are real drawbacks to maintain our current lifestyle. In fact, increasing interests have been gathered around efficient strategies to use energy sources that do not generate high CO2 titers. Thus, science-funding agencies have invested more resources into research on hydrogen among other biofuels as interesting energy vectors. This article reviews present energy challenges and frames it into the present fuel usage landscape. Different strategies for hydrogen production are explained and evaluated. Focus is on biological hydrogen production; fermentation and photon-fuelled hydrogen production are compared. Mathematical models in biology can be used to assess, explore and design production strategies for industrially relevant metabolites, such as biofuels. We assess the diverse construction and uses of genome-scale metabolic models of cyanobacterium Synechocystis sp. PCC6803 to efficiently obtain biofuels. This organism has been studied as a potential photon-fuelled production platform for its ability to grow from carbon dioxide, water and photons, on simple culture media. Finally, we review studies that propose production strategies to weigh this organism's viability as a biofuel production platform. Overall, the work presented in this review unveils the industrial capabilities of cyanobacterium Synechocystis sp. PCC6803 to evolve interesting metabolites as a clean biofuel production platform. PMID:24090244

  4. High-Throughput Tissue Bioenergetics Analysis Reveals Identical Metabolic Allometric Scaling for Teleost Hearts and Whole Organisms

    PubMed Central

    Jayasundara, Nishad; Kozal, Jordan S.; Arnold, Mariah C.; Chan, Sherine S. L.; Di Giulio, Richard T.

    2015-01-01

    Organismal metabolic rate, a fundamental metric in biology, demonstrates an allometric scaling relationship with body size. Fractal-like vascular distribution networks of biological systems are proposed to underlie metabolic rate allometric scaling laws from individual organisms to cells, mitochondria, and enzymes. Tissue-specific metabolic scaling is notably absent from this paradigm. In the current study, metabolic scaling relationships of hearts and brains with body size were examined by improving on a high-throughput whole-organ oxygen consumption rate (OCR) analysis method in five biomedically and environmentally relevant teleost model species. Tissue-specific metabolic scaling was compared with organismal routine metabolism (RMO2), which was measured using whole organismal respirometry. Basal heart OCR and organismal RMO2 scaled identically with body mass in a species-specific fashion across all five species tested. However, organismal maximum metabolic rates (MMO2) and pharmacologically-induced maximum cardiac metabolic rates in zebrafish Danio rerio did not show a similar relationship with body mass. Brain metabolic rates did not scale with body size. The identical allometric scaling of heart and organismal metabolic rates with body size suggests that hearts, the power generator of an organism’s vascular distribution network, might be crucial in determining teleost metabolic rate scaling under routine conditions. Furthermore, these findings indicate the possibility of measuring heart OCR utilizing the high-throughput approach presented here as a proxy for organismal metabolic rate—a useful metric in characterizing organismal fitness. In addition to heart and brain OCR, the current approach was also used to measure whole liver OCR, partition cardiac mitochondrial bioenergetic parameters using pharmacological agents, and estimate heart and brain glycolytic rates. This high-throughput whole-organ bioenergetic analysis method has important applications in

  5. Metabolic modelling of full-scale enhanced biological phosphorus removal sludge.

    PubMed

    Lanham, Ana B; Oehmen, Adrian; Saunders, Aaron M; Carvalho, Gilda; Nielsen, Per H; Reis, Maria A M

    2014-12-01

    This study investigates, for the first time, the application of metabolic models incorporating polyphosphate accumulating organisms (PAOs) and glycogen accumulating organisms (GAOs) towards describing the biochemical transformations of full-scale enhanced biological phosphorus removal (EBPR) activated sludge from wastewater treatment plants (WWTPs). For this purpose, it was required to modify previous metabolic models applied to lab-scale systems by incorporating the anaerobic utilisation of the TCA cycle and the aerobic maintenance processes based on sequential utilisation of polyhydroxyalkanoates, followed by glycogen and polyphosphate. The abundance of the PAO and GAO populations quantified by fluorescence in situ hybridisation served as the initial conditions of each biomass fraction, whereby the models were able to describe accurately the experimental data. The kinetic rates were found to change among the four different WWTPs studied or even in the same plant during different seasons, either suggesting the presence of additional PAO or GAO organisms, or varying microbial activities for the same organisms. Nevertheless, these variations in kinetic rates were largely found to be proportional to the difference in acetate uptake rate, suggesting a viable means of calibrating the metabolic model. The application of the metabolic model to full-scale sludge also revealed that different Accumulibacter clades likely possess different acetate uptake mechanisms, as a correlation was observed between the energetic requirement for acetate transport across the cell membrane with the diversity of Accumulibacter present. Using the model as a predictive tool, it was shown that lower acetate concentrations in the feed as well as longer aerobic retention times favour the dominance of the TCA metabolism over glycolysis, which could explain why the anaerobic TCA pathway seems to be more relevant in full-scale WWTPs than in lab-scale systems. PMID:25222332

  6. 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.

  7. Association of Lipid Accumulation Product with Cardio-Metabolic Risk Factors in Postmenopausal Women.

    PubMed

    Namazi Shabestari, Alireza; Asadi, Mojgan; Jouyandeh, Zahra; Qorbani, Mostafa; Kelishadi, Roya

    2016-06-01

    The lipid accumulation product is a novel, safe and inexpensive index of central lipid over accumulation based on waist circumference and fasting concentration of circulating triglycerides. This study was designed to investigate the ability of lipid accumulation product to predict Cardio-metabolic risk factors in postmenopausal women. In this Cross-sectional study, 264 postmenopausal women by using convenience sampling method were selected from menopause clinic in Tehran. Cardio-metabolic risk factors were measured, and lipid accumulation product (waist-58×triglycerides [nmol/L]) was calculated. Optimal cut-off point of lipid accumulation product for predicting metabolic syndrome was estimated by ROC (Receiver-operating characteristic) curve analysis. Metabolic syndrome was diagnosed in 41.2% of subjects. Optimal cut-off point of lipid accumulation product for predicting metabolic syndrome was 47.63 (sensitivity:75%; specificity:77.9%). High lipid accumulation product increases risk of all Cardio-metabolic risk factors except overweight, high Total Cholesterol, high Low Density Lipoprotein Cholesterol and high Fasting Blood Sugar in postmenopausal women. Our findings show that lipid accumulation product is associated with metabolic syndrome and some Cardio-metabolic risk factors Also lipid accumulation product may have been a useful tool for predicting cardiovascular disease and metabolic syndrome risk in postmenopausal women. PMID:27306343

  8. GSMN-TB: a web-based genome-scale network model of Mycobacterium tuberculosis metabolism

    PubMed Central

    Beste, Dany JV; Hooper, Tracy; Stewart, Graham; Bonde, Bhushan; Avignone-Rossa, Claudio; Bushell, Michael E; Wheeler, Paul; Klamt, Steffen; Kierzek, Andrzej M; McFadden, Johnjoe

    2007-01-01

    Background An impediment to the rational development of novel drugs against tuberculosis (TB) is a general paucity of knowledge concerning the metabolism of Mycobacterium tuberculosis, particularly during infection. Constraint-based modeling provides a novel approach to investigating microbial metabolism but has not yet been applied to genome-scale modeling of M. tuberculosis. Results GSMN-TB, a genome-scale metabolic model of M. tuberculosis, was constructed, consisting of 849 unique reactions and 739 metabolites, and involving 726 genes. The model was calibrated by growing Mycobacterium bovis bacille Calmette Guérin in continuous culture and steady-state growth parameters were measured. Flux balance analysis was used to calculate substrate consumption rates, which were shown to correspond closely to experimentally determined values. Predictions of gene essentiality were also made by flux balance analysis simulation and were compared with global mutagenesis data for M. tuberculosis grown in vitro. A prediction accuracy of 78% was achieved. Known drug targets were predicted to be essential by the model. The model demonstrated a potential role for the enzyme isocitrate lyase during the slow growth of mycobacteria, and this hypothesis was experimentally verified. An interactive web-based version of the model is available. Conclusion The GSMN-TB model successfully simulated many of the growth properties of M. tuberculosis. The model provides a means to examine the metabolic flexibility of bacteria and predict the phenotype of mutants, and it highlights previously unexplored features of M. tuberculosis metabolism. PMID:17521419

  9. Genome-scale reconstruction of metabolic networks of Lactobacillus casei ATCC 334 and 12A.

    PubMed

    Vinay-Lara, Elena; Hamilton, Joshua J; Stahl, Buffy; Broadbent, Jeff R; Reed, Jennifer L; Steele, James L

    2014-01-01

    Lactobacillus casei strains are widely used in industry and the utility of this organism in these industrial applications is strain dependent. Hence, tools capable of predicting strain specific phenotypes would have utility in the selection of strains for specific industrial processes. Genome-scale metabolic models can be utilized to better understand genotype-phenotype relationships and to compare different organisms. To assist in the selection and development of strains with enhanced industrial utility, genome-scale models for L. casei ATCC 334, a well characterized strain, and strain 12A, a corn silage isolate, were constructed. Draft models were generated from RAST genome annotations using the Model SEED database and refined by evaluating ATP generating cycles, mass-and-charge-balances of reactions, and growth phenotypes. After the validation process was finished, we compared the metabolic networks of these two strains to identify metabolic, genetic and ortholog differences that may lead to different phenotypic behaviors. We conclude that the metabolic capabilities of the two networks are highly similar. The L. casei ATCC 334 model accounts for 1,040 reactions, 959 metabolites and 548 genes, while the L. casei 12A model accounts for 1,076 reactions, 979 metabolites and 640 genes. The developed L. casei ATCC 334 and 12A metabolic models will enable better understanding of the physiology of these organisms and be valuable tools in the development and selection of strains with enhanced utility in a variety of industrial applications. PMID:25365062

  10. Metabolic versatility in full-scale wastewater treatment plants performing enhanced biological phosphorus removal.

    PubMed

    Lanham, Ana B; Oehmen, Adrian; Saunders, Aaron M; Carvalho, Gilda; Nielsen, Per H; Reis, Maria A M

    2013-12-01

    This study analysed the enhanced biological phosphorus removal (EBPR) microbial community and metabolic performance of five full-scale EBPR systems by using fluorescence in situ hybridisation combined with off-line batch tests fed with acetate under anaerobic-aerobic conditions. The phosphorus accumulating organisms (PAOs) in all systems were stable and showed little variability between each plant, while glycogen accumulating organisms (GAOs) were present in two of the plants. The metabolic activity of each sludge showed the frequent involvement of the anaerobic tricarboxylic acid cycle (TCA) in PAO metabolism for the anaerobic generation of reducing equivalents, in addition to the more frequently reported glycolysis pathway. Metabolic variability in the use of the two pathways was also observed, between different systems and in the same system over time. The metabolic dynamics was linked to the availability of glycogen, where a higher utilisation of the glycolysis pathway was observed in the two systems employing side-stream hydrolysis, and the TCA cycle was more active in the A(2)O systems. Full-scale plants that showed higher glycolysis activity also exhibited superior P removal performance, suggesting that promotion of the glycolysis pathway over the TCA cycle could be beneficial towards the optimisation of EBPR systems. PMID:24210547

  11. Genome –Scale Reconstruction of Metabolic Networks of Lactobacillus casei ATCC 334 and 12A

    PubMed Central

    Vinay-Lara, Elena; Hamilton, Joshua J.; Stahl, Buffy; Broadbent, Jeff R.; Reed, Jennifer L.; Steele, James L.

