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Sample records for constraint-based metabolic flux

  1. Carbon 13-Metabolic Flux Analysis derived constraint-based metabolic modelling of Clostridium acetobutylicum in stressed chemostat conditions.

    Science.gov (United States)

    Wallenius, Janne; Maaheimo, Hannu; Eerikäinen, Tero

    2016-11-01

    The metabolism of butanol producing bacteria Clostridium acetobutylicum was studied in chemostat with glucose limited conditions, butanol stimulus, and as a reference cultivation. COnstraint-Based Reconstruction and Analysis (COBRA) was applied using additional constraints from (13)C Metabolic Flux Analysis ((13)C-MFA) and experimental measurement results. A model consisting of 451 metabolites and 604 reactions was utilized in flux balance analysis (FBA). The stringency of the flux spaces considering different optimization objectives, i.e. growth rate maximization, ATP maintenance, and NADH/NADPH formation, for flux variance analysis (FVA) was studied in the different modelled conditions. Also a previously uncharacterized exopolysaccharide (EPS) produced by C. acetobutylicum was characterized on monosaccharide level. The major monosaccharide components of the EPS were 40n-% rhamnose, 34n-% glucose, 13n-% mannose, 10n-% galactose, and 2n-% arabinose. The EPS was studied to have butanol adsorbing property, 70(butanol)mg(EPS)g(-1) at 37°C. Copyright © 2016 Elsevier Ltd. All rights reserved.

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

    Science.gov (United States)

    Cotten, Cameron; Reed, Jennifer L

    2013-05-01

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

  3. Modelling central metabolic fluxes by constraint-based optimization reveals metabolic reprogramming of developing Solanum lycopersicum (tomato) fruit.

    Science.gov (United States)

    Colombié, Sophie; Nazaret, Christine; Bénard, Camille; Biais, Benoît; Mengin, Virginie; Solé, Marion; Fouillen, Laëtitia; Dieuaide-Noubhani, Martine; Mazat, Jean-Pierre; Beauvoit, Bertrand; Gibon, Yves

    2015-01-01

    Modelling of metabolic networks is a powerful tool to analyse the behaviour of developing plant organs, including fruits. Guided by our current understanding of heterotrophic metabolism of plant cells, a medium-scale stoichiometric model, including the balance of co-factors and energy, was constructed in order to describe metabolic shifts that occur through the nine sequential stages of Solanum lycopersicum (tomato) fruit development. The measured concentrations of the main biomass components and the accumulated metabolites in the pericarp, determined at each stage, were fitted in order to calculate, by derivation, the corresponding external fluxes. They were used as constraints to solve the model by minimizing the internal fluxes. The distribution of the calculated fluxes of central metabolism were then analysed and compared with known metabolic behaviours. For instance, the partition of the main metabolic pathways (glycolysis, pentose phosphate pathway, etc.) was relevant throughout fruit development. We also predicted a valid import of carbon and nitrogen by the fruit, as well as a consistent CO2 release. Interestingly, the energetic balance indicates that excess ATP is dissipated just before the onset of ripening, supporting the concept of the climacteric crisis. Finally, the apparent contradiction between calculated fluxes with low values compared with measured enzyme capacities suggest a complex reprogramming of the metabolic machinery during fruit development. With a powerful set of experimental data and an accurate definition of the metabolic system, this work provides important insight into the metabolic and physiological requirements of the developing tomato fruits.

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

    Science.gov (United States)

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

    2014-01-01

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

  5. Integration of a constraint-based metabolic model of Brassica napus developing seeds with 13C-Metabolic Flux Analysis

    Directory of Open Access Journals (Sweden)

    Jordan eHay

    2014-12-01

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

  6. Systematic Evaluation of Methods for Integration of Transcriptomic Data into Constraint-Based Models of Metabolism

    DEFF Research Database (Denmark)

    Machado, Daniel; Herrgard, Markus

    2014-01-01

    Constraint-based models of metabolism are a widely used framework for predicting flux distributions in genome-scale biochemical networks. The number of published methods for integration of transcriptomic data into constraint-based models has been rapidly increasing. So far the predictive capability...... of these methods has not been critically evaluated and compared. This work presents a survey of recently published methods that use transcript levels to try to improve metabolic flux predictions either by generating flux distributions or by creating context-specific models. A subset of these methods...... of the results to method-specific parameters is also evaluated, as well as their robustness to noise in the data. The results show that none of the methods outperforms the others for all cases. Also, it is observed that for many conditions, the predictions obtained by simple flux balance analysis using growth...

  7. Constraint based modeling in R using metabolic reconstruction databases

    NARCIS (Netherlands)

    Gavai, A.K.; Hettinga, H.; Leunissen, J.A.M.

    2015-01-01

    This package provides an interface to simulate metabolic reconstruction from the BiGG database(http://bigg.ucsd.edu/) and other metabolic reconstruction databases. The package facilitates flux balance analysis (FBA) and the sampling of feasible flux distributions. Metabolic networks and estimated fl

  8. Metabolic constraint-based refinement of transcriptional regulatory networks.

    Science.gov (United States)

    Chandrasekaran, Sriram; Price, Nathan D

    2013-01-01

    There is a strong need for computational frameworks that integrate different biological processes and data-types to unravel cellular regulation. Current efforts to reconstruct transcriptional regulatory networks (TRNs) focus primarily on proximal data such as gene co-expression and transcription factor (TF) binding. While such approaches enable rapid reconstruction of TRNs, the overwhelming combinatorics of possible networks limits identification of mechanistic regulatory interactions. Utilizing growth phenotypes and systems-level constraints to inform regulatory network reconstruction is an unmet challenge. We present our approach Gene Expression and Metabolism Integrated for Network Inference (GEMINI) that links a compendium of candidate regulatory interactions with the metabolic network to predict their systems-level effect on growth phenotypes. We then compare predictions with experimental phenotype data to select phenotype-consistent regulatory interactions. GEMINI makes use of the observation that only a small fraction of regulatory network states are compatible with a viable metabolic network, and outputs a regulatory network that is simultaneously consistent with the input genome-scale metabolic network model, gene expression data, and TF knockout phenotypes. GEMINI preferentially recalls gold-standard interactions (p-value = 10(-172)), significantly better than using gene expression alone. We applied GEMINI to create an integrated metabolic-regulatory network model for Saccharomyces cerevisiae involving 25,000 regulatory interactions controlling 1597 metabolic reactions. The model quantitatively predicts TF knockout phenotypes in new conditions (p-value = 10(-14)) and revealed potential condition-specific regulatory mechanisms. Our results suggest that a metabolic constraint-based approach can be successfully used to help reconstruct TRNs from high-throughput data, and highlights the potential of using a biochemically-detailed mechanistic framework to

  9. Mechanistic analysis of multi-omics datasets to generate kinetic parameters for constraint-based metabolic models

    Directory of Open Access Journals (Sweden)

    Cotten Cameron

    2013-01-01

    Full Text Available Abstract Background Constraint-based modeling uses mass balances, flux capacity, and reaction directionality constraints to predict fluxes through metabolism. Although transcriptional regulation and thermodynamic constraints have been integrated into constraint-based modeling, kinetic rate laws have not been extensively used. Results In this study, an in vivo kinetic parameter estimation problem was formulated and solved using multi-omic data sets for Escherichia coli. To narrow the confidence intervals for kinetic parameters, a series of kinetic model simplifications were made, resulting in fewer kinetic parameters than the full kinetic model. These new parameter values are able to account for flux and concentration data from 20 different experimental conditions used in our training dataset. Concentration estimates from the simplified kinetic model were within one standard deviation for 92.7% of the 790 experimental measurements in the training set. Gibbs free energy changes of reaction were calculated to identify reactions that were often operating close to or far from equilibrium. In addition, enzymes whose activities were positively or negatively influenced by metabolite concentrations were also identified. The kinetic model was then used to calculate the maximum and minimum possible flux values for individual reactions from independent metabolite and enzyme concentration data that were not used to estimate parameter values. Incorporating these kinetically-derived flux limits into the constraint-based metabolic model improved predictions for uptake and secretion rates and intracellular fluxes in constraint-based models of central metabolism. Conclusions This study has produced a method for in vivo kinetic parameter estimation and identified strategies and outcomes of kinetic model simplification. We also have illustrated how kinetic constraints can be used to improve constraint-based model predictions for intracellular fluxes and biomass

  10. Mechanistic analysis of multi-omics datasets to generate kinetic parameters for constraint-based metabolic models.

    Science.gov (United States)

    Cotten, Cameron; Reed, Jennifer L

    2013-01-30

    Constraint-based modeling uses mass balances, flux capacity, and reaction directionality constraints to predict fluxes through metabolism. Although transcriptional regulation and thermodynamic constraints have been integrated into constraint-based modeling, kinetic rate laws have not been extensively used. In this study, an in vivo kinetic parameter estimation problem was formulated and solved using multi-omic data sets for Escherichia coli. To narrow the confidence intervals for kinetic parameters, a series of kinetic model simplifications were made, resulting in fewer kinetic parameters than the full kinetic model. These new parameter values are able to account for flux and concentration data from 20 different experimental conditions used in our training dataset. Concentration estimates from the simplified kinetic model were within one standard deviation for 92.7% of the 790 experimental measurements in the training set. Gibbs free energy changes of reaction were calculated to identify reactions that were often operating close to or far from equilibrium. In addition, enzymes whose activities were positively or negatively influenced by metabolite concentrations were also identified. The kinetic model was then used to calculate the maximum and minimum possible flux values for individual reactions from independent metabolite and enzyme concentration data that were not used to estimate parameter values. Incorporating these kinetically-derived flux limits into the constraint-based metabolic model improved predictions for uptake and secretion rates and intracellular fluxes in constraint-based models of central metabolism. This study has produced a method for in vivo kinetic parameter estimation and identified strategies and outcomes of kinetic model simplification. We also have illustrated how kinetic constraints can be used to improve constraint-based model predictions for intracellular fluxes and biomass yield and identify potential metabolic limitations through the

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

    Science.gov (United States)

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

    2016-02-01

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

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

    Science.gov (United States)

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

    2017-04-01

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

  13. Synergy between 13C-metabolic flux analysis and flux balance analysis for understanding metabolic adaption to anaerobiosis in e. coli

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    Genome-based Flux Balance Analysis (FBA, constraints based flux analysis) and steady state isotopic-labeling-based Metabolic Flux Analysis (MFA) are complimentary approaches to predicting and measuring the operation and regulation of metabolic networks. Here a genome-derived model of E. coli metabol...

  14. Flux-P: Automating Metabolic Flux Analysis

    OpenAIRE

    Ebert, Birgitta E.; Anna-Lena Lamprecht; Bernhard Steffen; Blank, Lars M.

    2012-01-01

    Quantitative knowledge of intracellular fluxes in metabolic networks is invaluable for inferring metabolic system behavior and the design principles of biological systems. However, intracellular reaction rates can not often be calculated directly but have to be estimated; for instance, via 13C-based metabolic flux analysis, a model-based interpretation of stable carbon isotope patterns in intermediates of metabolism. Existing software such as FiatFlux, OpenFLUX or 13CFLUX supports experts in ...

  15. Characterizing the metabolism of Dehalococcoides with a constraint-based model.

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    M Ahsanul Islam

    Full Text Available Dehalococcoides strains respire a wide variety of chloro-organic compounds and are important for the bioremediation of toxic, persistent, carcinogenic, and ubiquitous ground water pollutants. In order to better understand metabolism and optimize their application, we have developed a pan-genome-scale metabolic network and constraint-based metabolic model of Dehalococcoides. The pan-genome was constructed from publicly available complete genome sequences of Dehalococcoides sp. strain CBDB1, strain 195, strain BAV1, and strain VS. We found that Dehalococcoides pan-genome consisted of 1118 core genes (shared by all, 457 dispensable genes (shared by some, and 486 unique genes (found in only one genome. The model included 549 metabolic genes that encoded 356 proteins catalyzing 497 gene-associated model reactions. Of these 497 reactions, 477 were associated with core metabolic genes, 18 with dispensable genes, and 2 with unique genes. This study, in addition to analyzing the metabolism of an environmentally important phylogenetic group on a pan-genome scale, provides valuable insights into Dehalococcoides metabolic limitations, low growth yields, and energy conservation. The model also provides a framework to anchor and compare disparate experimental data, as well as to give insights on the physiological impact of "incomplete" pathways, such as the TCA-cycle, CO(2 fixation, and cobalamin biosynthesis pathways. The model, referred to as iAI549, highlights the specialized and highly conserved nature of Dehalococcoides metabolism, and suggests that evolution of Dehalococcoides species is driven by the electron acceptor availability.

  16. Estimating Metabolic Fluxes Using a Maximum Network Flexibility Paradigm

    NARCIS (Netherlands)

    Megchelenbrink, W.; Rossell, S.; Huynen, M.A.; Notebaart, R.A.; Marchiori, E.

    2015-01-01

    MOTIVATION: Genome-scale metabolic networks can be modeled in a constraint-based fashion. Reaction stoichiometry combined with flux capacity constraints determine the space of allowable reaction rates. This space is often large and a central challenge in metabolic modeling is finding the biologicall

  17. Acorn: A grid computing system for constraint based modeling and visualization of the genome scale metabolic reaction networks via a web interface

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    Bushell Michael E

    2011-05-01

    Full Text Available Abstract Background Constraint-based approaches facilitate the prediction of cellular metabolic capabilities, based, in turn on predictions of the repertoire of enzymes encoded in the genome. Recently, genome annotations have been used to reconstruct genome scale metabolic reaction networks for numerous species, including Homo sapiens, which allow simulations that provide valuable insights into topics, including predictions of gene essentiality of pathogens, interpretation of genetic polymorphism in metabolic disease syndromes and suggestions for novel approaches to microbial metabolic engineering. These constraint-based simulations are being integrated with the functional genomics portals, an activity that requires efficient implementation of the constraint-based simulations in the web-based environment. Results Here, we present Acorn, an open source (GNU GPL grid computing system for constraint-based simulations of genome scale metabolic reaction networks within an interactive web environment. The grid-based architecture allows efficient execution of computationally intensive, iterative protocols such as Flux Variability Analysis, which can be readily scaled up as the numbers of models (and users increase. The web interface uses AJAX, which facilitates efficient model browsing and other search functions, and intuitive implementation of appropriate simulation conditions. Research groups can install Acorn locally and create user accounts. Users can also import models in the familiar SBML format and link reaction formulas to major functional genomics portals of choice. Selected models and simulation results can be shared between different users and made publically available. Users can construct pathway map layouts and import them into the server using a desktop editor integrated within the system. Pathway maps are then used to visualise numerical results within the web environment. To illustrate these features we have deployed Acorn and created a

  18. Improvement of constraint-based flux estimation during L-phenylalanine production with Escherichia coli using targeted knock-out mutants.

    Science.gov (United States)

    Weiner, Michael; Tröndle, Julia; Albermann, Christoph; Sprenger, Georg A; Weuster-Botz, Dirk

    2014-07-01

    Fed-batch production of the aromatic amino acid L-phenylalanine was studied with recombinant Escherichia coli strains on a 15 L-scale using glycerol as carbon source. Flux Variability Analysis (FVA) was applied for intracellular flux estimation to obtain an insight into intracellular flux distribution during L-phenylalanine production. Variability analysis revealed great flux uncertainties in the central carbon metabolism, especially concerning malate consumption. Due to these results two recombinant strains were genetically engineered differing in the ability of malate degradation and anaplerotic reactions (E. coli FUS4.11 ΔmaeA pF81kan and E. coli FUS4.11 ΔmaeA ΔmaeB pF81kan). Applying these malic enzyme knock-out mutants in the standardized L-phenylalanine production process resulted in almost identical process performances (e.g., L-phenylalanine concentration, production rate and byproduct formation). This clearly highlighted great redundancies in central metabolism in E. coli. Uncertainties of intracellular flux estimations by constraint-based analyses during fed-batch production of L-phenylalanine were drastically reduced by application of the malic enzyme knock-out mutants.

  19. Constraint-based model of Shewanella oneidensis MR-1 metabolism: a tool for data analysis and hypothesis generation.

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    Grigoriy E Pinchuk

    2010-06-01

    Full Text Available Shewanellae are gram-negative facultatively anaerobic metal-reducing bacteria commonly found in chemically (i.e., redox stratified environments. Occupying such niches requires the ability to rapidly acclimate to changes in electron donor/acceptor type and availability; hence, the ability to compete and thrive in such environments must ultimately be reflected in the organization and utilization of electron transfer networks, as well as central and peripheral carbon metabolism. To understand how Shewanella oneidensis MR-1 utilizes its resources, the metabolic network was reconstructed. The resulting network consists of 774 reactions, 783 genes, and 634 unique metabolites and contains biosynthesis pathways for all cell constituents. Using constraint-based modeling, we investigated aerobic growth of S. oneidensis MR-1 on numerous carbon sources. To achieve this, we (i used experimental data to formulate a biomass equation and estimate cellular ATP requirements, (ii developed an approach to identify cycles (such as futile cycles and circulations, (iii classified how reaction usage affects cellular growth, (iv predicted cellular biomass yields on different carbon sources and compared model predictions to experimental measurements, and (v used experimental results to refine metabolic fluxes for growth on lactate. The results revealed that aerobic lactate-grown cells of S. oneidensis MR-1 used less efficient enzymes to couple electron transport to proton motive force generation, and possibly operated at least one futile cycle involving malic enzymes. Several examples are provided whereby model predictions were validated by experimental data, in particular the role of serine hydroxymethyltransferase and glycine cleavage system in the metabolism of one-carbon units, and growth on different sources of carbon and energy. This work illustrates how integration of computational and experimental efforts facilitates the understanding of microbial metabolism at a

  20. Flux-P: Automating Metabolic Flux Analysis

    Directory of Open Access Journals (Sweden)

    Birgitta E. Ebert

    2012-11-01

    Full Text Available Quantitative knowledge of intracellular fluxes in metabolic networks is invaluable for inferring metabolic system behavior and the design principles of biological systems. However, intracellular reaction rates can not often be calculated directly but have to be estimated; for instance, via 13C-based metabolic flux analysis, a model-based interpretation of stable carbon isotope patterns in intermediates of metabolism. Existing software such as FiatFlux, OpenFLUX or 13CFLUX supports experts in this complex analysis, but requires several steps that have to be carried out manually, hence restricting the use of this software for data interpretation to a rather small number of experiments. In this paper, we present Flux-P as an approach to automate and standardize 13C-based metabolic flux analysis, using the Bio-jETI workflow framework. Exemplarily based on the FiatFlux software, it demonstrates how services can be created that carry out the different analysis steps autonomously and how these can subsequently be assembled into software workflows that perform automated, high-throughput intracellular flux analysis of high quality and reproducibility. Besides significant acceleration and standardization of the data analysis, the agile workflow-based realization supports flexible changes of the analysis workflows on the user level, making it easy to perform custom analyses.

  1. Constraint-based analysis of metabolic capacity of Salmonella typhimurium during host-pathogen interaction

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    Palsson Bernhard

    2009-04-01

    Full Text Available Abstract Background Infections with Salmonella cause significant morbidity and mortality worldwide. Replication of Salmonella typhimurium inside its host cell is a model system for studying the pathogenesis of intracellular bacterial infections. Genome-scale modeling of bacterial metabolic networks provides a powerful tool to identify and analyze pathways required for successful intracellular replication during host-pathogen interaction. Results We have developed and validated a genome-scale metabolic network of Salmonella typhimurium LT2 (iRR1083. This model accounts for 1,083 genes that encode proteins catalyzing 1,087 unique metabolic and transport reactions in the bacterium. We employed flux balance analysis and in silico gene essentiality analysis to investigate growth under a wide range of conditions that mimic in vitro and host cell environments. Gene expression profiling of S. typhimurium isolated from macrophage cell lines was used to constrain the model to predict metabolic pathways that are likely to be operational during infection. Conclusion Our analysis suggests that there is a robust minimal set of metabolic pathways that is required for successful replication of Salmonella inside the host cell. This model also serves as platform for the integration of high-throughput data. Its computational power allows identification of networked metabolic pathways and generation of hypotheses about metabolism during infection, which might be used for the rational design of novel antibiotics or vaccine strains.

  2. Thermodynamic analysis of regulation in metabolic networks using constraint-based modeling

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    Mahadevan Radhakrishnan

    2010-05-01

    Full Text Available Abstract Background Geobacter sulfurreducens is a member of the Geobacter species, which are capable of oxidation of organic waste coupled to the reduction of heavy metals and electrode with applications in bioremediation and bioenergy generation. While the metabolism of this organism has been studied through the development of a stoichiometry based genome-scale metabolic model, the associated regulatory network has not yet been well studied. In this manuscript, we report on the implementation of a thermodynamics based metabolic flux model for Geobacter sulfurreducens. We use this updated model to identify reactions that are subject to regulatory control in the metabolic network of G. sulfurreducens using thermodynamic variability analysis. Findings As a first step, we have validated the regulatory sites and bottleneck reactions predicted by the thermodynamic flux analysis in E. coli by evaluating the expression ranges of the corresponding genes. We then identified ten reactions in the metabolic network of G. sulfurreducens that are predicted to be candidates for regulation. We then compared the free energy ranges for these reactions with the corresponding gene expression fold changes under conditions of different environmental and genetic perturbations and show that the model predictions of regulation are consistent with data. In addition, we also identify reactions that operate close to equilibrium and show that the experimentally determined exchange coefficient (a measure of reversibility is significant for these reactions. Conclusions Application of the thermodynamic constraints resulted in identification of potential bottleneck reactions not only from the central metabolism but also from the nucleotide and amino acid subsystems, thereby showing the highly coupled nature of the thermodynamic constraints. In addition, thermodynamic variability analysis serves as a valuable tool in estimating the ranges of ΔrG' of every reaction in the model

  3. Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox v2.0

    OpenAIRE

    2011-01-01

    Over the past decade, a growing community of researchers has emerged around the use of COnstraint-Based Reconstruction and Analysis (COBRA) methods to simulate, analyze and predict a variety of metabolic phenotypes using genome-scale models. The COBRA Toolbox, a MATLAB package for implementing COBRA methods, was presented earlier. Here we present a significant update of this in silico ToolBox. Version 2.0 of the COBRA Toolbox expands the scope of computations by including in silico analysis m...

  4. Structural control of metabolic flux.

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    Max Sajitz-Hermstein

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

  5. Primary Metabolic Pathways and Metabolic Flux Analysis

    DEFF Research Database (Denmark)

    2015-01-01

    his chapter introduces the metabolic flux analysis (MFA) or stoichiometry-based MFA, and describes the quantitative basis for MFA. It discusses the catabolic pathways in which free energy is produced to drive the cell-building anabolic pathways. An overview of these primary pathways provides...

  6. Flux-coupled genes and their use in metabolic flux analysis.

    Science.gov (United States)

    Kim, Hyun Uk; Kim, Won Jun; Lee, Sang Yup

    2013-09-01

    As large volumes of omics data have become available, systems biology is playing increasingly important roles in elucidating new biological phenomena, especially through genome-scale metabolic network modeling and simulation. Much effort has been exerted on integrating omics data with metabolic flux simulation, but further development is necessary for more accurate flux estimation. To move one step forward, we adopted the concept of flux-coupled genes (FCGs), which show that their expression transition patterns upon perturbations are correlated with their corresponding flux values, as additional constraints in metabolic flux analysis. It was found that gnd, pfkB, rpe, sdhB, sdhD, sucA, and zwf genes, mostly associated with pentose phosphate pathway and TCA cycle, were the most consistent FCGs in Escherichia coli based on its transcriptome and (13) C-flux data obtained from the chemostat cultivation at five different dilution rates. Consequently, constraints-based flux analyses with FCGs as additional constraints were conducted for the seven single-gene knockout mutants, compared with those obtained without using FCGs. This strategy of constraining the metabolic flux analysis with FCGs is expected to be useful due to the relative ease in obtaining transcriptional information in the functional genomics era.

  7. Constraint-based modeling analysis of the metabolism of two Pelobacter species

    Directory of Open Access Journals (Sweden)

    Bui Olivia

    2010-12-01

    Full Text Available Abstract Background Pelobacter species are commonly found in a number of subsurface environments, and are unique members of the Geobacteraceae family. They are phylogenetically intertwined with both Geobacter and Desulfuromonas species. Pelobacter species likely play important roles in the fermentative degradation of unusual organic matters and syntrophic metabolism in the natural environments, and are of interest for applications in bioremediation and microbial fuel cells. Results In order to better understand the physiology of Pelobacter species, genome-scale metabolic models for Pelobacter carbinolicus and Pelobacter propionicus were developed. Model development was greatly aided by the availability of models of the closely related Geobacter sulfurreducens and G. metallireducens. The reconstructed P. carbinolicus model contains 741 genes and 708 reactions, whereas the reconstructed P. propionicus model contains 661 genes and 650 reactions. A total of 470 reactions are shared among the two Pelobacter models and the two Geobacter models. The different reactions between the Pelobacter and Geobacter models reflect some unique metabolic capabilities such as fermentative growth for both Pelobacter species. The reconstructed Pelobacter models were validated by simulating published growth conditions including fermentations, hydrogen production in syntrophic co-culture conditions, hydrogen utilization, and Fe(III reduction. Simulation results matched well with experimental data and indicated the accuracy of the models. Conclusions We have developed genome-scale metabolic models of P. carbinolicus and P. propionicus. These models of Pelobacter metabolism can now be incorporated into the growing repertoire of genome scale models of the Geobacteraceae family to aid in describing the growth and activity of these organisms in anoxic environments and in the study of their roles and interactions in the subsurface microbial community.

  8. Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox v2.0.

    Science.gov (United States)

    Schellenberger, Jan; Que, Richard; Fleming, Ronan M T; Thiele, Ines; Orth, Jeffrey D; Feist, Adam M; Zielinski, Daniel C; Bordbar, Aarash; Lewis, Nathan E; Rahmanian, Sorena; Kang, Joseph; Hyduke, Daniel R; Palsson, Bernhard Ø

    2011-08-04

    Over the past decade, a growing community of researchers has emerged around the use of constraint-based reconstruction and analysis (COBRA) methods to simulate, analyze and predict a variety of metabolic phenotypes using genome-scale models. The COBRA Toolbox, a MATLAB package for implementing COBRA methods, was presented earlier. Here we present a substantial update of this in silico toolbox. Version 2.0 of the COBRA Toolbox expands the scope of computations by including in silico analysis methods developed since its original release. New functions include (i) network gap filling, (ii) (13)C analysis, (iii) metabolic engineering, (iv) omics-guided analysis and (v) visualization. As with the first version, the COBRA Toolbox reads and writes systems biology markup language-formatted models. In version 2.0, we improved performance, usability and the level of documentation. A suite of test scripts can now be used to learn the core functionality of the toolbox and validate results. This toolbox lowers the barrier of entry to use powerful COBRA methods.

  9. Genome-scale comparison and constraint-based metabolic reconstruction of the facultative anaerobic Fe(III-reducer Rhodoferax ferrireducens

    Directory of Open Access Journals (Sweden)

    Daugherty Sean

    2009-09-01

    Full Text Available Abstract Background Rhodoferax ferrireducens is a metabolically versatile, Fe(III-reducing, subsurface microorganism that is likely to play an important role in the carbon and metal cycles in the subsurface. It also has the unique ability to convert sugars to electricity, oxidizing the sugars to carbon dioxide with quantitative electron transfer to graphite electrodes in microbial fuel cells. In order to expand our limited knowledge about R. ferrireducens, the complete genome sequence of this organism was further annotated and then the physiology of R. ferrireducens was investigated with a constraint-based, genome-scale in silico metabolic model and laboratory studies. Results The iterative modeling and experimental approach unveiled exciting, previously unknown physiological features, including an expanded range of substrates that support growth, such as cellobiose and citrate, and provided additional insights into important features such as the stoichiometry of the electron transport chain and the ability to grow via fumarate dismutation. Further analysis explained why R. ferrireducens is unable to grow via photosynthesis or fermentation of sugars like other members of this genus and uncovered novel genes for benzoate metabolism. The genome also revealed that R. ferrireducens is well-adapted for growth in the subsurface because it appears to be capable of dealing with a number of environmental insults, including heavy metals, aromatic compounds, nutrient limitation and oxidative stress. Conclusion This study demonstrates that combining genome-scale modeling with the annotation of a new genome sequence can guide experimental studies and accelerate the understanding of the physiology of under-studied yet environmentally relevant microorganisms.

  10. Flux-dependent graphs for metabolic networks

    OpenAIRE

    Beguerisse-Díaz, Mariano; Bosque, Gabriel; Oyarzún, Diego; Picó, Jesús; Barahona, Mauricio

    2016-01-01

    Cells adapt their metabolic fluxes in response to changes in the environment. We present a systematic flux-based framework for the construction of graphs to represent organism-wide metabolic networks. Our graphs encode the directionality of metabolic fluxes via links that represent the flow of metabolites from source to target reactions. The methodology can be applied in the absence of a specific biological context by modelling fluxes as probabilities, or tailored to different environmental c...

  11. Yeast dynamic metabolic flux measurement in nutrient-rich media by HPLC and accelerator mass spectrometry.

    Science.gov (United States)

    Stewart, Benjamin J; Navid, Ali; Turteltaub, Kenneth W; Bench, Graham

    2010-12-01

    Metabolic flux, the flow of metabolites through networks of enzymes, represents the dynamic productive output of cells. Improved understanding of intracellular metabolic fluxes will enable targeted manipulation of metabolic pathways of medical and industrial importance to a greater degree than is currently possible. Flux balance analysis (FBA) is a constraint-based approach to modeling metabolic fluxes, but its utility is limited by a lack of experimental measurements. Incorporation of experimentally measured fluxes as system constraints will significantly improve the overall accuracy of FBA. We applied a novel, two-tiered approach in the yeast Saccharomyces cerevisiae to measure nutrient consumption rates (extracellular fluxes) and a targeted intracellular flux using a (14)C-labeled precursor with HPLC separation and flux quantitation by accelerator mass spectrometry (AMS). The use of AMS to trace the intracellular fate of (14)C-glutamine allowed the calculation of intracellular metabolic flux through this pathway, with glutathione as the metabolic end point. Measured flux values provided global constraints for the yeast FBA model which reduced model uncertainty by more than 20%, proving the importance of additional constraints in improving the accuracy of model predictions and demonstrating the use of AMS to measure intracellular metabolic fluxes. Our results highlight the need to use intracellular fluxes to constrain the models. We show that inclusion of just one such measurement alone can reduce the average variability of model predicted fluxes by 10%.

  12. Improving metabolic flux predictions using absolute gene expression data

    Directory of Open Access Journals (Sweden)

    Lee Dave

    2012-06-01

    Full Text Available Abstract Background Constraint-based analysis of genome-scale metabolic models typically relies upon maximisation of a cellular objective function such as the rate or efficiency of biomass production. Whilst this assumption may be valid in the case of microorganisms growing under certain conditions, it is likely invalid in general, and especially for multicellular organisms, where cellular objectives differ greatly both between and within cell types. Moreover, for the purposes of biotechnological applications, it is normally the flux to a specific metabolite or product that is of interest rather than the rate of production of biomass per se. Results An alternative objective function is presented, that is based upon maximising the correlation between experimentally measured absolute gene expression data and predicted internal reaction fluxes. Using quantitative transcriptomics data acquired from Saccharomyces cerevisiae cultures under two growth conditions, the method outperforms traditional approaches for predicting experimentally measured exometabolic flux that are reliant upon maximisation of the rate of biomass production. Conclusion Due to its improved prediction of experimentally measured metabolic fluxes, and of its lack of a requirement for knowledge of the biomass composition of the organism under the conditions of interest, the approach is likely to be of rather general utility. The method has been shown to predict fluxes reliably in single cellular systems. Subsequent work will investigate the method’s ability to generate condition- and tissue-specific flux predictions in multicellular organisms.

  13. Estimating Metabolic Fluxes Using a Maximum Network Flexibility Paradigm

    Science.gov (United States)

    Megchelenbrink, Wout; Rossell, Sergio; Huynen, Martijn A.

    2015-01-01

    Motivation Genome-scale metabolic networks can be modeled in a constraint-based fashion. Reaction stoichiometry combined with flux capacity constraints determine the space of allowable reaction rates. This space is often large and a central challenge in metabolic modeling is finding the biologically most relevant flux distributions. A widely used method is flux balance analysis (FBA), which optimizes a biologically relevant objective such as growth or ATP production. Although FBA has proven to be highly useful for predicting growth and byproduct secretion, it cannot predict the intracellular fluxes under all environmental conditions. Therefore, alternative strategies have been developed to select flux distributions that are in agreement with experimental “omics” data, or by incorporating experimental flux measurements. The latter, unfortunately can only be applied to a limited set of reactions and is currently not feasible at the genome-scale. On the other hand, it has been observed that micro-organisms favor a suboptimal growth rate, possibly in exchange for a more “flexible” metabolic network. Instead of dedicating the internal network state to an optimal growth rate in one condition, a suboptimal growth rate is used, that allows for an easier switch to other nutrient sources. A small decrease in growth rate is exchanged for a relatively large gain in metabolic capability to adapt to changing environmental conditions. Results Here, we propose Maximum Metabolic Flexibility (MMF) a computational method that utilizes this observation to find the most probable intracellular flux distributions. By mapping measured flux data from central metabolism to the genome-scale models of Escherichia coli and Saccharomyces cerevisiae we show that i) indeed, most of the measured fluxes agree with a high adaptability of the network, ii) this result can be used to further reduce the space of feasible solutions iii) this reduced space improves the quantitative predictions

  14. Estimating Metabolic Fluxes Using a Maximum Network Flexibility Paradigm.

    Directory of Open Access Journals (Sweden)

    Wout Megchelenbrink

    Full Text Available Genome-scale metabolic networks can be modeled in a constraint-based fashion. Reaction stoichiometry combined with flux capacity constraints determine the space of allowable reaction rates. This space is often large and a central challenge in metabolic modeling is finding the biologically most relevant flux distributions. A widely used method is flux balance analysis (FBA, which optimizes a biologically relevant objective such as growth or ATP production. Although FBA has proven to be highly useful for predicting growth and byproduct secretion, it cannot predict the intracellular fluxes under all environmental conditions. Therefore, alternative strategies have been developed to select flux distributions that are in agreement with experimental "omics" data, or by incorporating experimental flux measurements. The latter, unfortunately can only be applied to a limited set of reactions and is currently not feasible at the genome-scale. On the other hand, it has been observed that micro-organisms favor a suboptimal growth rate, possibly in exchange for a more "flexible" metabolic network. Instead of dedicating the internal network state to an optimal growth rate in one condition, a suboptimal growth rate is used, that allows for an easier switch to other nutrient sources. A small decrease in growth rate is exchanged for a relatively large gain in metabolic capability to adapt to changing environmental conditions.Here, we propose Maximum Metabolic Flexibility (MMF a computational method that utilizes this observation to find the most probable intracellular flux distributions. By mapping measured flux data from central metabolism to the genome-scale models of Escherichia coli and Saccharomyces cerevisiae we show that i indeed, most of the measured fluxes agree with a high adaptability of the network, ii this result can be used to further reduce the space of feasible solutions iii this reduced space improves the quantitative predictions made by FBA and

  15. Biochemical characterization of human gluconokinase and the proposed metabolic impact of gluconic Acid as determined by constraint based metabolic network analysis

    DEFF Research Database (Denmark)

    Rohatgi, Neha; Nielsen, Tine Kragh; Bjørn, Sara Petersen

    2014-01-01

    and strict specificity towards gluconate out of 122 substrates tested. In order to evaluate the metabolic impact of gluconate in humans we modeled gluconate metabolism using steady state metabolic network analysis. The results indicate that significant metabolic flux changes in anabolic pathways linked......The metabolism of gluconate is well characterized in prokaryotes where it is known to be degraded following phosphorylation by gluconokinase. Less is known of gluconate metabolism in humans. Human gluconokinase activity was recently identified proposing questions about the metabolic role...... to the hexose monophosphate shunt (HMS) are induced through a small increase in gluconate concentration. We argue that the enzyme takes part in a context specific carbon flux route into the HMS that, in humans, remains incompletely explored. Apart from the biochemical description of human gluconokinase...