    2014-01-01

    Lactobacillus casei strains are widely used in industry and the utility of this organism in these industrial applications is strain dependent. Hence, tools capable of predicting strain specific phenotypes would have utility in the selection of strains for specific industrial processes. Genome-scale metabolic models can be utilized to better understand genotype-phenotype relationships and to compare different organisms. To assist in the selection and development of strains with enhanced industrial utility, genome-scale models for L. casei ATCC 334, a well characterized strain, and strain 12A, a corn silage isolate, were constructed. Draft models were generated from RAST genome annotations using the Model SEED database and refined by evaluating ATP generating cycles, mass-and-charge-balances of reactions, and growth phenotypes. After the validation process was finished, we compared the metabolic networks of these two strains to identify metabolic, genetic and ortholog differences that may lead to different phenotypic behaviors. We conclude that the metabolic capabilities of the two networks are highly similar. The L. casei ATCC 334 model accounts for 1,040 reactions, 959 metabolites and 548 genes, while the L. casei 12A model accounts for 1,076 reactions, 979 metabolites and 640 genes. The developed L. casei ATCC 334 and 12A metabolic models will enable better understanding of the physiology of these organisms and be valuable tools in the development and selection of strains with enhanced utility in a variety of industrial applications. PMID:25365062

  12. Model-guided metabolic gene knockout of gnd for enhanced succinate production in Escherichia coli from glucose and glycerol substrates.

    PubMed

    Mienda, Bashir Sajo; Shamsir, Mohd Shahir; Illias, Rosli Md

    2016-04-01

    The metabolic role of 6-phosphogluconate dehydrogenase (gnd) under anaerobic conditions with respect to succinate production in Escherichia coli remained largely unspecified. Herein we report what are to our knowledge the first metabolic gene knockout of gnd to have increased succinic acid production using both glucose and glycerol substrates in E. coli. Guided by a genome scale metabolic model, we engineered the E. coli host metabolism to enhance anaerobic production of succinic acid by deleting the gnd gene, considering its location in the boundary of oxidative and non-oxidative pentose phosphate pathway. This strategy induced either the activation of malic enzyme, causing up-regulation of phosphoenolpyruvate carboxylase (ppc) and down regulation of phosphoenolpyruvate carboxykinase (ppck) and/or prevents the decarboxylation of 6 phosphogluconate to increase the pool of glyceraldehyde-3-phosphate (GAP) that is required for the formation of phosphoenolpyruvate (PEP). This approach produced a mutant strain BMS2 with succinic acid production titers of 0.35gl(-1) and 1.40gl(-1) from glucose and glycerol substrates respectively. This work further clearly elucidates and informs other studies that the gnd gene, is a novel deletion target for increasing succinate production in E. coli under anaerobic condition using glucose and glycerol carbon sources. The knowledge gained in this study would help in E. coli and other microbial strains development for increasing succinate production and/or other industrial chemicals. PMID:26878126

  13. Genome-scale Metabolic Reaction Modeling: a New Approach to Geomicrobial Kinetics

    NASA Astrophysics Data System (ADS)

    McKernan, S. E.; Shapiro, B.; Jin, Q.

    2014-12-01

    Geomicrobial rates, rates of microbial metabolism in natural environments, are a key parameter of theoretical and practical problems in geobiology and biogeochemistry. Both laboratory- and field-based approaches have been applied to study rates of geomicrobial processes. Laboratory-based approaches analyze geomicrobial kinetics by incubating environmental samples under controlled laboratory conditions. Field methods quantify geomicrobial rates by observing the progress of geomicrobial processes. To take advantage of recent development in biogeochemical modeling and genome-scale metabolic modeling, we suggest that geomicrobial rates can also be predicted by simulating metabolic reaction networks of microbes. To predict geomicrobial rates, we developed a genome-scale metabolic model that describes enzyme reaction networks of microbial metabolism, and simulated the network model by accounting for the kinetics and thermodynamics of enzyme reactions. The model is simulated numerically to solve cellular enzyme abundance and hence metabolic rates under the constraints of cellular physiology. The new modeling approach differs from flux balance analysis of system biology in that it accounts for the thermodynamics and kinetics of enzymatic reactions. It builds on subcellular metabolic reaction networks, and hence also differs from classical biogeochemical reaction modeling. We applied the new approach to Methanosarcina acetivorans, an anaerobic, marine methanogen capable of disproportionating acetate to carbon dioxide and methane. The input of the new model includes (1) enzyme reaction network of acetoclastic methanogenesis, and (2) representative geochemical conditions of freshwater sedimentary environments. The output of the simulation includes the proteomics, metabolomics, and energy and matter fluxes of M. acetivorans. Our simulation results demonstrate the predictive power of the new modeling approach. Specifically, the results illustrate how methanogenesis rates vary

  14. Intraspecific scaling in frog calls: the interplay of temperature, body size and metabolic condition.

    PubMed

    Ziegler, Lucia; Arim, Matías; Bozinovic, Francisco

    2016-07-01

    Understanding physiological and environmental determinants of strategies of reproductive allocation is a pivotal aim in biology. Because of their high metabolic cost, properties of sexual acoustic signals may correlate with body size, temperature, and an individual's energetic state. A quantitative theory of acoustic communication, based on the metabolic scaling with temperature and mass, was recently proposed, adding to the well-reported empirical patterns. It provides quantitative predictions for frequencies, call rate, and durations. Here, we analysed the mass, temperature, and body condition scaling of spectral and temporal attributes of the advertisement call of the treefrog Hypsiboas pulchellus. Mass dependence of call frequency followed metabolic expectations (f~M (-0.25), where f is frequency and M is mass) although non-metabolic allometry could also account for the observed pattern. Temporal variables scaled inversely with mass contradicting metabolic expectations (d~M (0.25), where d is duration), supporting instead empirical patterns reported to date. Temperature was positively associated with call rate and negatively with temporal variables, which is congruent with metabolic predictions. We found no significant association between temperature and frequencies, adding to the bulk of empirical evidence. Finally, a result of particular relevance was that body condition consistently determined call characteristics, in interaction with temperature or mass. Our intraspecific study highlights that even if proximate determinants of call variability are rather well understood, the mechanisms through which they operate are proving to be more complex than previously thought. The determinants of call characteristics emerge as a key topic of research in behavioural and physiological biology, with several clear points under debate which need to be analysed on theoretical and empirical grounds. PMID:26552381

  15. A Computational Solution to Automatically Map Metabolite Libraries in the Context of Genome Scale Metabolic Networks.

    PubMed

    Merlet, Benjamin; Paulhe, Nils; Vinson, Florence; Frainay, Clément; Chazalviel, Maxime; Poupin, Nathalie; Gloaguen, Yoann; Giacomoni, Franck; Jourdan, Fabien

    2016-01-01

    This article describes a generic programmatic method for mapping chemical compound libraries on organism-specific metabolic networks from various databases (KEGG, BioCyc) and flat file formats (SBML and Matlab files). We show how this pipeline was successfully applied to decipher the coverage of chemical libraries set up by two metabolomics facilities MetaboHub (French National infrastructure for metabolomics and fluxomics) and Glasgow Polyomics (GP) on the metabolic networks available in the MetExplore web server. The present generic protocol is designed to formalize and reduce the volume of information transfer between the library and the network database. Matching of metabolites between libraries and metabolic networks is based on InChIs or InChIKeys and therefore requires that these identifiers are specified in both libraries and networks. In addition to providing covering statistics, this pipeline also allows the visualization of mapping results in the context of metabolic networks. In order to achieve this goal, we tackled issues on programmatic interaction between two servers, improvement of metabolite annotation in metabolic networks and automatic loading of a mapping in genome scale metabolic network analysis tool MetExplore. It is important to note that this mapping can also be performed on a single or a selection of organisms of interest and is thus not limited to large facilities. PMID:26909353

  16. Scale-dependent controls on the metabolic organization of river basins

    NASA Astrophysics Data System (ADS)

    Caylor, K.; Rodriguez-Iturbe, I.

    2012-04-01

    The metabolism of a river basin is defined as the set of processes through which the basin maintains its structure and responds to its environment. Green (or biotic) metabolism is measured via transpiration and blue (or abiotic) metabolism through runoff. Recently, a principle of equal metabolic rate per unit area throughout the basin structure has been developed and tested in a river basin characterized by large heterogeneities in precipitation, vegetation, soil, and geomorphology. Empirically derived, remarkably constant rates of average transpiration per unit area through the basin structure lead to a power law for the probability distribution of transpiration from a randomly chosen subbasin. While the empirical evidence suggests that river basin metabolic activity is linked with the fractal geometry of the network, a challenge remains in understanding how and when such organization plays a determining role in governing basin hydrological dynamics. In this presentation, I will review prior work seeking to understand the role of vegetation in governing basin response and propose use of geomorphological scaling laws as means for determining the potential for surface pattern (i.e. vegetation structure) to impact the dynamical behavior of river basin metabolism.

  17. A Computational Solution to Automatically Map Metabolite Libraries in the Context of Genome Scale Metabolic Networks

    PubMed Central

    Merlet, Benjamin; Paulhe, Nils; Vinson, Florence; Frainay, Clément; Chazalviel, Maxime; Poupin, Nathalie; Gloaguen, Yoann; Giacomoni, Franck; Jourdan, Fabien

    2016-01-01

    This article describes a generic programmatic method for mapping chemical compound libraries on organism-specific metabolic networks from various databases (KEGG, BioCyc) and flat file formats (SBML and Matlab files). We show how this pipeline was successfully applied to decipher the coverage of chemical libraries set up by two metabolomics facilities MetaboHub (French National infrastructure for metabolomics and fluxomics) and Glasgow Polyomics (GP) on the metabolic networks available in the MetExplore web server. The present generic protocol is designed to formalize and reduce the volume of information transfer between the library and the network database. Matching of metabolites between libraries and metabolic networks is based on InChIs or InChIKeys and therefore requires that these identifiers are specified in both libraries and networks. In addition to providing covering statistics, this pipeline also allows the visualization of mapping results in the context of metabolic networks. In order to achieve this goal, we tackled issues on programmatic interaction between two servers, improvement of metabolite annotation in metabolic networks and automatic loading of a mapping in genome scale metabolic network analysis tool MetExplore. It is important to note that this mapping can also be performed on a single or a selection of organisms of interest and is thus not limited to large facilities. PMID:26909353

  18. MetExplore: a web server to link metabolomic experiments and genome-scale metabolic networks.

    PubMed

    Cottret, Ludovic; Wildridge, David; Vinson, Florence; Barrett, Michael P; Charles, Hubert; Sagot, Marie-France; Jourdan, Fabien

    2010-07-01

    High-throughput metabolomic experiments aim at identifying and ultimately quantifying all metabolites present in biological systems. The metabolites are interconnected through metabolic reactions, generally grouped into metabolic pathways. Classical metabolic maps provide a relational context to help interpret metabolomics experiments and a wide range of tools have been developed to help place metabolites within metabolic pathways. However, the representation of metabolites within separate disconnected pathways overlooks most of the connectivity of the metabolome. By definition, reference pathways cannot integrate novel pathways nor show relationships between metabolites that may be linked by common neighbours without being considered as joint members of a classical biochemical pathway. MetExplore is a web server that offers the possibility to link metabolites identified in untargeted metabolomics experiments within the context of genome-scale reconstructed metabolic networks. The analysis pipeline comprises mapping metabolomics data onto the specific metabolic network of an organism, then applying graph-based methods and advanced visualization tools to enhance data analysis. The MetExplore web server is freely accessible at http://metexplore.toulouse.inra.fr. PMID:20444866