  16. MicrobesFlux: a web platform for drafting metabolic models from the KEGG database

    Directory of Open Access Journals (Sweden)

    Feng Xueyang

    2012-08-01

    Full Text Available Abstract Background Concurrent with the efforts currently underway in mapping microbial genomes using high-throughput sequencing methods, systems biologists are building metabolic models to characterize and predict cell metabolisms. One of the key steps in building a metabolic model is using multiple databases to collect and assemble essential information about genome-annotations and the architecture of the metabolic network for a specific organism. To speed up metabolic model development for a large number of microorganisms, we need a user-friendly platform to construct metabolic networks and to perform constraint-based flux balance analysis based on genome databases and experimental results. Results We have developed a semi-automatic, web-based platform (MicrobesFlux for generating and reconstructing metabolic models for annotated microorganisms. MicrobesFlux is able to automatically download the metabolic network (including enzymatic reactions and metabolites of ~1,200 species from the KEGG database (Kyoto Encyclopedia of Genes and Genomes and then convert it to a metabolic model draft. The platform also provides diverse customized tools, such as gene knockouts and the introduction of heterologous pathways, for users to reconstruct the model network. The reconstructed metabolic network can be formulated to a constraint-based flux model to predict and analyze the carbon fluxes in microbial metabolisms. The simulation results can be exported in the SBML format (The Systems Biology Markup Language. Furthermore, we also demonstrated the platform functionalities by developing an FBA model (including 229 reactions for a recent annotated bioethanol producer, Thermoanaerobacter sp. strain X514, to predict its biomass growth and ethanol production. Conclusion MicrobesFlux is an installation-free and open-source platform that enables biologists without prior programming knowledge to develop metabolic models for annotated microorganisms in the KEGG

  17. Optimal flux patterns in cellular metabolic networks

    Energy Technology Data Exchange (ETDEWEB)

    Almaas, E

    2007-01-20

    The availability of whole-cell level metabolic networks of high quality has made it possible to develop a predictive understanding of bacterial metabolism. Using the optimization framework of flux balance analysis, I investigate metabolic response and activity patterns to variations in the availability of nutrient and chemical factors such as oxygen and ammonia by simulating 30,000 random cellular environments. The distribution of reaction fluxes is heavy-tailed for the bacteria H. pylori and E. coli, and the eukaryote S. cerevisiae. While the majority of flux balance investigations have relied on implementations of the simplex method, it is necessary to use interior-point optimization algorithms to adequately characterize the full range of activity patterns on metabolic networks. The interior-point activity pattern is bimodal for E. coli and S. cerevisiae, suggesting that most metabolic reaction are either in frequent use or are rarely active. The trimodal activity pattern of H. pylori indicates that a group of its metabolic reactions (20%) are active in approximately half of the simulated environments. Constructing the high-flux backbone of the network for every environment, there is a clear trend that the more frequently a reaction is active, the more likely it is a part of the backbone. Finally, I briefly discuss the predicted activity patterns of the central-carbon metabolic pathways for the sample of random environments.

  18. Optimal flux patterns in cellular metabolic networks

    Energy Technology Data Exchange (ETDEWEB)

    Almaas, E

    2007-01-20

    The availability of whole-cell level metabolic networks of high quality has made it possible to develop a predictive understanding of bacterial metabolism. Using the optimization framework of flux balance analysis, I investigate metabolic response and activity patterns to variations in the availability of nutrient and chemical factors such as oxygen and ammonia by simulating 30,000 random cellular environments. The distribution of reaction fluxes is heavy-tailed for the bacteria H. pylori and E. coli, and the eukaryote S. cerevisiae. While the majority of flux balance investigations have relied on implementations of the simplex method, it is necessary to use interior-point optimization algorithms to adequately characterize the full range of activity patterns on metabolic networks. The interior-point activity pattern is bimodal for E. coli and S. cerevisiae, suggesting that most metabolic reaction are either in frequent use or are rarely active. The trimodal activity pattern of H. pylori indicates that a group of its metabolic reactions (20%) are active in approximately half of the simulated environments. Constructing the high-flux backbone of the network for every environment, there is a clear trend that the more frequently a reaction is active, the more likely it is a part of the backbone. Finally, I briefly discuss the predicted activity patterns of the central-carbon metabolic pathways for the sample of random environments.

  19. Thermodynamic principles governing metabolic operation : inference, analysis, and prediction

    NARCIS (Netherlands)

    Niebel, Bastian

    2015-01-01

    The principles governing metabolic flux are poorly understood. Because diverse organisms show similar metabolic flux patterns, we hypothesized that fundamental thermodynamic constraints might shape cellular metabolism. We developed a constraint-based model for Saccharomyces cerevisiae that included

  20. Metabolic flux analysis on arachidonic acid fermentation

    Institute of Scientific and Technical Information of China (English)

    JIN Mingjie; HUANG He; ZHANG Kun; YAN Jie; GAO Zhen

    2007-01-01

    The analysis of flux distributions in metabolic networks has become an important approach for understanding the fermentation characteristics of the process.A model of metabolic flux analysis of arachidonic acid (AA) synthesis in Mortierella alpina ME-1 was established and carbon flux distributions were estimated in different fermentation phases with different concentrations of N-source.During the exponential,decelerating and stationary phase,carbon fluxes to AA were 3.28%,8.80% and 6.97%,respectively,with sufficient N-source broth based on the flux of glucose uptake,and those were increased to 3.95%,19.21% and 39.29%,respectively,by regulating the shifts of carbon fluxes via fermentation with limited N-source broth and adding 0.05%NaNO3 at 96 h.Eventually AA yield was increased from 1.3 to 3.5 g.L-1.These results suggest a way to improve AA fermentation,that is,fermentation with limited N-source broth and adding low concentration N-source during the stationary phase.

  1. Analysis of metabolic flux using dynamic labelling and metabolic modelling.

    Science.gov (United States)

    Fernie, A R; Morgan, J A

    2013-09-01

    Metabolic fluxes and the capacity to modulate them are a crucial component of the ability of the plant cell to react to environmental perturbations. Our ability to quantify them and to attain information concerning the regulatory mechanisms that control them is therefore essential to understand and influence metabolic networks. For all but the simplest of flux measurements labelling methods have proven to be the most informative. Both steady-state and dynamic labelling approaches have been adopted in the study of plant metabolism. Here the conceptual basis of these complementary approaches, as well as their historical application in microbial, mammalian and plant sciences, is reviewed, and an update on technical developments in label distribution analyses is provided. This is supported by illustrative cases studies involving the kinetic modelling of secondary metabolism. One issue that is particularly complex in the analysis of plant fluxes is the extensive compartmentation of the plant cell. This problem is discussed from both theoretical and experimental perspectives, and the current approaches used to address it are assessed. Finally, current limitations and future perspectives of kinetic modelling of plant metabolism are discussed.

  2. Metabolic fluxes in an illuminated Arabidopsis rosette.

    Science.gov (United States)

    Szecowka, Marek; Heise, Robert; Tohge, Takayuki; Nunes-Nesi, Adriano; Vosloh, Daniel; Huege, Jan; Feil, Regina; Lunn, John; Nikoloski, Zoran; Stitt, Mark; Fernie, Alisdair R; Arrivault, Stéphanie

    2013-02-01

    Photosynthesis is the basis for life, and its optimization is a key biotechnological aim given the problems of population explosion and environmental deterioration. We describe a method to resolve intracellular fluxes in intact Arabidopsis thaliana rosettes based on time-dependent labeling patterns in the metabolome. Plants photosynthesizing under limiting irradiance and ambient CO2 in a custom-built chamber were transferred into a (13)CO2-enriched environment. The isotope labeling patterns of 40 metabolites were obtained using liquid or gas chromatography coupled to mass spectrometry. Labeling kinetics revealed striking differences between metabolites. At a qualitative level, they matched expectations in terms of pathway topology and stoichiometry, but some unexpected features point to the complexity of subcellular and cellular compartmentation. To achieve quantitative insights, the data set was used for estimating fluxes in the framework of kinetic flux profiling. We benchmarked flux estimates to four classically determined flux signatures of photosynthesis and assessed the robustness of the estimates with respect to different features of the underlying metabolic model and the time-resolved data set.

  3. Stoichiometric Representation of Gene–Protein–Reaction Associations Leverages Constraint-Based Analysis from Reaction to Gene-Level Phenotype Prediction

    DEFF Research Database (Denmark)

    Machado, Daniel; Herrgard, Markus; Rocha, Isabel

    2016-01-01

    Genome-scale metabolic reconstructions are currently available for hundreds of organisms. Constraint-based modeling enables the analysis of the phenotypic landscape of these organisms, predicting the response to genetic and environmental perturbations. However, since constraint-based models can...... level by explicitly accounting for the individual fluxes of enzymes (and subunits) encoded by each gene. We show how this can be applied to different kinds of constraint-based analysis: flux distribution prediction, gene essentiality analysis, random flux sampling, elementary mode analysis...... only describe the metabolic phenotype at the reaction level, understanding the mechanistic link between genotype and phenotype is still hampered by the complexity of gene-protein-reaction associations. We implement a model transformation that enables constraint-based methods to be applied at the gene...

  4. Flux balance analysis of plant metabolism: the effect of biomass composition and model structure on model predictions

    Directory of Open Access Journals (Sweden)

    Huili eYuan

    2016-04-01

    Full Text Available The biomass composition represented in constraint-based metabolic models is a key component for predicting cellular metabolism using flux balance analysis (FBA. Despite major advances in analytical technologies, it is often challenging to obtain a detailed composition of all major biomass components experimentally. Studies examining the influence of the biomass composition on the predictions of metabolic models have so far mostly been done on models of microorganisms. Little is known about the impact of varying biomass composition on flux prediction in FBA models of plants, whose metabolism is very versatile and complex because of the presence of multiple subcellular compartments. Also, the published metabolic models of plants differ in size and complexity. In this study, we examined the sensitivity of the predicted fluxes of plant metabolic models to biomass composition and model structure. These questions were addressed by evaluating the sensitivity of predictions of growth rates and central carbon metabolic fluxes to varying biomass compositions in three different genome-/large-scale metabolic models of Arabidopsis thaliana. Our results showed that fluxes through the central carbon metabolism were robust to changes in biomass composition. Nevertheless, comparisons between the predictions from three models using identical modelling constraints and objective function showed that model predictions were sensitive to the structure of the models, highlighting large discrepancies between the published models.

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

    Science.gov (United States)

    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.

  6. Metabolic flux analysis using 13C peptide label measurements

    Science.gov (United States)

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

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

    Science.gov (United States)

    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

  8. Metabolic fuels: regulating fluxes to select mix.

    Science.gov (United States)

    Weber, Jean-Michel

    2011-01-15

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

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

    Science.gov (United States)

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

    2016-11-01

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

  10. Constraint-based reachability

    Directory of Open Access Journals (Sweden)

    Arnaud Gotlieb

    2013-02-01

    Full Text Available Iterative imperative programs can be considered as infinite-state systems computing over possibly unbounded domains. Studying reachability in these systems is challenging as it requires to deal with an infinite number of states with standard backward or forward exploration strategies. An approach that we call Constraint-based reachability, is proposed to address reachability problems by exploring program states using a constraint model of the whole program. The keypoint of the approach is to interpret imperative constructions such as conditionals, loops, array and memory manipulations with the fundamental notion of constraint over a computational domain. By combining constraint filtering and abstraction techniques, Constraint-based reachability is able to solve reachability problems which are usually outside the scope of backward or forward exploration strategies. This paper proposes an interpretation of classical filtering consistencies used in Constraint Programming as abstract domain computations, and shows how this approach can be used to produce a constraint solver that efficiently generates solutions for reachability problems that are unsolvable by other approaches.

  11. Flux analysis in plant metabolic networks: increasing throughput and coverage.

    Science.gov (United States)

    Junker, Björn H

    2014-04-01

    Quantitative information about metabolic networks has been mainly obtained at the level of metabolite contents, transcript abundance, and enzyme activities. However, the active process of metabolism is represented by the flow of matter through the pathways. These metabolic fluxes can be predicted by Flux Balance Analysis or determined experimentally by (13)C-Metabolic Flux Analysis. These relatively complicated and time-consuming methods have recently seen significant improvements at the level of coverage and throughput. Metabolic models have developed from single cell models into whole-organism dynamic models. Advances in lab automation and data handling have significantly increased the throughput of flux measurements. This review summarizes advances to increase coverage and throughput of metabolic flux analysis in plants.

  12. Mathematical modeling of isotope labeling experiments for metabolic flux analysis.

    Science.gov (United States)

    Nargund, Shilpa; Sriram, Ganesh

    2014-01-01

    Isotope labeling experiments (ILEs) offer a powerful methodology to perform metabolic flux analysis. However, the task of interpreting data from these experiments to evaluate flux values requires significant mathematical modeling skills. Toward this, this chapter provides background information and examples to enable the reader to (1) model metabolic networks, (2) simulate ILEs, and (3) understand the optimization and statistical methods commonly used for flux evaluation. A compartmentalized model of plant glycolysis and pentose phosphate pathway illustrates the reconstruction of a typical metabolic network, whereas a simpler example network illustrates the underlying metabolite and isotopomer balancing techniques. We also discuss the salient features of commonly used flux estimation software 13CFLUX2, Metran, NMR2Flux+, FiatFlux, and OpenFLUX. Furthermore, we briefly discuss methods to improve flux estimates. A graphical checklist at the end of the chapter provides a reader a quick reference to the mathematical modeling concepts and resources.

  13. OpenFLUX: efficient modelling software for 13C-based metabolic flux analysis

    Directory of Open Access Journals (Sweden)

    Nielsen Lars K

    2009-05-01

    Full Text Available Abstract Background The quantitative analysis of metabolic fluxes, i.e., in vivo activities of intracellular enzymes and pathways, provides key information on biological systems in systems biology and metabolic engineering. It is based on a comprehensive approach combining (i tracer cultivation on 13C substrates, (ii 13C labelling analysis by mass spectrometry and (iii mathematical modelling for experimental design, data processing, flux calculation and statistics. Whereas the cultivation and the analytical part is fairly advanced, a lack of appropriate modelling software solutions for all modelling aspects in flux studies is limiting the application of metabolic flux analysis. Results We have developed OpenFLUX as a user friendly, yet flexible software application for small and large scale 13C metabolic flux analysis. The application is based on the new Elementary Metabolite Unit (EMU framework, significantly enhancing computation speed for flux calculation. From simple notation of metabolic reaction networks defined in a spreadsheet, the OpenFLUX parser automatically generates MATLAB-readable metabolite and isotopomer balances, thus strongly facilitating model creation. The model can be used to perform experimental design, parameter estimation and sensitivity analysis either using the built-in gradient-based search or Monte Carlo algorithms or in user-defined algorithms. Exemplified for a microbial flux study with 71 reactions, 8 free flux parameters and mass isotopomer distribution of 10 metabolites, OpenFLUX allowed to automatically compile the EMU-based model from an Excel file containing metabolic reactions and carbon transfer mechanisms, showing it's user-friendliness. It reliably reproduced the published data and optimum flux distributions for the network under study were found quickly ( Conclusion We have developed a fast, accurate application to perform steady-state 13C metabolic flux analysis. OpenFLUX will strongly facilitate and

  14. A robust and efficient method for estimating enzyme complex abundance and metabolic flux from expression data.

    Science.gov (United States)

    Barker, Brandon E; Sadagopan, Narayanan; Wang, Yiping; Smallbone, Kieran; Myers, Christopher R; Xi, Hongwei; Locasale, Jason W; Gu, Zhenglong

    2015-12-01

    A major theme in constraint-based modeling is unifying experimental data, such as biochemical information about the reactions that can occur in a system or the composition and localization of enzyme complexes, with high-throughput data including expression data, metabolomics, or DNA sequencing. The desired result is to increase predictive capability and improve our understanding of metabolism. The approach typically employed when only gene (or protein) intensities are available is the creation of tissue-specific models, which reduces the available reactions in an organism model, and does not provide an objective function for the estimation of fluxes. We develop a method, flux assignment with LAD (least absolute deviation) convex objectives and normalization (FALCON), that employs metabolic network reconstructions along with expression data to estimate fluxes. In order to use such a method, accurate measures of enzyme complex abundance are needed, so we first present an algorithm that addresses quantification of complex abundance. Our extensions to prior techniques include the capability to work with large models and significantly improved run-time performance even for smaller models, an improved analysis of enzyme complex formation, the ability to handle large enzyme complex rules that may incorporate multiple isoforms, and either maintained or significantly improved correlation with experimentally measured fluxes. FALCON has been implemented in MATLAB and ATS, and can be downloaded from: https://github.com/bbarker/FALCON. ATS is not required to compile the software, as intermediate C source code is available. FALCON requires use of the COBRA Toolbox, also implemented in MATLAB.

  15. Generic flux coupling analysis

    NARCIS (Netherlands)

    Reimers, A.C.; Goldstein, Y.; Bockmayr, A.

    2015-01-01

    Flux coupling analysis (FCA) has become a useful tool for aiding metabolic reconstructions and guiding genetic manipulations. Originally, it was introduced for constraint-based models of metabolic networks that are based on the steady-state assumption. Recently, we have shown that the steady-state a

  16. Metabolic flux ratio analysis and multi-objective optimization revealed a globally conserved and coordinated metabolic response of E. coli to paraquat-induced oxidative stress.

    Science.gov (United States)

    Shen, Tie; Rui, Bin; Zhou, Hong; Zhang, Ximing; Yi, Yin; Wen, Han; Zheng, Haoran; Wu, Jihui; Shi, Yunyu

    2013-01-27

    The ability of a microorganism to adapt to changes in the environment, such as in nutrient or oxygen availability, is essential for its competitive fitness and survival. The cellular objective and the strategy of the metabolic response to an extreme environment are therefore of tremendous interest and, thus, have been increasingly explored. However, the cellular objective of the complex regulatory structure of the metabolic changes has not yet been fully elucidated and more details regarding the quantitative behaviour of the metabolic flux redistribution are required to understand the systems-wide biological significance of this response. In this study, the intracellular metabolic flux ratios involved in the central carbon metabolism were determined by fractional (13)C-labeling and metabolic flux ratio analysis (MetaFoR) of the wild-type E. coli strain JM101 at an oxidative environment in a chemostat. We observed a significant increase in the flux through phosphoenolpyruvate carboxykinase (PEPCK), phosphoenolpyruvate carboxylase (PEPC), malic enzyme (MEZ) and serine hydroxymethyltransferase (SHMT). We applied an ε-constraint based multi-objective optimization to investigate the trade-off relationships between the biomass yield and the generation of reductive power using the in silico iJR904 genome-scale model of E. coli K-12. The theoretical metabolic redistribution supports that the trans-hydrogenase pathway should not play a direct role in the defence mounted by E. coli against oxidative stress. The agreement between the measured ratio and the theoretical redistribution established the significance of NADPH synthesis as the goal of the metabolic reprogramming that occurs in response to oxidative stress. Our work presents a framework that combines metabolic flux ratio analysis and multi-objective optimization to investigate the metabolic trade-offs that occur under varied environmental conditions. Our results led to the proposal that the metabolic response of E

  17. Functioning of a metabolic flux sensor in Escherichia coli

    NARCIS (Netherlands)

    Kochanowski, Karl; Volkmer, Benjamin; Gerosa, Luca; Haverkorn van Rijsewijk, Bart R; Schmidt, Alexander; Heinemann, Matthias

    2013-01-01

    Regulation of metabolic operation in response to extracellular cues is crucial for cells' survival. Next to the canonical nutrient sensors, which measure the concentration of nutrients, recently intracellular "metabolic flux" was proposed as a novel impetus for metabolic regulation. According to

  18. Functioning of a metabolic flux sensor in Escherichia coli

    NARCIS (Netherlands)

    Kochanowski, Karl; Volkmer, Benjamin; Gerosa, Luca; Haverkorn van Rijsewijk, Bart R; Schmidt, Alexander; Heinemann, Matthias

    2013-01-01

    Regulation of metabolic operation in response to extracellular cues is crucial for cells' survival. Next to the canonical nutrient sensors, which measure the concentration of nutrients, recently intracellular "metabolic flux" was proposed as a novel impetus for metabolic regulation. According to thi

  19. Insights into pH-induced metabolic switch by flux balance analysis.

    Science.gov (United States)

    Ivarsson, Marija; Noh, Heeju; Morbidelli, Massimo; Soos, Miroslav

    2015-01-01

    Lactate accumulation in mammalian cell culture is known to impede cellular growth and productivity. The control of lactate formation and consumption in a hybridoma cell line was achieved by pH alteration during the early exponential growth phase. In particular, lactate consumption was induced even at high glucose concentrations at pH 6.8, whereas highly increased production of lactate was obtained at pH 7.8. Consequently, constraint-based metabolic flux analysis was used to examine pH-induced metabolic states in the same growth state. We demonstrated that lactate influx at pH 6.8 led cells to maintain high fluxes in the TCA cycle and malate-aspartate shuttle resulting in a high ATP production rate. In contrast, under increased pH conditions, less ATP was generated and different ATP sources were utilized. Gene expression analysis led to the conclusion that lactate formation at high pH was enabled by gluconeogenic pathways in addition to facilitated glucose uptake. The obtained results provide new insights into the influence of pH on cellular metabolism, and are of importance when considering pH heterogeneities typically present in large scale industrial bioreactors.

  20. FiatFlux--a software for metabolic flux analysis from 13C-glucose experiments.

    Science.gov (United States)

    Zamboni, Nicola; Fischer, Eliane; Sauer, Uwe

    2005-08-25

    Quantitative knowledge of intracellular fluxes is important for a comprehensive characterization of metabolic networks and their functional operation. In contrast to direct assessment of metabolite concentrations, in vivo metabolite fluxes must be inferred indirectly from measurable quantities in 13C experiments. The required experience, the complicated network models, large and heterogeneous data sets, and the time-consuming set-up of highly controlled experimental conditions largely restricted metabolic flux analysis to few expert groups. A conceptual simplification of flux analysis is the analytical determination of metabolic flux ratios exclusively from MS data, which can then be used in a second step to estimate absolute in vivo fluxes. Here we describe the user-friendly software package FiatFlux that supports flux analysis for non-expert users. In the first module, ratios of converging fluxes are automatically calculated from GC-MS-detected 13C-pattern in protein-bound amino acids. Predefined fragmentation patterns are automatically identified and appropriate statistical data treatment is based on the comparison of redundant information in the MS spectra. In the second module, absolute intracellular fluxes may be calculated by a 13C-constrained flux balancing procedure that combines experimentally determined fluxes in and out of the cell and the above flux ratios. The software is preconfigured to derive flux ratios and absolute in vivo fluxes from [1-13C] and [U-13C]glucose experiments and GC-MS analysis of amino acids for a variety of microorganisms. FiatFlux is an intuitive tool for quantitative investigations of intracellular metabolism by users that are not familiar with numerical methods or isotopic tracer experiments. The aim of this open source software is to enable non-specialists to adapt the software to their specific scientific interests, including other 13C-substrates, labeling mixtures, and organisms.

  1. FiatFlux – a software for metabolic flux analysis from 13C-glucose experiments

    Directory of Open Access Journals (Sweden)

    Fischer Eliane

    2005-08-01

    Full Text Available Abstract Background Quantitative knowledge of intracellular fluxes is important for a comprehensive characterization of metabolic networks and their functional operation. In contrast to direct assessment of metabolite concentrations, in vivo metabolite fluxes must be inferred indirectly from measurable quantities in 13C experiments. The required experience, the complicated network models, large and heterogeneous data sets, and the time-consuming set-up of highly controlled experimental conditions largely restricted metabolic flux analysis to few expert groups. A conceptual simplification of flux analysis is the analytical determination of metabolic flux ratios exclusively from MS data, which can then be used in a second step to estimate absolute in vivo fluxes. Results Here we describe the user-friendly software package FiatFlux that supports flux analysis for non-expert users. In the first module, ratios of converging fluxes are automatically calculated from GC-MS-detected 13C-pattern in protein-bound amino acids. Predefined fragmentation patterns are automatically identified and appropriate statistical data treatment is based on the comparison of redundant information in the MS spectra. In the second module, absolute intracellular fluxes may be calculated by a 13C-constrained flux balancing procedure that combines experimentally determined fluxes in and out of the cell and the above flux ratios. The software is preconfigured to derive flux ratios and absolute in vivo fluxes from [1-13C] and [U-13C]glucose experiments and GC-MS analysis of amino acids for a variety of microorganisms. Conclusion FiatFlux is an intuitive tool for quantitative investigations of intracellular metabolism by users that are not familiar with numerical methods or isotopic tracer experiments. The aim of this open source software is to enable non-specialists to adapt the software to their specific scientific interests, including other 13C-substrates, labeling mixtures

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

    Science.gov (United States)

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

    2012-03-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

    O' Grady, J; Schwender, J; Shachar-Hill, Y; Morgan, JA

    2012-03-26

    For the past decade, flux maps have provided researchers with an in-depth perspective on plant metabolism. As a rapidly developing field, significant headway has been made recently in computation, experimentation, and overall understanding of metabolic flux analysis. These advances are particularly applicable to the study of plant metabolism. New dynamic computational methods such as non-stationary metabolic flux analysis are finding their place in the toolbox of metabolic engineering, allowing more organisms to be studied and decreasing the time necessary for experimentation, thereby opening new avenues by which to explore the vast diversity of plant metabolism. Also, improved methods of metabolite detection and measurement have been developed, enabling increasingly greater resolution of flux measurements and the analysis of a greater number of the multitude of plant metabolic pathways. Methods to deconvolute organelle-specific metabolism are employed with increasing effectiveness, elucidating the compartmental specificity inherent in plant metabolism. Advances in metabolite measurements have also enabled new types of experiments, such as the calculation of metabolic fluxes based on (CO2)-C-13 dynamic labelling data, and will continue to direct plant metabolic engineering. Newly calculated metabolic flux maps reveal surprising and useful information about plant metabolism, guiding future genetic engineering of crops to higher yields. Due to the significant level of complexity in plants, these methods in combination with other systems biology measurements are necessary to guide plant metabolic engineering in the future.

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

    Energy Technology Data Exchange (ETDEWEB)

    O' Grady J.; Schwender J.; Shachar-Hill, Y.; Morgan, J. A.

    2012-03-01

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

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

    Science.gov (United States)

    Toya, Yoshihiro; Shimizu, Hiroshi

    2013-11-01

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

  6. Recent advances in elementary flux modes and yield space analysis as useful tools in metabolic network studies.

    Science.gov (United States)

    Horvat, Predrag; Koller, Martin; Braunegg, Gerhart

    2015-09-01

    A review of the use of elementary flux modes (EFMs) and their applications in metabolic engineering covered with yield space analysis (YSA) is presented. EFMs are an invaluable tool in mathematical modeling of biochemical processes. They are described from their inception in 1994, followed by various improvements of their computation in later years. YSA constitutes another precious tool for metabolic network modeling, and is presented in details along with EFMs in this article. The application of these techniques is discussed for several case studies of metabolic network modeling provided in respective original articles. The article is concluded by some case studies in which the application of EFMs and YSA turned out to be most useful, such as the analysis of intracellular polyhydroxyalkanoate (PHA) formation and consumption in Cupriavidus necator, including the constraint-based description of the steady-state flux cone of the strain's metabolic network, the profound analysis of a continuous five-stage bioreactor cascade for PHA production by C. necator using EFMs and, finally, the study of metabolic fluxes in the metabolic network of C. necator cultivated on glycerol.

  7. OpenFLUX: efficient modelling software for 13C-based metabolic flux analysis

    OpenAIRE

    Nielsen Lars K; Wittmann Christoph; Quek Lake-Ee; Krömer Jens O

    2009-01-01

    Abstract Background The quantitative analysis of metabolic fluxes, i.e., in vivo activities of intracellular enzymes and pathways, provides key information on biological systems in systems biology and metabolic engineering. It is based on a comprehensive approach combining (i) tracer cultivation on 13C substrates, (ii) 13C labelling analysis by mass spectrometry and (iii) mathematical modelling for experimental design, data processing, flux calculation and statistics. Whereas the cultivation ...

  8. 13C-based metabolic flux analysis: fundamentals and practice.

    Science.gov (United States)

    Yang, Tae Hoon

    2013-01-01

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

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

    Science.gov (United States)

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

    2013-12-01

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

  10. Comprehensive analysis of glucose and xylose metabolism in Escherichia coli under aerobic and anaerobic conditions by (13)C metabolic flux analysis.

    Science.gov (United States)

    Gonzalez, Jacqueline E; Long, Christopher P; Antoniewicz, Maciek R

    2017-01-01

    Glucose and xylose are the two most abundant sugars derived from the breakdown of lignocellulosic biomass. While aerobic glucose metabolism is relatively well understood in E. coli, until now there have been only a handful of studies focused on anaerobic glucose metabolism and no (13)C-flux studies on xylose metabolism. In the absence of experimentally validated flux maps, constraint-based approaches such as MOMA and RELATCH cannot be used to guide new metabolic engineering designs. In this work, we have addressed this critical gap in current understanding by performing comprehensive characterizations of glucose and xylose metabolism under aerobic and anaerobic conditions, using recent state-of-the-art techniques in (13)C metabolic flux analysis ((13)C-MFA). Specifically, we quantified precise metabolic fluxes for each condition by performing parallel labeling experiments and analyzing the data through integrated (13)C-MFA using the optimal tracers [1,2-(13)C]glucose, [1,6-(13)C]glucose, [1,2-(13)C]xylose and [5-(13)C]xylose. We also quantified changes in biomass composition and confirmed turnover of macromolecules by applying [U-(13)C]glucose and [U-(13)C]xylose tracers. We demonstrated that under anaerobic growth conditions there is significant turnover of lipids and that a significant portion of CO2 originates from biomass turnover. Using knockout strains, we also demonstrated that β-oxidation is critical for anaerobic growth on xylose. Quantitative analysis of co-factor balances (NADH/FADH2, NADPH, and ATP) for different growth conditions provided new insights regarding the interplay of energy and redox metabolism and the impact on E. coli cell physiology.

  11. (13)C metabolic flux analysis of recombinant expression hosts.

    Science.gov (United States)

    Young, Jamey D

    2014-12-01

    Identifying host cell metabolic phenotypes that promote high recombinant protein titer is a major goal of the biotech industry. (13)C metabolic flux analysis (MFA) provides a rigorous approach to quantify these metabolic phenotypes by applying isotope tracers to map the flow of carbon through intracellular metabolic pathways. Recent advances in tracer theory and measurements are enabling more information to be extracted from (13)C labeling experiments. Sustained development of publicly available software tools and standardization of experimental workflows is simultaneously encouraging increased adoption of (13)C MFA within the biotech research community. A number of recent (13)C MFA studies have identified increased citric acid cycle and pentose phosphate pathway fluxes as consistent markers of high recombinant protein expression, both in mammalian and microbial hosts. Further work is needed to determine whether redirecting flux into these pathways can effectively enhance protein titers while maintaining acceptable glycan profiles.

  12. Metabolic flux prediction in cancer cells with altered substrate uptake.

    Science.gov (United States)

    Schwartz, Jean-Marc; Barber, Michael; Soons, Zita

    2015-12-01

    Proliferating cells, such as cancer cells, are known to have an unusual metabolism, characterized by an increased rate of glycolysis and amino acid metabolism. Our understanding of this phenomenon is limited but could potentially be used in order to develop new therapies. Computational modelling techniques, such as flux balance analysis (FBA), have been used to predict fluxes in various cell types, but remain of limited use to explain the unusual metabolic shifts and altered substrate uptake in human cancer cells. We implemented a new flux prediction method based on elementary modes (EMs) and structural flux (StruF) analysis and tested them against experimentally measured flux data obtained from (13)C-labelling in a cancer cell line. We assessed the quality of predictions using different objective functions along with different techniques in normalizing a metabolic network with more than one substrate input. Results show a good correlation between predicted and experimental values and indicate that the choice of cellular objective critically affects the quality of predictions. In particular, lactate gives an excellent correlation and correctly predicts the high flux through glycolysis, matching the observed characteristics of cancer cells. In contrast with FBA, which requires a priori definition of all uptake rates, often hard to measure, atomic StruFs (aStruFs) are able to predict uptake rates of multiple substrates.

  13. Symbolic flux analysis for genome-scale metabolic networks

    Directory of Open Access Journals (Sweden)

    Peterson Pearu

    2011-05-01

    Full Text Available Abstract Background With the advent of genomic technology, the size of metabolic networks that are subject to analysis is growing. A common task when analyzing metabolic networks is to find all possible steady state regimes. There are several technical issues that have to be addressed when analyzing large metabolic networks including accumulation of numerical errors and presentation of the solution to the researcher. One way to resolve those technical issues is to analyze the network using symbolic methods. The aim of this paper is to develop a routine that symbolically finds the steady state solutions of large metabolic networks. Results A symbolic Gauss-Jordan elimination routine was developed for analyzing large metabolic networks. This routine was tested by finding the steady state solutions for a number of curated stoichiometric matrices with the largest having about 4000 reactions. The routine was able to find the solution with a computational time similar to the time used by a numerical singular value decomposition routine. As an advantage of symbolic solution, a set of independent fluxes can be suggested by the researcher leading to the formation of a desired flux basis describing the steady state solution of the network. These independent fluxes can be constrained using experimental data. We demonstrate the application of constraints by calculating a flux distribution for the central metabolic and amino acid biosynthesis pathways of yeast. Conclusions We were able to find symbolic solutions for the steady state flux distribution of large metabolic networks. The ability to choose a flux basis was found to be useful in the constraint process and provides a strong argument for using symbolic Gauss-Jordan elimination in place of singular value decomposition.

  14. Symbolic flux analysis for genome-scale metabolic networks.

    Science.gov (United States)

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

    2011-05-23

    With the advent of genomic technology, the size of metabolic networks that are subject to analysis is growing. A common task when analyzing metabolic networks is to find all possible steady state regimes. There are several technical issues that have to be addressed when analyzing large metabolic networks including accumulation of numerical errors and presentation of the solution to the researcher. One way to resolve those technical issues is to analyze the network using symbolic methods. The aim of this paper is to develop a routine that symbolically finds the steady state solutions of large metabolic networks. A symbolic Gauss-Jordan elimination routine was developed for analyzing large metabolic networks. This routine was tested by finding the steady state solutions for a number of curated stoichiometric matrices with the largest having about 4000 reactions. The routine was able to find the solution with a computational time similar to the time used by a numerical singular value decomposition routine. As an advantage of symbolic solution, a set of independent fluxes can be suggested by the researcher leading to the formation of a desired flux basis describing the steady state solution of the network. These independent fluxes can be constrained using experimental data. We demonstrate the application of constraints by calculating a flux distribution for the central metabolic and amino acid biosynthesis pathways of yeast. We were able to find symbolic solutions for the steady state flux distribution of large metabolic networks. The ability to choose a flux basis was found to be useful in the constraint process and provides a strong argument for using symbolic Gauss-Jordan elimination in place of singular value decomposition.

  15. Prediction of metabolic flux distribution from gene expression data based on the flux minimization principle.

    Directory of Open Access Journals (Sweden)

    Hyun-Seob Song

    Full Text Available Prediction of possible flux distributions in a metabolic network provides detailed phenotypic information that links metabolism to cellular physiology. To estimate metabolic steady-state fluxes, the most common approach is to solve a set of macroscopic mass balance equations subjected to stoichiometric constraints while attempting to optimize an assumed optimal objective function. This assumption is justifiable in specific cases but may be invalid when tested across different conditions, cell populations, or other organisms. With an aim to providing a more consistent and reliable prediction of flux distributions over a wide range of conditions, in this article we propose a framework that uses the flux minimization principle to predict active metabolic pathways from mRNA expression data. The proposed algorithm minimizes a weighted sum of flux magnitudes, while biomass production can be bounded to fit an ample range from very low to very high values according to the analyzed context. We have formulated the flux weights as a function of the corresponding enzyme reaction's gene expression value, enabling the creation of context-specific fluxes based on a generic metabolic network. In case studies of wild-type Saccharomyces cerevisiae, and wild-type and mutant Escherichia coli strains, our method achieved high prediction accuracy, as gauged by correlation coefficients and sums of squared error, with respect to the experimentally measured values. In contrast to other approaches, our method was able to provide quantitative predictions for both model organisms under a variety of conditions. Our approach requires no prior knowledge or assumption of a context-specific metabolic functionality and does not require trial-and-error parameter adjustments. Thus, our framework is of general applicability for modeling the transcription-dependent metabolism of bacteria and yeasts.

  16. 13C metabolic flux analysis at a genome-scale.

    Science.gov (United States)

    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

  17. Comparative Metabolic Flux Profiling of Melanoma Cell Lines

    Science.gov (United States)

    Scott, David A.; Richardson, Adam D.; Filipp, Fabian V.; Knutzen, Christine A.; Chiang, Gary G.; Ronai, Ze'ev A.; Osterman, Andrei L.; Smith, Jeffrey W.