  19. Dehydratase mediated 1-propanol production in metabolically engineered Escherichia coli

    PubMed Central

    2011-01-01

    Background With the increasing consumption of fossil fuels, the question of meeting the global energy demand is of great importance in the near future. As an effective solution, production of higher alcohols from renewable sources by microorganisms has been proposed to address both energy crisis and environmental concerns. Higher alcohols contain more than two carbon atoms and have better physiochemical properties than ethanol as fuel substitutes. Results We designed a novel 1-propanol metabolic pathway by expanding the well-known 1,2-propanediol pathway with two more enzymatic steps catalyzed by a 1,2-propanediol dehydratase and an alcohol dehydrogenase. In order to engineer the pathway into E. coli, we evaluated the activities of eight different methylglyoxal synthases which play crucial roles in shunting carbon flux from glycolysis towards 1-propanol biosynthesis, as well as two secondary alcohol dehydrogenases of different origins that reduce both methylglyoxal and hydroxyacetone. It is evident from our results that the most active enzymes are the methylglyoxal synthase from Bacillus subtilis and the secondary alcohol dehydrogenase from Klebsiella pneumoniae, encoded by mgsA and budC respectively. With the expression of these two genes and the E. coli ydjG encoding methylglyoxal reductase, we achieved the production of 1,2-propanediol at 0.8 g/L in shake flask experiments. We then characterized the catalytic efficiency of three different diol dehydratases on 1,2-propanediol and identified the optimal one as the 1,2-propanediol dehydratase from Klebsiella oxytoca, encoded by the operon ppdABC. Co-expressing this enzyme with the above 1,2-propanediol pathway in wild type E. coli resulted in the production of 1-propanol at a titer of 0.25 g/L. Conclusions We have successfully established a new pathway for 1-propanol production by shunting the carbon flux from glycolysis. To our knowledge, it is the first time that this pathway has been utilized to produce 1

  20. Achieving Metabolic Flux Analysis for S. cerevisiae at a Genome-Scale: Challenges, Requirements, and Considerations

    PubMed Central

    Gopalakrishnan, Saratram; Maranas, Costas D.

    2015-01-01

    Recent advances in 13C-Metabolic flux analysis (13C-MFA) have increased its capability to accurately resolve fluxes using a genome-scale model with narrow confidence intervals without pre-judging the activity or inactivity of alternate metabolic pathways. However, the necessary precautions, computational challenges, and minimum data requirements for successful analysis remain poorly established. This review aims to establish the necessary guidelines for performing 13C-MFA at the genome-scale for a compartmentalized eukaryotic system such as yeast in terms of model and data requirements, while addressing key issues such as statistical analysis and network complexity. We describe the various approaches used to simplify the genome-scale model in the absence of sufficient experimental flux measurements, the availability and generation of reaction atom mapping information, and the experimental flux and metabolite labeling distribution measurements to ensure statistical validity of the obtained flux distribution. Organism-specific challenges such as the impact of compartmentalization of metabolism, variability of biomass composition, and the cell-cycle dependence of metabolism are discussed. Identification of errors arising from incorrect gene annotation and suggested alternate routes using MFA are also highlighted. PMID:26393660

  1. Genome-scale study reveals reduced metabolic adaptability in patients with non-alcoholic fatty liver disease.

    PubMed

    Hyötyläinen, Tuulia; Jerby, Livnat; Petäjä, Elina M; Mattila, Ismo; Jäntti, Sirkku; Auvinen, Petri; Gastaldelli, Amalia; Yki-Järvinen, Hannele; Ruppin, Eytan; Orešič, Matej

    2016-01-01

    Non-alcoholic fatty liver disease (NAFLD) is a major risk factor leading to chronic liver disease and type 2 diabetes. Here we chart liver metabolic activity and functionality in NAFLD by integrating global transcriptomic data, from human liver biopsies, and metabolic flux data, measured across the human splanchnic vascular bed, within a genome-scale model of human metabolism. We show that an increased amount of liver fat induces mitochondrial metabolism, lipolysis, glyceroneogenesis and a switch from lactate to glycerol as substrate for gluconeogenesis, indicating an intricate balance of exacerbated opposite metabolic processes in glycemic regulation. These changes were associated with reduced metabolic adaptability on a network level in the sense that liver fat accumulation puts increasing demands on the liver to adaptively regulate metabolic responses to maintain basic liver functions. We propose that failure to meet excessive metabolic challenges coupled with reduced metabolic adaptability may lead to a vicious pathogenic cycle leading to the co-morbidities of NAFLD. PMID:26839171

  2. Genome-scale study reveals reduced metabolic adaptability in patients with non-alcoholic fatty liver disease

    PubMed Central

    Hyötyläinen, Tuulia; Jerby, Livnat; Petäjä, Elina M.; Mattila, Ismo; Jäntti, Sirkku; Auvinen, Petri; Gastaldelli, Amalia; Yki-Järvinen, Hannele; Ruppin, Eytan; Orešič, Matej

    2016-01-01

    Non-alcoholic fatty liver disease (NAFLD) is a major risk factor leading to chronic liver disease and type 2 diabetes. Here we chart liver metabolic activity and functionality in NAFLD by integrating global transcriptomic data, from human liver biopsies, and metabolic flux data, measured across the human splanchnic vascular bed, within a genome-scale model of human metabolism. We show that an increased amount of liver fat induces mitochondrial metabolism, lipolysis, glyceroneogenesis and a switch from lactate to glycerol as substrate for gluconeogenesis, indicating an intricate balance of exacerbated opposite metabolic processes in glycemic regulation. These changes were associated with reduced metabolic adaptability on a network level in the sense that liver fat accumulation puts increasing demands on the liver to adaptively regulate metabolic responses to maintain basic liver functions. We propose that failure to meet excessive metabolic challenges coupled with reduced metabolic adaptability may lead to a vicious pathogenic cycle leading to the co-morbidities of NAFLD. PMID:26839171

  3. Reconstruction and analysis of genome-scale metabolic model of a photosynthetic bacterium

    PubMed Central

    2010-01-01

    Background Synechocystis sp. PCC6803 is a cyanobacterium considered as a candidate photo-biological production platform - an attractive cell factory capable of using CO2 and light as carbon and energy source, respectively. In order to enable efficient use of metabolic potential of Synechocystis sp. PCC6803, it is of importance to develop tools for uncovering stoichiometric and regulatory principles in the Synechocystis metabolic network. Results We report the most comprehensive metabolic model of Synechocystis sp. PCC6803 available, iSyn669, which includes 882 reactions, associated with 669 genes, and 790 metabolites. The model includes a detailed biomass equation which encompasses elementary building blocks that are needed for cell growth, as well as a detailed stoichiometric representation of photosynthesis. We demonstrate applicability of iSyn669 for stoichiometric analysis by simulating three physiologically relevant growth conditions of Synechocystis sp. PCC6803, and through in silico metabolic engineering simulations that allowed identification of a set of gene knock-out candidates towards enhanced succinate production. Gene essentiality and hydrogen production potential have also been assessed. Furthermore, iSyn669 was used as a transcriptomic data integration scaffold and thereby we found metabolic hot-spots around which gene regulation is dominant during light-shifting growth regimes. Conclusions iSyn669 provides a platform for facilitating the development of cyanobacteria as microbial cell factories. PMID:21083885

  4. Transcriptional Profiling of Hydrogen Production Metabolism of Rhodobacter capsulatus under Temperature Stress by Microarray Analysis.

    PubMed

    Gürgan, Muazzez; Erkal, Nilüfer Afşar; Özgür, Ebru; Gündüz, Ufuk; Eroglu, Inci; Yücel, Meral

    2015-01-01

    Biohydrogen is a clean and renewable form of hydrogen, which can be produced by photosynthetic bacteria in outdoor large-scale photobioreactors using sunlight. In this study, the transcriptional response of Rhodobacter capsulatus to cold (4 °C) and heat (42 °C) stress was studied using microarrays. Bacteria were grown in 30/2 acetate/glutamate medium at 30 °C for 48 h under continuous illumination. Then, cold and heat stresses were applied for two and six hours. Growth and hydrogen production were impaired under both stress conditions. Microarray chips for R. capsulatus were custom designed by Affymetrix (GeneChip®. TR_RCH2a520699F). The numbers of significantly changed genes were 328 and 293 out of 3685 genes under cold and heat stress, respectively. Our results indicate that temperature stress greatly affects the hydrogen production metabolisms of R. capsulatus. Specifically, the expression of genes that participate in nitrogen metabolism, photosynthesis and the electron transport system were induced by cold stress, while decreased by heat stress. Heat stress also resulted in down regulation of genes related to cell envelope, transporter and binding proteins. Transcriptome analysis and physiological results were consistent with each other. The results presented here may aid clarification of the genetic mechanisms for hydrogen production in purple non-sulfur (PNS) bacteria under temperature stress. PMID:26086826

  5. Transcriptional Profiling of Hydrogen Production Metabolism of Rhodobacter capsulatus under Temperature Stress by Microarray Analysis

    PubMed Central

    Gürgan, Muazzez; Afşar Erkal, Nilüfer; Özgür, Ebru; Gündüz, Ufuk; Eroglu, Inci; Yücel, Meral

    2015-01-01

    Biohydrogen is a clean and renewable form of hydrogen, which can be produced by photosynthetic bacteria in outdoor large-scale photobioreactors using sunlight. In this study, the transcriptional response of Rhodobacter capsulatus to cold (4 °C) and heat (42 °C) stress was studied using microarrays. Bacteria were grown in 30/2 acetate/glutamate medium at 30 °C for 48 h under continuous illumination. Then, cold and heat stresses were applied for two and six hours. Growth and hydrogen production were impaired under both stress conditions. Microarray chips for R. capsulatus were custom designed by Affymetrix (GeneChip®. TR_RCH2a520699F). The numbers of significantly changed genes were 328 and 293 out of 3685 genes under cold and heat stress, respectively. Our results indicate that temperature stress greatly affects the hydrogen production metabolisms of R. capsulatus. Specifically, the expression of genes that participate in nitrogen metabolism, photosynthesis and the electron transport system were induced by cold stress, while decreased by heat stress. Heat stress also resulted in down regulation of genes related to cell envelope, transporter and binding proteins. Transcriptome analysis and physiological results were consistent with each other. The results presented here may aid clarification of the genetic mechanisms for hydrogen production in purple non-sulfur (PNS) bacteria under temperature stress. PMID:26086826

  6. Genome-Scale Metabolic Model for the Green Alga Chlorella vulgaris UTEX 395 Accurately Predicts Phenotypes under Autotrophic, Heterotrophic, and Mixotrophic Growth Conditions.