    2011-01-01

    Metabolic rewiring is an established hallmark of cancer, but the details of this rewiring at a systems level are not well characterized. Here we acquire this insight in a melanoma cell line panel by tracking metabolic flux using isotopically labeled nutrients. Metabolic profiling and flux balance analysis were used to compare normal melanocytes to melanoma cell lines in both normoxic and hypoxic conditions. All melanoma cells exhibited the Warburg phenomenon; they used more glucose and produced more lactate than melanocytes. Other changes were observed in melanoma cells that are not described by the Warburg phenomenon. Hypoxic conditions increased fermentation of glucose to lactate in both melanocytes and melanoma cells (the Pasteur effect). However, metabolism was not strictly glycolytic, as the tricarboxylic acid (TCA) cycle was functional in all melanoma lines, even under hypoxia. Furthermore, glutamine was also a key nutrient providing a substantial anaplerotic contribution to the TCA cycle. In the WM35 melanoma line glutamine was metabolized in the “reverse” (reductive) direction in the TCA cycle, particularly under hypoxia. This reverse flux allowed the melanoma cells to synthesize fatty acids from glutamine while glucose was primarily converted to lactate. Altogether, this study, which is the first comprehensive comparative analysis of metabolism in melanoma cells, provides a foundation for targeting metabolism for therapeutic benefit in melanoma. PMID:21998308

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

    Science.gov (United States)

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

    2015-01-01

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

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

    Science.gov (United States)

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

    2016-07-11

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

  20. In vivo NMR for ¹³C Metabolic Flux Analysis.

    Science.gov (United States)

    Roscher, Albrecht; Troufflard, Stéphanie; Taghki, Abdelghani Idrissi

    2014-01-01

    The use of in vivo NMR within the framework of Metabolic Flux Analysis in plants is presented. In vivo NMR allows to visualize the active metabolic network, to determine metabolic and isotopic steady state and to measure metabolic fluxes which are not necessarily accessible by isotopic steady state (stationary) Metabolic Flux Analysis. The kinetic data can be used as input for dynamic (nonstationary) Metabolic Flux Analysis. Both 1D and 2D NMR methods are employed.

  1. Expanded flux variability analysis on metabolic network of Escherichia coli

    Institute of Scientific and Technical Information of China (English)

    CHEN Tong; XIE ZhengWei; OUYANG Qi

    2009-01-01

    Flux balance analysis,based on the mass conservation law in a cellular organism,has been extensively employed to study the interplay between structures and functions of cellular metabolic networks.Consequently,the phenotypes of the metabolism can be well elucidated.In this paper,we introduce the Expanded Flux Variability Analysis (EFVA) to characterize the intrinsic nature of metabolic reactions,such as flexibility,modularity and essentiality,by exploring the trend of the range,the maximum and the minimum flux of reactions.We took the metabolic network of Escherichia coli as an example and analyzed the variability of reaction fluxes under different growth rate constraints.The average variability of all reactions decreases dramatically when the growth rate increases.Consider the noise effect on the metabolic system,we thus argue that the microorganism may practically grow under a suboptimal state.Besides,under the EFVA framework,the reactions are easily to be grouped into catabolic and anabolic groups.And the anabolic groups can be further assigned to specific biomass constitute.We also discovered the growth rate dependent essentiality of reactions.

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

    Science.gov (United States)

    Tabe-Bordbar, Shayan; Marashi, Sayed-Amir

    2013-12-01

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

  3. Dynamic metabolic flux analysis--tools for probing transient states of metabolic networks.

    Science.gov (United States)

    Antoniewicz, Maciek R

    2013-12-01

    Computational approaches for analyzing dynamic states of metabolic networks provide a practical framework for design, control, and optimization of biotechnological processes. In recent years, two promising modeling approaches have emerged for characterizing transients in cellular metabolism, dynamic metabolic flux analysis (DMFA), and dynamic flux balance analysis (DFBA). Both approaches combine metabolic network analysis based on pseudo steady-state (PSS) assumption for intracellular metabolism with dynamic models for extracellular environment. One strategy to capture dynamics is by combining network analysis with a kinetic model. Predictive models are thus established that can be used to optimize bioprocessing conditions and identify useful genetic manipulations. Alternatively, by combining network analysis with methods for analyzing extracellular time-series data, transients in intracellular metabolic fluxes can be determined and applied for process monitoring and control.

  4. 13C-Metabolic Flux Analysis: An Accurate Approach to Demystify Microbial Metabolism for Biochemical Production

    OpenAIRE

    Weihua Guo; Jiayuan Sheng; Xueyang Feng

    2015-01-01

    Metabolic engineering of various industrial microorganisms to produce chemicals, fuels, and drugs has raised interest since it is environmentally friendly, sustainable, and independent of nonrenewable resources. However, microbial metabolism is so complex that only a few metabolic engineering efforts have been able to achieve a satisfactory yield, titer or productivity of the target chemicals for industrial commercialization. In order to overcome this challenge, 13C Metabolic Flux Analysis (1...

  5. Comparison between elementary flux modes analysis and 13C-metabolic fluxes measured in bacterial and plant cells

    Directory of Open Access Journals (Sweden)

    Dieuaide-Noubhani Martine

    2011-06-01

    Full Text Available Abstract Background 13C metabolic flux analysis is one of the pertinent ways to compare two or more physiological states. From a more theoretical standpoint, the structural properties of metabolic networks can be analysed to explore feasible metabolic behaviours and to define the boundaries of steady state flux distributions. Elementary flux mode analysis is one of the most efficient methods for performing this analysis. In this context, recent approaches have tended to compare experimental flux measurements with topological network analysis. Results Metabolic networks describing the main pathways of central carbon metabolism were set up for a bacteria species (Corynebacterium glutamicum and a plant species (Brassica napus for which experimental flux maps were available. The structural properties of each network were then studied using the concept of elementary flux modes. To do this, coefficients of flux efficiency were calculated for each reaction within the networks by using selected sets of elementary flux modes. Then the relative differences - reflecting the change of substrate i.e. a sugar source for C. glutamicum and a nitrogen source for B. napus - of both flux efficiency and flux measured experimentally were compared. For both organisms, there is a clear relationship between these parameters, thus indicating that the network structure described by the elementary flux modes had captured a significant part of the metabolic activity in both biological systems. In B. napus, the extension of the elementary flux mode analysis to an enlarged metabolic network still resulted in a clear relationship between the change in the coefficients and that of the measured fluxes. Nevertheless, the limitations of the method to fit some particular fluxes are discussed. Conclusion This consistency between EFM analysis and experimental flux measurements, validated on two metabolic systems allows us to conclude that elementary flux mode analysis could be a

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

    Science.gov (United States)

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

  7. Methods and advances in metabolic flux analysis: a mini-review.

    Science.gov (United States)

    Antoniewicz, Maciek R

    2015-03-01

    Metabolic flux analysis (MFA) is one of the pillars of metabolic engineering. Over the past three decades, it has been widely used to quantify intracellular metabolic fluxes in both native (wild type) and engineered biological systems. Through MFA, changes in metabolic pathway fluxes are quantified that result from genetic and/or environmental interventions. This information, in turn, provides insights into the regulation of metabolic pathways and may suggest new targets for further metabolic engineering of the strains. In this mini-review, we discuss and classify the various methods of MFA that have been developed, which include stoichiometric MFA, (13)C metabolic flux analysis, isotopic non-stationary (13)C metabolic flux analysis, dynamic metabolic flux analysis, and (13)C dynamic metabolic flux analysis. For each method, we discuss key advantages and limitations and conclude by highlighting important recent advances in flux analysis approaches.

  8. Software applications toward quantitative metabolic flux analysis and modeling.

    Science.gov (United States)

    Dandekar, Thomas; Fieselmann, Astrid; Majeed, Saman; Ahmed, Zeeshan

    2014-01-01

    Metabolites and their pathways are central for adaptation and survival. Metabolic modeling elucidates in silico all the possible flux pathways (flux balance analysis, FBA) and predicts the actual fluxes under a given situation, further refinement of these models is possible by including experimental isotopologue data. In this review, we initially introduce the key theoretical concepts and different analysis steps in the modeling process before comparing flux calculation and metabolite analysis programs such as C13, BioOpt, COBRA toolbox, Metatool, efmtool, FiatFlux, ReMatch, VANTED, iMAT and YANA. Their respective strengths and limitations are discussed and compared to alternative software. While data analysis of metabolites, calculation of metabolic fluxes, pathways and their condition-specific changes are all possible, we highlight the considerations that need to be taken into account before deciding on a specific software. Current challenges in the field include the computation of large-scale networks (in elementary mode analysis), regulatory interactions and detailed kinetics, and these are discussed in the light of powerful new approaches.

  9. Assessing compartmentalized flux in lipid metabolism with isotopes.

    Science.gov (United States)

    Allen, Doug K

    2016-09-01

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

  10. Metabolic flux analysis of Gluconacetobacter xylinus for bacterial cellulose production.

    Science.gov (United States)

    Zhong, Cheng; Zhang, Gui-Cai; Liu, Miao; Zheng, Xin-Tong; Han, Pei-Pei; Jia, Shi-Ru

    2013-07-01

    Metabolic flux analysis was used to reveal the metabolic distributions in Gluconacetobacter xylinus (CGMCC no. 2955) cultured on different carbon sources. Compared with other sources, glucose, fructose, and glycerol could achieve much higher bacterial cellulose (BC) yields from G. xylinus (CGMCC no. 2955). The glycerol led to the highest BC production with a metabolic yield of 14.7 g/mol C, which was approximately 1.69-fold and 2.38-fold greater than that produced using fructose and glucose medium, respectively. The highest BC productivity from G. xylinus CGMCC 2955 was 5.97 g BC/L (dry weight) when using glycerol as the sole carbon source. Metabolic flux analysis for the central carbon metabolism revealed that about 47.96 % of glycerol was transformed into BC, while only 19.05 % of glucose and 24.78 % of fructose were transformed into BC. Instead, when glucose was used as the sole carbon source, 40.03 % of glucose was turned into the by-product gluconic acid. Compared with BC from glucose and fructose, BC from the glycerol medium showed the highest tensile strength at 83.5 MPa, with thinner fibers and lower porosity. As a main byproduct of biodiesel production, glycerol holds great potential to produce BC with superior mechanical and microstructural characteristics.

  11. Metabolic Flux Analysis of Shewanella spp. Reveals Evolutionary Robustness in Central Carbon Metabolism

    Energy Technology Data Exchange (ETDEWEB)

    Tang, Yinjie J.; Martin, Hector Garcia; Dehal, Paramvir S.; Deutschbauer, Adam; Llora, Xavier; Meadows, Adam; Arkin, Adam; Keasling, Jay D.

    2009-08-19

    Shewanella spp. are a group of facultative anaerobic bacteria widely distributed in marine and fresh-water environments. In this study, we profiled the central metabolic fluxes of eight recently sequenced Shewanella species grown under the same condition in minimal med-ium with [3-13C] lactate. Although the tested Shewanella species had slightly different growth rates (0.23-0.29 h31) and produced different amounts of acetate and pyruvate during early exponential growth (pseudo-steady state), the relative intracellular metabolic flux distributions were remarkably similar. This result indicates that Shewanella species share similar regulation in regard to central carbon metabolic fluxes under steady growth conditions: the maintenance of metabolic robustness is not only evident in a single species under genetic perturbations (Fischer and Sauer, 2005; Nat Genet 37(6):636-640), but also observed through evolutionary related microbial species. This remarkable conservation of relative flux profiles through phylogenetic differences prompts us to introduce the concept of metabotype as an alternative scheme to classify microbial fluxomics. On the other hand, Shewanella spp. display flexibility in the relative flux profiles when switching their metabolism from consuming lactate to consuming pyruvate and acetate.

  12. Maintenance metabolism and carbon fluxes in Bacillus species

    Directory of Open Access Journals (Sweden)

    Decasper Seraina

    2008-06-01

    Full Text Available Abstract Background Selection of an appropriate host organism is crucial for the economic success of biotechnological processes. A generally important selection criterion is a low maintenance energy metabolism to reduce non-productive consumption of substrate. We here investigated, whether various bacilli that are closely related to Bacillus subtilis are potential riboflavin production hosts with low maintenance metabolism. Results While B. subtilis exhibited indeed the highest maintenance energy coefficient, B. licheniformis and B. amyloliquefaciens exhibited only statistically insignificantly reduced maintenance metabolism. Both B. pumilus and B. subtilis (natto exhibited irregular growth patterns under glucose limitation such that the maintenance metabolism could not be determined. The sole exception with significantly reduced maintenance energy requirements was the B. licheniformis strain T380B. The frequently used spo0A mutation significantly increased the maintenance metabolism of B. subtilis. At the level of 13C-detected intracellular fluxes, all investigated bacilli exhibited a significant flux through the pentose phosphate pathway, a prerequisite for efficient riboflavin production. Different from all other species, B. subtilis featured high respiratory tricarboxylic acid cycle fluxes in batch and chemostat cultures. In particular under glucose-limited conditions, this led to significant excess formation of NADPH of B. subtilis, while anabolic consumption was rather balanced with catabolic NADPH formation in the other bacilli. Conclusion Despite its successful commercial production of riboflavin, B. subtilis does not seem to be the optimal cell factory from a bioenergetic point of view. The best choice of the investigated strains is the sporulation-deficient B. licheniformis T380B strain. Beside a low maintenance energy coefficient, this strain grows robustly under different conditions and exhibits only moderate acetate overflow, hence

  13. Parallel labeling experiments validate Clostridium acetobutylicum metabolic network model for (13)C metabolic flux analysis.

    Science.gov (United States)

    Au, Jennifer; Choi, Jungik; Jones, Shawn W; Venkataramanan, Keerthi P; Antoniewicz, Maciek R

    2014-11-01

    In this work, we provide new insights into the metabolism of Clostridium acetobutylicum ATCC 824 obtained using a systematic approach for quantifying fluxes based on parallel labeling experiments and (13)C-metabolic flux analysis ((13)C-MFA). Here, cells were grown in parallel cultures with [1-(13)C]glucose and [U-(13)C]glucose as tracers and (13)C-MFA was used to quantify intracellular metabolic fluxes. Several metabolic network models were compared: an initial model based on current knowledge, and extended network models that included additional reactions that improved the fits of experimental data. While the initial network model did not produce a statistically acceptable fit of (13)C-labeling data, an extended network model with five additional reactions was able to fit all data with 292 redundant measurements. The model was subsequently trimmed to produce a minimal network model of C. acetobutylicum for (13)C-MFA, which could still reproduce all of the experimental data. The flux results provided valuable new insights into the metabolism of C. acetobutylicum. First, we found that TCA cycle was effectively incomplete, as there was no measurable flux between α-ketoglutarate and succinyl-CoA, succinate and fumarate, and malate and oxaloacetate. Second, an active pathway was identified from pyruvate to fumarate via aspartate. Third, we found that isoleucine was produced exclusively through the citramalate synthase pathway in C. acetobutylicum and that CAC3174 was likely responsible for citramalate synthase activity. These model predictions were confirmed in several follow-up tracer experiments. The validated metabolic network model established in this study can be used in future investigations for unbiased (13)C-flux measurements in C. acetobutylicum. Copyright © 2014 International Metabolic Engineering Society. Published by Elsevier Inc. All rights reserved.

  14. Aerobic glucose metabolism of Saccharomyces kluyveri: Growth, metabolite production, and quantification of metabolic fluxes

    DEFF Research Database (Denmark)

    Møller, Kasper; Christensen, B.; Förster, Jochen

    2002-01-01

    The growth and product formation of Saccharomyces kluyveri was characterized in aerobic batch cultivation on glucose. At these conditions it was found that ethyl acetate was a major overflow metabolite in S. kluyveri. During the exponential-growth phase on glucose ethyl acetate was produced.......29 +/- 0.01 g/g). The glucose metabolism of S. kluyveri was further characterized by the new and powerful techniques of metabolic network analysis. Flux distributions in the central carbon metabolism were estimated for respiro-fermentative growth in aerobic batch cultivation on glucose and respiratory...... growth in aerobic glucose-limited continuous cultivation. It was found that in S. kluyveri the flux into the pentose phosphate pathway was 18.8 mmole per 100 mmole glucose consumed during respiratory growth in aerobic glucose-limited continuous cultivation. Such a low flux into the pentose phosphate...

  15. Web application for genetic modification flux with database to estimate metabolic fluxes of genetic mutants.

    Science.gov (United States)

    Mohd Ali, Noorlin; Tsuboi, Ryo; Matsumoto, Yuta; Koishi, Daisuke; Inoue, Kentaro; Maeda, Kazuhiro; Kurata, Hiroyuki

    2016-07-01

    Computational analysis of metabolic fluxes is essential in understanding the structure and function of a metabolic network and in rationally designing genetically modified mutants for an engineering purpose. We had presented the genetic modification flux (GMF) that predicts the flux distribution of a broad range of genetically modified mutants. To enhance the feasibility and usability of GMF, we have developed a web application with a metabolic network database to predict a flux distribution of genetically modified mutants. One hundred and twelve data sets of Escherichia coli, Corynebacterium glutamicum, Saccharomyces cerevisiae, and Chinese hamster ovary were registered as standard models.

  16. 13C-Metabolic Flux Analysis: An Accurate Approach to Demystify Microbial Metabolism for Biochemical Production

    Directory of Open Access Journals (Sweden)

    Weihua Guo

    2015-12-01

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

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

    Science.gov (United States)

    Dalman, Tolga; Wiechert, Wolfgang; Nöh, Katharina

    2016-08-20

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

  18. Dynamic metabolic flux analysis of plant cell wall synthesis.

    Science.gov (United States)

    Chen, Xuewen; Alonso, Ana P; Shachar-Hill, Yair

    2013-07-01

    The regulation of plant cell wall synthesis pathways remains poorly understood. This has become a bottleneck in designing bioenergy crops. The goal of this study was to analyze the regulation of plant cell wall precursor metabolism using metabolic flux analysis based on dynamic labeling experiments. Arabidopsis T87 cells were cultured heterotrophically with (13)C labeled sucrose. The time course of ¹³C labeling patterns in cell wall precursors and related sugar phosphates was monitored using liquid chromatography tandem mass spectrometry until steady state labeling was reached. A kinetic model based on mass action reaction mechanisms was developed to simulate the carbon flow in the cell wall synthesis network. The kinetic parameters of the model were determined by fitting the model to the labeling time course data, cell wall composition, and synthesis rates. A metabolic control analysis was performed to predict metabolic regulations that may improve plant biomass composition for biofuel production. Our results describe the routes and rates of carbon flow from sucrose to cell wall precursors. We found that sucrose invertase is responsible for the entry of sucrose into metabolism and UDP-glucose-4-epimerase plays a dominant role in UDP-Gal synthesis in heterotrophic Aradidopsis cells under aerobic conditions. We also predicted reactions that exert strong regulatory influence over carbon flow to cell wall synthesis and its composition.

  19. Synergizing (13)C Metabolic Flux Analysis and Metabolic Engineering for Biochemical Production.

    Science.gov (United States)

    Guo, Weihua; Sheng, Jiayuan; Feng, Xueyang

    2017-04-20

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

  20. Fluxomers: a new approach for 13C metabolic flux analysis

    Directory of Open Access Journals (Sweden)

    Young Jamey D

    2011-08-01

    Full Text Available Abstract Background The ability to perform quantitative studies using isotope tracers and metabolic flux analysis (MFA is critical for detecting pathway bottlenecks and elucidating network regulation in biological systems, especially those that have been engineered to alter their native metabolic capacities. Mathematically, MFA models are traditionally formulated using separate state variables for reaction fluxes and isotopomer abundances. Analysis of isotope labeling experiments using this set of variables results in a non-convex optimization problem that suffers from both implementation complexity and convergence problems. Results This article addresses the mathematical and computational formulation of 13C MFA models using a new set of variables referred to as fluxomers. These composite variables combine both fluxes and isotopomer abundances, which results in a simply-posed formulation and an improved error model that is insensitive to isotopomer measurement normalization. A powerful fluxomer iterative algorithm (FIA is developed and applied to solve the MFA optimization problem. For moderate-sized networks, the algorithm is shown to outperform the commonly used 13CFLUX cumomer-based algorithm and the more recently introduced OpenFLUX software that relies upon an elementary metabolite unit (EMU network decomposition, both in terms of convergence time and output variability. Conclusions Substantial improvements in convergence time and statistical quality of results can be achieved by applying fluxomer variables and the FIA algorithm to compute best-fit solutions to MFA models. We expect that the fluxomer formulation will provide a more suitable basis for future algorithms that analyze very large scale networks and design optimal isotope labeling experiments.

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

    OpenAIRE

    Kogadeeva, Maria; Zamboni, Nicola

    2016-01-01

    Author Summary Living cells adapt to ever-changing environments by regulating metabolic fluxes, the rates of nutrient flow through the metabolic network, to produce metabolites that are currently in demand. 13C-labeling techniques coupled with metabolic flux analyses are widely used to estimate metabolic fluxes and provide insights into cellular physiology and adaptation relevant in biological, biomedical and biotechnological applications. However, the existing methods are either computationa...

  2. Reliable Metabolic Flux Estimation in Escherichia coli Central Carbon Metabolism Using Intracellular Free Amino Acids

    Directory of Open Access Journals (Sweden)

    Nobuyuki Okahashi

    2014-05-01

    Full Text Available 13C metabolic flux analysis (MFA is a tool of metabolic engineering for investigation of in vivo flux distribution. A direct 13C enrichment analysis of intracellular free amino acids (FAAs is expected to reduce time for labeling experiments of the MFA. Measurable FAAs should, however, vary among the MFA experiments since the pool sizes of intracellular free metabolites depend on cellular metabolic conditions. In this study, minimal 13C enrichment data of FAAs was investigated to perform the FAAs-based MFA. An examination of a continuous culture of Escherichia coli using 13C-labeled glucose showed that the time required to reach an isotopically steady state for FAAs is rather faster than that for conventional method using proteinogenic amino acids (PAAs. Considering 95% confidence intervals, it was found that the metabolic flux distribution estimated using FAAs has a similar reliability to that of the PAAs-based method. The comparative analysis identified glutamate, aspartate, alanine and phenylalanine as the common amino acids observed in E. coli under different culture conditions. The results of MFA also demonstrated that the 13C enrichment data of the four amino acids is required for a reliable analysis of the flux distribution.

  3. A robust and efficient method for estimating enzyme complex abundance and metabolic flux from expression data

    OpenAIRE

    Barker, Brandon E.; Sadagopan, Narayanan; Wang, Yiping; Smallbone, Kieran; Myers, Christopher R.; Xi, Hongwei; Locasale, Jason W.; Gu, Zhenglong

    2014-01-01

    A major theme in constraint-based modeling is unifying experimental data, such as biochemical information about the reactions that can occur in a system or the composition and localization of enzyme complexes, with highthroughput data including expression data, metabolomics, or DNA sequencing. The desired result is to increase predictive capability resulting in improved understanding of metabolism. The approach typically employed when only gene (or protein) intensities are available is the cr...

  4. Estimation of dynamic flux profiles from metabolic time series data

    Directory of Open Access Journals (Sweden)

    Chou I-Chun

    2012-07-01

    Full Text Available Abstract Background Advances in modern high-throughput techniques of molecular biology have enabled top-down approaches for the estimation of parameter values in metabolic systems, based on time series data. Special among them is the recent method of dynamic flux estimation (DFE, which uses such data not only for parameter estimation but also for the identification of functional forms of the processes governing a metabolic system. DFE furthermore provides diagnostic tools for the evaluation of model validity and of the quality of a model fit beyond residual errors. Unfortunately, DFE works only when the data are more or less complete and the system contains as many independent fluxes as metabolites. These drawbacks may be ameliorated with other types of estimation and information. However, such supplementations incur their own limitations. In particular, assumptions must be made regarding the functional forms of some processes and detailed kinetic information must be available, in addition to the time series data. Results The authors propose here a systematic approach that supplements DFE and overcomes some of its shortcomings. Like DFE, the approach is model-free and requires only minimal assumptions. If sufficient time series data are available, the approach allows the determination of a subset of fluxes that enables the subsequent applicability of DFE to the rest of the flux system. The authors demonstrate the procedure with three artificial pathway systems exhibiting distinct characteristics and with actual data of the trehalose pathway in Saccharomyces cerevisiae. Conclusions The results demonstrate that the proposed method successfully complements DFE under various situations and without a priori assumptions regarding the model representation. The proposed method also permits an examination of whether at all, to what degree, or within what range the available time series data can be validly represented in a particular functional format of

  5. Hierarchical organization of fluxes in Escherichia coli metabolic network: using flux coupling analysis for understanding the physiological properties of metabolic genes.

    Science.gov (United States)

    Hosseini, Zhaleh; Marashi, Sayed-Amir

    2015-05-01

    Flux coupling analysis is a method for investigating the connections between reactions of metabolic networks. Here, we construct the hierarchical flux coupling graph for the reactions of the Escherichia coli metabolic network model to determine the level of each reaction in the graph. This graph is constructed based on flux coupling analysis of metabolic network: if zero flux through reaction a results in zero flux through reaction b (and not vice versa), then reaction a is located at the top of reaction b in the flux coupling graph. We show that in general, more important, older and essential reactions are located at the top of the graph. Strikingly, genes corresponding to these reactions are found to be the genes which are most regulated.

  6. Quantification of Metabolic Rearrangements During Neural Stem Cells Differentiation into Astrocytes by Metabolic Flux Analysis.

    Science.gov (United States)

    Sá, João V; Kleiderman, Susanne; Brito, Catarina; Sonnewald, Ursula; Leist, Marcel; Teixeira, Ana P; Alves, Paula M

    2017-01-01

    Proliferation and differentiation of neural stem cells (NSCs) have a crucial role to ensure neurogenesis and gliogenesis in the mammalian brain throughout life. As there is growing evidence for the significance of metabolism in regulating cell fate, knowledge on the metabolic programs in NSCs and how they evolve during differentiation into somatic cells may provide novel therapeutic approaches to address brain diseases. In this work, we applied a quantitative analysis to assess how the central carbon metabolism evolves upon differentiation of NSCs into astrocytes. Murine embryonic stem cell (mESC)-derived NSCs and astrocytes were incubated with labelled [1-(13)C]glucose and the label incorporation into intracellular metabolites was followed by GC-MS. The obtained (13)C labelling patterns, together with uptake/secretion rates determined from supernatant analysis, were integrated into an isotopic non-stationary metabolic flux analysis ((13)C-MFA) model to estimate intracellular flux maps. Significant metabolic differences between NSCs and astrocytes were identified, with a general downregulation of central carbon metabolism during astrocytic differentiation. While glucose uptake was 1.7-fold higher in NSCs (on a per cell basis), a high lactate-secreting phenotype was common to both cell types. Furthermore, NSCs consumed glutamine from the medium; the highly active reductive carboxylation of alpha-ketoglutarate indicates that this was converted to citrate and used for biosynthetic purposes. In astrocytes, pyruvate entered the TCA cycle mostly through pyruvate carboxylase (81%). This pathway supported glutamine and citrate secretion, recapitulating well described metabolic features of these cells in vivo. Overall, this fluxomics study allowed us to quantify the metabolic rewiring accompanying astrocytic lineage specification from NSCs.

  7. C-13 Tracer experiments and metabolite balancing for metabolic flux analysis

    DEFF Research Database (Denmark)

    Schmidt, Karsten; Marx, A.; de Graaf, A. A.

    1998-01-01

    Conventional metabolic flux analysis uses the information gained from determination of measurable fluxes and a steady-state assumption for intracellular metabolites to calculate the metabolic fluxes in a given metabolic network. The determination of intracellular fluxes depends heavily...... on the correctness of the assumed stoichiometry including the presence of all reactions with a noticeable impact on the model metabolite balances. Determination of fluxes in complex metabolic networks often requires the inclusion of NADH and NADPH balances, which are subject: to controversial debate...... through the pentose phosphate pathway. Hence, wrong assumptions on the presence or activity of transhydrogenation reactions will result in wrong estimations of the intracellular flux distribution. Using C-13 tracer experiments and NMR analysis, flux analysis can be performed on the basis of only well...

  8. Hydrogen production and metabolic flux analysis of metabolically engineered Escherichia coli strains

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Seohyoung; Seol, Eunhee; Park, Sunghoon [Department of Chemical and Biochemical Engineering, Pusan National University, Busan 609-735 (Korea); Oh, You-Kwan [Bioenergy Research Center, Korea Institute of Energy Research, Daejeon 305-543 (Korea); Wang, G.Y. [Department of Oceanography, University of Hawaii at Manoa Honolulu, HI 96822 (United States)

    2009-09-15

    Escherichia coli can produce H{sub 2} from glucose via formate hydrogen lyase (FHL). In order to improve the H{sub 2} production rate and yield, metabolically engineered E. coli strains, which included pathway alterations in their H{sub 2} production and central carbon metabolism, were developed and characterized by batch experiments and metabolic flux analysis. Deletion of hycA, a negative regulator for FHL, resulted in twofold increase of FHL activity. Deletion of two uptake hydrogenases (1 (hya) and hydrogenase 2 (hyb)) increased H{sub 2} production yield from 1.20 mol/mol glucose to 1.48 mol/mol glucose. Deletion of lactate dehydrogenase (ldhA) and fumarate reductase (frdAB) further improved the H{sub 2} yield; 1.80 mol/mol glucose under high H{sub 2} pressure or 2.11 mol/mol glucose under reduced H{sub 2} pressure. Several batch experiments at varying concentrations of glucose (2.5-10 g/L) and yeast extract (0.3 or 3.0 g/L) were conducted for the strain containing all these genetic alternations, and their carbon and energy balances were analyzed. The metabolic flux analysis revealed that deletion of ldhA and frdAB directed most of the carbons from glucose to the glycolytic pathway leading to H{sub 2} production by FHL, not to the pentose phosphate pathway. (author)

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

    Directory of Open Access Journals (Sweden)

    Min Kyung Kim

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

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

    Directory of Open Access Journals (Sweden)

    Jörg eSchwender

    2014-11-01

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

  11. OpenMebius: An Open Source Software for Isotopically Nonstationary 13C-Based Metabolic Flux Analysis

    OpenAIRE

    Shuichi Kajihata; Chikara Furusawa; Fumio Matsuda; Hiroshi Shimizu

    2014-01-01

    The in vivo measurement of metabolic flux by 13C-based metabolic flux analysis (13C-MFA) provides valuable information regarding cell physiology. Bioinformatics tools have been developed to estimate metabolic flux distributions from the results of tracer isotopic labeling experiments using a 13C-labeled carbon source. Metabolic flux is determined by nonlinear fitting of a metabolic model to the isotopic labeling enrichment of intracellular metabolites measured by mass spectrometry. Whereas 13...

  12. Flux balance analysis of cyanobacterial metabolism: the metabolic network of Synechocystis sp. PCC 6803.

    Directory of Open Access Journals (Sweden)

    Henning Knoop

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

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

    Science.gov (United States)

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

    2013-01-01

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

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

    Science.gov (United States)

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

    2014-09-01

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

  15. Metabolic flux analysis of the halophilic archaeon Haladaptatus paucihalophilus

    Energy Technology Data Exchange (ETDEWEB)

    Liu, Guangxiu; Zhang, Manxiao [Key Laboratory of Desert and Desertification, Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou, 730000 (China); Key Laboratory of Extreme Environmental Microbial Resources and Engineering, Gansu Province, Lanzhou, 730000 (China); Mo, Tianlu [Department of Chemistry, Fudan University, Shanghai, 200433 (China); He, Lian [Key Laboratory of Combinatory Biosynthesis and Drug Discovery (Ministry of Education), School of Pharmaceutical Sciences, Wuhan University, Wuhan, 430071 (China); Zhang, Wei [Key Laboratory of Desert and Desertification, Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou, 730000 (China); Key Laboratory of Extreme Environmental Microbial Resources and Engineering, Gansu Province, Lanzhou, 730000 (China); Yu, Yi, E-mail: yu_yi@whu.edu.cn [Key Laboratory of Combinatory Biosynthesis and Drug Discovery (Ministry of Education), School of Pharmaceutical Sciences, Wuhan University, Wuhan, 430071 (China); Zhang, Qi, E-mail: qizhang@sioc.ac.cn [Department of Chemistry, Fudan University, Shanghai, 200433 (China); Ding, Wei, E-mail: dingw@lzu.edu.cn [Key Laboratory of Desert and Desertification, Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou, 730000 (China); Key Laboratory of Extreme Environmental Microbial Resources and Engineering, Gansu Province, Lanzhou, 730000 (China); Department of Chemistry, Fudan University, Shanghai, 200433 (China)

    2015-11-27

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

  16. Robustness and plasticity of metabolic pathway flux among uropathogenic isolates of Pseudomonas aeruginosa.

    Directory of Open Access Journals (Sweden)

    Antje Berger

    Full Text Available Pseudomonas aeruginosa is a human pathogen that frequently causes urinary tract and catheter-associated urinary tract infections. Here, using 13C-metabolic flux analysis, we conducted quantitative analysis of metabolic fluxes in the model strain P. aeruginosa PAO1 and 17 clinical isolates. All P. aeruginosa strains catabolized glucose through the Entner-Doudoroff pathway with fully respiratory metabolism and no overflow. Together with other NADPH supplying reactions, this high-flux pathway provided by far more NADPH than needed for anabolism: a benefit for the pathogen to counteract oxidative stress imposed by the host. P. aeruginosa recruited the pentose phosphate pathway exclusively for biosynthesis. In contrast to glycolytic metabolism, which was conserved among all isolates, the flux through pyruvate metabolism, the tricarboxylic acid cycle, and the glyoxylate shunt was highly variable, likely caused by adaptive processes in individual strains during infection. This aspect of metabolism was niche-specific with respect to the corresponding flux because strains isolated from the urinary tract clustered separately from those originating from catheter-associated infections. Interestingly, most glucose-grown strains exhibited significant flux through the glyoxylate shunt. Projection into the theoretical flux space, which was computed using elementary flux-mode analysis, indicated that P. aeruginosa metabolism is optimized for efficient growth and exhibits significant potential for increasing NADPH supply to drive oxidative stress response.

  17. Hybrid optimization for 13C metabolic flux analysis using systems parametrized by compactification

    Directory of Open Access Journals (Sweden)

    Frick Oliver

    2008-03-01

    Full Text Available Abstract Background The importance and power of isotope-based metabolic flux analysis and its contribution to understanding the metabolic network is increasingly recognized. Its application is, however, still limited partly due to computational inefficiency. 13C metabolic flux analysis aims to compute in vivo metabolic fluxes in terms of metabolite balancing extended by carbon isotopomer balances and involves a nonlinear least-squares problem. To solve the problem more efficiently, improved numerical optimization techniques are necessary. Results For flux computation, we developed a gradient-based hybrid optimization algorithm. Here, independent flux variables were compactified into [0, 1-ranged variables using a single transformation rule. The compactified parameters could be discriminated between non-identifiable and identifiable variables after model linearization. The developed hybrid algorithm was applied to the central metabolism of Bacillus subtilis with only succinate and glutamate as carbon sources. This creates difficulties caused by symmetry of succinate leading to limited introduction of 13C labeling information into the system. The algorithm was found to be superior to its parent algorithms and to global optimization methods both in accuracy and speed. The hybrid optimization with tolerance adjustment quickly converged to the minimum with close to zero deviation and exactly re-estimated flux variables. In the metabolic network studied, some fluxes were found to be either non-identifiable or nonlinearly correlated. The non-identifiable fluxes could correctly be predicted a priori using the model identification method applied, whereas the nonlinear flux correlation was revealed only by identification runs using different starting values a posteriori. Conclusion This fast, robust and accurate optimization method is useful for high-throughput metabolic flux analysis, a posteriori identification of possible parameter correlations, and

  18. Efficient Modeling of MS/MS Data for Metabolic Flux Analysis.

    Science.gov (United States)

    Tepper, Naama; Shlomi, Tomer

    2015-01-01

    Metabolic flux analysis (MFA) is a widely used method for quantifying intracellular metabolic fluxes. It works by feeding cells with isotopic labeled nutrients, measuring metabolite isotopic labeling, and computationally interpreting the measured labeling data to estimate flux. Tandem mass-spectrometry (MS/MS) has been shown to be useful for MFA, providing positional isotopic labeling data. Specifically, MS/MS enables the measurement of a metabolite tandem mass-isotopomer distribution, representing the abundance in which certain parent and product fragments of a metabolite have different number of labeled atoms. However, a major limitation in using MFA with MS/MS data is the lack of a computationally efficient method for simulating such isotopic labeling data. Here, we describe the tandemer approach for efficiently computing metabolite tandem mass-isotopomer distributions in a metabolic network, given an estimation of metabolic fluxes. This approach can be used by MFA to find optimal metabolic fluxes, whose induced metabolite labeling patterns match tandem mass-isotopomer distributions measured by MS/MS. The tandemer approach is applied to simulate MS/MS data in a small-scale metabolic network model of mammalian methionine metabolism and in a large-scale metabolic network model of E. coli. It is shown to significantly improve the running time by between two to three orders of magnitude compared to the state-of-the-art, cumomers approach. We expect the tandemer approach to promote broader usage of MS/MS technology in metabolic flux analysis.

  19. An exact arithmetic toolbox for a consistent and reproducible structural analysis of metabolic network models.

    Science.gov (United States)

    Chindelevitch, Leonid; Trigg, Jason; Regev, Aviv; Berger, Bonnie

    2014-10-07

    Constraint-based models are currently the only methodology that allows the study of metabolism at the whole-genome scale. Flux balance analysis is commonly used to analyse constraint-based models. Curiously, the results of this analysis vary with the software being run, a situation that we show can be remedied by using exact rather than floating-point arithmetic. Here we introduce MONGOOSE, a toolbox for analysing the structure of constraint-based metabolic models in exact arithmetic. We apply MONGOOSE to the analysis of 98 existing metabolic network models and find that the biomass reaction is surprisingly blocked (unable to sustain non-zero flux) in nearly half of them. We propose a principled approach for unblocking these reactions and extend it to the problems of identifying essential and synthetic lethal reactions and minimal media. Our structural insights enable a systematic study of constraint-based metabolic models, yielding a deeper understanding of their possibilities and limitations.

  20. Interpreting expression data with metabolic flux models: predicting Mycobacterium tuberculosis mycolic acid production.

    Directory of Open Access Journals (Sweden)

    Caroline Colijn

    2009-08-01

    Full Text Available Metabolism is central to cell physiology, and metabolic disturbances play a role in numerous disease states. Despite its importance, the ability to study metabolism at a global scale using genomic technologies is limited. In principle, complete genome sequences describe the range of metabolic reactions that are possible for an organism, but cannot quantitatively describe the behaviour of these reactions. We present a novel method for modeling metabolic states using whole cell measurements of gene expression. Our method, which we call E-Flux (as a combination of flux and expression, extends the technique of Flux Balance Analysis by modeling maximum flux constraints as a function of measured gene expression. In contrast to previous methods for metabolically interpreting gene expression data, E-Flux utilizes a model of the underlying metabolic network to directly predict changes in metabolic flux capacity. We applied E-Flux to Mycobacterium tuberculosis, the bacterium that causes tuberculosis (TB. Key components of mycobacterial cell walls are mycolic acids which are targets for several first-line TB drugs. We used E-Flux to predict the impact of 75 different drugs, drug combinations, and nutrient conditions on mycolic acid biosynthesis capacity in M. tuberculosis, using a public compendium of over 400 expression arrays. We tested our method using a model of mycolic acid biosynthesis as well as on a genome-scale model of M. tuberculosis metabolism. Our method correctly predicts seven of the eight known fatty acid inhibitors in this compendium and makes accurate predictions regarding the specificity of these compounds for fatty acid biosynthesis. Our method also predicts a number of additional potential modulators of TB mycolic acid biosynthesis. E-Flux thus provides a promising new approach for algorithmically predicting metabolic state from gene expression data.

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

    Science.gov (United States)

    Antoniewicz, Maciek R

    2015-12-01

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

  2. Using bioconductor package BiGGR for metabolic flux estimation based on gene expression changes in brain

    NARCIS (Netherlands)

    Gavai, A.K.; Supandi, F.; Hettling, H.; Murrell, P.; Leunissen, J.A.M.; Beek, van J.H.G.M.

    2015-01-01

    Predicting the distribution of metabolic fluxes in biochemical networks is of major interest in systems biology. Several databases provide metabolic reconstructions for different organisms. Software to analyze flux distributions exists, among others for the proprietary MATLAB environment. Given the

  3. RELATCH: relative optimality in metabolic networks explains robust metabolic and regulatory responses to perturbations.

    Science.gov (United States)

    Kim, Joonhoon; Reed, Jennifer L

    2012-07-05

    Predicting cellular responses to perturbations is an important task in systems biology. We report a new approach, RELATCH, which uses flux and gene expression data from a reference state to predict metabolic responses in a genetically or environmentally perturbed state. Using the concept of relative optimality, which considers relative flux changes from a reference state, we hypothesize a relative metabolic flux pattern is maintained from one state to another, and that cells adapt to perturbations using metabolic and regulatory reprogramming to preserve this relative flux pattern. This constraint-based approach will have broad utility where predictions of metabolic responses are needed.

  4. 13C labeling analysis of sugars by high resolution-mass spectrometry for metabolic flux analysis.

    Science.gov (United States)

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

    2017-02-14

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

  5. Metabolic flux analysis of Escherichia coli knockouts: lessons from the Keio collection and future outlook.

    Science.gov (United States)

    Long, Christopher P; Antoniewicz, Maciek R

    2014-08-01

    Cellular metabolic and regulatory systems are of fundamental interest to biologists and engineers. Incomplete understanding of these complex systems remains an obstacle to progress in biotechnology and metabolic engineering. An established method for obtaining new information on network structure, regulation and dynamics is to study the cellular system following a perturbation such as a genetic knockout. The Keio collection of all viable Escherichia coli single-gene knockouts is facilitating a systematic investigation of the regulation and metabolism of E. coli. Of all omics measurements available, the metabolic flux profile (the fluxome) provides the most direct and relevant representation of the cellular phenotype. Recent advances in (13)C-metabolic flux analysis are now permitting highly precise and accurate flux measurements for investigating cellular systems and guiding metabolic engineering efforts.

  6. Genome-scale modeling using flux ratio constraints to enable metabolic engineering of clostridial metabolism in silico

    Directory of Open Access Journals (Sweden)

    McAnulty Michael J

    2012-05-01

    Full Text Available Abstract Background Genome-scale metabolic networks and flux models are an effective platform for linking an organism genotype to its phenotype. However, few modeling approaches offer predictive capabilities to evaluate potential metabolic engineering strategies in silico. Results A new method called “flux balance analysis with flux ratios (FBrAtio” was developed in this research and applied to a new genome-scale model of Clostridium acetobutylicum ATCC 824 (iCAC490 that contains 707 metabolites and 794 reactions. FBrAtio was used to model wild-type metabolism and metabolically engineered strains of C. acetobutylicum where only flux ratio constraints and thermodynamic reversibility of reactions were required. The FBrAtio approach allowed solutions to be found through standard linear programming. Five flux ratio constraints were required to achieve a qualitative picture of wild-type metabolism for C. acetobutylicum for the production of: (i acetate, (ii lactate, (iii butyrate, (iv acetone, (v butanol, (vi ethanol, (vii CO2 and (viii H2. Results of this simulation study coincide with published experimental results and show the knockdown of the acetoacetyl-CoA transferase increases butanol to acetone selectivity, while the simultaneous over-expression of the aldehyde/alcohol dehydrogenase greatly increases ethanol production. Conclusions FBrAtio is a promising new method for constraining genome-scale models using internal flux ratios. The method was effective for modeling wild-type and engineered strains of C. acetobutylicum.

  7. Assessing compartmentalized flux in lipid metabolism with isotopes

    Science.gov (United States)

    Metabolism in plants takes place across multiple cell types and subpopulations in distinct organelles. The distributions equate to spatial heterogeneity; though the limited means to experimentally asses metabolism frequently involve homogenizing tissues and mixing metabolites from different location...

  8. Dynamic metabolic flux analysis using a convex analysis approach: Application to hybridoma cell cultures in perfusion.

    Science.gov (United States)

    Fernandes de Sousa, Sofia; Bastin, Georges; Jolicoeur, Mario; Vande Wouwer, Alain

    2016-05-01

    In recent years, dynamic metabolic flux analysis (DMFA) has been developed in order to evaluate the dynamic evolution of the metabolic fluxes. Most of the proposed approaches are dedicated to exactly determined or overdetermined systems. When an underdetermined system is considered, the literature suggests the use of dynamic flux balance analysis (DFBA). However the main challenge of this approach is to determine an appropriate objective function, which remains valid over the whole culture. In this work, we propose an alternative dynamic metabolic flux analysis based on convex analysis, DMFCA, which allows the determination of bounded intervals for the fluxes using the available knowledge of the metabolic network and information provided by the time evolution of extracellular component concentrations. Smoothing splines and mass balance differential equations are used to estimate the time evolution of the uptake and excretion rates from this experimental data. The main advantage of the proposed procedure is that it does not require additional constraints or objective functions, and provides relatively narrow intervals for the intracellular metabolic fluxes. DMFCA is applied to experimental data from hybridoma HB58 cell perfusion cultures, in order to investigate the influence of the operating mode (batch and perfusion) on the metabolic flux distribution.

  9. Combining pathway analysis with flux balance analysis for the comprehensive study of metabolic systems.

    Science.gov (United States)

    Schilling, C H; Edwards, J S; Letscher, D; Palsson, B Ø

    The elucidation of organism-scale metabolic networks necessitates the development of integrative methods to analyze and interpret the systemic properties of cellular metabolism. A shift in emphasis from single metabolic reactions to systemically defined pathways is one consequence of such an integrative analysis of metabolic systems. The constraints of systemic stoichiometry, and limited thermodynamics have led to the definition of the flux space within the context of convex analysis. The flux space of the metabolic system, containing all allowable flux distributions, is constrained to a convex polyhedral cone in a high-dimensional space. From metabolic pathway analysis, the edges of the high-dimensional flux cone are vectors that correspond to systemically defined "extreme pathways" spanning the capabilities of the system. The addition of maximum flux capacities of individual metabolic reactions serves to further constrain the flux space and has led to the development of flux balance analysis using linear optimization to calculate optimal flux distributions. Here we provide the precise theoretical connections between pathway analysis and flux balance analysis allowing for their combined application to study integrated metabolic function. Shifts in metabolic behavior are calculated using linear optimization and are then interpreted using the extreme pathways to demonstrate the concept of pathway utilization. Changes to the reaction network, such as the removal of a reaction, can lead to the generation of suboptimal phenotypes that can be directly attributed to the loss of pathway function and capabilities. Optimal growth phenotypes are calculated as a function of environmental variables, such as the availability of substrate and oxygen, leading to the definition of phenotypic phase planes. It is illustrated how optimality properties of the computed flux distributions can be interpreted in terms of the extreme pathways. Together these developments are applied to an

  10. Insights into primary metabolism in oilseeds from labeling and flux analysis

    Science.gov (United States)

    Labeling investigations along with metabolic flux analysis have enabled quantification of important cellular phenotypes. These descriptions have documented uses of enzymes in unique ways and characterized the contributions of pathways to oil, protein and carbohydrate compositions in seeds. The diffe...

  11. In vivo dynamics of galactose metabolism in Saccharomyces cerevisiae: Metabolic fluxes and metabolite levels

    DEFF Research Database (Denmark)

    Østergaard, Simon; Olsson, Lisbeth; Nielsen, Jens

    2001-01-01

    limitation (0.37 +/- 0.05 mu mol/g CDW) than what has been reported for growth under glucose limitation. The galactose pulse of 5.58 mM was consumed within 40 min (t = 40) and 7 min after the pulse was added cell growth stopped. Subsequently, the cells started to grow and at t = 30 the specific growth rate......-1P was measured, which may be responsible for a toxic metabolic response in S. cerevisiae. The increase in the Gal-1P concentration is intensified by the low affinity of Gal7 towards Gal-1P and, hence, under the physiological conditions examined Gal7 seems to exert control over flux through...

  12. Optimization of steady-state ¹³C-labeling experiments for metabolic flux analysis.

    Science.gov (United States)

    Kruger, Nicholas J; Masakapalli, Shyam K; Ratcliffe, R George

    2014-01-01

    While steady-state (13)C metabolic flux analysis is a powerful method for deducing multiple fluxes in the central metabolic network of heterotrophic and mixotrophic plant tissues, it is also time-consuming and technically challenging. Key steps in the design and interpretation of steady-state (13)C labeling experiments are illustrated with a generic protocol based on applications to plant cell suspension cultures.

  13. From metabolomics to fluxomics: a computational procedure to translate metabolite profiles into metabolic fluxes.

    Science.gov (United States)

    Cortassa, Sonia; Caceres, Viviane; Bell, Lauren N; O'Rourke, Brian; Paolocci, Nazareno; Aon, Miguel A

    2015-01-06

    We describe a believed-novel procedure for translating metabolite profiles (metabolome) into the set of metabolic fluxes (fluxome) from which they originated. Methodologically, computational modeling is integrated with an analytical platform comprising linear optimization, continuation and dynamic analyses, and metabolic control. The procedure was tested with metabolite profiles obtained from ex vivo mice Langendorff-heart preparations perfused with glucose. The metabolic profiles were analyzed using a detailed kinetic model of the glucose catabolic pathways including glycolysis, pentose phosphate (PP), glycogenolysis, and polyols to translate the glucose metabolome of the heart into the fluxome. After optimization, the ability of the model to simulate the initial metabolite profile was confirmed, and metabolic fluxes as well as the structure of control and regulation of the glucose catabolic network could be calculated. We show that the step catalyzed by phosphofructokinase together with ATP demand and glycogenolysis exert the highest control on the glycolytic flux. The negative flux control exerted by phosphofructokinase on the PP and polyol pathways revealed that the extent of glycolytic flux directly affects flux redirection through these pathways, i.e., the higher the glycolytic flux the lower the PP and polyols. This believed-novel methodological approach represents a step forward that may help in designing therapeutic strategies targeted to diagnose, prevent, and treat metabolic diseases.

  14. Invariability of Central Metabolic Flux Distribution in Shewanella oneidensis MR-1 Under Environmental or Genetic Perturbations

    Energy Technology Data Exchange (ETDEWEB)

    Tang, Yinjie; Martin, Hector Garcia; Deutschbauer, Adam; Feng, Xueyang; Huang, Rick; Llora, Xavier; Arkin, Adam; Keasling, Jay D.

    2009-04-21

    An environmentally important bacterium with versatile respiration, Shewanella oneidensis MR-1, displayed significantly different growth rates under three culture conditions: minimal medium (doubling time {approx} 3 hrs), salt stressed minimal medium (doubling time {approx} 6 hrs), and minimal medium with amino acid supplementation (doubling time {approx}1.5 hrs). {sup 13}C-based metabolic flux analysis indicated that fluxes of central metabolic reactions remained relatively constant under the three growth conditions, which is in stark contrast to the reported significant changes in the transcript and metabolite profiles under various growth conditions. Furthermore, ten transposon mutants of S. oneidensis MR-1 were randomly chosen from a transposon library and their flux distributions through central metabolic pathways were revealed to be identical, even though such mutational processes altered the secondary metabolism, for example, glycine and C1 (5,10-Me-THF) metabolism.

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

    NARCIS (Netherlands)

    Masakapalli, S.K.; Ritala, A.; Dong, L.M.; Krol, van der A.R.; Oksman-Caldentey, K.M.; Ratcliffe, R.G.; Sweetlove, L.J.

    2014-01-01

    The goal of this study was to characterise the metabolic flux phenotype of transgenic tobacco (Nicotiana tabacum) hairy roots engineered for increased biosynthesis of geraniol, an intermediate of the terpenoid indole alkaloid pathway. Steady state, stable isotope labelling was used to determine flux

  16. FASIMU: flexible software for flux-balance computation series in large metabolic networks

    Directory of Open Access Journals (Sweden)

    Gille Christoph

    2011-01-01

    Full Text Available Abstract Background Flux-balance analysis based on linear optimization is widely used to compute metabolic fluxes in large metabolic networks and gains increasingly importance in network curation and structural analysis. Thus, a computational tool flexible enough to realize a wide variety of FBA algorithms and able to handle batch series of flux-balance optimizations is of great benefit. Results We present FASIMU, a command line oriented software for the computation of flux distributions using a variety of the most common FBA algorithms, including the first available implementation of (i weighted flux minimization, (ii fitness maximization for partially inhibited enzymes, and (iii of the concentration-based thermodynamic feasibility constraint. It allows batch computation with varying objectives and constraints suited for network pruning, leak analysis, flux-variability analysis, and systematic probing of metabolic objectives for network curation. Input and output supports SBML. FASIMU can work with free (lp_solve and GLPK or commercial solvers (CPLEX, LINDO. A new plugin (faBiNA for BiNA allows to conveniently visualize calculated flux distributions. The platform-independent program is an open-source project, freely available under GNU public license at http://www.bioinformatics.org/fasimu including manual, tutorial, and plugins. Conclusions We present a flux-balance optimization program whose main merits are the implementation of thermodynamics as a constraint, batch series of computations, free availability of sources, choice on various external solvers, and the flexibility on metabolic objectives and constraints.

  17. [Breeding of Actinobacillus succiniogenes mutants with improved succinate production based on metabolic flux analysis].

    Science.gov (United States)

    Pan, Lijun; Li, Xingjiang; Jiang, Shaotong; Wei, Zhaojun; Chen, Xiaohui; Cai, Licheng; Wang, Hefeng; Jiang, Jijun

    2008-09-01

    It is very important to obtain high yield mutant strains on the base of metabolic flux analysis of Actinobacillus succinogenes S.JST for the industrial bioconversion of succinic acid. The metabolic pathway was analized at first and the flux of the metabolic networks was calculated by matrix. In order to decrease acetic acid flux, the strains mutated by soft X-ray of synchronous radiation were screened on the plates with high concentration of fluoroacetic acid. For decreasing the metabolic flux of ethanol the site-directed mutagenesis was carried out for the reduction of alcohol dehydrogenase(Adh) specific activity. Then the enzyme activity determination and the gene sequence analysis of the mutant strain was compared with those of the parent strain. Metabolic flux analysis of the parent strain indicated that the flux of succinic acid was 1.78(mmol/g/h) and that the flux of acetic acid and ethanol were 0.60 (mmol/g/h) and 1.04( mmol/g/h), respectively. Meanwhile the metabolic pathway analysis showed that the ethanol metabolism enhanced the lacking of H electron donor during the synthesis of succinic acid and that the succinic acid flux was weakened by the metabolism of byproducts ethanol and acetic acid. Compared with the parent strain, the acetic acid flux of anti-fluoroacetic mutant strain S.JST1 was 0.024 (mmol/g/h), decreasing by 96%. Then the enzyme determination showed that the specific activity unit of phosphotransacetylase(Pta) decreased from 602 to 74 and a mutated site was founded in the pta gene of the mutant strain S.JST1. Compared with that of the parent strain S.JST1 the ethanol flux of adh-site-directed mutant strain S.JST2 was 0.020 (mmol/g/h), decreasing by 98%. Then the enzyme determination showed that the specific activity unit of Adh decreased from 585 to 62 and the yield of end product succinic acid was 65.7 (g/L). The interdiction of Adh and Pta decreased the metabolism of byproducts and the H electron donor was well balanced, thus the succinic

  18. Central metabolic responses to the overproduction of fatty acids in Escherichia coli based on 13C-metabolic flux analysis.

    Science.gov (United States)

    He, Lian; Xiao, Yi; Gebreselassie, Nikodimos; Zhang, Fuzhong; Antoniewiez, Maciek R; Tang, Yinjie J; Peng, Lifeng

    2014-03-01

    We engineered a fatty acid overproducing Escherichia coli strain through overexpressing tesA (“pull”) and fadR (“push”) and knocking out fadE (“block”). This “pull-push-block” strategy yielded 0.17 g of fatty acids (C12–C18) per gram of glucose (equivalent to 48% of the maximum theoretical yield) in batch cultures during the exponential growth phase under aerobic conditions. Metabolic fluxes were determined for the engineered E. coli and its control strain using tracer ([1,2-13C]glucose) experiments and 13C-metabolic flux analysis. Cofactor (NADPH) and energy (ATP) balances were also investigated for both strains based on estimated fluxes. Compared to the control strain, fatty acid overproduction led to significant metabolic responses in the central metabolism: (1) Acetic acid secretion flux decreased 10-fold; (2) Pentose phosphate pathway and Entner–Doudoroff pathway fluxes increased 1.5- and 2.0-fold, respectively; (3) Biomass synthesis flux was reduced 1.9-fold; (4) Anaplerotic phosphoenolpyruvate carboxylation flux decreased 1.7-fold; (5) Transhydrogenation flux converting NADH to NADPH increased by 1.7-fold. Real-time quantitative RT-PCR analysis revealed the engineered strain increased the transcription levels of pntA (encoding the membrane-bound transhydrogenase) by 2.1-fold and udhA (encoding the soluble transhydrogenase) by 1.4-fold, which is in agreement with the increased transhydrogenation flux. Cofactor and energy balances analyses showed that the fatty acid overproducing E. coli consumed significantly higher cellular maintenance energy than the control strain. We discussed the strategies to future strain development and process improvements for fatty acid production in E. coli.

  19. COMPLETE-MFA: complementary parallel labeling experiments technique for metabolic flux analysis.

    Science.gov (United States)

    Leighty, Robert W; Antoniewicz, Maciek R

    2013-11-01

    We have developed a novel approach for measuring highly accurate and precise metabolic fluxes in living cells, termed COMPLETE-MFA, short for complementary parallel labeling experiments technique for metabolic flux analysis. The COMPLETE-MFA method is based on combined analysis of multiple isotopic labeling experiments, where the synergy of using complementary tracers greatly improves the precision of estimated fluxes. In this work, we demonstrate the COMPLETE-MFA approach using all singly labeled glucose tracers, [1-(13)C], [2-(13)C], [3-(13)C], [4-(13)C], [5-(13)C], and [6-(13)C]glucose to determine precise metabolic fluxes for wild-type Escherichia coli. Cells were grown in six parallel cultures on defined medium with glucose as the only carbon source. Mass isotopomers of biomass amino acids were measured by gas chromatography-mass spectrometry (GC-MS). The data from all six experiments were then fitted simultaneously to a single flux model to determine accurate intracellular fluxes. We obtained a statistically acceptable fit with more than 300 redundant measurements. The estimated flux map is the most precise flux result obtained thus far for E. coli cells. To our knowledge, this is the first time that six isotopic labeling experiments have been successfully integrated for high-resolution (13)C-flux analysis.

  20. Constraint-based modeling of heterologous pathways: application and experimental demonstration for overproduction of fatty acids in Escherichia coli.

    Science.gov (United States)

    Ip, Kuhn; Donoghue, Neil; Kim, Min Kyung; Lun, Desmond S

    2014-10-01

    Constraint-based modeling has been shown, in many instances, to be useful for metabolic engineering by allowing the prediction of the metabolic phenotype resulting from genetic manipulations. But the basic premise of constraint-based modeling-that of applying constraints to preclude certain behaviors-only makes sense for certain genetic manipulations (such as knockouts and knockdowns). In particular, when genes (such as those associated with a heterologous pathway) are introduced under artificial control, it is unclear how to predict the correct behavior. In this paper, we introduce a modeling method that we call proportional flux forcing (PFF) to model artificially induced enzymatic genes. The model modifications introduced by PFF can be transformed into a set of simple mass balance constraints, which allows computational methods for strain optimization based on flux balance analysis (FBA) to be utilized. We applied PFF to the metabolic engineering of Escherichia coli (E. coli) for free fatty acid (FFA) production-a metabolic engineering problem that has attracted significant attention because FFAs are a precursor to liquid transportation fuels such as biodiesel and biogasoline. We show that PFF used in conjunction with FBA-based computational strain optimization methods can yield non-obvious genetic manipulation strategies that significantly increase FFA production in E. coli. The two mutant strains constructed and successfully tested in this work had peak fatty acid (FA) yields of 0.050 g FA/g carbon source (17.4% theoretical yield) and 0.035 g FA/g carbon source (12.3% theoretical yield) when they were grown using a mixed carbon source of glucose and casamino acids in a ratio of 2-to-1. These yields represent increases of 5.4- and 3.8-fold, respectively, over the baseline strain.

  1. Flux-Enabled Exploration of the Role of Sip1 in galactose yeast metabolism

    DEFF Research Database (Denmark)

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

    2017-01-01

    13C metabolic flux analysis (13C MFA) is an important systems biology technique that has been used to investigate microbial metabolism for decades. The heterotrimer Snf1 kinase complex plays a key role in the preference Saccharomyces cerevisiae exhibits for glucose over galactose, a phenomenon kn...

  2. Continuous-time Markov chain-based flux analysis in metabolism.

    Science.gov (United States)

    Huo, Yunzhang; Ji, Ping

    2014-09-01

    Metabolic flux analysis (MFA), a key technology in bioinformatics, is an effective way of analyzing the entire metabolic system by measuring fluxes. Many existing MFA approaches are based on differential equations, which are complicated to be solved mathematically. So MFA requires some simple approaches to investigate metabolism further. In this article, we applied continuous-time Markov chain to MFA, called MMFA approach, and transformed the MFA problem into a set of quadratic equations by analyzing the transition probability of each carbon atom in the entire metabolic system. Unlike the other methods, MMFA analyzes the metabolic model only through the transition probability. This approach is very generic and it could be applied to any metabolic system if all the reaction mechanisms in the system are known. The results of the MMFA approach were compared with several chemical reaction equilibrium constants from early experiments by taking pentose phosphate pathway as an example.

  3. A comprehensive metabolic profile of cultured astrocytes using isotopic transient metabolic flux analysis and 13C-labeled glucose

    Directory of Open Access Journals (Sweden)

    Ana I Amaral

    2011-09-01

    Full Text Available Metabolic models have been used to elucidate important aspects of brain metabolism in recent years. This work applies for the first time the concept of isotopic transient 13C metabolic flux analysis (MFA to estimate intracellular fluxes of cultured astrocytes. This methodology comprehensively explores the information provided by 13C labeling time-courses of intracellular metabolites after administration of a 13C labeled substrate. Cells were incubated with medium containing [1-13C]glucose for 24 h and samples of cell supernatant and extracts collected at different time-points were then analyzed by mass spectrometry and/or HPLC. Metabolic fluxes were estimated by fitting a carbon labeling network model to isotopomer profiles experimentally determined. Both the fast isotopic equilibrium of glycolytic metabolite pools and the slow labeling dynamics of TCA cycle intermediates are described well by the model. The large pools of glutamate and aspartate which are linked to the TCA cycle via reversible aminotransferase reactions are likely to be responsible for the observed delay in equilibration of TCA cycle intermediates. Furthermore, it was estimated that 11% of the glucose taken up by astrocytes was diverted to the pentose phosphate pathway. In addition, considerable fluxes through pyruvate carboxylase (PC (PC/pyruvate dehydrogenase (PDH ratio = 0.5, malic enzyme (5% of the total pyruvate production and catabolism of branched-chained amino acids (contributing with ~40% to total acetyl-CoA produced confirmed the significance of these pathways to astrocytic metabolism. Consistent with the need of maintaining cytosolic redox potential, the fluxes through the malate-aspartate shuttle and the PDH pathway were comparable. Finally, the estimated glutamate/α-ketoglutarate exchange rate (~0.7 µmol.mg prot-1.h-1 was similar to the TCA cycle flux. In conclusion, this work demonstrates the potential of isotopic transient MFA for a comprehensive analysis of

  4. Synergizing metabolic flux analysis and nucleotide sugar metabolism to understand the control of glycosylation of recombinant protein in CHO cells

    LENUS (Irish Health Repository)

    Burleigh, Susan C

    2011-10-18

    Abstract Background The glycosylation of recombinant proteins can be altered by a range of parameters including cellular metabolism, metabolic flux and the efficiency of the glycosylation process. We present an experimental set-up that allows determination of these key processes associated with the control of N-linked glycosylation of recombinant proteins. Results Chinese hamster ovary cells (CHO) were cultivated in shake flasks at 0 mM glutamine and displayed a reduced growth rate, glucose metabolism and a slower decrease in pH, when compared to other glutamine-supplemented cultures. The N-linked glycosylation of recombinant human chorionic gonadotrophin (HCG) was also altered under these conditions; the sialylation, fucosylation and antennarity decreased, while the proportion of neutral structures increased. A continuous culture set-up was subsequently used to understand the control of HCG glycosylation in the presence of varied glutamine concentrations; when glycolytic flux was reduced in the absence of glutamine, the glycosylation changes that were observed in shake flask culture were similarly detected. The intracellular content of UDP-GlcNAc was also reduced, which correlated with a decrease in sialylation and antennarity of the N-linked glycans attached to HCG. Conclusions The use of metabolic flux analysis illustrated a case of steady state multiplicity, where use of the same operating conditions at each steady state resulted in altered flux through glycolysis and the TCA cycle. This study clearly demonstrated that the control of glycoprotein microheterogeneity may be examined by use of a continuous culture system, metabolic flux analysis and assay of intracellular nucleotides. This system advances our knowledge of the relationship between metabolic flux and the glycosylation of biotherapeutics in CHO cells and will be of benefit to the bioprocessing industry.

  5. Synergizing metabolic flux analysis and nucleotide sugar metabolism to understand the control of glycosylation of recombinant protein in CHO cells

    Directory of Open Access Journals (Sweden)

    Rudd Pauline M

    2011-10-01

    Full Text Available Abstract Background The glycosylation of recombinant proteins can be altered by a range of parameters including cellular metabolism, metabolic flux and the efficiency of the glycosylation process. We present an experimental set-up that allows determination of these key processes associated with the control of N-linked glycosylation of recombinant proteins. Results Chinese hamster ovary cells (CHO were cultivated in shake flasks at 0 mM glutamine and displayed a reduced growth rate, glucose metabolism and a slower decrease in pH, when compared to other glutamine-supplemented cultures. The N-linked glycosylation of recombinant human chorionic gonadotrophin (HCG was also altered under these conditions; the sialylation, fucosylation and antennarity decreased, while the proportion of neutral structures increased. A continuous culture set-up was subsequently used to understand the control of HCG glycosylation in the presence of varied glutamine concentrations; when glycolytic flux was reduced in the absence of glutamine, the glycosylation changes that were observed in shake flask culture were similarly detected. The intracellular content of UDP-GlcNAc was also reduced, which correlated with a decrease in sialylation and antennarity of the N-linked glycans attached to HCG. Conclusions The use of metabolic flux analysis illustrated a case of steady state multiplicity, where use of the same operating conditions at each steady state resulted in altered flux through glycolysis and the TCA cycle. This study clearly demonstrated that the control of glycoprotein microheterogeneity may be examined by use of a continuous culture system, metabolic flux analysis and assay of intracellular nucleotides. This system advances our knowledge of the relationship between metabolic flux and the glycosylation of biotherapeutics in CHO cells and will be of benefit to the bioprocessing industry.

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

    Science.gov (United States)

    Riemer, S Alexander; Rex, René; Schomburg, Dietmar

    2013-04-12

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

  7. Flux Analysis Uncovers Key Role of Functional Redundancy in Formaldehyde Metabolism

    OpenAIRE

    Christopher J Marx; Van Dien, Stephen J.; Mary E Lidstrom

    2005-01-01

    Genome-scale analysis of predicted metabolic pathways has revealed the common occurrence of apparent redundancy for specific functional units, or metabolic modules. In many cases, mutation analysis does not resolve function, and instead, direct experimental analysis of metabolic flux under changing conditions is necessary. In order to use genome sequences to build models of cellular function, it is important to define function for such apparently redundant systems. Here we describe direct flu...

  8. Co-regulation of metabolic genes is better explained by flux coupling than by network distance.

    Directory of Open Access Journals (Sweden)

    Richard A Notebaart

    2008-01-01

    Full Text Available To what extent can modes of gene regulation be explained by systems-level properties of metabolic networks? Prior studies on co-regulation of metabolic genes have mainly focused on graph-theoretical features of metabolic networks and demonstrated a decreasing level of co-expression with increasing network distance, a naïve, but widely used, topological index. Others have suggested that static graph representations can poorly capture dynamic functional associations, e.g., in the form of dependence of metabolic fluxes across genes in the network. Here, we systematically tested the relative importance of metabolic flux coupling and network position on gene co-regulation, using a genome-scale metabolic model of Escherichia coli. After validating the computational method with empirical data on flux correlations, we confirm that genes coupled by their enzymatic fluxes not only show similar expression patterns, but also share transcriptional regulators and frequently reside in the same operon. In contrast, we demonstrate that network distance per se has relatively minor influence on gene co-regulation. Moreover, the type of flux coupling can explain refined properties of the regulatory network that are ignored by simple graph-theoretical indices. Our results underline the importance of studying functional states of cellular networks to define physiologically relevant associations between genes and should stimulate future developments of novel functional genomic tools.

  9. Deriving metabolic engineering strategies from genome-scale modeling with flux ratio constraints.

    Science.gov (United States)

    Yen, Jiun Y; Nazem-Bokaee, Hadi; Freedman, Benjamin G; Athamneh, Ahmad I M; Senger, Ryan S

    2013-05-01

    Optimized production of bio-based fuels and chemicals from microbial cell factories is a central goal of systems metabolic engineering. To achieve this goal, a new computational method of using flux balance analysis with flux ratios (FBrAtio) was further developed in this research and applied to five case studies to evaluate and design metabolic engineering strategies. The approach was implemented using publicly available genome-scale metabolic flux models. Synthetic pathways were added to these models along with flux ratio constraints by FBrAtio to achieve increased (i) cellulose production from Arabidopsis thaliana; (ii) isobutanol production from Saccharomyces cerevisiae; (iii) acetone production from Synechocystis sp. PCC6803; (iv) H2 production from Escherichia coli MG1655; and (v) isopropanol, butanol, and ethanol (IBE) production from engineered Clostridium acetobutylicum. The FBrAtio approach was applied to each case to simulate a metabolic engineering strategy already implemented experimentally, and flux ratios were continually adjusted to find (i) the end-limit of increased production using the existing strategy, (ii) new potential strategies to increase production, and (iii) the impact of these metabolic engineering strategies on product yield and culture growth. The FBrAtio approach has the potential to design "fine-tuned" metabolic engineering strategies in silico that can be implemented directly with available genomic tools.

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

    Science.gov (United States)

    Kogadeeva, Maria; Zamboni, Nicola

    2016-09-01

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

  11. INCA: a computational platform for isotopically non-stationary metabolic flux analysis.

    Science.gov (United States)

    Young, Jamey D

    2014-05-01

    13C flux analysis studies have become an essential component of metabolic engineering research. The scope of these studies has gradually expanded to include both isotopically steady-state and transient labeling experiments, the latter of which are uniquely applicable to photosynthetic organisms and slow-to-label mammalian cell cultures. Isotopomer network compartmental analysis (INCA) is the first publicly available software package that can perform both steady-state metabolic flux analysis and isotopically non-stationary metabolic flux analysis. The software provides a framework for comprehensive analysis of metabolic networks using mass balances and elementary metabolite unit balances. The generation of balance equations and their computational solution is completely automated and can be performed on networks of arbitrary complexity.

  12. Integrated 13C-metabolic flux analysis of 14 parallel labeling experiments in Escherichia coli.

    Science.gov (United States)

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

    2015-03-01

    The use of parallel labeling experiments for (13)C metabolic flux analysis ((13)C-MFA) has emerged in recent years as the new gold standard in fluxomics. The methodology has been termed COMPLETE-MFA, short for complementary parallel labeling experiments technique for metabolic flux analysis. In this contribution, we have tested the limits of COMPLETE-MFA by demonstrating integrated analysis of 14 parallel labeling experiments with Escherichia coli. An effort on such a massive scale has never been attempted before. In addition to several widely used isotopic tracers such as [1,2-(13)C]glucose and mixtures of [1-(13)C]glucose and [U-(13)C]glucose, four novel tracers were applied in this study: [2,3-(13)C]glucose, [4,5,6-(13)C]glucose, [2,3,4,5,6-(13)C]glucose and a mixture of [1-(13)C]glucose and [4,5,6-(13)C]glucose. This allowed us for the first time to compare the performance of a large number of isotopic tracers. Overall, there was no single best tracer for the entire E. coli metabolic network model. Tracers that produced well-resolved fluxes in the upper part of metabolism (glycolysis and pentose phosphate pathways) showed poor performance for fluxes in the lower part of metabolism (TCA cycle and anaplerotic reactions), and vice versa. The best tracer for upper metabolism was 80% [1-(13)C]glucose+20% [U-(13)C]glucose, while [4,5,6-(13)C]glucose and [5-(13)C]glucose both produced optimal flux resolution in the lower part of metabolism. COMPLETE-MFA improved both flux precision and flux observability, i.e. more independent fluxes were resolved with smaller confidence intervals, especially exchange fluxes. Overall, this study demonstrates that COMPLETE-MFA is a powerful approach for improving flux measurements and that this methodology should be considered in future studies that require very high flux resolution.

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

    Science.gov (United States)

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

    2012-12-01

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

  14. Bacterial adaptation through distributed sensing of metabolic fluxes

    NARCIS (Netherlands)

    Kotte, Oliver; Zaugg, Judith B.; Heinemann, Matthias

    2010-01-01

    The recognition of carbon sources and the regulatory adjustments to recognized changes are of particular importance for bacterial survival in fluctuating environments. Despite a thorough knowledge base of Escherichia coli’s central metabolism and its regulation, fundamental aspects of the employed s

  15. 293SF metabolic flux analysis during cell growth and infection with an adenoviral vector.