    PubMed

    Zuñiga, Cristal; Li, Chien-Ting; Huelsman, Tyler; Levering, Jennifer; Zielinski, Daniel C; McConnell, Brian O; Long, Christopher P; Knoshaug, Eric P; Guarnieri, Michael T; Antoniewicz, Maciek R; Betenbaugh, Michael J; Zengler, Karsten

    2016-09-01

    The green microalga Chlorella vulgaris has been widely recognized as a promising candidate for biofuel production due to its ability to store high lipid content and its natural metabolic versatility. Compartmentalized genome-scale metabolic models constructed from genome sequences enable quantitative insight into the transport and metabolism of compounds within a target organism. These metabolic models have long been utilized to generate optimized design strategies for an improved production process. Here, we describe the reconstruction, validation, and application of a genome-scale metabolic model for C. vulgaris UTEX 395, iCZ843. The reconstruction represents the most comprehensive model for any eukaryotic photosynthetic organism to date, based on the genome size and number of genes in the reconstruction. The highly curated model accurately predicts phenotypes under photoautotrophic, heterotrophic, and mixotrophic conditions. The model was validated against experimental data and lays the foundation for model-driven strain design and medium alteration to improve yield. Calculated flux distributions under different trophic conditions show that a number of key pathways are affected by nitrogen starvation conditions, including central carbon metabolism and amino acid, nucleotide, and pigment biosynthetic pathways. Furthermore, model prediction of growth rates under various medium compositions and subsequent experimental validation showed an increased growth rate with the addition of tryptophan and methionine. PMID:27372244

  7. Genome-Scale NAD(H/+) Availability Patterns as a Differentiating Feature between Saccharomyces cerevisiae and Scheffersomyces stipitis in Relation to Fermentative Metabolism

    PubMed Central

    Acevedo, Alejandro; Aroca, German; Conejeros, Raul

    2014-01-01

    Scheffersomyces stipitis is a yeast able to ferment pentoses to ethanol, unlike Saccharomyces cerevisiae, it does not present the so-called overflow phenomenon. Metabolic features characterizing the presence or not of this phenomenon have not been fully elucidated. This work proposes that genome-scale metabolic response to variations in NAD(H/+) availability characterizes fermentative behavior in both yeasts. Thus, differentiating features in S. stipitis and S. cerevisiae were determined analyzing growth sensitivity response to changes in available reducing capacity in relation to ethanol production capacity and overall metabolic flux span. Using genome-scale constraint-based metabolic models, phenotypic phase planes and shadow price analyses, an excess of available reducing capacity for growth was found in S. cerevisiae at every metabolic phenotype where growth is limited by oxygen uptake, while in S. stipitis this was observed only for a subset of those phenotypes. Moreover, by using flux variability analysis, an increased metabolic flux span was found in S. cerevisiae at growth limited by oxygen uptake, while in S. stipitis flux span was invariant. Therefore, each yeast can be characterized by a significantly different metabolic response and flux span when growth is limited by oxygen uptake, both features suggesting a higher metabolic flexibility in S. cerevisiae. By applying an optimization-based approach on the genome-scale models, three single reaction deletions were found to generate in S. stipitis the reducing capacity availability pattern found in S. cerevisiae, two of them correspond to reactions involved in the overflow phenomenon. These results show a close relationship between the growth sensitivity response given by the metabolic network and fermentative behavior. PMID:24489927

  8. Genome-scale estimate of the metabolic turnover of E. Coli from the energy balance analysis

    NASA Astrophysics Data System (ADS)

    De Martino, D.

    2016-02-01

    In this article the notion of metabolic turnover is revisited in the light of recent results of out-of-equilibrium thermodynamics. By means of Monte Carlo methods we perform an exact sampling of the enzymatic fluxes in a genome scale metabolic network of E. Coli in stationary growth conditions from which we infer the metabolites turnover times. However the latter are inferred from net fluxes, and we argue that this approximation is not valid for enzymes working nearby thermodynamic equilibrium. We recalculate turnover times from total fluxes by performing an energy balance analysis of the network and recurring to the fluctuation theorem. We find in many cases values one of order of magnitude lower, implying a faster picture of intermediate metabolism.

  9. Metabolic engineering of Corynebacterium glutamicum aimed at alternative carbon sources and new products.

    PubMed

    Zahoor, Ahmed; Lindner, Steffen N; Wendisch, Volker F

    2012-01-01

    Corynebacterium glutamicum is well known as the amino acid-producing workhorse of fermentation industry, being used for multi-million-ton scale production of glutamate and lysine for more than 60 years. However, it is only recently that extensive research has focused on engineering it beyond the scope of amino acids. Meanwhile, a variety of corynebacterial strains allows access to alternative carbon sources and/or allows production of a wide range of industrially relevant compounds. Some of these efforts set new standards in terms of titers and productivities achieved whereas others represent a proof-of-principle. These achievements manifest the position of C. glutamicum as an important industrial microorganism with capabilities far beyond the traditional amino acid production. In this review we focus on the state of the art of metabolic engineering of C. glutamicum for utilization of alternative carbon sources, (e.g. coming from wastes and unprocessed sources), and construction of C. glutamicum strains for production of new products such as diamines, organic acids and alcohols. PMID:24688664

  10. Metabolic engineering of Corynebacterium glutamicum aimed at alternative carbon sources and new products

    PubMed Central

    Zahoor, Ahmed; Lindner, Steffen N.; Wendisch, Volker F.

    2012-01-01

    Corynebacterium glutamicum is well known as the amino acid-producing workhorse of fermentation industry, being used for multi-million-ton scale production of glutamate and lysine for more than 60 years. However, it is only recently that extensive research has focused on engineering it beyond the scope of amino acids. Meanwhile, a variety of corynebacterial strains allows access to alternative carbon sources and/or allows production of a wide range of industrially relevant compounds. Some of these efforts set new standards in terms of titers and productivities achieved whereas others represent a proof-of-principle. These achievements manifest the position of C. glutamicum as an important industrial microorganism with capabilities far beyond the traditional amino acid production. In this review we focus on the state of the art of metabolic engineering of C. glutamicum for utilization of alternative carbon sources, (e.g. coming from wastes and unprocessed sources), and construction of C. glutamicum strains for production of new products such as diamines, organic acids and alcohols PMID:24688664

  11. Network Thermodynamic Curation of Human and Yeast Genome-Scale Metabolic Models

    PubMed Central

    Martínez, Verónica S.; Quek, Lake-Ee; Nielsen, Lars K.

    2014-01-01

    Genome-scale models are used for an ever-widening range of applications. Although there has been much focus on specifying the stoichiometric matrix, the predictive power of genome-scale models equally depends on reaction directions. Two-thirds of reactions in the two eukaryotic reconstructions Homo sapiens Recon 1 and Yeast 5 are specified as irreversible. However, these specifications are mainly based on biochemical textbooks or on their similarity to other organisms and are rarely underpinned by detailed thermodynamic analysis. In this study, a to our knowledge new workflow combining network-embedded thermodynamic and flux variability analysis was used to evaluate existing irreversibility constraints in Recon 1 and Yeast 5 and to identify new ones. A total of 27 and 16 new irreversible reactions were identified in Recon 1 and Yeast 5, respectively, whereas only four reactions were found with directions incorrectly specified against thermodynamics (three in Yeast 5 and one in Recon 1). The workflow further identified for both models several isolated internal loops that require further curation. The framework also highlighted the need for substrate channeling (in human) and ATP hydrolysis (in yeast) for the essential reaction catalyzed by phosphoribosylaminoimidazole carboxylase in purine metabolism. Finally, the framework highlighted differences in proline metabolism between yeast (cytosolic anabolism and mitochondrial catabolism) and humans (exclusively mitochondrial metabolism). We conclude that network-embedded thermodynamics facilitates the specification and validation of irreversibility constraints in compartmentalized metabolic models, at the same time providing further insight into network properties. PMID:25028891

  12. Genome-Scale Model Reveals Metabolic Basis of Biomass Partitioning in a Model Diatom.

    PubMed

    Levering, Jennifer; Broddrick, Jared; Dupont, Christopher L; Peers, Graham; Beeri, Karen; Mayers, Joshua; Gallina, Alessandra A; Allen, Andrew E; Palsson, Bernhard O; Zengler, Karsten

    2016-01-01

    Diatoms are eukaryotic microalgae that contain genes from various sources, including bacteria and the secondary endosymbiotic host. Due to this unique combination of genes, diatoms are taxonomically and functionally distinct from other algae and vascular plants and confer novel metabolic capabilities. Based on the genome annotation, we performed a genome-scale metabolic network reconstruction for the marine diatom Phaeodactylum tricornutum. Due to their endosymbiotic origin, diatoms possess a complex chloroplast structure which complicates the prediction of subcellular protein localization. Based on previous work we implemented a pipeline that exploits a series of bioinformatics tools to predict protein localization. The manually curated reconstructed metabolic network iLB1027_lipid accounts for 1,027 genes associated with 4,456 reactions and 2,172 metabolites distributed across six compartments. To constrain the genome-scale model, we determined the organism specific biomass composition in terms of lipids, carbohydrates, and proteins using Fourier transform infrared spectrometry. Our simulations indicate the presence of a yet unknown glutamine-ornithine shunt that could be used to transfer reducing equivalents generated by photosynthesis to the mitochondria. The model reflects the known biochemical composition of P. tricornutum in defined culture conditions and enables metabolic engineering strategies to improve the use of P. tricornutum for biotechnological applications. PMID:27152931

  13. An experimentally-supported genome-scale metabolic network reconstruction for Yersinia pestis CO92

    PubMed Central

    2011-01-01

    Background Yersinia pestis is a gram-negative bacterium that causes plague, a disease linked historically to the Black Death in Europe during the Middle Ages and to several outbreaks during the modern era. Metabolism in Y. pestis displays remarkable flexibility and robustness, allowing the bacterium to proliferate in both warm-blooded mammalian hosts and cold-blooded insect vectors such as fleas. Results Here we report a genome-scale reconstruction and mathematical model of metabolism for Y. pestis CO92 and supporting experimental growth and metabolite measurements. The model contains 815 genes, 678 proteins, 963 unique metabolites and 1678 reactions, accurately simulates growth on a range of carbon sources both qualitatively and quantitatively, and identifies gaps in several key biosynthetic pathways and suggests how those gaps might be filled. Furthermore, our model presents hypotheses to explain certain known nutritional requirements characteristic of this strain. Conclusions Y. pestis continues to be a dangerous threat to human health during modern times. The Y. pestis genome-scale metabolic reconstruction presented here, which has been benchmarked against experimental data and correctly reproduces known phenotypes, provides an in silico platform with which to investigate the metabolism of this important human pathogen. PMID:21995956

  14. An Experimentally-Supported Genome-Scale Metabolic Network Reconstruction for Yersinia pestis CO92

    SciTech Connect

    Charusanti, Pep; Chauhan, Sadhana; Mcateer, Kathleen; Lerman, Joshua A.; Hyduke, Daniel R.; Motin, Vladimir L.; Ansong, Charles; Adkins, Joshua N.; Palsson, Bernhard O.

    2011-10-13

    Yersinia pestis is a gram-negative bacterium that causes plague, a disease linked historically to the Black Death in Europe during the Middle Ages and to several outbreaks during the modern era. Metabolism in Y. pestis displays remarkable flexibility and robustness, allowing the bacterium to proliferate in both warm-blooded mammalian hosts and cold-blooded insect vectors such as fleas. Here we report a genome-scale reconstruction and mathematical model of metabolism for Y. pestis CO92 and supporting experimental growth and metabolite measurements. The model contains 815 genes, 678 proteins, 963 unique metabolites and 1678 reactions, accurately simulates growth on a range of carbon sources both qualitatively and quantitatively, and identifies gaps in several key biosynthetic pathways and suggests how those gaps might be filled. Furthermore, our model presents hypotheses to explain certain known nutritional requirements characteristic of this strain. Y. pestis continues to be a dangerous threat to human health during modern times. The Y. pestis genome-scale metabolic reconstruction presented here, which has been benchmarked against experimental data and correctly reproduces known phenotypes, thus provides an in silico platform with which to investigate the metabolism of this important human pathogen.