    Science.gov (United States)

    Nadeau, I; Jacob, D; Perrier, M; Kamen, A

    2000-01-01

    Metabolic flux quantification of cell culture is becoming a crucial means to improve cell growth as well as protein and vector productions. The technique allows rapid determination of cell culture status, thus providing a tool for further feeding improvements. Herein, we report on key results of a metabolic investigation using 293 cells adapted to suspension and serum-free medium (293SF) during growth and infection with an adenoviral vector encoding the green fluorescence protein (GFP). The model developed contains 35 fluxes, which include the main fluxes of glycolysis, glutaminolysis, and amino acids pathways. It requires specific consumption and production rate measurements of amino acids, glucose, lactate, NH(3), and O(2), as well as DNA and total proteins biosynthesis rate measurements. Also, it was found that extracellular protein concentration measurement is important for flux calculation accuracy. With this model, we are able to describe the 293SF cell metabolism, grown under different culture conditions in a 3-L controlled bioreactor for batch and fed-batch with low glucose. The metabolism is also investigated during infection under two different feeding strategies: a fed-batch starting at the end of the growth phase and extending during infection without medium change and a fed-batch after infection following medium renewal. Differences in metabolism are observed between growth and infection, as well as between the different feeding strategies, thus providing a better understanding of the general metabolism.

  16. Reliable and efficient solution of genome-scale models of Metabolism and macromolecular Expression

    DEFF Research Database (Denmark)

    Ma, Ding; Yang, Laurence; Fleming, Ronan M. T.

    2017-01-01

    Constraint-Based Reconstruction and Analysis (COBRA) is currently the only methodology that permits integrated modeling of Metabolism and macromolecular Expression (ME) at genome-scale. Linear optimization computes steady-state flux solutions to ME models, but flux values are spread over many...

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

    Science.gov (United States)

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

    2010-04-19

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

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

    Directory of Open Access Journals (Sweden)

    Pinto José P

    2010-04-01

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

  19. Analysis and Engineering of Metabolic Pathway Fluxes in Corynebacterium glutamicum

    Science.gov (United States)

    Wittmann, Christoph

    The Gram-positive soil bacterium Corynebacterium glutamicum was discovered as a natural overproducer of glutamate about 50 years ago. Linked to the steadily increasing economical importance of this microorganism for production of glutamate and other amino acids, the quest for efficient production strains has been an intense area of research during the past few decades. Efficient production strains were created by applying classical mutagenesis and selection and especially metabolic engineering strategies with the advent of recombinant DNA technology. Hereby experimental and computational approaches have provided fascinating insights into the metabolism of this microorganism and directed strain engineering. Today, C. glutamicum is applied to the industrial production of more than 2 million tons of amino acids per year. The huge achievements in recent years, including the sequencing of the complete genome and efficient post genomic approaches, now provide the basis for a new, fascinating era of research - analysis of metabolic and regulatory properties of C. glutamicum on a global scale towards novel and superior bioprocesses.

  20. Pool size measurements facilitate the determination of fluxes at branching points in non-stationary metabolic flux analysis: the case of Arabidopsis thaliana.

    Science.gov (United States)

    Heise, Robert; Fernie, Alisdair R; Stitt, Mark; Nikoloski, Zoran

    2015-01-01

    Pool size measurements are important for the estimation of absolute intracellular fluxes in particular scenarios based on data from heavy carbon isotope experiments. Recently, steady-state fluxes estimates were obtained for central carbon metabolism in an intact illuminated rosette of Arabidopsis thaliana grown photoautotrophically (Szecowka et al., 2013; Heise et al., 2014). Fluxes were estimated therein by integrating mass-spectrometric data of the dynamics of the unlabeled metabolic fraction, data on metabolic pool sizes, partitioning of metabolic pools between cellular compartments and estimates of photosynthetically inactive pools, with a simplified model of plant central carbon metabolism. However, the fluxes were determined by treating the pool sizes as fixed parameters. Here we investigated whether and, if so, to what extent the treatment of pool sizes as parameters to be optimized in three scenarios may affect the flux estimates. The results are discussed in terms of benchmark values for canonical pathways and reactions, including starch and sucrose synthesis as well as the ribulose-1,5-bisphosphate carboxylation and oxygenation reactions. In addition, we discuss pathways emerging from a divergent branch point for which pool sizes are required for flux estimation, irrespective of the computational approach used for the simulation of the observable labeling pattern. Therefore, our findings indicate the necessity for development of techniques for accurate pool size measurements to improve the quality of flux estimates from non-stationary flux estimates in intact plant cells in the absence of alternative flux measurements.

  1. Pool size measurements facilitate the determination of fluxes at branching points in nonstationary metabolic flux analysis: The case of Arabidopsis thaliana

    Directory of Open Access Journals (Sweden)

    Robert eHeise

    2015-06-01

    Full Text Available Pool size measurements are important for the estimation of absolute intracellular fluxes in particular scenarios based on data from heavy carbon isotope experiments. Recently, steady-state fluxes estimates were obtained for central carbon metabolism in an intact illuminated rosette of Arabidopsis thaliana grown photoautotrophically (Szecowka et al., 2013; Heise et al., 2014. Fluxes were estimated therein by integrating mass-spectrometric data of the dynamics of the unlabeled metabolic fraction, data on metabolic pool sizes, partitioning of metabolic pools between cellular compartments and estimates of photosynthetically inactive pools, with a simplified model of plant central carbon metabolism. However, the fluxes were determined by treating the pool sizes as fixed parameters. Here we investigated whether and, if so, to what extent the treatment of pool sizes as parameters to be optimized in three scenarios may affect the flux estimates. The results are discussed in terms of benchmark values for canonical pathways and reactions, including starch and sucrose synthesis as well as the ribulose-1,5-bisphosphate carboxylation and oxygenation reactions. In addition, we discuss pathways emerging from a divergent branch point for which pool sizes are required for flux estimation, irrespective of the computational approach used for the simulation of the observable labelling pattern. Therefore, our findings indicate the necessity for development of techniques for accurate pool size measurements to improve the quality of flux estimates from nonstationary flux estimates in intact plant cells in the absence of alternative flux measurements.

  2. MID Max: LC–MS/MS Method for Measuring the Precursor and Product Mass Isotopomer Distributions of Metabolic Intermediates and Cofactors for Metabolic Flux Analysis Applications

    DEFF Research Database (Denmark)

    McCloskey, Douglas; Young, Jamey D.; Xu, Sibei

    2016-01-01

    The analytical challenges to acquire accurate isotopic data of intracellular metabolic intermediates for stationary, nonstationary, and dynamic metabolic flux analysis (MFA) are numerous. This work presents MID Max, a novel LC–MS/MS workflow, acquisition, and isotopomer deconvolution method for MFA...... product spectra) with accuracy and precision. The compounds measured included metabolic intermediates in central carbohydrate metabolism and cofactors of peripheral metabolism (e.g., ATP). Using only a subset of the acquired MIDs, the method was found to improve the precision of flux estimations...... and number of resolved exchange fluxes for wild-type E. coli compared to traditional methods and previously published data sets....

  3. Multiobjective flux balancing using the NISE method for metabolic network analysis.

    Science.gov (United States)

    Oh, Young-Gyun; Lee, Dong-Yup; Lee, Sang Yup; Park, Sunwon

    2009-01-01

    Flux balance analysis (FBA) is well acknowledged as an analysis tool of metabolic networks in the framework of metabolic engineering. However, FBA has a limitation for solving a multiobjective optimization problem which considers multiple conflicting objectives. In this study, we propose a novel multiobjective flux balance analysis method, which adapts the noninferior set estimation (NISE) method (Solanki et al., 1993) for multiobjective linear programming (MOLP) problems. NISE method can generate an approximation of the Pareto curve for conflicting objectives without redundant iterations of single objective optimization. Furthermore, the flux distributions at each Pareto optimal solution can be obtained for understanding the internal flux changes in the metabolic network. The functionality of this approach is shown by applying it to a genome-scale in silico model of E. coli. Multiple objectives for the poly(3-hydroxybutyrate) [P(3HB)] production are considered simultaneously, and relationships among them are identified. The Pareto curve for maximizing succinic acid production vs. maximizing biomass production is used for the in silico analysis of various combinatorial knockout strains. This proposed method accelerates the strain improvement in the metabolic engineering by reducing computation time of obtaining the Pareto curve and analysis time of flux distribution at each Pareto optimal solution. (c) 2009 American Institute of Chemical Engineers Biotechnol. Prog., 2009.

  4. FluxSimulator: An R Package to Simulate Isotopomer Distributions in Metabolic Networks

    Directory of Open Access Journals (Sweden)

    Thomas W. Binsl

    2007-01-01

    Full Text Available The representation of biochemical knowledge in terms of fluxes (transformation rates in a metabolic network is often a crucial step in the development of new drugs and efficient bioreactors. Mass spectroscopy (MS and nuclear magnetic resonance spectroscopy (NMRS in combination with 13C labeled substrates are experimental techniques resulting in data that may be used to quantify fluxes in the metabolic network underlying a process. The massive amount of data generated by spectroscopic experiments increasingly requires software which models the dynamics of the underlying biological system. In this work we present an approach to handle isotopomer distributions in metabolic networks using an object-oriented programming approach, implemented using S4 classes in R. The developed package is called FluxSimulator and provides a user friendly interface to specify the topological information of the metabolic network as well as carbon atom transitions in plain text files. The package automatically derives the mathematical representation of the formulated network, and assembles a set of ordinary differential equations (ODEs describing the change of each isotopomer pool over time. These ODEs are subsequently solved numerically. In a case study FluxSimulator was applied to an example network. Our results indicate that the package is able to reproduce exact changes in isotopomer compositions of the metabolite pools over time at given flux rates.

  5. Metabolic flux analysis of Escherichia coli MG1655 under octanoic acid (C8) stress.

    Science.gov (United States)

    Fu, Yanfen; Yoon, Jong Moon; Jarboe, Laura; Shanks, Jacqueline V

    2015-05-01

    Systems metabolic engineering has made the renewable production of industrial chemicals a feasible alternative to modern operations. One major example of a renewable process is the production of carboxylic acids, such as octanoic acid (C8), from Escherichia coli, engineered to express thioesterase enzymes. C8, however, is toxic to E. coli above a certain concentration, which limits the final titer. (13)C metabolic flux analysis of E. coli was performed for both C8 stress and control conditions using NMR2Flux with isotopomer balancing. A mixture of labeled and unlabeled glucose was used as the sole carbon source for bacterial growth for (13)C flux analysis. By comparing the metabolic flux maps of the control condition and C8 stress condition, pathways that were altered under the stress condition were identified. C8 stress was found to reduce carbon flux in several pathways: the tricarboxylic acid (TCA) cycle, the CO2 production, and the pyruvate dehydrogenase pathway. Meanwhile, a few pathways became more active: the pyruvate oxidative pathway, and the extracellular acetate production. These results were statistically significant for three biological replicates between the control condition and C8 stress. As a working hypothesis, the following causes are proposed to be the main causes for growth inhibition and flux alteration for a cell under stress: membrane disruption, low activity of electron transport chain, and the activation of the pyruvate dehydrogenase regulator (PdhR).

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

    Science.gov (United States)

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

    2012-01-01

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

  7. Detection of metabolic fluxes of O and H atoms into intracellular water in mammalian cells.

    Science.gov (United States)

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

    2012-01-01

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

  8. Detection of metabolic fluxes of O and H atoms into intracellular water in mammalian cells.

    Directory of Open Access Journals (Sweden)

    Helen W Kreuzer

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

  9. OpenMebius: An Open Source Software for Isotopically Nonstationary 13C-Based Metabolic Flux Analysis

    Directory of Open Access Journals (Sweden)

    Shuichi Kajihata

    2014-01-01

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

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

    Science.gov (United States)

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

    2014-01-01

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

  11. Effect of carbon source perturbations on transcriptional regulation of metabolic fluxes in Saccharomyces cerevisiae

    Directory of Open Access Journals (Sweden)

    Ülgen Kutlu Ö

    2007-03-01

    Full Text Available Abstract Background Control effective flux (CEF of a reaction is the weighted sum of all fluxes through that reaction, derived from elementary flux modes (EFM of a metabolic network. Change in CEFs under different environmental conditions has earlier been proven to be correlated with the corresponding changes in the transcriptome. Here we use this to investigate the degree of transcriptional regulation of fluxes in the metabolism of Saccharomyces cerevisiae. We do this by quantifying correlations between changes in CEFs and changes in transcript levels for shifts in carbon source, i.e. between the fermentative carbon source glucose and nonfermentative carbon sources like ethanol, acetate, and lactate. The CEF analysis is based on a simple stoichiometric model that includes reactions of the central carbon metabolism and the amino acid metabolism. Results The effect of the carbon shift on the metabolic fluxes was investigated for both batch and chemostat cultures. For growth on glucose in batch (respiro-fermentative cultures, EFMs with no by-product formation were removed from the analysis of the CEFs, whereas those including any by-products (ethanol, glycerol, acetate, succinate were omitted in the analysis of growth on glucose in chemostat (respiratory cultures. This resulted in improved correlations between CEF changes and transcript levels. A regression correlation coefficient of 0.60 was obtained between CEF changes and gene expression changes in the central carbon metabolism for the analysis of 5 different perturbations. Out of 45 data points there were no more than 6 data points deviating from the correlation. Additionally, up- or down-regulation of at least 75% of the genes were in qualitative agreement with the CEF changes for all perturbations studied. Conclusion The analysis indicates that changes in carbon source are associated with a high degree of hierarchical regulation of metabolic fluxes in the central carbon metabolism as the

  12. Development of a screening approach for exploring cell factory potential through metabolic flux analysis and physiology

    DEFF Research Database (Denmark)

    Knudsen, Peter Boldsen; Nielsen, Kristian Fog; Thykær, Jette

    2012-01-01

    The recent developments within the field of metabolic engineering have significantly increased the speed by which fungal recombinant strains are being constructed, pushing focus towards physiological characterisation and analysis. This raises demand for a tool for diligent analysis of the recombi...... and work-load connected with screening and selection of potential cell factories with attractive properties, compared with more “traditional” methodologies where metabolic flux analysis is applied at a much later state in the characterisation process.......The recent developments within the field of metabolic engineering have significantly increased the speed by which fungal recombinant strains are being constructed, pushing focus towards physiological characterisation and analysis. This raises demand for a tool for diligent analysis...... on a Hamilton robotic system. This method aimed at characterising physiology at two levels: (1) An approach focusing on the traditional growth related parameters, i.e. growth rate, yield coefficients and extracellular metabolites. (2) 13C-labelling experiments, where metabolic fluxes are quantified...

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

    NARCIS (Netherlands)

    Chaudhary, N.; Tøndel, K.; Bhatnagar, R.; Martins dos Santos, V.A.P.; Puchalka, J.

    2016-01-01

    Genome-Scale Metabolic Reconstructions (GSMRs), along with optimization-based methods, predominantly Flux Balance Analysis (FBA) and its derivatives, are widely applied for assessing and predicting the behavior of metabolic networks upon perturbation, thereby enabling identification of potential nov

  14. Metabolic network reconstruction, growth characterization and 13C-metabolic flux analysis of the extremophile Thermus thermophilus HB8.

    Science.gov (United States)

    Swarup, Aditi; Lu, Jing; DeWoody, Kathleen C; Antoniewicz, Maciek R

    2014-07-01

    Thermus thermophilus is an extremely thermophilic bacterium with significant biotechnological potential. In this work, we have characterized aerobic growth characteristics of T. thermophilus HB8 at temperatures between 50 and 85°C, constructed a metabolic network model of its central carbon metabolism and validated the model using (13)C-metabolic flux analysis ((13)C-MFA). First, cells were grown in batch cultures in custom constructed mini-bioreactors at different temperatures to determine optimal growth conditions. The optimal temperature for T. thermophilus grown on defined medium with glucose was 81°C. The maximum growth rate was 0.25h(-1). Between 50 and 81°C the growth rate increased by 7-fold and the temperature dependence was described well by an Arrhenius model with an activation energy of 47kJ/mol. Next, we performed a (13)C-labeling experiment with [1,2-(13)C] glucose as the tracer and calculated intracellular metabolic fluxes using (13)C-MFA. The results provided support for the constructed network model and highlighted several interesting characteristics of T. thermophilus metabolism. We found that T. thermophilus largely uses glycolysis and TCA cycle to produce biosynthetic precursors, ATP and reducing equivalents needed for cells growth. Consistent with its proposed metabolic network model, we did not detect any oxidative pentose phosphate pathway flux or Entner-Doudoroff pathway activity. The biomass precursors erythrose-4-phosphate and ribose-5-phosphate were produced via the non-oxidative pentose phosphate pathway, and largely via transketolase, with little contribution from transaldolase. The high biomass yield on glucose that was measured experimentally was also confirmed independently by (13)C-MFA. The results presented here provide a solid foundation for future studies of T. thermophilus and its metabolic engineering applications.

  15. (13)C Metabolic Flux Analysis for Systematic Metabolic Engineering of S. cerevisiae for Overproduction of Fatty Acids.

    Science.gov (United States)

    Ghosh, Amit; Ando, David; Gin, Jennifer; Runguphan, Weerawat; Denby, Charles; Wang, George; Baidoo, Edward E K; Shymansky, Chris; Keasling, Jay D; García Martín, Héctor

    2016-01-01

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

  16. 13C Metabolic Flux Analysis for systematic metabolic engineering of S. cerevisiae for overproduction of fatty acids.

    Directory of Open Access Journals (Sweden)

    Amit Ghosh

    2016-10-01

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

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

    DEFF Research Database (Denmark)

    Rocha, I.; Maia, P.; Evangelista, P.

    2010-01-01

    software aimed at being the reference computational application in the field. It is the first tool to incorporate strain optimization tasks, i.e., the identification of Metabolic Engineering targets, using Evolutionary Algorithms/Simulated Annealing metaheuristics or the previously proposed Opt......, computing the admissible flux space given a set of measured fluxes, and (iii) pathway analysis through the calculation of Elementary Flux Modes. OptFlux also contemplates several methods for model simplification and other pre-processing operations aimed at reducing the search space for optimization...... algorithms. The software supports importing/exporting to several flat file formats and it is compatible with the SBML standard. OptFlux has a visualization module that allows the analysis of the model structure that is compatible with the layout information of Cell Designer, allowing the superimposition...

  18. Metabolic fluxes in the central carbon metabolism of Dinoroseobacter shibae and Phaeobacter gallaeciensis, two members of the marine Roseobacter clade

    Directory of Open Access Journals (Sweden)

    Rabus Ralf

    2009-09-01

    Full Text Available Abstract Background In the present work the central carbon metabolism of Dinoroseobacter shibae and Phaeobacter gallaeciensis was studied at the level of metabolic fluxes. These two strains belong to the marine Roseobacter clade, a dominant bacterial group in various marine habitats, and represent surface-associated, biofilm-forming growth (P. gallaeciensis and symbiotic growth with eukaryotic algae (D. shibae. Based on information from recently sequenced genomes, a rich repertoire of pathways has been identified in the carbon core metabolism of these organisms, but little is known about the actual contribution of the various reactions in vivo. Results Using 13C labelling techniques in specifically designed experiments, it could be shown that glucose-grown cells of D. shibae catabolise the carbon source exclusively via the Entner-Doudoroff pathway, whereas alternative routes of glycolysis and the pentose phosphate pathway are obviously utilised for anabolic purposes only. Enzyme assays confirmed this flux pattern and link the lack of glycolytic flux to the absence of phosphofructokinase activity. The previously suggested formation of phosphoenolpyruvate from pyruvate during mixotrophic CO2 assimilation was found to be inactive under the conditions studied. Moreover, it could be shown that pyruvate carboxylase is involved in CO2 assimilation and that the cyclic respiratory mode of the TCA cycle is utilised. Interestingly, the use of intracellular pathways was highly similar for P. gallaeciensis. Conclusion The present study reveals the first insight into pathway utilisation within the Roseobacter group. Fluxes through major intracellular pathways of the central carbon metabolism, which are closely linked to the various important traits found for the Roseobacter clade, could be determined. The close similarity of fluxes between the two physiologically rather different species might provide the first indication of more general key properties among

  19. FluxExplorer: A general platform for modeling and analyses of metabolic networks based on stoichiometry

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    Stoichiometry-based analyses of meta- bolic networks have aroused significant interest of systems biology researchers in recent years. It is necessary to develop a more convenient modeling platform on which users can reconstruct their network models using completely graphical operations, and explore them with powerful analyzing modules to get a better understanding of the properties of metabolic systems. Herein, an in silico platform, FluxExplorer, for metabolic modeling and analyses based on stoichiometry has been developed as a publicly available tool for systems biology research. This platform integrates various analytic approaches, in- cluding flux balance analysis, minimization of meta- bolic adjustment, extreme pathways analysis, shadow prices analysis, and singular value decom- position, providing a thorough characterization of the metabolic system. Using a graphic modeling process, metabolic networks can be reconstructed and modi- fied intuitively and conveniently. The inconsistencies of a model with respect to the FBA principles can be proved automatically. In addition, this platform sup- ports systems biology markup language (SBML). FluxExplorer has been applied to rebuild a metabolic network in mammalian mitochondria, producing meaningful results. Generally, it is a powerful and very convenient tool for metabolic network modeling and analysis.

  20. Flux analysis and control of the central metabolic pathways in Escherichia coli.

    Science.gov (United States)

    Holms, H

    1996-12-01

    The growth of the bacterial cell involves the co-ordination of the fluxes of carbon into a considerable diversity of products that are the components of the cell. Fortunately the monomers from which the cell's polymers are made are themselves synthesised from a relatively small group of precursors that are the products of the central metabolic pathways. This simplification renders cell metabolism accessible to flux analysis, a method for handling experimental data to derive metabolic fluxes. Through such analysis of the growth of Escherichia coli ML308 on 11 single carbon sources in batch, turbidostat or chemostat culture general patterns are discernible. Most significant among these are that growth on different carbon sources is achieved without any obvious enzyme acting as a regulator of metabolic flux, except when acetate is the sole source of carbon. In this case a junction is created at which iso citrate dehydrogenase (ICDH) and isocitrate lyase (ICL) compete for their common substrate and this competition is resolved by partial inactivation of ICDH to match flux through ICL and this balance limits growth rate. In this sense, flux through ICDH and ICL is 'rate-limiting'. Uptake of six of the remaining carbon inputs exceeds the capacity of the central metabolic pathways (CMPs) to sustain flux to the precursors required for growth and the CMPs are balanced by excretion of acetate. Restriction of carbon uptake by chemostat progressively diminishes growth rate and acetate excretion until acetate excretion is prevented. For the four remaining carbon sources, uptake is apparently restricted and the products are biomass, carbon dioxide and water. Carbon sources feeding the phosphorylated parts of the CMPs flux relatively more carbon to precursors (Pre-C) than CO2 when compared with carbon sources which feed into the non-phosphorylated pathways. Pre-C/CO2 ratios for the former are 1.73-3.91 and for the latter are 0.46-0.78. Flux analysis of all 11 carbon sources shows

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

    Directory of Open Access Journals (Sweden)

    Jordà Joel

    2012-05-01

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

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

    Science.gov (United States)

    Jordà, Joel; Jouhten, Paula; Cámara, Elena; Maaheimo, Hannu; Albiol, Joan; Ferrer, Pau

    2012-05-08

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

  3. Using bioconductor package BiGGR for metabolic flux estimation based on gene expression changes in brain.

    Science.gov (United States)

    Gavai, Anand K; Supandi, Farahaniza; Hettling, Hannes; Murrell, Paul; Leunissen, Jack A M; van Beek, Johannes H G M

    2015-01-01

    Predicting the distribution of metabolic fluxes in biochemical networks is of major interest in systems biology. Several databases provide metabolic reconstructions for different organisms. Software to analyze flux distributions exists, among others for the proprietary MATLAB environment. Given the large user community for the R computing environment, a simple implementation of flux analysis in R appears desirable and will facilitate easy interaction with computational tools to handle gene expression data. We extended the R software package BiGGR, an implementation of metabolic flux analysis in R. BiGGR makes use of public metabolic reconstruction databases, and contains the BiGG database and the reconstruction of human metabolism Recon2 as Systems Biology Markup Language (SBML) objects. Models can be assembled by querying the databases for pathways, genes or reactions of interest. Fluxes can then be estimated by maximization or minimization of an objective function using linear inverse modeling algorithms. Furthermore, BiGGR provides functionality to quantify the uncertainty in flux estimates by sampling the constrained multidimensional flux space. As a result, ensembles of possible flux configurations are constructed that agree with measured data within precision limits. BiGGR also features automatic visualization of selected parts of metabolic networks using hypergraphs, with hyperedge widths proportional to estimated flux values. BiGGR supports import and export of models encoded in SBML and is therefore interoperable with different modeling and analysis tools. As an application example, we calculated the flux distribution in healthy human brain using a model of central carbon metabolism. We introduce a new algorithm termed Least-squares with equalities and inequalities Flux Balance Analysis (Lsei-FBA) to predict flux changes from gene expression changes, for instance during disease. Our estimates of brain metabolic flux pattern with Lsei-FBA for Alzheimer

  4. (13)C Metabolic Flux Analysis of acetate conversion to lipids by Yarrowia lipolytica.

    Science.gov (United States)

    Liu, Nian; Qiao, Kangjian; Stephanopoulos, Gregory

    2016-11-01

    Volatile fatty acids (VFAs) are an inexpensive and renewable carbon source that can be generated from gas fermentation and anaerobic digestion of fermentable wastes. The oleaginous yeast Yarrowia lipolytica is a promising biocatalyst that can utilize VFAs and convert them into triacylglycerides (TAGs). However, currently there is limited knowledge on the metabolism of Y. lipolytica when cultured on VFAs. To develop a better understanding, we used acetate as the sole carbon source to culture two strains, a control strain and a previously engineered strain for lipid overaccumulation. For both strains, metabolism during the growth phase and lipid production phase were investigated by metabolic flux analysis using two parallel sodium acetate tracers. The resolved flux distributions demonstrate that the glyoxylate shunt pathway is constantly active and the flux through gluconeogenesis varies depending on strain and phase. In particular, by regulating the activities of malate transport and pyruvate kinase, the cells divert only a portion of the glyoxylate shunt flux required to satisfy the needs for anaplerotic reactions and NADPH production through gluconeogenesis and the oxidative pentose phosphate pathway (PPP). Excess flux flows back to the tricarboxylic acid (TCA) cycle for energy production. As with the case of glucose as the substrate, the primary source for lipogenic NADPH is derived from the oxidative PPP.

  5. (13)C-metabolic flux analysis of co-cultures: A novel approach.

    Science.gov (United States)

    Gebreselassie, Nikodimos A; Antoniewicz, Maciek R

    2015-09-01

    In this work, we present a novel approach for performing (13)C metabolic flux analysis ((13)C-MFA) of co-culture systems. We demonstrate for the first time that it is possible to determine metabolic flux distributions in multiple species simultaneously without the need for physical separation of cells or proteins, or overexpression of species-specific products. Instead, metabolic fluxes for each species in a co-culture are estimated directly from isotopic labeling of total biomass obtained using conventional mass spectrometry approaches such as GC-MS. In addition to determining metabolic fluxes, this approach estimates the relative population size of each species in a mixed culture and inter-species metabolite exchange. As such, it enables detailed studies of microbial communities including species dynamics and interactions between community members. The methodology is experimentally validated here using a co-culture of two E. coli knockout strains. Taken together, this work greatly extends the scope of (13)C-MFA to a large number of multi-cellular systems that are of significant importance in biotechnology and medicine.

  6. Rational design of 13C-labeling experiments for metabolic flux analysis in mammalian cells

    Directory of Open Access Journals (Sweden)

    Crown Scott B

    2012-05-01

    Full Text Available Abstract Background 13C-Metabolic flux analysis (13C-MFA is a standard technique to probe cellular metabolism and elucidate in vivo metabolic fluxes. 13C-Tracer selection is an important step in conducting 13C-MFA, however, current methods are restricted to trial-and-error approaches, which commonly focus on an arbitrary subset of the tracer design space. To systematically probe the complete tracer design space, especially for complex systems such as mammalian cells, there is a pressing need for new rational approaches to identify optimal tracers. Results Recently, we introduced a new framework for optimal 13C-tracer design based on elementary metabolite units (EMU decomposition, in which a measured metabolite is decomposed into a linear combination of so-called EMU basis vectors. In this contribution, we applied the EMU method to a realistic network model of mammalian metabolism with lactate as the measured metabolite. The method was used to select optimal tracers for two free fluxes in the system, the oxidative pentose phosphate pathway (oxPPP flux and anaplerosis by pyruvate carboxylase (PC. Our approach was based on sensitivity analysis of EMU basis vector coefficients with respect to free fluxes. Through efficient grouping of coefficient sensitivities, simple tracer selection rules were derived for high-resolution quantification of the fluxes in the mammalian network model. The approach resulted in a significant reduction of the number of possible tracers and the feasible tracers were evaluated using numerical simulations. Two optimal, novel tracers were identified that have not been previously considered for 13C-MFA of mammalian cells, specifically [2,3,4,5,6-13C]glucose for elucidating oxPPP flux and [3,4-13C]glucose for elucidating PC flux. We demonstrate that 13C-glutamine tracers perform poorly in this system in comparison to the optimal glucose tracers. Conclusions In this work, we have demonstrated that optimal tracer design does not

  7. Metabolic flux network analysis of fermentative hydrogen production: using Clostridium tyrobutyricum as an example.

    Science.gov (United States)

    Cheng, Hai-Hsuan; Whang, Liang-Ming; Lin, Che-An; Liu, I-Chun; Wu, Chao-Wei

    2013-08-01

    This study applies metabolic flux network analysis (MFA) to evaluate the metabolic flux of fermentative hydrogen production (FHP) with the use of Clostridium tyrobutyricum fed with either glucose or lactate/acetate as substrates. The MFA results suggest that hydraulic retention time (HRT) presents significant impact on hydrogen production from glucose. At HRT between 4 and 18 h, increase of HRT increased hydrogen production but decreased lactate production, while at HRT below 4 h decrease of HRT increased hydrogen production but decreased lactate production. The flux for lactate, butyrate and acetate seemed to affect H₂ production, due presumably to their impacts on the balance of NADH, ferredoxin and ATP. It is suggested that the MFA can be a useful tool to provide valuable information for optimization and design of the fermentative hydrogen production process.

  8. Metabolic-flux analysis of hydrogen production pathway in Citrobacter amalonaticus Y19

    Energy Technology Data Exchange (ETDEWEB)

    Oh, You-Kwan; Kim, Mi-Sun [Bioenergy Research Center, Korea Institute of Energy Research, Daejeon 305-343 (Korea); Kim, Heung-Joo; Park, Sunghoon [Department of Chemical and Biochemical Engineering and Institute for Environmental Technology and Industry, Pusan National University, Busan 609-735 (Korea); Ryu, Dewey D.Y. [Biochemical Engineering Program, Department of Chemical Engineering and Material Science, University of California, Davis, CA 95616 (United States)

    2008-03-15

    For the newly isolated chemoheterotrophic bacterium Citrobacter amalonaticus Y19, anaerobic glucose metabolism and hydrogen (H{sub 2}) production pathway were studied using batch cultivation and an in silico metabolic-flux analysis. Batch cultivation was conducted under varying initial glucose concentration between 1.5 and 9.5 g/L with quantitative measurement of major metabolites to obtain accurate carbon material balance. The metabolic flux of Y19 was analyzed using a metabolic-pathway model which was constructed from 81 biochemical reactions. The linear optimization program MetaFluxNet was employed for the analysis. When the specific growth rate of cells was chosen as an objective function, the model described the batch culture characteristics of Ci. amalonaticus Y19 reasonably well. When the specific H{sub 2} production rate was selected as an objective function, on the other hand, the achievable maximal H{sub 2} production yield (8.7molH{sub 2}/mol glucose) and the metabolic pathway enabling the high H{sub 2} yield were identified. The pathway involved non-native NAD(P)-linked hydrogenase and H{sub 2} production from NAD(P)H which were supplied at a high rate from glucose degradation through the pentose phosphate pathway. (author)

  9. 13C metabolic flux analysis in Clostridium acetobutylicum during growth on L-arabinose

    Science.gov (United States)

    Hurley, Margaret; Sund, Christian; Liu, Sanchao; Germane, Katherine; Servinsky, Matthew; Gerlach, Elliot

    2015-03-01

    Clostridium acetobutylicum's metabolic pathways have been studied for decades due to its metabolic diversity and industrial value, yet many details of its metabolism are continuing to emerge. To elucidate the role of xylulose-5-P/fructose-6-P phosphoketolase (XFP), and the recently discovered Pentose Phosphate Pathway (PKP) in C. acetobutylicum, experimental and computational metabolic isotope analysis was performed under growth on glucose, xylose, and arabinose. Results indicate that PKP utilization increased with increasing xylose concentration and this trend was further pronounced during growth on arabinose. This was confirmed by mutation of the gene encoding XFP, which almost completely abolished flux through the PKP during growth on arabinose and resulted in decreased acetate:butyrate ratios. We discuss these experimental and computational results here, and the implications for our understanding of sugar metabolism in C. acetobutylicum.

  10. Understanding the control of acyl flux through the lipid metabolic network of plant oil biosynthesis.

    Science.gov (United States)

    Bates, Philip D

    2016-09-01

    Plant oil biosynthesis involves a complex metabolic network with multiple subcellular compartments, parallel pathways, cycles, and pathways that have a dual function to produce essential membrane lipids and triacylglycerol. Modern molecular biology techniques provide tools to alter plant oil compositions through bioengineering, however with few exceptions the final composition of triacylglycerol cannot be predicted. One reason for limited success in oilseed bioengineering is the inadequate understanding of how to control the flux of fatty acids through various fatty acid modification, and triacylglycerol assembly pathways of the lipid metabolic network. This review focuses on the mechanisms of acyl flux through the lipid metabolic network, and highlights where uncertainty resides in our understanding of seed oil biosynthesis. This article is part of a Special Issue entitled: Plant Lipid Biology edited by Kent D. Chapman and Ivo Feussner.

  11. Dynamic metabolic flux analysis using B-splines to study the effects of temperature shift on CHO cell metabolism

    Directory of Open Access Journals (Sweden)

    Verónica S. Martínez

    2015-12-01

    Full Text Available Metabolic flux analysis (MFA is widely used to estimate intracellular fluxes. Conventional MFA, however, is limited to continuous cultures and the mid-exponential growth phase of batch cultures. Dynamic MFA (DMFA has emerged to characterize time-resolved metabolic fluxes for the entire culture period. Here, the linear DMFA approach was extended using B-spline fitting (B-DMFA to estimate mass balanced fluxes. Smoother fits were achieved using reduced number of knots and parameters. Additionally, computation time was greatly reduced using a new heuristic algorithm for knot placement. B-DMFA revealed that Chinese hamster ovary cells shifted from 37 °C to 32 °C maintained a constant IgG volume-specific productivity, whereas the productivity for the controls peaked during mid-exponential growth phase and declined afterward. The observed 42% increase in product titer at 32 °C was explained by a prolonged cell growth with high cell viability, a larger cell volume and a more stable volume-specific productivity.

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

    DEFF Research Database (Denmark)

    Montagud, Arnau; Zelezniak, Aleksej; Navarro, Emilio

    2011-01-01

    activities and metabolic physiology, flux coupling analysis was performed for iSyn811 under four different growth conditions, viz., autotrophy, mixotrophy, heterotrophy, and light-activated heterotrophy (LH). Initial steps of carbon acquisition and catabolism formed the versatile center of the flux coupling...... and reporter flux coupling groups - regulatory hot spots during metabolic shifts triggered by the availability of light. Overall, flux coupling analysis provided insight into the structural organization of Synechocystis sp. PCC6803 metabolic network toward designing of a photosynthesis-based production......-scale metabolic model is a pre-requisite toward achieving a proficient photosynthetic cell factory. To this end, we report iSyn811, an upgraded genome-scale metabolic model of Synechocystis sp. PCC6803 consisting of 956 reactions and accounting for 811 genes. To gain insights into the interplay between flux...

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

    Directory of Open Access Journals (Sweden)

    Christopher M. Shymansky

    2017-05-01

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

  14. Application of (13)C flux analysis to identify high-productivity CHO metabolic phenotypes.

    Science.gov (United States)

    Templeton, Neil; Smith, Kevin D; McAtee-Pereira, Allison G; Dorai, Haimanti; Betenbaugh, Michael J; Lang, Steven E; Young, Jamey D

    2017-01-23

    Industrial bioprocesses place high demands on the energy metabolism of host cells to meet biosynthetic requirements for maximal protein expression. Identifying metabolic phenotypes that promote high expression is therefore a major goal of the biotech industry. We conducted a series of (13)C flux analysis studies to examine the metabolic response to IgG expression during early stationary phase of CHO cell cultures grown in 3L fed-batch bioreactors. We examined eight clones expressing four different IgGs and compared with three non-expressing host-cell controls. Some clones were genetically manipulated to be apoptosis-resistant by expressing Bcl-2Δ, which correlated with increased IgG production and elevated glucose metabolism. The metabolic phenotypes of the non-expressing, IgG-expressing, and Bcl-2Δ/IgG-expressing clones were fully segregated by hierarchical clustering analysis. Lactate consumption and citric acid cycle fluxes were most strongly associated with specific IgG productivity. These studies indicate that enhanced oxidative metabolism is a characteristic of high-producing CHO cell lines.