  15. Genome-scale model reveals metabolic basis of biomass partitioning in a model diatom

    DOE PAGESBeta

    Levering, Jennifer; Broddrick, Jared; Dupont, Christopher L.; Peers, Graham; Beeri, Karen; Mayers, Joshua; Gallina, Alessandra A.; Allen, Andrew E.; Palsson, Bernhard O.; Zengler, Karsten; et al

    2016-05-06

    Diatoms are eukaryotic microalgae that contain genes from various sources, including bacteria and the secondary endosymbiotic host. Due to this unique combination of genes, diatoms are taxonomically and functionally distinct from other algae and vascular plants and confer novel metabolic capabilities. Based on the genome annotation, we performed a genome-scale metabolic network reconstruction for the marine diatom Phaeodactylum tricornutum. Due to their endosymbiotic origin, diatoms possess a complex chloroplast structure which complicates the prediction of subcellular protein localization. Based on previous work we implemented a pipeline that exploits a series of bioinformatics tools to predict protein localization. The manually curatedmore » reconstructed metabolic network iLB1027_lipid accounts for 1,027 genes associated with 4,456 reactions and 2,172 metabolites distributed across six compartments. To constrain the genome-scale model, we determined the organism specific biomass composition in terms of lipids, carbohydrates, and proteins using Fourier transform infrared spectrometry. Our simulations indicate the presence of a yet unknown glutamine-ornithine shunt that could be used to transfer reducing equivalents generated by photosynthesis to the mitochondria. Furthermore, the model reflects the known biochemical composition of P. tricornutum in defined culture conditions and enables metabolic engineering strategies to improve the use of P. tricornutum for biotechnological applications.« less

  16. Genome-Scale Model Reveals Metabolic Basis of Biomass Partitioning in a Model Diatom

    PubMed Central

    Broddrick, Jared; Dupont, Christopher L.; Peers, Graham; Beeri, Karen; Mayers, Joshua; Gallina, Alessandra A.; Allen, Andrew E.; Palsson, Bernhard O.; Zengler, Karsten

    2016-01-01

    Diatoms are eukaryotic microalgae that contain genes from various sources, including bacteria and the secondary endosymbiotic host. Due to this unique combination of genes, diatoms are taxonomically and functionally distinct from other algae and vascular plants and confer novel metabolic capabilities. Based on the genome annotation, we performed a genome-scale metabolic network reconstruction for the marine diatom Phaeodactylum tricornutum. Due to their endosymbiotic origin, diatoms possess a complex chloroplast structure which complicates the prediction of subcellular protein localization. Based on previous work we implemented a pipeline that exploits a series of bioinformatics tools to predict protein localization. The manually curated reconstructed metabolic network iLB1027_lipid accounts for 1,027 genes associated with 4,456 reactions and 2,172 metabolites distributed across six compartments. To constrain the genome-scale model, we determined the organism specific biomass composition in terms of lipids, carbohydrates, and proteins using Fourier transform infrared spectrometry. Our simulations indicate the presence of a yet unknown glutamine-ornithine shunt that could be used to transfer reducing equivalents generated by photosynthesis to the mitochondria. The model reflects the known biochemical composition of P. tricornutum in defined culture conditions and enables metabolic engineering strategies to improve the use of P. tricornutum for biotechnological applications. PMID:27152931

  17. A Genome-Scale Database and Reconstruction of Caenorhabditis elegans Metabolism.

    PubMed

    Gebauer, Juliane; Gentsch, Christoph; Mansfeld, Johannes; Schmeißer, Kathrin; Waschina, Silvio; Brandes, Susanne; Klimmasch, Lukas; Zamboni, Nicola; Zarse, Kim; Schuster, Stefan; Ristow, Michael; Schäuble, Sascha; Kaleta, Christoph

    2016-05-25

    We present a genome-scale model of Caenorhabditis elegans metabolism along with the public database ElegCyc (http://elegcyc.bioinf.uni-jena.de:1100), which represents a reference for metabolic pathways in the worm and allows for the visualization as well as analysis of omics datasets. Our model reflects the metabolic peculiarities of C. elegans that make it distinct from other higher eukaryotes and mammals, including mice and humans. We experimentally verify one of these peculiarities by showing that the lifespan-extending effect of L-tryptophan supplementation is dose dependent (hormetic). Finally, we show the utility of our model for analyzing omics datasets through predicting changes in amino acid concentrations after genetic perturbations and analyzing metabolic changes during normal aging as well as during two distinct, reactive oxygen species (ROS)-related lifespan-extending treatments. Our analyses reveal a notable similarity in metabolic adaptation between distinct lifespan-extending interventions and point to key pathways affecting lifespan in nematodes. PMID:27211858

  18. Is the scaling of swim speed in sharks driven by metabolism?

    PubMed

    Jacoby, David M P; Siriwat, Penthai; Freeman, Robin; Carbone, Chris

    2015-12-01

    The movement rates of sharks are intrinsically linked to foraging ecology, predator-prey dynamics and wider ecosystem functioning in marine systems. During ram ventilation, however, shark movement rates are linked not only to ecological parameters, but also to physiology, as minimum speeds are required to provide sufficient water flow across the gills to maintain metabolism. We develop a geometric model predicting a positive scaling relationship between swim speeds in relation to body size and ultimately shark metabolism, taking into account estimates for the scaling of gill dimensions. Empirical data from 64 studies (26 species) were compiled to test our model while controlling for the influence of phylogenetic similarity between related species. Our model predictions were found to closely resemble the observed relationships from tracked sharks, providing a means to infer mobility in particularly intractable species. PMID:26631246

  19. Variation of foraging rate and wing loading, but not resting metabolic rate scaling, of insect pollinators

    NASA Astrophysics Data System (ADS)

    Terblanche, John S.; Anderson, Bruce

    2010-08-01

    Morphological, physiological and behavioural variation with body size (i.e. scaling) may affect costs of living in a particular environment for insects and, ultimately, pollination or foraging success. However, few studies have directly assessed the scaling of these traits at the species level. Using two similar-sized pollinator species (the hawkmoth Macroglossum trochilus and the fly Moegistorhynchus longirostrus), we compare intraspecific scaling relationships of resting metabolic rate (RMR), foraging rate (FR) and wing loading (WL) to address this paucity of data. Scaling of RMR was similar for both taxa although the intercepts for the relationships differed. However, these two species showed variation in WL scaling relationships and fundamentally different FR scaling. For M. longirostrus, FR scaling was positive but non-significantly related to body mass while for M. trochilus FR scaling was negative. This suggests that variation in FR and WL, but not RMR scaling, among these flies and hawkmoths may impose significant energetic costs which could affect animal-plant interactions in the wild.

  20. Fermentative Production of the Diamine Putrescine: System Metabolic Engineering of Corynebacterium Glutamicum

    PubMed Central

    Nguyen, Anh Q. D.; Schneider, Jens; Reddy, Gajendar Komati; Wendisch, Volker F.

    2015-01-01

    Corynebacterium glutamicum shows great potential for the production of the glutamate-derived diamine putrescine, a monomeric compound of polyamides. A genome-scale stoichiometric model of a C. glutamicum strain with reduced ornithine transcarbamoylase activity, derepressed arginine biosynthesis, and an anabolic plasmid-addiction system for heterologous expression of E. coli ornithine decarboxylase gene speC was investigated by flux balance analysis with respect to its putrescine production potential. Based on these simulations, enhancing glycolysis and anaplerosis by plasmid-borne overexpression of the genes for glyceraldehyde 3-phosphate dehydrogenase and pyruvate carboxylase as well as reducing 2-oxoglutarate dehydrogenase activity were chosen as targets for metabolic engineering. Changing the translational start codon of the chromosomal gene for 2-oxoglutarate dehydrogenase subunit E1o to the less preferred TTG and changing threonine 15 of OdhI to alanine reduced 2-oxoglutarate dehydrogenase activity about five fold and improved putrescine titers by 28%. Additional engineering steps improved further putrescine production with the largest contributions from preventing the formation of the by-product N-acetylputrescine by deletion of spermi(di)ne N-acetyltransferase gene snaA and from overexpression of the gene for a feedback-resistant N-acetylglutamate kinase variant. The resulting C. glutamicum strain NA6 obtained by systems metabolic engineering accumulated two fold more putrescine than the base strain, i.e., 58.1 ± 0.2 mM, and showed a specific productivity of 0.045 g·g−1·h−1 and a yield on glucose of 0.26 g·g−1. PMID:25919117

  1. Fermentative production of the diamine putrescine: system metabolic engineering of corynebacterium glutamicum.

    PubMed

    Nguyen, Anh Q D; Schneider, Jens; Reddy, Gajendar Komati; Wendisch, Volker F

    2015-01-01

    Corynebacterium glutamicum shows great potential for the production of the glutamate-derived diamine putrescine, a monomeric compound of polyamides. A genome-scale stoichiometric model of a C. glutamicum strain with reduced ornithine transcarbamoylase activity, derepressed arginine biosynthesis, and an anabolic plasmid-addiction system for heterologous expression of E. coli ornithine decarboxylase gene speC was investigated by flux balance analysis with respect to its putrescine production potential. Based on these simulations, enhancing glycolysis and anaplerosis by plasmid-borne overexpression of the genes for glyceraldehyde 3-phosphate dehydrogenase and pyruvate carboxylase as well as reducing 2-oxoglutarate dehydrogenase activity were chosen as targets for metabolic engineering. Changing the translational start codon of the chromosomal gene for 2-oxoglutarate dehydrogenase subunit E1o to the less preferred TTG and changing threonine 15 of OdhI to alanine reduced 2-oxoglutarate dehydrogenase activity about five fold and improved putrescine titers by 28%. Additional engineering steps improved further putrescine production with the largest contributions from preventing the formation of the by-product N-acetylputrescine by deletion of spermi(di)ne N-acetyltransferase gene snaA and from overexpression of the gene for a feedback-resistant N-acetylglutamate kinase variant. The resulting C. glutamicum strain NA6 obtained by systems metabolic engineering accumulated two fold more putrescine than the base strain, i.e., 58.1 ± 0.2 mM, and showed a specific productivity of 0.045 g·g-1·h-1 and a yield on glucose of 0.26 g·g-1. PMID:25919117

  2. An extended bioreaction database that significantly improves reconstruction and analysis of genome-scale metabolic networks.

    PubMed

    Stelzer, Michael; Sun, Jibin; Kamphans, Tom; Fekete, Sándor P; Zeng, An-Ping

    2011-11-01

    The bioreaction database established by Ma and Zeng (Bioinformatics, 2003, 19, 270-277) for in silico reconstruction of genome-scale metabolic networks has been widely used. Based on more recent information in the reference databases KEGG LIGAND and Brenda, we upgrade the bioreaction database in this work by almost doubling the number of reactions from 3565 to 6851. Over 70% of the reactions have been manually updated/revised in terms of reversibility, reactant pairs, currency metabolites and error correction. For the first time, 41 spontaneous sugar mutarotation reactions are introduced into the biochemical database. The upgrade significantly improves the reconstruction of genome scale metabolic networks. Many gaps or missing biochemical links can be recovered, as exemplified with three model organisms Homo sapiens, Aspergillus niger, and Escherichia coli. The topological parameters of the constructed networks were also largely affected, however, the overall network structure remains scale-free. Furthermore, we consider the problem of computing biologically feasible shortest paths in reconstructed metabolic networks. We show that these paths are hard to compute and present solutions to find such paths in networks of small and medium size. PMID:21952610

  3. Endogenous fructose production and metabolism in the liver contributes to the development of metabolic syndrome

    PubMed Central

    Lanaspa, Miguel A; Ishimoto, Takuji; Li, Nanxing; Cicerchi, Christina; Orlicky, David J.; Ruzicky, Philip; Rivard, Christopher; Inaba, Shinichiro; Roncal-Jimenez, Carlos A.; Bales, Elise S.; Diggle, Christine P.; Asipu, Aruna; Petrash, J. Mark; Kosugi, Tomoki; Maruyama, Shoichi; Sanchez-Lozada, Laura G.; McManaman, James L.; Bonthron, David T; Sautin, Yuri Y.; Johnson, Richard J.