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

    Energy Technology Data Exchange (ETDEWEB)

    Maranas, Costas D

    2012-05-21

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

  16. To be certain about the uncertainty: Bayesian statistics for (13) C metabolic flux analysis.

    Science.gov (United States)

    Theorell, Axel; Leweke, Samuel; Wiechert, Wolfgang; Nöh, Katharina

    2017-07-11

    (13) C Metabolic Fluxes Analysis ((13) C MFA) remains to be the most powerful approach to determine intracellular metabolic reaction rates. Decisions on strain engineering and experimentation heavily rely upon the certainty with which these fluxes are estimated. For uncertainty quantification, the vast majority of (13) C MFA studies relies on confidence intervals from the paradigm of Frequentist statistics. However, it is well known that the confidence intervals for a given experimental outcome are not uniquely defined. As a result, confidence intervals produced by different methods can be different, but nevertheless equally valid. This is of high relevance to (13) C MFA, since practitioners regularly use three different approximate approaches for calculating confidence intervals. By means of a computational study with a realistic model of the central carbon metabolism of E. coli, we provide strong evidence that confidence intervals used in the field depend strongly on the technique with which they were calculated and, thus, their use leads to misinterpretation of the flux uncertainty. In order to provide a better alternative to confidence intervals in (13) C MFA, we demonstrate that credible intervals from the paradigm of Bayesian statistics give more reliable flux uncertainty quantifications which can be readily computed with high accuracy using Markov chain Monte Carlo. In addition, the widely applied chi-square test, as a means of testing whether the model reproduces the data, is examined closer. © 2017 Wiley Periodicals, Inc.

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

    Science.gov (United States)

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

    2014-03-01

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

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

    Science.gov (United States)

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

    2013-11-01

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

  19. (13)C-metabolic flux analysis for mevalonate-producing strain of Escherichia coli.

    Science.gov (United States)

    Wada, Keisuke; Toya, Yoshihiro; Banno, Satomi; Yoshikawa, Katsunori; Matsuda, Fumio; Shimizu, Hiroshi

    2017-02-01

    Mevalonate (MVA) is used to produce various useful products such as drugs, cosmetics and food additives. An MVA-producing strain of Escherichia coli (engineered) was constructed by introducing mvaES genes from Enterococcus faecalis. The engineered strain produced 1.84 mmol/gDCW/h yielding 22% (C-mol/C-mol) of MVA from glucose in the aerobic exponential growth phase. The mass balance analysis revealed that the MVA yield of the engineered strain was close to the upper limit at the biomass yield. Since MVA is synthesized from acetyl-CoA using NADPH as a cofactor, the production of MVA affects central metabolism in terms of carbon utilization and NADPH requirements. The reason for this highly efficient MVA production was investigated based on (13)C-metabolic flux analysis. The estimated flux distributions revealed that the fluxes of acetate formation and the TCA cycle in the engineered strain were lower than those in the control strain. Although the oxidative pentose phosphate pathway is considered as the NADPH generating pathway in E. coli, no difference of the flux was observed between the control and engineered strains. The production/consumption balance of NADPH suggested that additional requirement of NADPH for MVA synthesis was obtained from the transhydrogenase reaction in the engineered strain. Comparison between the measured flux distribution and the ideal values for MVA production proposes a strategy for further engineering to improve the MVA production in E. coli.

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

    Science.gov (United States)

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

    2015-08-01

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

  1. Tissue-specific metabolic reprogramming drives nutrient flux in diabetic complications

    Science.gov (United States)

    Sas, Kelli M.; Kayampilly, Pradeep; Byun, Jaeman; Nair, Viji; Hinder, Lucy M.; Zhang, Hongyu; Lin, Chengmao; Qi, Nathan R.; Michailidis, George; Groop, Per-Henrik; Nelson, Robert G.; Darshi, Manjula; Sharma, Kumar; Schelling, Jeffrey R.; Sedor, John R.; Pop-Busui, Rodica; Weinberg, Joel M.; Soleimanpour, Scott A.; Abcouwer, Steven F.; Gardner, Thomas W.; Burant, Charles F.; Feldman, Eva L.; Kretzler, Matthias; Brosius, Frank C.

    2016-01-01

    Diabetes is associated with altered cellular metabolism, but how altered metabolism contributes to the development of diabetic complications is unknown. We used the BKS db/db diabetic mouse model to investigate changes in carbohydrate and lipid metabolism in kidney cortex, peripheral nerve, and retina. A systems approach using transcriptomics, metabolomics, and metabolic flux analysis identified tissue-specific differences, with increased glucose and fatty acid metabolism in the kidney, a moderate increase in the retina, and a decrease in the nerve. In the kidney, increased metabolism was associated with enhanced protein acetylation and mitochondrial dysfunction. To confirm these findings in human disease, we analyzed diabetic kidney transcriptomic data and urinary metabolites from a cohort of Southwestern American Indians. The urinary findings were replicated in 2 independent patient cohorts, the Finnish Diabetic Nephropathy and the Family Investigation of Nephropathy and Diabetes studies. Increased concentrations of TCA cycle metabolites in urine, but not in plasma, predicted progression of diabetic kidney disease, and there was an enrichment of pathways involved in glycolysis and fatty acid and amino acid metabolism. Our findings highlight tissue-specific changes in metabolism in complication-prone tissues in diabetes and suggest that urinary TCA cycle intermediates are potential prognostic biomarkers of diabetic kidney disease progression. PMID:27699244

  2. ¹³C-based metabolic flux analysis of recombinant Pichia pastoris.

    Science.gov (United States)

    Ferrer, Pau; Albiol, Joan

    2014-01-01

    Overexpression of a foreign protein may negatively affect several cell growth parameters, as well as cause cellular stress. Central (or core) metabolism plays a crucial role since it supplies energy, reduction equivalents, and precursor molecules for the recombinant product, cell's maintenance, and growth needs. However, the number of quantitative physiology studies of the impact of recombinant protein production on the central metabolic pathways of yeast cell factories has been traditionally rather limited, thereby hampering the application of rational strain engineering strategies targeting central metabolism.The development and application of quantitative physiology and modelling tools and methodologies is allowing for a systems-level understanding of the effect of bioprocess parameters such as growth rate, temperature, oxygen availability, and substrate(s) choice on metabolism, and its subsequent interactions with recombinant protein synthesis, folding, and secretion.Here, we review the recent developments and applications of (13)C-based metabolic flux analysis ((13)C-MFA) of Pichia pastoris and the gained understanding of the metabolic behavior of this yeast in recombinant protein production bioprocesses. We also discuss the potential of multilevel studies integrating (13)C-MFA with other omics analyses, as well as future perspectives on the metabolic modelling approaches to study and design metabolic engineering strategies for improved protein production.

  3. Tools for the analysis of metabolic flux through the sphingolipid pathway.

    Science.gov (United States)

    Martínez-Montañés, Fernando; Schneiter, Roger

    2016-11-01

    Discerning the complex regulation of the enzymatic steps necessary for sphingolipid biosynthesis is facilitated by the utilization of tracers that allow a time-resolved analysis of the pathway dynamics without affecting the metabolic flux. Different strategies have been used and new tools are continuously being developed to probe the various enzymatic conversions that occur within this complex pathway. Here, we provide a short overview of the divergent fungal and mammalian sphingolipid biosynthetic routes, and of the tracers and methods that are frequently employed to follow the flux of intermediates throughout these pathways.

  4. Metabolic flux analysis using ¹³C peptide label measurements.

    Science.gov (United States)

    Mandy, Dominic E; Goldford, Joshua E; Yang, Hong; Allen, Doug K; Libourel, Igor G L

    2014-02-01

    ¹³C metabolic flux analysis (MFA) has become the experimental method of choice to investigate the cellular metabolism of microbes, cell cultures and plant seeds. Conventional steady-state MFA utilizes isotopic labeling measurements of amino acids obtained from protein hydrolysates. To retain spatial information in conventional steady-state MFA, tissues or subcellular fractions must be dissected or biochemically purified. In contrast, peptides retain their identity in complex protein extracts, and may therefore be associated with a specific time of expression, tissue type and subcellular compartment. To enable 'single-sample' spatially and temporally resolved steady-state flux analysis, we investigated the suitability of peptide mass distributions (PMDs) as an alternative to amino acid label measurements. PMDs are the discrete convolution of the mass distributions of the constituent amino acids of a peptide. We investigated the requirements for the unique deconvolution of PMDs into amino acid mass distributions (AAMDs), the influence of peptide sequence length on parameter sensitivity, and how AAMD and flux estimates that are determined through deconvolution compare to estimates from a conventional GC-MS measurement-based approach. Deconvolution of PMDs of the storage protein β-conglycinin of soybean (Glycine max) resulted in good AAMD and flux estimates if fluxes were directly fitted to PMDs. Unconstrained deconvolution resulted in inferior AAMD and flux estimates. PMD measurements do not include amino acid backbone fragments, which increase the information content in GC-MS-derived analyses. Nonetheless, the resulting flux maps were of comparable quality due to the precision of Orbitrap quantification and the larger number of peptide measurements.

  5. Genome-scale constraint-based modeling of Geobacter metallireducens

    Directory of Open Access Journals (Sweden)

    Famili Iman

    2009-01-01

    Full Text Available Abstract Background Geobacter metallireducens was the first organism that can be grown in pure culture to completely oxidize organic compounds with Fe(III oxide serving as electron acceptor. Geobacter species, including G. sulfurreducens and G. metallireducens, are used for bioremediation and electricity generation from waste organic matter and renewable biomass. The constraint-based modeling approach enables the development of genome-scale in silico models that can predict the behavior of complex biological systems and their responses to the environments. Such a modeling approach was applied to provide physiological and ecological insights on the metabolism of G. metallireducens. Results The genome-scale metabolic model of G. metallireducens was constructed to include 747 genes and 697 reactions. Compared to the G. sulfurreducens model, the G. metallireducens metabolic model contains 118 unique reactions that reflect many of G. metallireducens' specific metabolic capabilities. Detailed examination of the G. metallireducens model suggests that its central metabolism contains several energy-inefficient reactions that are not present in the G. sulfurreducens model. Experimental biomass yield of G. metallireducens growing on pyruvate was lower than the predicted optimal biomass yield. Microarray data of G. metallireducens growing with benzoate and acetate indicated that genes encoding these energy-inefficient reactions were up-regulated by benzoate. These results suggested that the energy-inefficient reactions were likely turned off during G. metallireducens growth with acetate for optimal biomass yield, but were up-regulated during growth with complex electron donors such as benzoate for rapid energy generation. Furthermore, several computational modeling approaches were applied to accelerate G. metallireducens research. For example, growth of G. metallireducens with different electron donors and electron acceptors were studied using the genome

  6. Flux analysis of central metabolic pathways in Geobactermetallireducens during reduction of solubleFe(III)-NTA

    Energy Technology Data Exchange (ETDEWEB)

    Tang, Yinjie J.; Chakraborty, Romy; Garcia-Martin, Hector; Chu,Jeannie; Hazen, Terry C.; Keasling, Jay D.

    2007-01-01

    We analyzed the carbon fluxes in the central metabolism ofGeobacter metallireducens strain GS-15 using 13C isotopomer modeling.Acetate labeled in the 1st or 2nd position was the sole carbon source,and Fe-NTA was the sole terminal electron acceptor. The measured labeledacetate uptake rate was 21 mmol/gdw/h in the exponential growth phase.The resulting isotope labeling pattern of amino acids allowed an accuratedetermination of the in vivo global metabolic reaction rates (fluxes)through the central metabolic pathways using a computational isotopomermodel. The tracer experiments showed that G. metallireducens containedcomplete biosynthesis pathways for essential metabolism, and this strainmight also have an unusual isoleucine biosynthesis route (usingacetyl-CoA and pyruvate as the precursors). The model indicated that over90 percent of the acetate was completely oxidized to CO2 via a completetricarboxylic acid (TCA) cycle while reducing iron. Pyruvate carboxylaseand phosphoenolpyruvate carboxykinase were present under theseconditions, but enzymes in the glyoxylate shunt and malic enzyme wereabsent. Gluconeogenesis and the pentose phosphate pathway were mainlyemployed for biosynthesis and accounted for less than 3 percent of totalcarbon consumption. The model also indicated surprisingly highreversibility in the reaction between oxoglutarate and succinate. Thisstep operates close to the thermodynamic equilibrium possibly becausesuccinate is synthesized via a transferase reaction, and the conversionof oxoglutarate to succinate is a rate limiting step for carbonmetabolism. These findings enable a better understanding of therelationship between genome annotation and extant metabolic pathways inG. metallireducens.

  7. In situ metabolic flux analysis to quantify the liver metabolic response to experimental burn injury.

    Science.gov (United States)

    Izamis, Maria-Louisa; Sharma, Nripen S; Uygun, Basak; Bieganski, Robert; Saeidi, Nima; Nahmias, Yaakov; Uygun, Korkut; Yarmush, Martin L; Berthiaume, Francois

    2011-04-01

    Trauma such as burns induces a hypermetabolic response associated with altered central carbon and nitrogen metabolism. The liver plays a key role in these metabolic changes; however, studies to date have evaluated the metabolic state of liver using ex vivo perfusions or isotope labeling techniques targeted to specific pathways. Herein, we developed a unique mass balance approach to characterize the metabolic state of the liver in situ, and used it to quantify the metabolic changes to experimental burn injury in rats. Rats received a sham (control uninjured), 20% or 40% total body surface area (TBSA) scald burn, and were allowed to develop a hypermetabolic response. One day prior to evaluation, all animals were fasted to deplete glycogen stores. Four days post-burn, blood flow rates in major vessels of the liver were measured, and blood samples harvested. We combined measurements of metabolite concentrations and flow rates in the major vessels entering and leaving the liver with a steady-state mass balance model to generate a quantitative picture of the metabolic state of liver. The main findings were: (1) Sham-burned animals exhibited a gluconeogenic pattern, consistent with the fasted state; (2) the 20% TBSA burn inhibited gluconeogenesis and exhibited glycolytic-like features with very few other significant changes; (3) the 40% TBSA burn, by contrast, further enhanced gluconeogenesis and also increased amino acid extraction, urea cycle reactions, and several reactions involved in oxidative phosphorylation. These results suggest that increasing the severity of injury does not lead to a simple dose-dependent metabolic response, but rather leads to qualitatively different responses.

  8. Overcoming the metabolic burden of protein secretion in Schizosaccharomyces pombe--a quantitative approach using 13C-based metabolic flux analysis.

    Science.gov (United States)

    Klein, Tobias; Lange, Sabrina; Wilhelm, Nadine; Bureik, Matthias; Yang, Tae-Hoon; Heinzle, Elmar; Schneider, Konstantin

    2014-01-01

    Protein secretion in yeast is generally associated with a burden to cellular metabolism. To investigate this metabolic burden in Schizosaccharomyces pombe, we constructed a set of strains secreting the model protein maltase in different amounts. We quantified the influence of protein secretion on the metabolism applying (13)C-based metabolic flux analysis in chemostat cultures. Analysis of the macromolecular biomass composition revealed an increase in cellular lipid content at elevated levels of protein secretion and we observed altered metabolic fluxes in the pentose phosphate pathway, the TCA cycle, and around the pyruvate node including mitochondrial NADPH supply. Supplementing acetate to glucose or glycerol minimal media was found to improve protein secretion, accompanied by an increased cellular lipid content and carbon flux through the TCA cycle as well as increased mitochondrial NADPH production. Thus, systematic metabolic analyses can assist in identifying factors limiting protein secretion and in deriving strategies to overcome these limitations.

  9. Metabolic flux balance analysis and the in silico analysis of Escherichia coli K-12 gene deletions

    Directory of Open Access Journals (Sweden)

    Edwards Jeremy S

    2000-07-01

    Full Text Available Abstract Background Genome sequencing and bioinformatics are producing detailed lists of the molecular components contained in many prokaryotic organisms. From this 'parts catalogue' of a microbial cell, in silico representations of integrated metabolic functions can be constructed and analyzed using flux balance analysis (FBA. FBA is particularly well-suited to study metabolic networks based on genomic, biochemical, and strain specific information. Results Herein, we have utilized FBA to interpret and analyze the metabolic capabilities of Escherichia coli. We have computationally mapped the metabolic capabilities of E. coli using FBA and examined the optimal utilization of the E. coli metabolic pathways as a function of environmental variables. We have used an in silico analysis to identify seven gene products of central metabolism (glycolysis, pentose phosphate pathway, TCA cycle, electron transport system essential for aerobic growth of E. coli on glucose minimal media, and 15 gene products essential for anaerobic growth on glucose minimal media. The in silico tpi-, zwf, and pta- mutant strains were examined in more detail by mapping the capabilities of these in silico isogenic strains. Conclusions We found that computational models of E. coli metabolism based on physicochemical constraints can be used to interpret mutant behavior. These in silica results lead to a further understanding of the complex genotype-phenotype relation. Supplementary information: http://gcrg.ucsd.edu/supplementary_data/DeletionAnalysis/main.htm

  10. Metabolic flux analysis of CHO cells at growth and non-growth phases using isotopic tracers and mass spectrometry.

    Science.gov (United States)

    Ahn, Woo Suk; Antoniewicz, Maciek R

    2011-09-01

    Chinese hamster ovary (CHO) cells are the main platform for production of biotherapeutics in the biopharmaceutical industry. However, relatively little is known about the metabolism of CHO cells in cell culture. In this work, metabolism of CHO cells was studied at the growth phase and early stationary phase using isotopic tracers and mass spectrometry. CHO cells were grown in fed-batch culture over a period of six days. On days 2 and 4, [1,2-(13)C] glucose was introduced and the labeling of intracellular metabolites was measured by gas chromatography-mass spectrometry (GC-MS) at 6, 12 and 24h following the introduction of tracer. Intracellular metabolic fluxes were quantified from measured extracellular rates and (13)C-labeling dynamics of intracellular metabolites using non-stationary (13)C-metabolic flux analysis ((13)C-MFA). The flux results revealed significant rewiring of intracellular metabolic fluxes in the transition from growth to non-growth, including changes in energy metabolism, redox metabolism, oxidative pentose phosphate pathway and anaplerosis. At the exponential phase, CHO cell metabolism was characterized by a high flux of glycolysis from glucose to lactate, anaplerosis from pyruvate to oxaloacetate and from glutamate to α-ketoglutarate, and cataplerosis though malic enzyme. At the stationary phase, the flux map was characterized by a reduced flux of glycolysis, net lactate uptake, oxidative pentose phosphate pathway flux, and reduced rate of anaplerosis. The fluxes of pyruvate dehydrogenase and TCA cycle were similar at the exponential and stationary phase. The results presented here provide a solid foundation for future studies of CHO cell metabolism for applications such as cell line development and medium optimization for high-titer production of recombinant proteins.

  11. Metabolic flux analysis during the exponential growth phase of Saccharomyces cerevisiae in wine fermentations.

    Directory of Open Access Journals (Sweden)

    Manuel Quirós

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

  12. Metabolic flux analysis during the exponential growth phase of Saccharomyces cerevisiae in wine fermentations.

    Science.gov (United States)

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

    2013-01-01

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

  13. Counting and Correcting Thermodynamically Infeasible Flux Cycles in Genome-Scale Metabolic Networks

    Directory of Open Access Journals (Sweden)

    Andrea De Martino

    2013-10-01

    Full Text Available Thermodynamics constrains the flow of matter in a reaction network to occur through routes along which the Gibbs energy decreases, implying that viable steady-state flux patterns should be void of closed reaction cycles. Identifying and removing cycles in large reaction networks can unfortunately be a highly challenging task from a computational viewpoint. We propose here a method that accomplishes it by combining a relaxation algorithm and a Monte Carlo procedure to detect loops, with ad hoc rules (discussed in detail to eliminate them. As test cases, we tackle (a the problem of identifying infeasible cycles in the E. coli metabolic network and (b the problem of correcting thermodynamic infeasibilities in the Flux-Balance-Analysis solutions for 15 human cell-type-specific metabolic networks. Results for (a are compared with previous analyses of the same issue, while results for (b are weighed against alternative methods to retrieve thermodynamically viable flux patterns based on minimizing specific global quantities. Our method, on the one hand, outperforms previous techniques and, on the other, corrects loopy solutions to Flux Balance Analysis. As a byproduct, it also turns out to be able to reveal possible inconsistencies in model reconstructions.

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

    Science.gov (United States)

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

    2015-11-01

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

  15. Bayesian flux balance analysis applied to a skeletal muscle metabolic model.

    Science.gov (United States)

    Heino, Jenni; Tunyan, Knarik; Calvetti, Daniela; Somersalo, Erkki

    2007-09-01

    In this article, the steady state condition for the multi-compartment models for cellular metabolism is considered. The problem is to estimate the reaction and transport fluxes, as well as the concentrations in venous blood when the stoichiometry and bound constraints for the fluxes and the concentrations are given. The problem has been addressed previously by a number of authors, and optimization-based approaches as well as extreme pathway analysis have been proposed. These approaches are briefly discussed here. The main emphasis of this work is a Bayesian statistical approach to the flux balance analysis (FBA). We show how the bound constraints and optimality conditions such as maximizing the oxidative phosphorylation flux can be incorporated into the model in the Bayesian framework by proper construction of the prior densities. We propose an effective Markov chain Monte Carlo (MCMC) scheme to explore the posterior densities, and compare the results with those obtained via the previously studied linear programming (LP) approach. The proposed methodology, which is applied here to a two-compartment model for skeletal muscle metabolism, can be extended to more complex models.

  16. Fuzzy Constraint-Based Agent Negotiation

    Institute of Scientific and Technical Information of China (English)

    Menq-Wen Lin; K. Robert Lai; Ting-Jung Yu

    2005-01-01

    Conflicts between two or more parties arise for various reasons and perspectives. Thus, resolution of conflicts frequently relies on some form of negotiation. This paper presents a general problem-solving framework for modeling multi-issue multilateral negotiation using fuzzy constraints. Agent negotiation is formulated as a distributed fuzzy constraint satisfaction problem (DFCSP). Fuzzy constrains are thus used to naturally represent each agent's desires involving imprecision and human conceptualization, particularly when lexical imprecision and subjective matters are concerned. On the other hand, based on fuzzy constraint-based problem-solving, our approach enables an agent not only to systematically relax fuzzy constraints to generate a proposal, but also to employ fuzzy similarity to select the alternative that is subject to its acceptability by the opponents. This task of problem-solving is to reach an agreement that benefits all agents with a high satisfaction degree of fuzzy constraints, and move towards the deal more quickly since their search focuses only on the feasible solution space. An application to multilateral negotiation of a travel planning is provided to demonstrate the usefulness and effectiveness of our framework.

  17. (13) C-metabolic flux analysis of human adenovirus infection: Implications for viral vector production.

    Science.gov (United States)

    Carinhas, Nuno; Koshkin, Alexey; Pais, Daniel A M; Alves, Paula M; Teixeira, Ana P

    2017-01-01

    Adenoviruses are human pathogens increasingly used as gene therapy and vaccination vectors. However, their impact on cell metabolism is poorly characterized. We performed carbon labeling experiments with [1,2-(13) C]glucose or [U-(13) C]glutamine to evaluate metabolic alterations in the amniocyte-derived, E1-transformed 1G3 cell line during production of a human adenovirus type 5 vector (AdV5). Nonstationary (13) C-metabolic flux analysis revealed increased fluxes of glycolysis (17%) and markedly PPP (over fourfold) and cytosolic AcCoA formation (nearly twofold) following infection of growing cells. Interestingly, infection of growth-arrested cells increased overall carbon flow even more, including glutamine anaplerosis and TCA cycle activity (both over 1.5-fold), but was unable to stimulate the PPP and was associated with a steep drop in AdV5 replication (almost 80%). Our results underscore the importance of nucleic and fatty acid biosynthesis for adenovirus replication. Overall, we portray a metabolic blueprint of human adenovirus infection, highlighting similarities with other viruses and cancer, and suggest strategies to improve AdV5 production. Biotechnol. Bioeng. 2017;114: 195-207. © 2016 Wiley Periodicals, Inc.

  18. Regulation of amino-acid metabolism controls flux to lipid accumulation in Yarrowia lipolytica

    DEFF Research Database (Denmark)

    Kerkhoven, Eduard J.; Pomraning, Kyle R.; Baker, Scott E.

    2016-01-01

    cultures. We first reconstructed a genome-scale metabolic model and used this for integrative analysis of multilevel omics data. Metabolite profiling and lipidomics was used to quantify the cellular physiology, while regulatory changes were measured using RNAseq. Analysis of the data showed that lipid......Yarrowia lipolytica is a promising microbial cell factory for the production of lipids to be used as fuels and chemicals, but there are few studies on regulation of its metabolism. Here we performed the first integrated data analysis of Y. lipolytica grown in carbon and nitrogen limited chemostat...... accumulation in Y. lipolytica does not involve transcriptional regulation of lipid metabolism but is associated with regulation of amino-acid biosynthesis, resulting in redirection of carbon flux during nitrogen limitation from amino acids to lipids. Lipid accumulation in Y. lipolytica at nitrogen limitation...

  19. A MILP-based flux alternative generation and NMR experimental design strategy for metabolic engineering.

    Science.gov (United States)

    Phalakornkule, C; Lee, S; Zhu, T; Koepsel, R; Ataai, M M; Grossmann, I E; Domach, M M

    2001-04-01

    A mixed-integer linear program (MILP) is described that can enumerate all the ways fluxes can distribute in a metabolic network while still satisfying the same constraints and objective function. The multiple solutions can be used to (1) generate alternative flux scenarios that can account for limited experimental observations, (2) forecast the potential responses to mutation (e.g., new reaction pathways may be used), and (3) (as illustrated) design (13)C NMR experiments such that different potential flux patterns in a mutant can be distinguished. The experimental design is enabled by using the MILP results as an input to an isotopomer mapping matrices (IMM)-based program, which accounts for the network circulation of (13)C from a precursor such as glucose. The IMM-based program can interface to common plotting programs with the result that the user is provided with predicted NMR spectra that are complete with splittings and Lorentzian line-shape features. The example considered is the trafficking of carbon in an Escherichia coli mutant, which has pyruvate kinase activity deleted for the purpose of eliminating acetate production. Similar yields and extracellular measurements would be manifested by the flux alternatives. The MILP-IMM results suggest how NMR experiments can be designed such that the spectra of glutamate for two flux distribution scenarios differ significantly.

  20. Metabolic flux analysis of hydrogen production network by Clostridium butyricum W5: Effect of pH and glucose concentrations

    Energy Technology Data Exchange (ETDEWEB)

    Cai, Guiqin [School of Earth and Environmental Sciences, The University of Adelaide, Adelaide, SA 5005 (Australia); Jin, Bo [School of Earth and Environmental Sciences, The University of Adelaide, Adelaide, SA 5005 (Australia); School of Chemical Engineering, The University of Adelaide, Adelaide, SA 5005 (Australia); Australian Water Quality Centre, SA Water Corporation, 250 Victoria Square, Adelaide, SA 5100 (Australia); Saint, Chris [School of Earth and Environmental Sciences, The University of Adelaide, Adelaide, SA 5005 (Australia); Australian Water Quality Centre, SA Water Corporation, 250 Victoria Square, Adelaide, SA 5100 (Australia); Monis, Paul [Australian Water Quality Centre, SA Water Corporation, 250 Victoria Square, Adelaide, SA 5100 (Australia)

    2010-07-15

    Fermentative hydrogen production by strict anaerobes has been widely reported. There is a lack of information related to metabolic flux distribution and its variation with respect to fermentation conditions in the metabolic production system. This study aimed to get a better understanding of the metabolic network and to conduct metabolic flux analysis (MFA) of fermentative hydrogen production by a recently isolated Clostridium butyricum strain W5. We chose the specific growth rate as the objective function and used specific H{sub 2} production rate as the criterion to evaluate the experimental results with the in silico MFA. For the first time, we constructed an in silico metabolic flux model for the anaerobic glucose metabolism of C. butyricum W5 with assistance of a modeling program MetaFluxNet. The model was used to evaluate metabolic flux distribution in the fermentative hydrogen production network, and to study the fractional flux response to variations in initial glucose concentration and operational pH. The MFA results suggested that pH has a more significant effect on hydrogen production yield compared to the glucose concentration. The MFA is a useful tool to provide valuable information for optimization and design of the fermentative hydrogen production process. (author)

  1. Systems-level metabolic flux profiling elucidates a complete, bifurcated tricarboxylic acid cycle in Clostridium acetobutylicum.

    Science.gov (United States)

    Amador-Noguez, Daniel; Feng, Xiao-Jiang; Fan, Jing; Roquet, Nathaniel; Rabitz, Herschel; Rabinowitz, Joshua D

    2010-09-01

    Obligatory anaerobic bacteria are major contributors to the overall metabolism of soil and the human gut. The metabolic pathways of these bacteria remain, however, poorly understood. Using isotope tracers, mass spectrometry, and quantitative flux modeling, here we directly map the metabolic pathways of Clostridium acetobutylicum, a soil bacterium whose major fermentation products include the biofuels butanol and hydrogen. While genome annotation suggests the absence of most tricarboxylic acid (TCA) cycle enzymes, our results demonstrate that this bacterium has a complete, albeit bifurcated, TCA cycle; oxaloacetate flows to succinate both through citrate/alpha-ketoglutarate and via malate/fumarate. Our investigations also yielded insights into the pathways utilized for glucose catabolism and amino acid biosynthesis and revealed that the organism's one-carbon metabolism is distinct from that of model microbes, involving reversible pyruvate decarboxylation and the use of pyruvate as the one-carbon donor for biosynthetic reactions. This study represents the first in vivo characterization of the TCA cycle and central metabolism of C. acetobutylicum. Our results establish a role for the full TCA cycle in an obligatory anaerobic organism and demonstrate the importance of complementing genome annotation with isotope tracer studies for determining the metabolic pathways of diverse microbes.

  2. Mapping cancer cell metabolism with 13 C flux analysis: Recent progress and future challenges

    Directory of Open Access Journals (Sweden)

    Casey Scott Duckwall

    2013-01-01

    Full Text Available The reprogramming of energy metabolism is emerging as an important molecular hallmark of cancer cells. Recent discoveries linking specific metabolic alterations to cancer development have strengthened the idea that altered metabolism is more than a side effect of malignant transformation, but may in fact be a functional driver of tumor growth and progression in some cancers. As a result, dysregulated metabolic pathways have become attractive targets for cancer therapeutics. This review highlights the application of 13 C metabolic flux analysis (MFA to map the flow of carbon through intracellular biochemical pathways of cancer cells. We summarize several recent applications of MFA that have identified novel biosynthetic pathways involved in cancer cell proliferation and shed light on the role of specific oncogenes in regulating these pathways. Through such studies, it has become apparent that the metabolic phenotypes of cancer cells are not as homogeneous as once thought, but instead depend strongly on the molecular alterations and environmental factors at play in each case.

  3. Investigating the effects of perturbations to pgi and eno gene expression on central carbon metabolism in Escherichia coli using 13 C metabolic flux analysis

    Directory of Open Access Journals (Sweden)

    Usui Yuki

    2012-06-01

    Full Text Available Abstract Background It has long been recognized that analyzing the behaviour of the complex intracellular biological networks is important for breeding industrially useful microorganisms. However, because of the complexity of these biological networks, it is currently not possible to obtain all the desired microorganisms. In this study, we constructed a system for analyzing the effect of gene expression perturbations on the behavior of biological networks in Escherichia coli. Specifically, we utilized 13 C metabolic flux analysis (13 C-MFA to analyze the effect of perturbations to the expression levels of pgi and eno genes encoding phosphoglucose isomerase and enolase, respectively on metabolic fluxes. Results We constructed gene expression-controllable E. coli strains using a single-copy mini F plasmid. Using the pgi expression-controllable strain, we found that the specific growth rate correlated with the pgi expression level. 13 C-MFA of this strain revealed that the fluxes for the pentose phosphate pathway and Entner-Doudoroff pathway decreased, as the pgi expression lelvel increased. In addition, the glyoxylate shunt became active when the pgi expression level was almost zero. Moreover, the flux for the glyoxylate shunt increased when the pgi expression level decreased, but was significantly reduced in the pgi-knockout cells. Comparatively, eno expression could not be decreased compared to the parent strain, but we found that increased eno expression resulted in a decreased specific growth rate. 13 C-MFA revealed that the metabolic flux distribution was not altered by an increased eno expression level, but the overall metabolic activity of the central metabolism decreased. Furthermore, to evaluate the impact of perturbed expression of pgi and eno genes on changes in metabolic fluxes in E. coli quantitatively, metabolic sensitivity analysis was performed. As a result, the perturbed expression of pgi gene had a great impact to the

  4. Exo-MFA - A 13C metabolic flux analysis framework to dissect tumor microenvironment-secreted exosome contributions towards cancer cell metabolism.

    Science.gov (United States)

    Achreja, Abhinav; Zhao, Hongyun; Yang, Lifeng; Yun, Tae Hyun; Marini, Juan; Nagrath, Deepak

    2017-09-01

    Dissecting the pleiotropic roles of tumor micro-environment (TME) on cancer progression has been brought to the foreground of research on cancer pathology. Extracellular vesicles such as exosomes, transport proteins, lipids, and nucleic acids, to mediate intercellular communication between TME components and have emerged as candidates for anti-cancer therapy. We previously reported that cancer-associated fibroblast (CAF) derived exosomes (CDEs) contain metabolites in their cargo that are utilized by cancer cells for central carbon metabolism and promote cancer growth. However, the metabolic fluxes involved in donor cells towards packaging of metabolites in extracellular vesicles and exosome-mediated metabolite flux upregulation in recipient cells are still not known. Here, we have developed a novel empirical and computational technique, exosome-mediated metabolic flux analysis (Exo-MFA) to quantify flow of cargo from source cells to recipient cells via vesicular transport. Our algorithm, which is based on (13)C metabolic flux analysis, successfully predicts packaging fluxes to metabolite cargo in CAFs, dynamic changes in rate of exosome internalization by cancer cells, and flux of cargo release over time. We find that cancer cells internalize exosomes rapidly leading to depletion of extracellular exosomes within 24h. However, metabolite cargo significantly alters intracellular metabolism over the course of 24h by regulating glycolysis pathway fluxes via lactate supply. Furthermore, it can supply up to 35% of the TCA cycle fluxes by providing TCA intermediates and glutamine. Our algorithm will help gain insight into (i) metabolic interactions in multicellular systems (ii) biogenesis of extracellular vesicles and their differential packaging of cargo under changing environments, and (iii) regulation of cancer cell metabolism by its microenvironment. Copyright © 2017 International Metabolic Engineering Society. Published by Elsevier Inc. All rights reserved.

  5. MID Max: LC-MS/MS Method for Measuring the Precursor and Product Mass Isotopomer Distributions of Metabolic Intermediates and Cofactors for Metabolic Flux Analysis Applications.

    Science.gov (United States)

    McCloskey, Douglas; Young, Jamey D; Xu, Sibei; Palsson, Bernhard O; Feist, Adam M

    2016-01-19

    The analytical challenges to acquire accurate isotopic data of intracellular metabolic intermediates for stationary, nonstationary, and dynamic metabolic flux analysis (MFA) are numerous. This work presents MID Max, a novel LC-MS/MS workflow, acquisition, and isotopomer deconvolution method for MFA that takes advantage of additional scan types that maximizes the number of mass isotopomer distributions (MIDs) that can be acquired in a given experiment. The analytical method was found to measure the MIDs of 97 metabolites, corresponding to 74 unique metabolite-fragment pairs (32 precursor spectra and 42 product spectra) with accuracy and precision. The compounds measured included metabolic intermediates in central carbohydrate metabolism and cofactors of peripheral metabolism (e.g., ATP). Using only a subset of the acquired MIDs, the method was found to improve the precision of flux estimations and number of resolved exchange fluxes for wild-type E. coli compared to traditional methods and previously published data sets.

  6. Linking high-resolution metabolic flux phenotypes and transcriptional regulation in yeast modulated by the global regulator Gcn4p

    DEFF Research Database (Denmark)

    Moxley, Joel F.; Jewett, Michael Christopher; Antoniewicz, Maciek R.