    2013-01-01

    Carbohydrates with high glycemic index are proposed to promote the development of obesity, insulin resistance and fatty liver, but the mechanism by which this occurs remains unknown. High serum glucose concentrations glucose are known to induce the polyol pathway and increase fructose generation in the liver. Here we show that this hepatic, endogenously-produced fructose causes systemic metabolic changes. We demonstrate that mice unable to metabolize fructose are protected from an increase in energy intake and body weight, visceral obesity, fatty liver, elevated insulin levels and hyperleptinemia after exposure to 10% glucose for 14 weeks. In normal mice, glucose consumption is accompanied by aldose reductase and polyol pathway activation in steatotic areas. In this regard, we show that aldose reductase deficient mice were protected against glucose-induced fatty liver. We conclude that endogenous fructose generation and metabolism in the liver represents an important mechanism whereby glucose promotes the development of metabolic syndrome. PMID:24022321

  4. Metabolic engineering approaches for production of biochemicals in food and medicinal plants.

    PubMed

    Wilson, Sarah A; Roberts, Susan C

    2014-04-01

    Historically, plants are a vital source of nutrients and pharmaceuticals. Recent advances in metabolic engineering have made it possible to not only increase the concentration of desired compounds, but also introduce novel biosynthetic pathways to a variety of species, allowing for enhanced nutritional or commercial value. To improve metabolic engineering capabilities, new transformation techniques have been developed to allow for gene specific silencing strategies or stacking of multiple genes within the same region of the chromosome. The 'omics' era has provided a new resource for elucidation of uncharacterized biosynthetic pathways, enabling novel metabolic engineering approaches. These resources are now allowing for advanced metabolic engineering of plant production systems, as well as the synthesis of increasingly complex products in engineered microbial hosts. The status of current metabolic engineering efforts is highlighted for the in vitro production of paclitaxel and the in vivo production of β-carotene in Golden Rice and other food crops. PMID:24556196

  5. A common genetic basis to the origin of the leaf economics spectrum and metabolic scaling allometry.

    PubMed

    Vasseur, François; Violle, Cyrille; Enquist, Brian J; Granier, Christine; Vile, Denis

    2012-10-01

    Many facets of plant form and function are reflected in general cross-taxa scaling relationships. Metabolic scaling theory (MST) and the leaf economics spectrum (LES) have each proposed unifying frameworks and organisational principles to understand the origin of botanical diversity. Here, we test the evolutionary assumptions of MST and the LES using a cross of two genetic variants of Arabidopsis thaliana. We show that there is enough genetic variation to generate a large fraction of variation in the LES and MST scaling functions. The progeny sharing the parental, naturally occurring, allelic combinations at two pleiotropic genes exhibited the theorised optimum ¾ allometric scaling of growth rate and intermediate leaf economics. Our findings: (1) imply that a few pleiotropic genes underlie many plant functional traits and life histories; (2) unify MST and LES within a common genetic framework and (3) suggest that observed intermediate size and longevity in natural populations originate from stabilising selection to optimise physiological trade-offs. PMID:22856883

  6. Metabolic model of Synechococcus sp. PCC 7002: Prediction of flux distribution and network modification for enhanced biofuel production.

    PubMed

    Hendry, John I; Prasannan, Charulata B; Joshi, Aditi; Dasgupta, Santanu; Wangikar, Pramod P

    2016-08-01

    Flux Balance Analysis was performed with the Genome Scale Metabolic Model of a fast growing cyanobacterium Synechococcus sp. PCC 7002 to gain insights that would help in engineering the organism as a production host. Gene essentiality and synthetic lethality analysis revealed a reduced metabolic robustness under genetic perturbation compared to the heterotrophic bacteria Escherichia coli. Under glycerol heterotrophy the reducing equivalents were generated from tricarboxylic acid cycle rather than the oxidative pentose phosphate pathway. During mixotrophic growth in glycerol the photosynthetic electron transport chain was predominantly used for ATP synthesis with a photosystem I/photosystem II flux ratio higher than that observed under autotrophy. An exhaustive analysis of all possible double reaction knock outs was performed to reroute fixed carbon towards ethanol and butanol production. It was predicted that only ∼10% of fixed carbon could be diverted for ethanol and butanol production. PMID:27036328

  7. Heterologous production of α-farnesene in metabolically engineered strains of Yarrowia lipolytica.

    PubMed

    Yang, Xia; Nambou, Komi; Wei, Liujing; Hua, Qiang

    2016-09-01

    Herein, we studied the heterologous production of α-farnesene, a valuable sesquiterpene with various biotechnological applications, by metabolic engineering of Yarrowia lipolytica. Different overexpression vectors harboring combinations of tHMG1, IDI, ERG20 and codon-optimized α-farnesene synthase (OptFS) genes were constructed and integrated into the genome of Y. lipolytica Po1h. The engineered strain produced 57.08±1.43mg/L of α-farnesene corresponding to 20.8-fold increase over the initial production of 2.75±0.29mg/L in the YPD medium in shake flasks. Bioreactor scale-up in PM medium led to α-farnesene concentration of 259.98±2.15mg/L with α-farnesene to biomass ratio of 33.98±1.51mg/g, which was a 94.5-fold increase over the initial production. This first report on α-farnesene synthesis in Y. lipolytica lays a foundation for future research on production of sesquitepenes in Y. lipolytica and other closest yeast species and will potentially contribute in its industrial production. PMID:27347651

  8. Metabolic response to air temperature and wind in day-old mallards and a standard operative temperature scale

    USGS Publications Warehouse

    Bakken, G.S.; Reynolds, P.S.; Kenow, K.P.; Korschgen, C.E.; Boysen, A.F.

    1999-01-01

    Most duckling mortality occurs during the week following hatching and is often associated with cold, windy, wet weather and scattering of the brood. We estimated the thermoregulatory demands imposed by cold, windy weather on isolated 1-d-old mallard (Anas platyrhynchos) ducklings resting in cover. We measured O-2 consumption and evaporative water loss at air temperatures from 5 degrees to 25 degrees C and wind speeds of 0.1, 0.2, 0.5, and 1.0 mis. Metabolic heat production increased as wind increased or temperature decreased but was less sensitive to wind than that of either adult passerines or small mammals. Evaporative heat loss ranged from 5% to 17% of heat production. Evaporative heal loss and the ratio of evaporative heat loss to metabolic heat production was significantly lower in rest phase. These data were used to define a standard operative temperature (T-es) scale for night or heavy overcast conditions. An increase of wind speed from 0.1 to 1 mis decreased T-es by 3 degrees-5 degrees C.

  9. Production, transport, and metabolism of ethanol in eastern cottonwood

    SciTech Connect

    MacDonald, R.C.

    1991-01-01

    In plant tissues, the production of acetaldehyde and ethanol are usually thought to occur as a mechanism to allow tolerance of hypoxic conditions. Acetaldehyde and ethanol were found to be common in vascular cambium and the transpiration stream of trees. Ethanol concentrations in the vascular cambium of Populus deltoides were not changed by placing logs from nonflooded trees in a pure oxygen environment for as long as 96 h, but increased by almost 3 orders of magnitude when exposed to low external pO[sub 2]s. Ethanol is present in the xylem sap of flooded and nonflooded trees. Because of the constitutive presence of alcohol dehydrogenase in the mature leaves of woody plants, it was hypothesized that the leaves and shoots of trees had the ability to metabolize ethanol supplied by the transpiration stream. 1-[[sup 14]C]ethanol was supplied to excised leaves and shoots of Populus deltoides Bartr. in short- and long-term experiments. Greater than 99% of the radiolabel was incorporated into plant tissue in short-term experiments, with more than 95% of the label remaining in plant tissue after 24 h. Very little label reached the leaf mesophyll cells of excised shoots, as revealed by autoradiography. Radiolabel appeared primarily in the water- and chloroform-soluble fractions in short-term experiments, while in long-term experiments, label was also incorporated into protein. When labelled ethanol was supplied to excised petioles in a 5 min pulse, 41% of the label was incorporated into organic acids. Some label was also incorporated into amino acids, protein, and the chloroform-soluble fraction, with very little appearing in neutral sugars, starch, or the insoluble pellet. Labelled organic acids were separated by HPLC, and were comprised of acetate, isocitrate, [alpha]-ketoglutarate, and succinate. There was no apparent incorporation of label into phosphorylated compounds.

  10. Metabolic pathway engineering for fatty acid ethyl ester production in Saccharomyces cerevisiae using stable chromosomal integration.

    PubMed

    de Jong, Bouke Wim; Shi, Shuobo; Valle-Rodríguez, Juan Octavio; Siewers, Verena; Nielsen, Jens

    2015-03-01

    Fatty acid ethyl esters are fatty acid derived molecules similar to first generation biodiesel (fatty acid methyl esters; FAMEs) which can be produced in a microbial cell factory. Saccharomyces cerevisiae is a suitable candidate for microbial large scale and long term cultivations, which is the typical industrial production setting for biofuels. It is crucial to conserve the metabolic design of the cell factory during industrial cultivation conditions that require extensive propagation. Genetic modifications therefore have to be introduced in a stable manner. Here, several metabolic engineering strategies for improved production of fatty acid ethyl esters in S. cerevisiae were combined and the genes were stably expressed from the organisms' chromosomes. A wax ester synthase (ws2) was expressed in different yeast strains with an engineered acetyl-CoA and fatty acid metabolism. Thus, we compared expression of ws2 with and without overexpression of alcohol dehydrogenase (ADH2), acetaldehyde dehydrogenase (ALD6) and acetyl-CoA synthetase (acs SE (L641P) ) and further evaluated additional overexpression of a mutant version of acetyl-CoA decarboxylase (ACC1 (S1157A,S659A) ) and the acyl-CoA binding protein (ACB1). The combined engineering efforts of the implementation of ws2, ADH2, ALD6 and acs SE (L641P) , ACC1 (S1157A,S659A) and ACB1 in a S. cerevisiae strain lacking storage lipid formation (are1Δ, are2Δ, dga1Δ and lro1Δ) and β-oxidation (pox1Δ) resulted in a 4.1-fold improvement compared with sole expression of ws2 in S. cerevisiae. PMID:25422103

  11. Scaling properties of light-cluster production

    NASA Astrophysics Data System (ADS)

    Chajecki, Zbigniew; Youngs, Michael; Coupland, Daniel D.; Lynch, William; Tsang, Betty; Chbihi, Abdelouahad; Danielewicz, Pawel; Desouza, Romualdo; Famiano, Michael; Ghosh, Tilak; Giacherio, B.; Henzl, Vlad; Henzlova, Daniela; Hudan, Sylvie; Kilburn, Micha; Lee, Jenny; Lu, Fei; Rogers, Andrew; Russotto, Paulo; Verde, Giuseppe; Sanetullaev, Alisher; Showalter, Rachel; Sobotka, Lee; Wallace, Mark; Winkelbauer, Jack

    2014-09-01

    We show, using the experimental data from Ca+Ca and Sn+Sn collisions, that ratios of light-particle energy spectra display scaling properties that can be accurately described by effective local chemical potentials. This demonstrates the equivalence of t/3He and n/p spectral ratios and provides an essential test of theoretical predictions of isotopically resolved light-particle spectra. In addition, this approach allows direct comparisons of many theoretical n/p spectral ratios to experiments where charged-particle spectra but not neutron spectra are accurately measured. Such experiments may provide much more quantitative constraints on the density and momentum dependence of the symmetry energy.

  12. Metabolic Engineering of Escherichia coli for the Production of Xylonate

    PubMed Central

    Cao, Yujin; Xian, Mo; Zou, Huibin; Zhang, Haibo

    2013-01-01

    Xylonate is a valuable chemical for versatile applications. Although the chemical synthesis route and microbial conversion pathway were established decades ago, no commercial production of xylonate has been obtained so far. In this study, the industrially important microorganism Escherichia coli was engineered to produce xylonate from xylose. Through the coexpression of a xylose dehydrogenase (xdh) and a xylonolactonase (xylC) from Caulobacter crescentus, the recombinant strain could convert 1 g/L xylose to 0.84 g/L xylonate and 0.10 g/L xylonolactone after being induced for 12 h. Furthermore, the competitive pathway for xylose catabolism in E. coli was blocked by disrupting two genes (xylA and xylB) encoding xylose isomerase and xylulose kinase. Under fed-batch conditions, the finally engineered strain produced up to 27.3 g/L xylonate and 1.7 g/L xylonolactone from 30 g/L xylose, about 88% of the theoretical yield. These results suggest that the engineered E. coli strain has a promising perspective for large-scale production of xylonate. PMID:23861757

  13. Tree Morphologic Plasticity Explains Deviation from Metabolic Scaling Theory in Semi-Arid Conifer Forests, Southwestern USA.

    PubMed

    Swetnam, Tyson L; O'Connor, Christopher D; Lynch, Ann M

    2016-01-01

    A significant concern about Metabolic Scaling Theory (MST) in real forests relates to consistent differences between the values of power law scaling exponents of tree primary size measures used to estimate mass and those predicted by MST. Here we consider why observed scaling exponents for diameter and height relationships deviate from MST predictions across three semi-arid conifer forests in relation to: (1) tree condition and physical form, (2) the level of inter-tree competition (e.g. open vs closed stand structure), (3) increasing tree age, and (4) differences in site productivity. Scaling exponent values derived from non-linear least-squares regression for trees in excellent condition (n = 381) were above the MST prediction at the 95% confidence level, while the exponent for trees in good condition were no different than MST (n = 926). Trees that were in fair or poor condition, characterized as diseased, leaning, or sparsely crowned had exponent values below MST predictions (n = 2,058), as did recently dead standing trees (n = 375). Exponent value of the mean-tree model that disregarded tree condition (n = 3,740) was consistent with other studies that reject MST scaling. Ostensibly, as stand density and competition increase trees exhibited greater morphological plasticity whereby the majority had characteristically fair or poor growth forms. Fitting by least-squares regression biases the mean-tree model scaling exponent toward values that are below MST idealized predictions. For 368 trees from Arizona with known establishment dates, increasing age had no significant impact on expected scaling. We further suggest height to diameter ratios below MST relate to vertical truncation caused by limitation in plant water availability. Even with environmentally imposed height limitation, proportionality between height and diameter scaling exponents were consistent with the predictions of MST. PMID:27391084

  14. Tree Morphologic Plasticity Explains Deviation from Metabolic Scaling Theory in Semi-Arid Conifer Forests, Southwestern USA

    PubMed Central

    O’Connor, Christopher D.; Lynch, Ann M.

    2016-01-01

    A significant concern about Metabolic Scaling Theory (MST) in real forests relates to consistent differences between the values of power law scaling exponents of tree primary size measures used to estimate mass and those predicted by MST. Here we consider why observed scaling exponents for diameter and height relationships deviate from MST predictions across three semi-arid conifer forests in relation to: (1) tree condition and physical form, (2) the level of inter-tree competition (e.g. open vs closed stand structure), (3) increasing tree age, and (4) differences in site productivity. Scaling exponent values derived from non-linear least-squares regression for trees in excellent condition (n = 381) were above the MST prediction at the 95% confidence level, while the exponent for trees in good condition were no different than MST (n = 926). Trees that were in fair or poor condition, characterized as diseased, leaning, or sparsely crowned had exponent values below MST predictions (n = 2,058), as did recently dead standing trees (n = 375). Exponent value of the mean-tree model that disregarded tree condition (n = 3,740) was consistent with other studies that reject MST scaling. Ostensibly, as stand density and competition increase trees exhibited greater morphological plasticity whereby the majority had characteristically fair or poor growth forms. Fitting by least-squares regression biases the mean-tree model scaling exponent toward values that are below MST idealized predictions. For 368 trees from Arizona with known establishment dates, increasing age had no significant impact on expected scaling. We further suggest height to diameter ratios below MST relate to vertical truncation caused by limitation in plant water availability. Even with environmentally imposed height limitation, proportionality between height and diameter scaling exponents were consistent with the predictions of MST. PMID:27391084

  15. Metabolism

    MedlinePlus

    Metabolism refers to all the physical and chemical processes in the body that convert or use energy, ... Tortora GJ, Derrickson BH. Metabolism. In: Tortora GJ, Derrickson BH. Principles of Anatomy and Physiology . 14th ed. Hoboken, NJ: John H Wiley and Sons; 2013: ...

  16. Scaling up from traits to communities to ecosystems across broad climate gradients: Testing Metabolic Scaling Theories predictions for forests

    NASA Astrophysics Data System (ADS)

    Enquist, B. J.; Michaletz, S. T.; Buzzard, V.

    2015-12-01

    Key insights in global ecology will come from mechanistically linking pattern and process across scales. Macrosystems ecology specifically attempts to link ecological processes across spatiotemporal scales. The goal s to link the processing of energy and nutrients from cells all the way ecosystems and to understand how shifting climate influences ecosystem processes. Using new data collected from NSF funded Macrosystems project we report on new findings from forests sites across a broad temperature gradient. Our study sites span tropical, temperate, and high elevation forests we assess several key predictions and assumptions of Metabolic Scaling Theory (MST) as well as several other competing hypotheses for the role of climate, light, and plant traits on influencing forest demography and forest ecosystems. Specifically, we assess the importance of plant size, light limitation, size structure, and various climatic factors on forest growth, demography, and ecosystem functioning. We provide some of the first systematic tests of several key predictions from MST. We show that MST predictions are largely upheld and that new insights from assessing theories predictions yields new observations and findings that help modify and extend MST's predictions and applicability. We discuss how theory is critically needed to further our understanding of how to scale pattern and process in ecology - from traits to ecosystems - in order to develop a more predictive global change biology.

  17. ReacKnock: Identifying Reaction Deletion Strategies for Microbial Strain Optimization Based on Genome-Scale Metabolic Network

    PubMed Central

    Xu, Zixiang; Zheng, Ping; Sun, Jibin; Ma, Yanhe

    2013-01-01

    Gene knockout has been used as a common strategy to improve microbial strains for producing chemicals. Several algorithms are available to predict the target reactions to be deleted. Most of them apply mixed integer bi-level linear programming (MIBLP) based on metabolic networks, and use duality theory to transform bi-level optimization problem of large-scale MIBLP to single-level programming. However, the validity of the transformation was not proved. Solution of MIBLP depends on the structure of inner problem. If the inner problem is continuous, Karush-Kuhn-Tucker (KKT) method can be used to reformulate the MIBLP to a single-level one. We adopt KKT technique in our algorithm ReacKnock to attack the intractable problem of the solution of MIBLP, demonstrated with the genome-scale metabolic network model of E. coli for producing various chemicals such as succinate, ethanol, threonine and etc. Compared to the previous methods, our algorithm is fast, stable and reliable to find the optimal solutions for all the chemical products tested, and able to provide all the alternative deletion strategies which lead to the same industrial objective. PMID:24348984

  18. Systems metabolic engineering of Corynebacterium glutamicum for production of the chemical chaperone ectoine

    PubMed Central

    2013-01-01

    Background The stabilizing and function-preserving effects of ectoines have attracted considerable biotechnological interest up to industrial scale processes for their production. These rely on the release of ectoines from high-salinity-cultivated microbial producer cells upon an osmotic down-shock in rather complex processor configurations. There is growing interest in uncoupling the production of ectoines from the typical conditions required for their synthesis, and instead design strains that naturally release ectoines into the medium without the need for osmotic changes, since the use of high-salinity media in the fermentation process imposes notable constraints on the costs, design, and durability of fermenter systems. Results Here, we used a Corynebacterium glutamicum strain as a cellular chassis to establish a microbial cell factory for the biotechnological production of ectoines. The implementation of a mutant aspartokinase enzyme ensured efficient supply of L-aspartate-beta-semialdehyde, the precursor for ectoine biosynthesis. We further engineered the genome of the basic C. glutamicum strain by integrating a codon-optimized synthetic ectABCD gene cluster under expressional control of the strong and constitutive C. glutamicum tuf promoter. The resulting recombinant strain produced ectoine and excreted it into the medium; however, lysine was still found as a by-product. Subsequent inactivation of the L-lysine exporter prevented the undesired excretion of lysine while ectoine was still exported. Using the streamlined cell factory, a fed-batch process was established that allowed the production of ectoine with an overall productivity of 6.7 g L-1 day-1 under growth conditions that did not rely on the use of high-salinity media. Conclusions The present study describes the construction of a stable microbial cell factory for recombinant production of ectoine. We successfully applied metabolic engineering strategies to optimize its synthetic production in the

  19. Why does offspring size affect performance? Integrating metabolic scaling with life-history theory.

    PubMed

    Pettersen, Amanda K; White, Craig R; Marshall, Dustin J

    2015-11-22

    Within species, larger offspring typically outperform smaller offspring. While the relationship between offspring size and performance is ubiquitous, the cause of this relationship remains elusive. By linking metabolic and life-history theory, we provide a general explanation for why larger offspring perform better than smaller offspring. Using high-throughput respirometry arrays, we link metabolic rate to offspring size in two species of marine bryozoan. We found that metabolism scales allometrically with offspring size in both species: while larger offspring use absolutely more energy than smaller offspring, larger offspring use proportionally less of their maternally derived energy throughout the dependent, non-feeding phase. The increased metabolic efficiency of larger offspring while dependent on maternal investment may explain offspring size effects-larger offspring reach nutritional independence (feed for themselves) with a higher proportion of energy relative to structure than smaller offspring. These findings offer a potentially universal explanation for why larger offspring tend to perform better than smaller offspring but studies on other taxa are needed. PMID:26559952

  20. Genome-scale reconstruction of metabolic network for a halophilic extremophile, Chromohalobacter salexigens DSM 3043

    PubMed Central

    2011-01-01

    Background Chromohalobacter salexigens (formerly Halomonas elongata DSM 3043) is a halophilic extremophile with a very broad salinity range and is used as a model organism to elucidate prokaryotic osmoadaptation due to its strong euryhaline phenotype. Results C. salexigens DSM 3043's metabolism was reconstructed based on genomic, biochemical and physiological information via a non-automated but iterative process. This manually-curated reconstruction accounts for 584 genes, 1386 reactions, and 1411 metabolites. By using flux balance analysis, the model was extensively validated against literature data on the C. salexigens phenotypic features, the transport and use of different substrates for growth as well as against experimental observations on the uptake and accumulation of industrially important organic osmolytes, ectoine, betaine, and its precursor choline, which play important roles in the adaptive response to osmotic stress. Conclusions This work presents the first comprehensive genome-scale metabolic model of a halophilic bacterium. Being a useful guide for identification and filling of knowledge gaps, the reconstructed metabolic network iOA584 will accelerate the research on halophilic bacteria towards application of systems biology approaches and design of metabolic engineering strategies. PMID:21251315

  1. Debottlenecking recombinant protein production in Bacillus megaterium under large-scale conditions--targeted precursor feeding designed from metabolomics.