    2009-01-01

    Genome sequencing dramatically increased our ability to understand cellular response to perturbation. Integrating system-wide measurements such as gene expression with networks of protein protein interactions and transcription factor binding revealed critical insights into cellular behavior. Howe...... that an integrated approach focusing on metabolic measurements will facilitate construction of more realistic models of cellular regulation for understanding diseases and constructing strains for industrial applications.......RNA and metabolic flux data that combines information from both interaction network models and flux determination models. We started by quantifying 5,764 mRNAs, 54 metabolites, and 83 experimental C-13-based reaction fluxes in continuous cultures of yeast under stress in the absence or presence of global regulator...... of metabolic flux (i.e., use of different reaction pathways) by transcriptional regulation and metabolite interaction density (i.e., level of pairwise metabolite-protein interactions) as a key biosynthetic control determinant. Furthermore, this model predicted flux rewiring in studies of follow...

  7. Tracking the metabolic pulse of plant lipid production with isotopic labeling and flux analyses: Past, present and future.

    Science.gov (United States)

    Allen, Doug K; Bates, Philip D; Tjellström, Henrik

    2015-04-01

    Metabolism is comprised of networks of chemical transformations, organized into integrated biochemical pathways that are the basis of cellular operation, and function to sustain life. Metabolism, and thus life, is not static. The rate of metabolites transitioning through biochemical pathways (i.e., flux) determines cellular phenotypes, and is constantly changing in response to genetic or environmental perturbations. Each change evokes a response in metabolic pathway flow, and the quantification of fluxes under varied conditions helps to elucidate major and minor routes, and regulatory aspects of metabolism. To measure fluxes requires experimental methods that assess the movements and transformations of metabolites without creating artifacts. Isotopic labeling fills this role and is a long-standing experimental approach to identify pathways and quantify their metabolic relevance in different tissues or under different conditions. The application of labeling techniques to plant science is however far from reaching it potential. In light of advances in genetics and molecular biology that provide a means to alter metabolism, and given recent improvements in instrumentation, computational tools and available isotopes, the use of isotopic labeling to probe metabolism is becoming more and more powerful. We review the principal analytical methods for isotopic labeling with a focus on seminal studies of pathways and fluxes in lipid metabolism and carbon partitioning through central metabolism. Central carbon metabolic steps are directly linked to lipid production by serving to generate the precursors for fatty acid biosynthesis and lipid assembly. Additionally some of the ideas for labeling techniques that may be most applicable for lipid metabolism in the future were originally developed to investigate other aspects of central metabolism. We conclude by describing recent advances that will play an important future role in quantifying flux and metabolic operation in plant

  8. Study on roles of anaplerotic pathways in glutamate overproduction of Corynebacterium glutamicum by metabolic flux analysis

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    Shioya Suteaki

    2007-06-01

    Full Text Available Abstract Background Corynebacterium glutamicum has several anaplerotic pathways (anaplerosis, which are essential for the productions of amino acids, such as lysine and glutamate. It is still not clear how flux changes in anaplerotic pathways happen when glutamate production is induced by triggers, such as biotin depletion and the addition of the detergent material, Tween 40. In this study, we quantitatively analyzed which anaplerotic pathway flux most markedly changes the glutamate overproduction induced by Tween 40 addition. Results We performed a metabolic flux analysis (MFA with [1-13C]- and [U-13C]-labeled glucose in the glutamate production phase of C. glutamicum, based on the analysis of the time courses of 13C incorporation into proteinogenic amino acids by gas chromatography-mass spectrometry (GC-MS. The flux from phosphoenolpyruvate (PEP to oxaloacetate (Oxa catalyzed by phosphoenolpyruvate carboxylase (PEPc was active in the growth phase not producing glutamate, whereas that from pyruvate to Oxa catalyzed by pyruvate carboxylase (Pc was inactive. In the glutamate overproduction phase induced by the addition of the detergent material Tween 40, the reaction catalyzed by Pc also became active in addition to the reaction catalyzed by PEPc. Conclusion It was clarified by a quantitative 13C MFA that the reaction catalyzed by Pc is most markedly increased, whereas other fluxes of PEPc and PEPck remain constant in the glutamate overproduction induced by Tween 40. This result is consistent with the previous results obtained in a comparative study on the glutamate productions of genetically recombinant Pc- and PEPc-overexpressing strains. The importance of a specific reaction in an anaplerotic pathway was elucidated at a metabolic level by MFA.

  9. Oxygen dependence of metabolic fluxes and energy generation of Saccharomyces cerevisiae CEN.PK113-1A

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    Wiebe Marilyn

    2008-07-01

    Full Text Available Abstract Background The yeast Saccharomyces cerevisiae is able to adjust to external oxygen availability by utilizing both respirative and fermentative metabolic modes. Adjusting the metabolic mode involves alteration of the intracellular metabolic fluxes that are determined by the cell's multilevel regulatory network. Oxygen is a major determinant of the physiology of S. cerevisiae but understanding of the oxygen dependence of intracellular flux distributions is still scarce. Results Metabolic flux distributions of S. cerevisiae CEN.PK113-1A growing in glucose-limited chemostat cultures at a dilution rate of 0.1 h-1 with 20.9%, 2.8%, 1.0%, 0.5% or 0.0% O2 in the inlet gas were quantified by 13C-MFA. Metabolic flux ratios from fractional [U-13C]glucose labelling experiments were used to solve the underdetermined MFA system of central carbon metabolism of S. cerevisiae. While ethanol production was observed already in 2.8% oxygen, only minor differences in the flux distribution were observed, compared to fully aerobic conditions. However, in 1.0% and 0.5% oxygen the respiratory rate was severely restricted, resulting in progressively reduced fluxes through the TCA cycle and the direction of major fluxes to the fermentative pathway. A redistribution of fluxes was observed in all branching points of central carbon metabolism. Yet only when oxygen provision was reduced to 0.5%, was the biomass yield exceeded by the yields of ethanol and CO2. Respirative ATP generation provided 59% of the ATP demand in fully aerobic conditions and still a substantial 25% in 0.5% oxygenation. An extensive redistribution of fluxes was observed in anaerobic conditions compared to all the aerobic conditions. Positive correlation between the transcriptional levels of metabolic enzymes and the corresponding fluxes in the different oxygenation conditions was found only in the respirative pathway. Conclusion 13C-constrained MFA enabled quantitative determination of

  10. A procedure for the estimation over time of metabolic fluxes in scenarios where measurements are uncertain and/or insufficient

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    Picó Jesús

    2007-10-01

    Full Text Available Abstract Background An indirect approach is usually used to estimate the metabolic fluxes of an organism: couple the available measurements with known biological constraints (e.g. stoichiometry. Typically this estimation is done under a static point of view. Therefore, the fluxes so obtained are only valid while the environmental conditions and the cell state remain stable. However, estimating the evolution over time of the metabolic fluxes is valuable to investigate the dynamic behaviour of an organism and also to monitor industrial processes. Although Metabolic Flux Analysis can be successively applied with this aim, this approach has two drawbacks: i sometimes it cannot be used because there is a lack of measurable fluxes, and ii the uncertainty of experimental measurements cannot be considered. The Flux Balance Analysis could be used instead, but the assumption of optimal behaviour of the organism brings other difficulties. Results We propose a procedure to estimate the evolution of the metabolic fluxes that is structured as follows: 1 measure the concentrations of extracellular species and biomass, 2 convert this data to measured fluxes and 3 estimate the non-measured fluxes using the Flux Spectrum Approach, a variant of Metabolic Flux Analysis that overcomes the difficulties mentioned above without assuming optimal behaviour. We apply the procedure to a real problem taken from the literature: estimate the metabolic fluxes during a cultivation of CHO cells in batch mode. We show that it provides a reliable and rich estimation of the non-measured fluxes, thanks to considering measurements uncertainty and reversibility constraints. We also demonstrate that this procedure can estimate the non-measured fluxes even when there is a lack of measurable species. In addition, it offers a new method to deal with inconsistency. Conclusion This work introduces a procedure to estimate time-varying metabolic fluxes that copes with the insufficiency of

  11. High-throughput data pipelines for metabolic flux analysis in plants.

    Science.gov (United States)

    Poskar, C Hart; Huege, Jan; Krach, Christian; Shachar-Hill, Yair; Junker, Björn H

    2014-01-01

    In this chapter we illustrate the methodology for high-throughput metabolic flux analysis. Central to this is developing an end to end data pipeline, crucial for integrating the wet lab experiments and analytics, combining hardware and software automation, and standardizing data representation providing importers and exporters to support third party tools. The use of existing software at the start, data extraction from the chromatogram, and the end, MFA analysis, allows for the most flexibility in this workflow. Developing iMS2Flux provided a standard, extensible, platform independent tool to act as the "glue" between these end points. Most importantly this tool can be easily adapted to support different data formats, data verification and data correction steps allowing it to be central to managing the data necessary for high-throughput MFA. An additional tool was needed to automate the MFA software and in particular to take advantage of the course grained parallel nature of high-throughput analysis and available high performance computing facilities.In combination these methods show the development of high-throughput pipelines that allow metabolic flux analysis to join as a full member of the omics family.

  12. Comparative metabolic flux analysis of an Ashbya gossypii wild type strain and a high riboflavin-producing mutant strain.

    Science.gov (United States)

    Jeong, Bo-Young; Wittmann, Christoph; Kato, Tatsuya; Park, Enoch Y

    2015-01-01

    In the present study, we analyzed the central metabolic pathway of an Ashbya gossypii wild type strain and a riboflavin over-producing mutant strain developed in a previous study in order to characterize the riboflavin over-production pathway. (13)C-Metabolic flux analysis ((13)C-MFA) was carried out in both strains, and the resulting data were fit to a steady-state flux isotopomer model using OpenFLUX. Flux to pentose-5-phosphate (P5P) via the pentose phosphate pathway (PPP) was 9% higher in the mutant strain compared to the wild type strain. The flux from purine synthesis to riboflavin in the mutant strain was 1.6%, while that of the wild type strain was only 0.1%, a 16-fold difference. In addition, the flux from the cytoplasmic pyruvate pool to the extracellular metabolites, pyruvate, lactate, and alanine, was 2-fold higher in the mutant strain compared to the wild type strain. This result demonstrates that increased guanosine triphosphate (GTP) flux through the PPP and purine synthesis pathway (PSP) increased riboflavin production in the mutant strain. The present study provides the first insight into metabolic flux through the central carbon pathway in A. gossypii and sets the foundation for development of a quantitative and functional model of the A. gossypii metabolic network.

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

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

    2015-12-01

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

  14. Impacts of high β-galactosidase expression on central metabolism of recombinant Pichia pastoris GS115 using glucose as sole carbon source via (13)C metabolic flux analysis.

    Science.gov (United States)

    Nie, Yongsheng; Huang, Mingzhi; Lu, Junjie; Qian, Jiangchao; Lin, Weilu; Chu, Ju; Zhuang, Yingping; Zhang, Siliang

    2014-10-10

    The yeast Pichia pastoris GS115 is a widely used microbial cell factory for the production of heterologous protein. In order to reveal the impacts of high heterologous protein expression on the central metabolism of Pichia pastoris GS115 using glucose as sole carbon source, we engineered a high β-galactosidase expression strain P. pastoris G1HL and a low expression control strain P. pastoris GHL through controlling the initiation strength of constitutive promoter pGAP. The carbon flux distributions in these two strains were quantified via (13)C metabolic flux analysis. Compared to the control strain, G1HL showed a lower growth rate, a higher flux through glycolysis pathway, a higher flux through pentose phosphate pathway, and a lower flux through by-products secretion pathway. The metabolic flux redistribution in G1HL was thought to compensate the increased redox cofactors and energy demands caused by the high protein expression. Although the fluxes through Krebs cycle in two engineered strains were almost the same, they were significantly lower than those in wild strain. The enhanced expression of β-galactosidase by glutamate supplementation demonstrated the potential of P. pastoris GS115 to catabolize more carbon through the Krebs cycle for even higher protein expression. In conclusion, our work indicates that P. pastoris GS115 can readjusts the central metabolism for higher heterologous protein expression and provides strategies for strain development or process optimization for enhancing production of heterologous protein.

  15. iMS2Flux – a high–throughput processing tool for stable isotope labeled mass spectrometric data used for metabolic flux analysis

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    Poskar C Hart

    2012-11-01

    Full Text Available Abstract Background Metabolic flux analysis has become an established method in systems biology and functional genomics. The most common approach for determining intracellular metabolic fluxes is to utilize mass spectrometry in combination with stable isotope labeling experiments. However, before the mass spectrometric data can be used it has to be corrected for biases caused by naturally occurring stable isotopes, by the analytical technique(s employed, or by the biological sample itself. Finally the MS data and the labeling information it contains have to be assembled into a data format usable by flux analysis software (of which several dedicated packages exist. Currently the processing of mass spectrometric data is time-consuming and error-prone requiring peak by peak cut-and-paste analysis and manual curation. In order to facilitate high-throughput metabolic flux analysis, the automation of multiple steps in the analytical workflow is necessary. Results Here we describe iMS2Flux, software developed to automate, standardize and connect the data flow between mass spectrometric measurements and flux analysis programs. This tool streamlines the transfer of data from extraction via correction tools to 13C-Flux software by processing MS data from stable isotope labeling experiments. It allows the correction of large and heterogeneous MS datasets for the presence of naturally occurring stable isotopes, initial biomass and several mass spectrometry effects. Before and after data correction, several checks can be performed to ensure accurate data. The corrected data may be returned in a variety of formats including those used by metabolic flux analysis software such as 13CFLUX, OpenFLUX and 13CFLUX2. Conclusion iMS2Flux is a versatile, easy to use tool for the automated processing of mass spectrometric data containing isotope labeling information. It represents the core framework for a standardized workflow and data processing. Due to its flexibility

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

    Science.gov (United States)

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

    2017-03-01

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

  17. Carbon conversion efficiency and central metabolic fluxes in developing sunflower (Helianthus annuus L.) embryos.

    Science.gov (United States)

    Alonso, Ana P; Goffman, Fernando D; Ohlrogge, John B; Shachar-Hill, Yair

    2007-10-01

    The efficiency with which developing sunflower embryos convert substrates into seed storage reserves was determined by labeling embryos with [U-(14)C6]glucose or [U-(14)C5]glutamine and measuring their conversion to CO2, oil, protein and other biomass compounds. The average carbon conversion efficiency was 50%, which contrasts with a value of over 80% previously observed in Brassica napus embryos (Goffman et al., 2005), in which light and the RuBisCO bypass pathway allow more efficient conversion of hexose to oil. Labeling levels after incubating sunflower embryos with [U-(14)C4]malate indicated that some carbon from malate enters the plastidic compartment and contributes to oil synthesis. To test this and to map the underlying pattern of metabolic fluxes, separate experiments were carried out in which embryos were labeled to isotopic steady state using [1-(13)C1]glucose, [2-(13)C1]glucose, or [U-(13)C5]glutamine. The resultant labeling in sugars, starch, fatty acids and amino acids was analyzed by NMR and GC-MS. The fluxes through intermediary metabolism were then quantified by computer-aided modeling. The resulting flux map accounted well for the labeling data, was in good agreement with the observed carbon efficiency, and was further validated by testing for agreement with gas exchange measurements. The map shows that the influx of malate into oil is low and that flux through futile cycles (wasting ATP) is low, which contrasts with the high rates previously determined for growing root tips and heterotrophic cell cultures.

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

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    Akιn Ata

    2007-12-01

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

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

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

    2015-10-01

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

  20. Genome-scale modeling for metabolic engineering

    Energy Technology Data Exchange (ETDEWEB)

    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.

  1. Genome-scale modeling for metabolic engineering.

    Science.gov (United States)

    Simeonidis, Evangelos; Price, Nathan D

    2015-03-01

    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.

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

    Science.gov (United States)

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

    2016-01-01

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

  3. The role of flexibility and optimality in the prediction of intracellular fluxes of microbial central carbon metabolism.

    Science.gov (United States)

    Tarlak, Fatih; Sadıkoğlu, Hasan; Çakır, Tunahan

    2014-07-29

    Prediction of intracellular metabolic fluxes based on optimal biomass assumption is a well-known computational approach. While there has been a significant emphasis on the optimality, cellular flexibility, the co-occurrence of suboptimal flux distributions in a microbial population, has hardly been considered in the related computational methods. We have implemented a flexibility-incorporated optimization framework to calculate intracellular fluxes based on a few extracellular measurement constraints. Taking into account slightly suboptimal flux distributions together with a dual-optimality framework (maximization of the growth rate followed by the minimization of the total enzyme amount) we were able to show the positive effect of incorporating flexibility and minimal enzyme consumption on the better prediction of intracellular fluxes of central carbon metabolism of two microorganisms: E. coli and S. cerevisiae.

  4. Computational analysis of storage synthesis in developing Brassica napus L. (oilseed rape) embryos: Flux variability analysis in relation to 13C-metabolic flux analysis

    Energy Technology Data Exchange (ETDEWEB)

    Hay, J.; Schwender, J.

    2011-08-01

    Plant oils are an important renewable resource, and seed oil content is a key agronomical trait that is in part controlled by the metabolic processes within developing seeds. A large-scale model of cellular metabolism in developing embryos of Brassica napus (bna572) was used to predict biomass formation and to analyze metabolic steady states by flux variability analysis under different physiological conditions. Predicted flux patterns are highly correlated with results from prior 13C metabolic flux analysis of B. napus developing embryos. Minor differences from the experimental results arose because bna572 always selected only one sugar and one nitrogen source from the available alternatives, and failed to predict the use of the oxidative pentose phosphate pathway. Flux variability, indicative of alternative optimal solutions, revealed alternative pathways that can provide pyruvate and NADPH to plastidic fatty acid synthesis. The nutritional values of different medium substrates were compared based on the overall carbon conversion efficiency (CCE) for the biosynthesis of biomass. Although bna572 has a functional nitrogen assimilation pathway via glutamate synthase, the simulations predict an unexpected role of glycine decarboxylase operating in the direction of NH4+ assimilation. Analysis of the light-dependent improvement of carbon economy predicted two metabolic phases. At very low light levels small reductions in CO2 efflux can be attributed to enzymes of the tricarboxylic acid cycle (oxoglutarate dehydrogenase, isocitrate dehydrogenase) and glycine decarboxylase. At higher light levels relevant to the 13C flux studies, ribulose-1,5-bisphosphate carboxylase activity is predicted to account fully for the light-dependent changes in carbon balance.

  5. Computational analysis of storage synthesis in developing Brassica napus L. (oilseed rape) embryos: flux variability analysis in relation to ¹³C metabolic flux analysis.

    Science.gov (United States)

    Hay, Jordan; Schwender, Jörg

    2011-08-01

    Plant oils are an important renewable resource, and seed oil content is a key agronomical trait that is in part controlled by the metabolic processes within developing seeds. A large-scale model of cellular metabolism in developing embryos of Brassica napus (bna572) was used to predict biomass formation and to analyze metabolic steady states by flux variability analysis under different physiological conditions. Predicted flux patterns are highly correlated with results from prior ¹³C metabolic flux analysis of B. napus developing embryos. Minor differences from the experimental results arose because bna572 always selected only one sugar and one nitrogen source from the available alternatives, and failed to predict the use of the oxidative pentose phosphate pathway. Flux variability, indicative of alternative optimal solutions, revealed alternative pathways that can provide pyruvate and NADPH to plastidic fatty acid synthesis. The nutritional values of different medium substrates were compared based on the overall carbon conversion efficiency (CCE) for the biosynthesis of biomass. Although bna572 has a functional nitrogen assimilation pathway via glutamate synthase, the simulations predict an unexpected role of glycine decarboxylase operating in the direction of NH₄⁺ assimilation. Analysis of the light-dependent improvement of carbon economy predicted two metabolic phases. At very low light levels small reductions in CO₂ efflux can be attributed to enzymes of the tricarboxylic acid cycle (oxoglutarate dehydrogenase, isocitrate dehydrogenase) and glycine decarboxylase. At higher light levels relevant to the ¹³C flux studies, ribulose-1,5-bisphosphate carboxylase activity is predicted to account fully for the light-dependent changes in carbon balance.

  6. Exploring lysine riboswitch for metabolic flux control and improvement of L-lysine synthesis in Corynebacterium glutamicum.

    Science.gov (United States)

    Zhou, Li-Bang; Zeng, An-Ping

    2015-06-19

    Riboswitch, a regulatory part of an mRNA molecule that can specifically bind a metabolite and regulate gene expression, is attractive for engineering biological systems, especially for the control of metabolic fluxes in industrial microorganisms. Here, we demonstrate the use of lysine riboswitch and intracellular l-lysine as a signal to control the competing but essential metabolic by-pathways of lysine biosynthesis. To this end, we first examined the natural lysine riboswitches of Eschericia coli (ECRS) and Bacillus subtilis (BSRS) to control the expression of citrate synthase (gltA) and thus the metabolic flux in the tricarboxylic acid (TCA) cycle in E. coli. ECRS and BSRS were then successfully used to control the gltA gene and TCA cycle activity in a lysine producing strain Corynebacterium glutamicum LP917, respectively. Compared with the strain LP917, the growth of both lysine riboswitch-gltA mutants was slower, suggesting a reduced TCA cycle activity. The lysine production was 63% higher in the mutant ECRS-gltA and 38% higher in the mutant BSRS-gltA, indicating a higher metabolic flux into the lysine synthesis pathway. This is the first report on using an amino acid riboswitch for improvement of lysine biosynthesis. The lysine riboswitches can be easily adapted to dynamically control other essential but competing metabolic pathways or even be engineered as an "on-switch" to enhance the metabolic fluxes of desired metabolic pathways.

  7. Isotopically non-stationary metabolic flux analysis: complex yet highly informative.

    Science.gov (United States)

    Wiechert, Wolfgang; Nöh, Katharina

    2013-12-01

    Metabolic flux analysis (MFA) using isotopic tracers aims at the experimental determination of in vivo reaction rates (fluxes). In recent years, the well-established 13C-MFA method based on metabolic and isotopic steady state was extended to INST-MFA (isotopically non-stationary MFA), which is performed in a transient labeling state. INST-MFA offers short-time experiments with a maximal information gain, and can moreover be applied to a wider range of growth conditions or organisms. Some of these conditions are not accessible by conventional methods. This comes at the price of significant methodological complexity involving high-frequency sampling and quenching, precise analysis of many samples and an extraordinary computational effort. This review gives a brief overview of basic principles, experimental workflows, and recent progress in this field. Special emphasis is laid on the trade-off between total effort and information gain, particularly on the suitability of INST-MFA for certain types of biological questions. In order to integrate INST-MFA as a viable method into the toolbox of MFA, some major challenges must be addressed in the coming years. These are discussed in the outlook. Copyright © 2013 Elsevier Ltd. All rights reserved.

  8. Metabolic flux analysis of Saccharomyces cerevisiae in a sealed winemaking fermentation system.

    Science.gov (United States)

    Li, Hua; Su, Jing; Ma, Wen; Guo, Anque; Shan, Zuhua; Wang, Hua

    2015-03-01

    A sealed fermentation (SF) system and an anaerobic fermentation (AF) system (under normal atmospheric pressure conditions) were employed to study the influence of endogenous carbon dioxide (CO2) on the metabolism of Saccharomyces cerevisiae. The results showed that the fermentation stopped when 82.0 g L(-1) glucose was consumed and the endogenously produced CO2: pressure reached to 14.3 MPa in SF system, while the sugar was used up during AF. The total yeast viable count in the end of AF was higher than that of SF. It was also observed that the ethanol yield in AF and SF was similar, the glycerol yield in AF was 1.26 times higher than that in SF, while the succinic acid and acetic acid yields in SF were 24.7 and 26 times higher than that in AF, respectively. Additionally, this work provides a stoichiometric model used for metabolic flux analysis of S. cerevisiae to compare the flux distribution in SF and AF. The results showed that CO2 had an important effect on the pathways of oxaloacetic acid formation from pyruvic acid and ribose-5-phosphate formation from glucose-6-phosphate. However, the pathway of ethanol formation from pyruvic acid (decarboxylation reaction), catalyzed by pyruvate decarboxylase, was insensitive to CO2.

  9. Predicting growth conditions from internal metabolic fluxes in an in-silico model of E. coli.

    Directory of Open Access Journals (Sweden)

    Viswanadham Sridhara

    Full Text Available A widely studied problem in systems biology is to predict bacterial phenotype from growth conditions, using mechanistic models such as flux balance analysis (FBA. However, the inverse prediction of growth conditions from phenotype is rarely considered. Here we develop a computational framework to carry out this inverse prediction on a computational model of bacterial metabolism. We use FBA to calculate bacterial phenotypes from growth conditions in E. coli, and then we assess how accurately we can predict the original growth conditions from the phenotypes. Prediction is carried out via regularized multinomial regression. Our analysis provides several important physiological and statistical insights. First, we show that by analyzing metabolic end products we can consistently predict growth conditions. Second, prediction is reliable even in the presence of small amounts of impurities. Third, flux through a relatively small number of reactions per growth source (∼10 is sufficient for accurate prediction. Fourth, combining the predictions from two separate models, one trained only on carbon sources and one only on nitrogen sources, performs better than models trained to perform joint prediction. Finally, that separate predictions perform better than a more sophisticated joint prediction scheme suggests that carbon and nitrogen utilization pathways, despite jointly affecting cellular growth, may be fairly decoupled in terms of their dependence on specific assortments of molecular precursors.

  10. Hybrid metabolic flux analysis: combining stoichiometric and statistical constraints to model the formation of complex recombinant products

    Directory of Open Access Journals (Sweden)

    Alves Paula M

    2011-02-01

    Full Text Available Abstract Background Stoichiometric models constitute the basic framework for fluxome quantification in the realm of metabolic engineering. A recurrent bottleneck, however, is the establishment of consistent stoichiometric models for the synthesis of recombinant proteins or viruses. Although optimization algorithms for in silico metabolic redesign have been developed in the context of genome-scale stoichiometric models for small molecule production, still rudimentary knowledge of how different cellular levels are regulated and phenotypically expressed prevents their full applicability for complex product optimization. Results A hybrid framework is presented combining classical metabolic flux analysis with projection to latent structures to further link estimated metabolic fluxes with measured productivities. We first explore the functional metabolic decomposition of a baculovirus-producing insect cell line from experimental data, highlighting the TCA cycle and mitochondrial respiration as pathways strongly associated with viral replication. To reduce uncertainty in metabolic target identification, a Monte Carlo sampling method was used to select meaningful associations with the target, from which 66% of the estimated fluxome had to be screened out due to weak correlations and/or high estimation errors. The proposed hybrid model was then validated using a subset of preliminary experiments to pinpoint the same determinant pathways, while predicting the productivity of independent cultures. Conclusions Overall, the results indicate our hybrid metabolic flux analysis framework is an advantageous tool for metabolic identification and quantification in incomplete or ill-defined metabolic networks. As experimental and computational solutions for constructing comprehensive global cellular models are in development, the contribution of hybrid metabolic flux analysis should constitute a valuable complement to current computational platforms in bridging the

  11. Metabolic flux analysis of the hydrogen production potential in Synechocystis sp. PCC6803

    Energy Technology Data Exchange (ETDEWEB)

    Navarro, E. [Departamento de Lenguajes y Ciencias de la Computacion, Campus de Teatrinos, Universidad de Malaga, 29071 Malaga (Spain); Montagud, A.; Fernandez de Cordoba, P.; Urchueguia, J.F. [Instituto Universitario de Matematica Pura y Aplicada, Universidad Politecnica de Valencia, Camino de Vera 14, 46022 Valencia (Spain)

    2009-11-15

    Hydrogen is a promising energy vector; however, finding methods to produce it from renewable sources is essential to allow its wide-scale use. In that line, biological hydrogen production, although it is considered as a possible alternative, requires substantial improvements to overcome its present low yields. In that direction, genetic manipulation probably will play a central role and from that point of view metabolic flux analysis (MFA) constitutes an important tool to guide a priori most suitable genetic modifications oriented to a hydrogen yield increase. In this work MFA has been applied to analyze hydrogen photoproduction of Synechocystis sp. PCC6803. Flux analysis was carried out based on literature data and several basic fluxes were estimated in different growing conditions of the system. From this analysis, an upper limit for hydrogen photoproduction has been determined indicating a wide margin for improvement. MFA was also used to find a feasible operating space for hydrogen production, which avoids oxygen inhibition, one of the most important limitations to make hydrogen production cost effective. In addition, a set of biotechnological strategies are proposed that would be consistent with the performed mathematical analysis. (author)

  12. Systems Biology Approach to Bioremediation of Nitroaromatics: Constraint-Based Analysis of 2,4,6-Trinitrotoluene Biotransformation by Escherichia coli

    Directory of Open Access Journals (Sweden)

    Maryam Iman

    2017-08-01

    Full Text Available Microbial remediation of nitroaromatic compounds (NACs is a promising environmentally friendly and cost-effective approach to the removal of these life-threating agents. Escherichia coli (E. coli has shown remarkable capability for the biotransformation of 2,4,6-trinitro-toluene (TNT. Efforts to develop E. coli as an efficient TNT degrading biocatalyst will benefit from holistic flux-level description of interactions between multiple TNT transforming pathways operating in the strain. To gain such an insight, we extended the genome-scale constraint-based model of E. coli to account for a curated version of major TNT transformation pathways known or evidently hypothesized to be active in E. coli in present of TNT. Using constraint-based analysis (CBA methods, we then performed several series of in silico experiments to elucidate the contribution of these pathways individually or in combination to the E. coli TNT transformation capacity. Results of our analyses were validated by replicating several experimentally observed TNT degradation phenotypes in E. coli cultures. We further used the extended model to explore the influence of process parameters, including aeration regime, TNT concentration, cell density, and carbon source on TNT degradation efficiency. We also conducted an in silico metabolic engineering study to design a series of E. coli mutants capable of degrading TNT at higher yield compared with the wild-type strain. Our study, therefore, extends the application of CBA to bioremediation of nitroaromatics and demonstrates the usefulness of this approach to inform bioremediation research.

  13. Genome-based metabolic mapping and 13C flux analysis reveal systematic properties of an oleaginous microalga Chlorella protothecoides.

    Science.gov (United States)

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

    2015-02-01

    Integrated and genome-based flux balance analysis, metabolomics, and (13)C-label profiling of phototrophic and heterotrophic metabolism in Chlorella protothecoides, an oleaginous green alga for biofuel. The green alga Chlorella protothecoides, capable of autotrophic and heterotrophic growth with rapid lipid synthesis, is a promising candidate for biofuel production. Based on the newly available genome knowledge of the alga, we reconstructed the compartmentalized metabolic network consisting of 272 metabolic reactions, 270 enzymes, and 461 encoding genes and simulated the growth in different cultivation conditions with flux balance analysis. Phenotype-phase plane analysis shows conditions achieving theoretical maximum of the biomass and corresponding fatty acid-producing rate for phototrophic cells (the ratio of photon uptake rate to CO2 uptake rate equals 8.4) and heterotrophic ones (the glucose uptake rate to O2 consumption rate reaches 2.4), respectively. Isotope-assisted liquid chromatography-mass spectrometry/mass spectrometry reveals higher metabolite concentrations in the glycolytic pathway and the tricarboxylic acid cycle in heterotrophic cells compared with autotrophic cells. We also observed enhanced levels of ATP, nicotinamide adenine dinucleotide (phosphate), reduced, acetyl-Coenzyme A, and malonyl-Coenzyme A in heterotrophic cells consistently, consistent with a strong activity of lipid synthesis. To profile the flux map in experimental conditions, we applied nonstationary (13)C metabolic flux analysis as a complementing strategy to flux balance analysis. The result reveals negligible photorespiratory fluxes and a metabolically low active tricarboxylic acid cycle in phototrophic C. protothecoides. In comparison, high throughput of amphibolic reactions and the tricarboxylic acid cycle with no glyoxylate shunt activities were measured for heterotrophic cells. Taken together, the metabolic network modeling assisted by experimental metabolomics and (13)C

  14. Evidence for transketolase-like TKTL1 flux in CHO cells based on parallel labeling experiments and (13)C-metabolic flux analysis.

    Science.gov (United States)

    Ahn, Woo Suk; Crown, Scott B; Antoniewicz, Maciek R

    2016-09-01

    The pentose phosphate pathway (PPP) is a fundamental component of cellular metabolism. It provides precursors for the biosynthesis of nucleotides and contributes to the production of reducing power in the form of NADPH. It has been hypothesized that mammalian cells may contain a hidden reaction in PPP catalyzed by transketolase-like protein 1 (TKTL1) that is closely related to the classical transketolase enzyme; however, until now there has been no direct experimental evidence for this reaction. In this work, we have applied state-of-the-art techniques in (13)C metabolic flux analysis ((13)C-MFA) based on parallel labeling experiments and integrated flux fitting to estimate the TKTL1 flux in CHO cells. We identified a set of three parallel labeling experiments with [1-(13)C]glucose+[4,5,6-(13)C]glucose, [2-(13)C]glucose+[4,5,6-(13)C]glucose, and [3-(13)C]glucose+[4,5,6-(13)C]glucose and developed a new method to measure (13)C-labeling of fructose 6-phosphate by GC-MS that allows intuitive interpretation of mass isotopomer distributions to determine key fluxes in the model, including glycolysis, oxidative PPP, non-oxidative PPP, and the TKTL1 flux. Using these tracers we detected a significant TKTL1 flux in CHO cells at the stationary phase. The flux results suggest that the main function of oxidative PPP in CHO cells at the stationary phase is to fuel the TKTL1 reaction. Overall, this study demonstrates for the first time that carbon atoms can be lost in the PPP, by means other than the oxidative PPP, and that this loss of carbon atoms is consistent with the hypothesized TKTL1 reaction in mammalian cells.

  15. In Silico Constraint-Based Strain Optimization Methods: the Quest for Optimal Cell Factories.

    Science.gov (United States)

    Maia, Paulo; Rocha, Miguel; Rocha, Isabel

    2016-03-01

    Shifting from chemical to biotechnological processes is one of the cornerstones of 21st century industry. The production of a great range of chemicals via biotechnological means is a key challenge on the way toward a bio-based economy. However, this shift is occurring at a pace slower than initially expected. The development of efficient cell factories that allow for competitive production yields is of paramount importance for this leap to happen. Constraint-based models of metabolism, together with in silico strain design algorithms, promise to reveal insights into the best genetic design strategies, a step further toward achieving that goal. In this work, a thorough analysis of the main in silico constraint-based strain design strategies and algorithms is presented, their application in real-world case studies is analyzed, and a path for the future is discussed.

  16. MIRAGE: a functional genomics-based approach for metabolic network model reconstruction and its application to cyanobacteria networks.

    Science.gov (United States)

    Vitkin, Edward; Shlomi, Tomer

    2012-11-29

    Genome-scale metabolic network reconstructions are considered a key step in quantifying the genotype-phenotype relationship. We present a novel gap-filling approach, MetabolIc Reconstruction via functionAl GEnomics (MIRAGE), which identifies missing network reactions by integrating metabolic flux analysis and functional genomics data. MIRAGE's performance is demonstrated on the reconstruction of metabolic network models of E. coli and Synechocystis sp. and validated via existing networks for these species. Then, it is applied to reconstruct genome-scale metabolic network models for 36 sequenced cyanobacteria amenable for constraint-based modeling analysis and specifically for metabolic engineering. The reconstructed network models are supplied via standard SBML files.

  17. The ability of flux balance analysis to predict evolution of central metabolism scales with the initial distance to the optimum.

    Directory of Open Access Journals (Sweden)

    William R Harcombe

    Full Text Available The most powerful genome-scale framework to model metabolism, flux balance analysis (FBA, is an evolutionary optimality model. It hypothesizes selection upon a proposed optimality criterion in order to predict the set of internal fluxes that would maximize fitness. Here we present a direct test of the optimality assumption underlying FBA by comparing the central metabolic fluxes predicted by multiple criteria to changes measurable by a (13C-labeling method for experimentally-evolved strains. We considered datasets for three Escherichia coli evolution experiments that varied in their length, consistency of environment, and initial optimality. For ten populations that were evolved for 50,000 generations in glucose minimal medium, we observed modest changes in relative fluxes that led to small, but significant decreases in optimality and increased the distance to the predicted optimal flux distribution. In contrast, seven populations evolved on the poor substrate lactate for 900 generations collectively became more optimal and had flux distributions that moved toward predictions. For three pairs of central metabolic knockouts evolved on glucose for 600-800 generations, there was a balance between cases where optimality and flux patterns moved toward or away from FBA predictions. Despite this variation in predictability of changes in central metabolism, two generalities emerged. First, improved growth largely derived from evolved increases in the rate of substrate use. Second, FBA predictions bore out well for the two experiments initiated with ancestors with relatively sub-optimal yield, whereas those begun already quite optimal tended to move somewhat away from predictions. These findings suggest that the tradeoff between rate and yield is surprisingly modest. The observed positive correlation between rate and yield when adaptation initiated further from the optimum resulted in the ability of FBA to use stoichiometric constraints to predict the

  18. A holistic view of dietary carbohydrate utilization in lobster: digestion, postprandial nutrient flux, and metabolism.