    PubMed

    Korneli, Claudia; Bolten, Christoph Josef; Godard, Thibault; Franco-Lara, Ezequiel; Wittmann, Christoph

    2012-06-01

    In the present work the impact of large production scale was investigated for Bacillus megaterium expressing green fluorescent protein (GFP). Specifically designed scale-down studies, mimicking the intermittent and continuous nutrient supply of large- and small-scale processes, were carried out for this purpose. The recombinant strain revealed a 40% reduced GFP yield for the large-scale conditions. In line with extended carbon loss via formation of acetate and carbon dioxide, this indicated obvious limitations in the underlying metabolism of B. megaterium under the large-scale conditions. Quantitative analysis of intracellular amino acids via validated fast filtration protocols revealed that their level strongly differed between the two scenarios. During cultivation in large-scale set-up, the availability of most amino acids, serving as key building blocks of the recombinant protein, was substantially reduced. This was most pronounced for tryptophan, aspartate, histidine, glutamine, and lysine. In contrast alanine was increased, probably related to a bottleneck at the level of pyruvate which also triggered acetate overflow metabolism. The pre-cursor quantifications could then be exploited to verify the presumed bottlenecks and improve recombinant protein production under large-scale conditions. Addition of only 5 mM tryptophan, aspartate, histidine, glutamine, and lysine to the feed solution increased the GFP yield by 100%. This rational concept of driving the lab scale productivity of recombinant microorganisms under suboptimal feeding conditions emulating large scale can easily be extended to other processes and production hosts. PMID:22252649

  2. Biodiesel: Small Scale Production and Quality Requirements

    NASA Astrophysics Data System (ADS)

    van Gerpen, Jon

    Biodiesel is produced by reacting vegetable oils or animal fats with alcohol in the presence of an alkaline catalyst. The resulting methyl esters, which are the biodiesel fuel, are separated from the by-product glycerin, and then washed with water and dehydrated to produce fuel that must meet standardized specifications. Degraded oils containing high levels of free fatty acids can also be converted to biodiesel, but pretreatment with acid-catalyzed esterification is required. The resulting fuel is suitable for use as a neat fuel in diesel engines or blended with conventional diesel fuel.

  3. Exact quantification of cellular robustness in genome-scale metabolic networks

    PubMed Central

    Gerstl, Matthias P.; Klamt, Steffen; Jungreuthmayer, Christian; Zanghellini, Jürgen

    2016-01-01

    Motivation: Robustness, the ability of biological networks to uphold their functionality in spite of perturbations, is a key characteristic of all living systems. Although several theoretical approaches have been developed to formalize robustness, it still eludes an exact quantification. Here, we present a rigorous and quantitative approach for the structural robustness of metabolic networks by measuring their ability to tolerate random reaction (or gene) knockouts. Results: In analogy to reliability theory, based on an explicit consideration of all possible knockout sets, we exactly quantify the probability of failure for a given network function (e.g. growth). This measure can be computed if the network’s minimal cut sets (MSCs) are known. We show that even in genome-scale metabolic networks the probability of (network) failure can be reliably estimated from MSCs with lowest cardinalities. We demonstrate the applicability of our theory by analyzing the structural robustness of multiple Enterobacteriaceae and Blattibacteriaceae and show a dramatically low structural robustness for the latter. We find that structural robustness develops from the ability to proliferate in multiple growth environments consistent with experimentally found knowledge. Conclusion: The probability of (network) failure provides thus a reliable and easily computable measure of structural robustness and redundancy in (genome-scale) metabolic networks. Availability and implementation: Source code is available under the GNU General Public License at https://github.com/mpgerstl/networkRobustnessToolbox. Contact: juergen.zanghellini@boku.ac.at Supplementary information: Supplementary data are available at Bioinformatics online. PMID:26543173

  4. The allometry of the smallest: superlinear scaling of microbial metabolic rates in the Atlantic Ocean.

    PubMed

    García, Francisca C; García-Martín, Enma Elena; Taboada, Fernando González; Sal, Sofía; Serret, Pablo; López-Urrutia, Ángel

    2016-05-01

    Prokaryotic planktonic organisms are small in size but largely relevant in marine biogeochemical cycles. Due to their reduced size range (0.2 to 1 μm in diameter), the effects of cell size on their metabolism have been hardly considered and are usually not examined in field studies. Here, we show the results of size-fractionated experiments of marine microbial respiration rate along a latitudinal transect in the Atlantic Ocean. The scaling exponents obtained from the power relationship between respiration rate and size were significantly higher than one. This superlinearity was ubiquitous across the latitudinal transect but its value was not universal revealing a strong albeit heterogeneous effect of cell size on microbial metabolism. Our results suggest that the latitudinal differences observed are the combined result of changes in cell size and composition between functional groups within prokaryotes. Communities where the largest size fraction was dominated by prokaryotic cyanobacteria, especially Prochlorococcus, have lower allometric exponents. We hypothesize that these larger, more complex prokaryotes fall close to the evolutionary transition between prokaryotes and protists, in a range where surface area starts to constrain metabolism and, hence, are expected to follow a scaling closer to linearity. PMID:26636550

  5. Elucidation and Structural Analysis of Conserved Pools for Genome-Scale Metabolic Reconstructions

    PubMed Central

    Nikolaev, Evgeni V.; Burgard, Anthony P.; Maranas, Costas D.

    2005-01-01

    In this article, we introduce metabolite concentration coupling analysis (MCCA) to study conservation relationships for metabolite concentrations in genome-scale metabolic networks. The analysis allows the global identification of subsets of metabolites whose concentrations are always coupled within common conserved pools. Also, the minimal conserved pool identification (MCPI) procedure is developed for elucidating conserved pools for targeted metabolites without computing the entire basis conservation relationships. The approaches are demonstrated on genome-scale metabolic reconstructions of Helicobacter pylori, Escherichia coli, and Saccharomyces cerevisiae. Despite significant differences in the size and complexity of the examined organism's models, we find that the concentrations of nearly all metabolites are coupled within a relatively small number of subsets. These correspond to the overall exchange of carbon molecules into and out of the networks, interconversion of energy and redox cofactors, and the transfer of nitrogen, sulfur, phosphate, coenzyme A, and acyl carrier protein moieties among metabolites. The presence of large conserved pools can be viewed as global biophysical barriers protecting cellular systems from stresses, maintaining coordinated interconversions between key metabolites, and providing an additional mode of global metabolic regulation. The developed approaches thus provide novel and versatile tools for elucidating coupling relationships between metabolite concentrations with implications in biotechnological and medical applications. PMID:15489308

  6. Pulmonary diffusional screening and the scaling laws of mammalian metabolic rates

    NASA Astrophysics Data System (ADS)

    Hou, Chen; Mayo, Michael

    2011-12-01

    Theoretical considerations suggest that the mammalian metabolic rate is linearly proportional to the surface areas of mitochondria, capillary, and alveolar membranes. However, the scaling exponents of these surface areas to the mammals' body mass (approximately 0.9-1) are higher than exponents of the resting metabolic rate (RMR) to body mass (approximately 0.75), although similar to the one of exercise metabolic rate (EMR); the underlying physiological cause of this mismatch remains unclear. The analysis presented here shows that discrepancies between the scaling exponents of RMR and the relevant surface areas may originate from, at least for the system of alveolar membranes in mammalian lungs, the facts that (i) not all of the surface area is involved in the gas exchange and (ii) that larger mammals host a smaller effective surface area that participates in the material exchange rate. A result of these facts is that lung surface areas unused at rest are activated under heavy breathing conditions (e.g., exercise), wherein larger mammals support larger activated surface areas that provide a higher capability to increase the gas-exchange rate, allowing for mammals to meet, for example, the high energetic demands of foraging and predation.

  7. Integrating Kinetic Model of E. coli with Genome Scale Metabolic Fluxes Overcomes Its Open System Problem and Reveals Bistability in Central Metabolism

    PubMed Central

    Mannan, Ahmad A.; Toya, Yoshihiro; Shimizu, Kazuyuki; McFadden, Johnjoe; Kierzek, Andrzej M.; Rocco, Andrea

    2015-01-01

    An understanding of the dynamics of the metabolic profile of a bacterial cell is sought from a dynamical systems analysis of kinetic models. This modelling formalism relies on a deterministic mathematical description of enzyme kinetics and their metabolite regulation. However, it is severely impeded by the lack of available kinetic information, limiting the size of the system that can be modelled. Furthermore, the subsystem of the metabolic network whose dynamics can be modelled is faced with three problems: how to parameterize the model with mostly incomplete steady state data, how to close what is now an inherently open system, and how to account for the impact on growth. In this study we address these challenges of kinetic modelling by capitalizing on multi-‘omics’ steady state data and a genome-scale metabolic network model. We use these to generate parameters that integrate knowledge embedded in the genome-scale metabolic network model, into the most comprehensive kinetic model of the central carbon metabolism of E. coli realized to date. As an application, we performed a dynamical systems analysis of the resulting enriched model. This revealed bistability of the central carbon metabolism and thus its potential to express two distinct metabolic states. Furthermore, since our model-informing technique ensures both stable states are constrained by the same thermodynamically feasible steady state growth rate, the ensuing bistability represents a temporal coexistence of the two states, and by extension, reveals the emergence of a phenotypically heterogeneous population. PMID:26469081

  8. Whole-body CO2 production as an index of the metabolic response to sepsis

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Whole-body carbon dioxide (CO2) production (RaCO2) is an index of substrate oxidation and energy expenditure; therefore, it may provide information about the metabolic response to sepsis. Using stable isotope techniques, we determined RaCO2 and its relationship to protein and glucose metabolism in m...

  9. Expanded bed absorption from laboratory to production scale

    SciTech Connect

    Johansson, S.; Akervall, A.; Hagel, L.

    1995-12-01

    Expanded bed adsorption is a new technique using stable homogeneous fluidization for initial recovery of a product from crude fermentation broth. The technique makes it possible to combine clarification, concentration and product capture in one unit operation. This study shows a 144 fold scale-up from laboratory to production scale. The column sizes used are 50 mm I.D. and 600 mm I.D. respectively. Residence time distribution (RTD), the response from an injected step, was used to evaluate the scale up. This reflects the hydrodynamics of the system. Adsorption kinetics was determined from a breakthrough curve of bovine serum albumine and the binding capacity was calculated. The results show that expanded bed adsorption is scaleable from laboratory to production scale with retained properties.

  10. Temporal and spatial simulation of production-scale irrigated cotton

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Site-specific management of cotton (Gossypium hirsutum) cropping systems at the production-scale requires information regarding interactions between soil, plant, weather, and agronomic inputs. Management decisions regarding the spatially and temporally variable addition of agronomic inputs are most ...