    Directory of Open Access Journals (Sweden)

    Leandro Rodríguez-Viera

    Full Text Available Crustaceans exhibit a remarkable variation in their feeding habits and food type, but most knowledge on carbohydrate digestion and utilization in this group has come from research on few species. The aim of this study was to make an integrative analysis of dietary carbohydrate utilization in the spiny lobster Panulirus argus. We used complementary methodologies such as different assessments of digestibility, activity measurements of digestive and metabolic enzymes, and post-feeding flux of nutrients and metabolites. Several carbohydrates were well digested by the lobster, but maize starch was less digestible than all other starches studied, and its inclusion in diet affected protein digestibility. Most intense hydrolysis of carbohydrates in the gastric chamber of lobster occurred between 2-6 h after ingestion and afterwards free glucose increased in hemolymph. The inclusion of wheat in diet produced a slow clearance of glucose from the gastric fluid and a gradual increase in hemolymph glucose. More intense hydrolysis of protein in the gastric chamber occurred 6-12 h after ingestion and then amino acids tended to increase in hemolymph. Triglyceride concentration in hemolymph rose earlier in wheat-fed lobsters than in lobsters fed other carbohydrates, but it decreased the most 24 h later. Analyses of metabolite levels and activities of different metabolic enzymes revealed that intermolt lobsters had a low capacity to store and use glycogen, although it was slightly higher in wheat-fed lobsters. Lobsters fed maize and rice diets increased amino acid catabolism, while wheat-fed lobsters exhibited higher utilization of fatty acids. Multivariate analysis confirmed that the type of carbohydrate ingested had a profound effect on overall metabolism. Although we found no evidence of a protein-sparing effect of dietary carbohydrate, differences in the kinetics of their digestion and absorption impacted lobster metabolism determining the fate of other

  19. A holistic view of dietary carbohydrate utilization in lobster: digestion, postprandial nutrient flux, and metabolism.

    Science.gov (United States)

    Rodríguez-Viera, Leandro; Perera, Erick; Casuso, Antonio; Perdomo-Morales, Rolando; Gutierrez, Odilia; Scull, Idania; Carrillo, Olimpia; Martos-Sitcha, Juan A; García-Galano, Tsai; Mancera, Juan Miguel

    2014-01-01

    Crustaceans exhibit a remarkable variation in their feeding habits and food type, but most knowledge on carbohydrate digestion and utilization in this group has come from research on few species. The aim of this study was to make an integrative analysis of dietary carbohydrate utilization in the spiny lobster Panulirus argus. We used complementary methodologies such as different assessments of digestibility, activity measurements of digestive and metabolic enzymes, and post-feeding flux of nutrients and metabolites. Several carbohydrates were well digested by the lobster, but maize starch was less digestible than all other starches studied, and its inclusion in diet affected protein digestibility. Most intense hydrolysis of carbohydrates in the gastric chamber of lobster occurred between 2-6 h after ingestion and afterwards free glucose increased in hemolymph. The inclusion of wheat in diet produced a slow clearance of glucose from the gastric fluid and a gradual increase in hemolymph glucose. More intense hydrolysis of protein in the gastric chamber occurred 6-12 h after ingestion and then amino acids tended to increase in hemolymph. Triglyceride concentration in hemolymph rose earlier in wheat-fed lobsters than in lobsters fed other carbohydrates, but it decreased the most 24 h later. Analyses of metabolite levels and activities of different metabolic enzymes revealed that intermolt lobsters had a low capacity to store and use glycogen, although it was slightly higher in wheat-fed lobsters. Lobsters fed maize and rice diets increased amino acid catabolism, while wheat-fed lobsters exhibited higher utilization of fatty acids. Multivariate analysis confirmed that the type of carbohydrate ingested had a profound effect on overall metabolism. Although we found no evidence of a protein-sparing effect of dietary carbohydrate, differences in the kinetics of their digestion and absorption impacted lobster metabolism determining the fate of other nutrients.

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

    Science.gov (United States)

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

    2016-11-01

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

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

    Directory of Open Access Journals (Sweden)

    Fan Chen

    2017-06-01

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

  2. Elementary Flux Mode Analysis Revealed Cyclization Pathway as a Powerful Way for NADPH Regeneration of Central Carbon Metabolism.

    Directory of Open Access Journals (Sweden)

    Bin Rui

    Full Text Available NADPH regeneration capacity is attracting growing research attention due to its important role in resisting oxidative stress. Besides, NADPH availability has been regarded as a limiting factor in production of industrially valuable compounds. The central carbon metabolism carries the carbon skeleton flux supporting the operation of NADPH-regenerating enzyme and offers flexibility in coping with NADPH demand for varied intracellular environment. To acquire an insightful understanding of its NADPH regeneration capacity, the elementary mode method was employed to compute all elementary flux modes (EFMs of a network representative of central carbon metabolism. Based on the metabolic flux distributions of these modes, a cluster analysis of EFMs with high NADPH regeneration rate was conducted using the self-organizing map clustering algorithm. The clustering results were used to study the relationship between the flux of total NADPH regeneration and the flux in each NADPH producing enzyme. The results identified several reaction combinations supporting high NADPH regeneration, which are proven to be feasible in cells via thermodynamic analysis and coincident with a great deal of previous experimental report. Meanwhile, the reaction combinations showed some common characteristics: there were one or two decarboxylation oxidation reactions in the combinations that produced NADPH and the combination constitution included certain gluconeogenesis pathways. These findings suggested cyclization pathways as a powerful way for NADPH regeneration capacity of bacterial central carbon metabolism.

  3. 13C代谢通量分析%Advances in 13C Metabolic Flux Analysis

    Institute of Scientific and Technical Information of China (English)

    李晓静; 陈涛; 陈洵; 李祥高; 赵学明

    2006-01-01

    代谢通量分析(metabolic flux analysis,MFA)是通过确定代谢网络中代谢流分布来表征细胞代谢状态的强有力的工具.鉴于计量学代谢通量分析在处理复杂代谢网络时表现出的局限性,发展了以13C标记实验为基础的13C MFA.本文介绍了13C MFA的原理与方法,总结和评述了13C MFA在实验与数据分析方面的最新进展以及MFA在功能基因组研究中的重要地位,同时对代谢通量分析的发展前景进行了展望.

  4. A dynamic metabolic flux balance based model of fed-batch fermentation of Bordetella pertussis.

    Science.gov (United States)

    Budman, Hector; Patel, Nilesh; Tamer, Melih; Al-Gherwi, Walid

    2013-01-01

    A mathematical model based on a dynamic metabolic flux balance (DMFB) is developed for a process of fed-batch fermentation of Bordetella pertussis. The model is based on the maximization of growth rate at each time interval subject to stoichiometric constraints. The model is calibrated and verified with experimental data obtained in two different bioreactor experimental systems. It was found that the model calibration was mostly sensitive to the consumption or production rates of tyrosine and, for high supplementation rates, to the consumption rate of glutamate. Following this calibration the model correctly predicts biomass and by-products concentrations for different supplementation rates. Comparisons of model predictions to oxygen uptake and carbon emission rates measurements indicate that the TCA cycle is fully functional.

  5. An ensemble approach to the study of the emergence of metabolic and proliferative disorders via Flux Balance Analysis

    Directory of Open Access Journals (Sweden)

    Giancarlo Mauri

    2013-09-01

    Full Text Available An extensive rewiring of cell metabolism supports enhanced proliferation in cancer cells. We propose a systems level approach to describe this phenomenon based on Flux Balance Analysis (FBA. The approach does not explicit a cell biomass formation reaction to be maximized, but takes into account an ensemble of alternative flux distributions that match the cancer metabolic rewiring (CMR phenotype description. The underlying concept is that the analysis the common/distinguishing properties of the ensemble can provide indications on how CMR is achieved and sustained and thus on how it can be controlled.

  6. Regioisomeric SCFA attachment to hexosamines separates metabolic flux from cytotoxicity and MUC1 suppression.

    Science.gov (United States)

    Aich, Udayanath; Campbell, Christopher T; Elmouelhi, Noha; Weier, Christopher A; Sampathkumar, S-Gopalan; Choi, Sean S; Yarema, Kevin J

    2008-04-18

    Chemical biology studies, exemplified by metabolic glycoengineering experiments that employ short chain fatty acid (SCFA)-hexosamine monosaccharide hybrid molecules, often suffer from off-target effects. Here we demonstrate that systematic structure-activity relationship (SAR) studies can deconvolute multiple biological activities of SCFA-hexosamine analogues by demonstrating that triacylated monosaccharides, including both n-butyrate- and acetate-modified ManNAc analogues, had dramatically different activities depending on whether the free hydroxyl group was at the C1 or C6 position. The C1-OH (hemiacetal) analogues enhanced growth inhibition in MDA-MB-231 human breast cancer cells and suppressed expression of MUC1, which are attractive properties for an anticancer agent. By contrast, C6-OH analogues supported high metabolic flux into the sialic acid pathway with negligible growth inhibition or toxicity, which are desirable properties for glycan labeling in healthy cells. Importantly, these SAR were general, applying to other hexosamines ( e.g., GlcNAc) and non-natural sugar "scaffolds" ( e.g., ManNLev). From a practical standpoint, the ability to separate toxicity from flux will facilitate the use of MOE analogues for cancer treatment and glycomics applications, respectively. Mechanistically, these findings overturn the premise that the bioactivities of SCFA-monosaccharide hybrid molecules result from their hydrolysis products ( e.g., n-butyrate, which acts as a histone deacetylase inhibitor, and ManNAc, which activates sialic acid biosynthesis); instead the SAR establish that inherent properties of partially acylated hexosamines supersede the cellular responses supported by either the acyl or monosaccharide moieties.

  7. Designer labels for plant metabolism: statistical design of isotope labeling experiments for improved quantification of flux in complex plant metabolic networks.

    Science.gov (United States)

    Nargund, Shilpa; Sriram, Ganesh

    2013-01-27

    Metabolic fluxes are powerful indicators of cell physiology and can be estimated by isotope-assisted metabolic flux analysis (MFA). The complexity of the compartmented metabolic networks of plants has constrained the application of isotope-assisted MFA to them, principally because of poor identifiability of fluxes from the measured isotope labeling patterns. However, flux identifiability can be significantly improved by a priori design of isotope labeling experiments (ILEs). This computational design involves evaluating the effect of different isotope label and isotopomer measurement combinations on flux identifiability, and thereby identifying optimal labels and measurements toward evaluating the fluxes of interest with the highest confidence. This article reports ILE designs for two major, compartmented plant metabolic pathways - the pentose phosphate pathway (PPP) and γ-aminobutyric acid (GABA) shunt. Together, these pathways represent common motifs in plant metabolism including duplication of pathways in different subcellular compartments, reversible reactions and cyclic carbon flow. To compare various ILE designs, we employed statistical A- and D-optimality criteria. Our computations showed that 1,2-(13)C Glc is a powerful and robust label for the plant PPPs, given currently popular isotopomer measurement techniques (single quadrupole mass spectrometry [MS] and 2-D nuclear magnetic resonance [NMR]). Further analysis revealed that this label can estimate several PPP fluxes better than the popular label 1-(13)C Glc. Furthermore, the concurrent measurement of the isotopomers of hexose and pentose moieties synthesized exclusively in the cytosol or the plastid compartments (measurable through intracellular glucose or sucrose, starch, RNA ribose and histidine) considerably improves the identifiability of PPP fluxes in the individual compartments. Additionally, MS-derived isotopomer measurements outperform NMR-derived measurements in identifying PPP fluxes. The

  8. Estimating biological elementary flux modes that decompose a flux distribution by the minimal branching property

    DEFF Research Database (Denmark)

    Chan, Siu Hung Joshua; Solem, Christian; Jensen, Peter Ruhdal;

    2014-01-01

    MOTIVATION: Elementary flux mode (EFM) is a useful tool in constraint-based modeling of metabolic networks. The property that every flux distribution can be decomposed as a weighted sum of EFMs allows certain applications of EFMs to studying flux distributions. The existence of biologically...... infeasible EFMs and the non-uniqueness of the decomposition, however, undermine the applicability of such methods. Efforts have been made to find biologically feasible EFMs by incorporating information from transcriptional regulation and thermodynamics. Yet, no attempt has been made to distinguish...... reduced the solution space in which the decomposition is often unique. An experimental flux distribution from a previous study on mouse cardiomyocyte was decomposed using MBD. Comparison with decomposition by a minimum number of EFMs showed that MBD found EFMs more consistent with established biological...

  9. Combining rational metabolic engineering and flux optimization strategies for efficient production of fumaric acid.

    Science.gov (United States)

    Song, Chan Woo; Lee, Sang Yup

    2015-10-01

    Fumaric acid is an important C4-dicarboxylic acid widely used in chemical, food, and pharmaceutical industries. Rational metabolic engineering together with flux optimization were performed for the development of an Escherichia coli strain capable of efficiently producing fumaric acid. The initial engineered strain, CWF4N overexpressing phosphoenolpyruvate carboxylase (PPC), produced 5.30 g/L of fumaric acid. Optimization of PPC flux by examining 24 types of synthetic PPC expression vectors further increased the titer up to 5.72 g/L with a yield of 0.432 g/g·glucose. Overexpression of the succinate dehydrogenase complex (sdhCDAB) led to an increase in carbon yield up to 0.493 g/g·glucose. Based on this mutant strain, citrate synthase (CS) was combinatorially overexpressed and balanced with PPC using 48 types of synthetic expression vectors. As a result, 6.24 g/L of fumaric acid was produced with a yield of 0.500 g/g·glucose. Fed-batch culture of this final strain allowed production of 25.5 g/L of fumaric acid with a yield of 0.366 g/g·glucose. Deletion of the aspA gene encoding aspartase and supplementation of aspartic acid further increased the fumaric acid titer to 35.1 g/L with a yield of 0.490 g/g·glucose.

  10. Phosphoketolase pathway for xylose catabolism in Clostridium acetobutylicum revealed by 13C metabolic flux analysis.

    Science.gov (United States)

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

    2012-10-01

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

  11. Electroanalysis of metabolic flux from single cells in simple picoliter-volume microsystems.

    Science.gov (United States)

    Yasukawa, Tomoyuki; Glidle, Andrew; Cooper, Jonathan M; Matsue, Tomokazu

    2002-10-01

    A picoliter-volume electrochemical analytical chamber has been developed for detecting the metabolic flux resulting from the stress responses of a single plant cell. Electrochemical cells, with volumes as small as 100 pL, were fabricated by controlled electrochemical dissolution of a gold wire sealed in glass (the back-etching of the metal realizing an ultralow-volume titer chamber). In the first instance, the electrode contained within the chamber was characterized by the microinjection of standard aliquots of either ascorbic acid or hydrogen peroxide. In all cases, experimental currents obtained correlated well with theoretical calculations. Subsequently, single plant cells were micromanipulated into the chambers and were exposed to amounts of the detergent SDS (which permeabilized the cell membrane and released the intracellular contents). The flux of metabolite released from a single cell was estimated by using electrochemical-linked assays based upon the enzymes catalase, ascorbate oxidase, and horseradish peroxidase (in each case), in the presence of a mediator. In so doing, we investigated the activity of the cellular protection mechanisms through the determination of peroxides, while the individual cell was "stressed". The technique was found to provide a reliable and reproducible method for making single-cell measurements, using fabrication procedures that are both simple and do not require photolithographic methods.

  12. Pyruvate modifies metabolic flux and nutrient sensing during extracorporeal membrane oxygenation in an immature swine model

    Energy Technology Data Exchange (ETDEWEB)

    Ledee, Dolena R.; Kajimoto, Masaki; O' Kelly-Priddy, Colleen M.; Olson, Aaron; Isern, Nancy G.; Robillard Frayne, Isabelle; Des Rosiers, Christine; Portman, Michael A.

    2015-07-01

    Extracorporeal membrane oxygenation (ECMO) provides mechanical circulatory support for infants and children with postoperative cardiopulmonary failure. Nutritional support is mandatory during ECMO, although specific actions for substrates on the heart have not been delineated. Prior work shows that enhancing pyruvate oxidation promotes successful weaning from ECMO. Accordingly, we closely examined the role of prolonged systemic pyruvate supplementation in modifying metabolic parameters during the unique conditions of ventricular unloading provided by ECMO. Twelve male mixed breed Yorkshire piglets (age 30-49 days) received systemic infusion of either normal saline (Group C) or pyruvate (Group P) during ECMO for 8 hours. Over the final hour piglets received [2-13C] pyruvate, and [13C6]-L-leucine, as an indicator for oxidation and protein synthesis. A significant increase in lactate and pyruvate concentrations occurred, along with an increase in the absolute concentration of all measured CAC intermediates. Group P showed greater anaplerotic flux through pyruvate carboxylation although pyruvate oxidation relative to citrate synthase flux was similar to Group C. The groups demonstrated similar leucine fractional contributions to acetyl-CoA and fractional protein synthesis rates. Pyruvate also promoted an increase in the phosphorylation state of several nutrient sensitive enzymes, such as AMPK and ACC, and promoted O-GlcNAcylation through the hexosamine biosynthetic pathway (HBP). In conclusion, prolonged pyruvate supplementation during ECMO modified anaplerotic pyruvate flux and elicited changes in important nutrient and energy sensitive pathways, while preserving protein synthesis. Therefore, the observed results support the further study of nutritional supplementation and its downstream effects on cardiac adaptation during ventricular unloading.

  13. Metabolic engineering and flux analysis of Corynebacterium glutamicum for L-serine production.

    Science.gov (United States)

    Lai, Shujuan; Zhang, Yun; Liu, Shuwen; Liang, Yong; Shang, Xiuling; Chai, Xin; Wen, Tingyi

    2012-04-01

    L-Serine plays a critical role as a building block for cell growth, and thus it is difficult to achieve the direct fermentation of L-serine from glucose. In this study, Corynebacterium glutamicum ATCC 13032 was engineered de novo by blocking and attenuating the conversion of L-serine to pyruvate and glycine, releasing the feedback inhibition by L-serine to 3-phosphoglycerate dehydrogenase (PGDH), in combination with the co-expression of 3-phosphoglycerate kinase (PGK) and feedback-resistant PGDH (PGDH(r)). The resulting strain, SER-8, exhibited a lower specific growth rate and significant differences in L-serine levels from Phase I to Phase V as determined for fed-batch fermentation. The intracellular L-serine pool reached (14.22 ± 1.41) μmol g(CDM) (-1), which was higher than glycine pool, contrary to fermentation with the wild-type strain. Furthermore, metabolic flux analysis demonstrated that the over-expression of PGK directed the flux of the pentose phosphate pathway (PPP) towards the glycolysis pathway (EMP), and the expression of PGDH(r) improved the L-serine biosynthesis pathway. In addition, the flux from L-serine to glycine dropped by 24%, indicating that the deletion of the activator GlyR resulted in down-regulation of serine hydroxymethyltransferase (SHMT) expression. Taken together, our findings imply that L-serine pool management is fundamental for sustaining the viability of C. glutamicum, and improvement of C(1) units generation by introducing the glycine cleavage system (GCV) to degrade the excessive glycine is a promising target for L-serine production in C. glutamicum.

  14. Integrating flux balance analysis into kinetic models to decipher the dynamic metabolism of Shewanella oneidensis MR-1.

    Directory of Open Access Journals (Sweden)

    Xueyang Feng

    2012-02-01

    Full Text Available Shewanella oneidensis MR-1 sequentially utilizes lactate and its waste products (pyruvate and acetate during batch culture. To decipher MR-1 metabolism, we integrated genome-scale flux balance analysis (FBA into a multiple-substrate Monod model to perform the dynamic flux balance analysis (dFBA. The dFBA employed a static optimization approach (SOA by dividing the batch time into small intervals (i.e., ∼400 mini-FBAs, then the Monod model provided time-dependent inflow/outflow fluxes to constrain the mini-FBAs to profile the pseudo-steady-state fluxes in each time interval. The mini-FBAs used a dual-objective function (a weighted combination of "maximizing growth rate" and "minimizing overall flux" to capture trade-offs between optimal growth and minimal enzyme usage. By fitting the experimental data, a bi-level optimization of dFBA revealed that the optimal weight in the dual-objective function was time-dependent: the objective function was constant in the early growth stage, while the functional weight of minimal enzyme usage increased significantly when lactate became scarce. The dFBA profiled biologically meaningful dynamic MR-1 metabolisms: 1. the oxidative TCA cycle fluxes increased initially and then decreased in the late growth stage; 2. fluxes in the pentose phosphate pathway and gluconeogenesis were stable in the exponential growth period; and 3. the glyoxylate shunt was up-regulated when acetate became the main carbon source for MR-1 growth.

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

    NARCIS (Netherlands)

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

    2016-01-01

    13C labeling experiments in aerobic glucose limited cultures of Saccharomyces cerevisiae at four different growth rates (0.054; 0.101, 0.207, 0.307 h-1) are used for calculating fluxes that include intracellular cycles (e.g., storage carbohydrate cycles, exchange fluxes with amino acids), which are

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

    NARCIS (Netherlands)

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

    2016-01-01

    13C labeling experiments in aerobic glucose limited cultures of Saccharomyces cerevisiae at four different growth rates (0.054; 0.101, 0.207, 0.307 h−1) are used for calculating fluxes that include intracellular cycles (e.g., storage carbohydrate cycles, exchange fluxes with amino acids), which are

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

    Science.gov (United States)

    Yoshikawa, Katsunori; Toya, Yoshihiro; Shimizu, Hiroshi

    2017-05-01

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

  18. Quantitative Metabolomics and Instationary 13C-Metabolic Flux Analysis Reveals Impact of Recombinant Protein Production on Trehalose and Energy Metabolism in Pichia pastoris

    NARCIS (Netherlands)

    Jorda, J.; Cueto Rojas, H.F.; Carnicer, M.; Wahl, S.A.; Ferrer, P.; Albiol, J.

    2014-01-01

    Pichia pastoris has been recognized as an effective host for recombinant protein production. In this work, we combine metabolomics and instationary 13C metabolic flux analysis (INST 13C-MFA) using GC-MS and LC-MS/MS to evaluate the potential impact of the production of a Rhizopus oryzae lipase (Rol)

  19. Quantitative Metabolomics and Instationary 13C-Metabolic Flux Analysis Reveals Impact of Recombinant Protein Production on Trehalose and Energy Metabolism in Pichia pastoris

    NARCIS (Netherlands)

    Jorda, J.; Cueto Rojas, H.F.; Carnicer, M.; Wahl, S.A.; Ferrer, P.; Albiol, J.

    2014-01-01

    Pichia pastoris has been recognized as an effective host for recombinant protein production. In this work, we combine metabolomics and instationary 13C metabolic flux analysis (INST 13C-MFA) using GC-MS and LC-MS/MS to evaluate the potential impact of the production of a Rhizopus oryzae lipase (Rol)

  20. 13C Metabolic Flux Analysis for Systematic Metabolic Engineering of S. cerevisiae for Overproduction of Fatty Acids

    DEFF Research Database (Denmark)

    Ghosh, Amit; Ando, David; Gin, Jennifer

    2016-01-01

    Efficient redirection of microbial metabolism into the abundant production of desired bioproducts remains non-trivial. Here, we used flux-based modeling approaches to improve yields of fatty acids in Saccharomyces cerevisiae. We combined 13C labeling data with comprehensive genome-scale models to...

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

    Science.gov (United States)

    Wegener, Pam; Covino, Tim; Wohl, Ellen

    2017-06-01

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

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

    Science.gov (United States)

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

    2016-03-01

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

  3. Metabolic flux rearrangement in the amino acid metabolism reduces ammonia stress in the α1-antitrypsin producing human AGE1.HN cell line.

    Science.gov (United States)

    Priesnitz, Christian; Niklas, Jens; Rose, Thomas; Sandig, Volker; Heinzle, Elmar

    2012-03-01

    This study focused on metabolic changes in the neuronal human cell line AGE1.HN upon increased ammonia stress. Batch cultivations of α(1)-antitrypsin (A1AT) producing AGE1.HN cells were carried out in media with initial ammonia concentrations ranging from 0mM to 5mM. Growth, A1AT production, metabolite dynamics and finally metabolic fluxes calculated by metabolite balancing were compared. Growth and A1AT production decreased with increasing ammonia concentration. The maximum A1AT concentration decreased from 0.63g/l to 0.51g/l. Central energy metabolism remained relatively unaffected exhibiting only slightly increased glycolytic flux at high initial ammonia concentration in the medium. However, the amino acid metabolism was significantly changed. Fluxes through transaminases involved in amino acid degradation were reduced concurrently with a reduced uptake of amino acids. On the other hand fluxes through transaminases working in the direction of amino acid synthesis, i.e., alanine and phosphoserine, were increased leading to increased storage of excess nitrogen in extracellular alanine and serine. Glutamate dehydrogenase flux was reversed increasingly fixing free ammonia with increasing ammonia concentration. Urea production additionally observed was associated with arginine uptake by the cells and did not increase at high ammonia stress. It was therefore not used as nitrogen sink to remove excess ammonia. The results indicate that the AGE1.HN cell line can adapt to ammonia concentrations usually present during the cultivation process to a large extent by changing metabolism but with slightly reduced A1AT production and growth.

  4. Tracking the metabolic pulse of plant lipid production with isotopic labeling and flux analyses: Past, present and future

    Science.gov (United States)

    Metabolic networks are comprised of chemical transformations that are the basis of cellular operation and function to sustain life. The molecular rate of transitioning through biochemical pathways (i.e. flux) establishes cellular phenotypes that can be studied in response to genetic or environmental...

  5. Effective Estimation of Dynamic Metabolic Fluxes Using 13C Labeling and Piecewise Affine Approximation: From Theory to Practical Applicability

    NARCIS (Netherlands)

    Schumacher, R.; Wahl, S.A.

    2015-01-01

    The design of microbial production processes relies on rational choices for metabolic engineering of the production host and the process conditions. These require a systematic and quantitative understanding of cellular regulation. Therefore, a novel method for dynamic flux identification using quant

  6. Extraction, purification, methylation and GC-MS analysis of short-chain carboxylic acids for metabolic flux analysis.

    Science.gov (United States)

    Tivendale, Nathan D; Jewett, Erin M; Hegeman, Adrian D; Cohen, Jerry D

    2016-08-15

    Dynamic metabolic flux analysis requires efficient and effective methods for extraction, purification and analysis of a plethora of naturally-occurring compounds. One area of metabolism that would be highly informative to study using metabolic flux analysis is the tricarboxylic acid (TCA) cycle, which consists of short-chain carboxylic acids. Here, we describe a newly-developed method for extraction, purification, derivatization and analysis of short-chain carboxylic acids involved in the TCA cycle. The method consists of snap-freezing the plant material, followed by maceration and a 12-15h extraction at -80 °C. The extracts are then subject to reduction (to stabilize β-keto acids), purified by strong anion exchange solid phase extraction and methylated with methanolic HCl. This method could also be readily adapted to quantify many other short-chain carboxylic acids.

  7. Effects of temperature and UVR on organic matter fluxes and the metabolic activity of Acropora muricata

    Directory of Open Access Journals (Sweden)

    Lucile Courtial

    2017-08-01

    Full Text Available Coral bleaching events are predicted to occur more frequently in the coming decades with global warming. The susceptibility of corals to bleaching during thermal stress episodes depends on many factors, including the magnitude of thermal stress and irradiance. The interactions among these two factors, and in particular with ultra-violet radiation (UVR, the most harmful component of light, are more complex than assumed, and are not yet well understood. This paper explores the individual and combined effects of temperature and UVR on the metabolism of Acropora muricata, one of the most abundant coral species worldwide. Particulate and dissolved organic matter (POM/DOM fluxes and organic matter (OM degradation by the mucus-associated bacteria were also monitored in all conditions. The results show that UVR exposure exacerbated the temperature-induced bleaching, but did not affect OM fluxes, which were only altered by seawater warming. Temperature increase induced a shift from POM release and DOM uptake in healthy corals to POM uptake and DOM release in stressed ones. POM uptake was linked to a significant grazing of pico- and nanoplankton particles during the incubation, to fulfil the energetic requirements of A. muricata in the absence of autotrophy. Finally, OM degradation by mucus-associated bacterial activity was unaffected by UVR exposure, but significantly increased under high temperature. Altogether, our results demonstrate that seawater warming and UVR not only affect coral physiology, but also the way corals interact with the surrounding seawater, with potential consequences for coral reef biogeochemical cycles and food webs.

  8. Flux balance analysis of photoautotrophic metabolism: Uncovering new biological details of subsystems involved in cyanobacterial photosynthesis.

    Science.gov (United States)

    Qian, Xiao; Kim, Min Kyung; Kumaraswamy, G Kenchappa; Agarwal, Ananya; Lun, Desmond S; Dismukes, G Charles

    2017-04-01

    We have constructed and experimentally tested a comprehensive genome-scale model of photoautotrophic growth, denoted iSyp821, for the cyanobacterium Synechococcus sp. PCC 7002. iSyp821 incorporates a variable biomass objective function (vBOF), in which stoichiometries of the major biomass components vary according to light intensity. The vBOF was constrained to fit the measured cellular carbohydrate/protein content under different light intensities. iSyp821 provides rigorous agreement with experimentally measured cell growth rates and inorganic carbon uptake rates as a function of light intensity. iSyp821 predicts two observed metabolic transitions that occur as light intensity increases: 1) from PSI-cyclic to linear electron flow (greater redox energy), and 2) from carbon allocation as proteins (growth) to carbohydrates (energy storage) mode. iSyp821 predicts photoautotrophic carbon flux into 1) a hybrid gluconeogenesis-pentose phosphate (PP) pathway that produces glycogen by an alternative pathway than conventional gluconeogenesis, and 2) the photorespiration pathway to synthesize the essential amino acid, glycine. Quantitative fluxes through both pathways were verified experimentally by following the kinetics of formation of (13)C metabolites from (13)CO2 fixation. iSyp821 was modified to include changes in gene products (enzymes) from experimentally measured transcriptomic data and applied to estimate changes in concentrations of metabolites arising from nutrient stress. Using this strategy, we found that iSyp821 correctly predicts the observed redistribution pattern of carbon products under nitrogen depletion, including decreased rates of CO2 uptake, amino acid synthesis, and increased rates of glycogen and lipid synthesis. Copyright © 2016. Published by Elsevier B.V.

  9. Quantitative Metabolomics and Instationary 13C-Metabolic Flux Analysis Reveals Impact of Recombinant Protein Production on Trehalose and Energy Metabolism in Pichia pastoris.

    Science.gov (United States)

    Jordà, Joel; Rojas, Hugo Cueto; Carnicer, Marc; Wahl, Aljoscha; Ferrer, Pau; Albiol, Joan

    2014-05-05

    Pichia pastoris has been recognized as an effective host for recombinant protein production. In this work, we combine metabolomics and instationary 13C metabolic flux analysis (INST 13C-MFA) using GC-MS and LC-MS/MS to evaluate the potential impact of the production of a Rhizopus oryzae lipase (Rol) on P. pastoris central carbon metabolism. Higher oxygen uptake and CO2 production rates and slightly reduced biomass yield suggest an increased energy demand for the producing strain. This observation is further confirmed by 13C-based metabolic flux analysis. In particular, the flux through the methanol oxidation pathway and the TCA cycle was increased in the Rol-producing strain compared to the reference strain. Next to changes in the flux distribution, significant variations in intracellular metabolite concentrations were observed. Most notably, the pools of trehalose, which is related to cellular stress response, and xylose, which is linked to methanol assimilation, were significantly increased in the recombinant strain.

  10. Quantitative Metabolomics and Instationary 13C-Metabolic Flux Analysis Reveals Impact of Recombinant Protein Production on Trehalose and Energy Metabolism in Pichia pastoris

    Directory of Open Access Journals (Sweden)

    Joel Jordà

    2014-05-01

    Full Text Available Pichia pastoris has been recognized as an effective host for recombinant protein production. In this work, we combine metabolomics and instationary 13C metabolic flux analysis (INST 13C-MFA using GC-MS and LC-MS/MS to evaluate the potential impact of the production of a Rhizopus oryzae lipase (Rol on P. pastoris central carbon metabolism. Higher oxygen uptake and CO2 production rates and slightly reduced biomass yield suggest an increased energy demand for the producing strain. This observation is further confirmed by 13C-based metabolic flux analysis. In particular, the flux through the methanol oxidation pathway and the TCA cycle was increased in the Rol-producing strain compared to the reference strain. Next to changes in the flux distribution, significant variations in intracellular metabolite concentrations were observed. Most notably, the pools of trehalose, which is related to cellular stress response, and xylose, which is linked to methanol assimilation, were significantly increased in the recombinant strain.

  11. Large-Scale Constraint-Based Pattern Mining

    Science.gov (United States)

    Zhu, Feida

    2009-01-01

    We studied the problem of constraint-based pattern mining for three different data formats, item-set, sequence and graph, and focused on mining patterns of large sizes. Colossal patterns in each data formats are studied to discover pruning properties that are useful for direct mining of these patterns. For item-set data, we observed robustness of…

  12. Teaching Database Design with Constraint-Based Tutors

    Science.gov (United States)

    Mitrovic, Antonija; Suraweera, Pramuditha

    2016-01-01

    Design tasks are difficult to teach, due to large, unstructured solution spaces, underspecified problems, non-existent problem solving algorithms and stopping criteria. In this paper, we comment on our approach to develop KERMIT, a constraint-based tutor that taught database design. In later work, we re-implemented KERMIT as EER-Tutor, and…

  13. Semi-automated curation of metabolic models via flux balance analysis: a case study with Mycoplasma gallisepticum.

    Directory of Open Access Journals (Sweden)

    Eddy J Bautista

    Full Text Available Primarily used for metabolic engineering and synthetic biology, genome-scale metabolic modeling shows tremendous potential as a tool for fundamental research and curation of metabolism. Through a novel integration of flux balance analysis and genetic algorithms, a strategy to curate metabolic networks and facilitate identification of metabolic pathways that may not be directly inferable solely from genome annotation was developed. Specifically, metabolites involved in unknown reactions can be determined, and potentially erroneous pathways can be identified. The procedure developed allows for new fundamental insight into metabolism, as well as acting as a semi-automated curation methodology for genome-scale metabolic modeling. To validate the methodology, a genome-scale metabolic model for the bacterium Mycoplasma gallisepticum was created. Several reactions not predicted by the genome annotation were postulated and validated via the literature. The model predicted an average growth rate of 0.358±0.12[Formula: see text], closely matching the experimentally determined growth rate of M. gallisepticum of 0.244±0.03[Formula: see text]. This work presents a powerful algorithm for facilitating the identification and curation of previously known and new metabolic pathways, as well as presenting the first genome-scale reconstruction of M. gallisepticum.

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

    Science.gov (United States)

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

    2016-11-15

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

  15. Optimal design of metabolic flux analysis experiments for anchorage-dependent mammalian cells using a cellular automaton model.

    Science.gov (United States)

    Meadows, Adam L; Roy, Siddhartha; Clark, Douglas S; Blanch, Harvey W

    2007-09-01

    Metabolic flux analysis (MFA) is widely used to quantify metabolic pathway activity. Typical applications involve isotopically labeled substrates, which require both metabolic and isotopic steady states for simplified data analysis. For bacterial systems, these steady states are readily achieved in chemostat cultures. However, mammalian cells are often anchorage dependent and experiments are typically conducted in batch or fed-batch systems, such as tissue culture dishes or microcarrier-containing bioreactors. Surface adherence may cause deviations from exponential growth, resulting in metabolically heterogeneous populations and a varying number of cellular "nearest neighbors" that may affect the observed metabolism. Here, we discuss different growth models suitable for deconvoluting these effects and their application to the design and optimization of MFA experiments employing surface-adherent mammalian cells. We describe a stochastic two-dimensional (2D) cellular automaton model, with empirical descriptions of cell number and non-growing cell fraction, suitable for easy application to most anchorage-dependent mammalian cell cultures. Model utility was verified by studying the impact of contact inhibition on the growth rate, specific extracellular flux rates, and isotopic labeling in lactate for MCF7 cells, a commonly studied breast cancer cell line. The model successfully defined the time over which exponential growth and a metabolically homogeneous growing cell population could be assumed. The cellular automaton model developed is shown to be a useful tool in designing optimal MFA experiments.

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

    Science.gov (United States)

    Wittmann, Christoph; Heinzle, Elmar

    2002-12-01

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

  17. Improvement of glucaric acid production in E. coli via dynamic control of metabolic fluxes

    Directory of Open Access Journals (Sweden)

    Irene M. Brockman Reizman

    2015-12-01

    Full Text Available D-glucaric acid can be used as a building block for biopolymers as well as in the formulation of detergents and corrosion inhibitors. A biosynthetic route for production in Escherichia coli has been developed (Moon et al., 2009, but previous work with the glucaric acid pathway has indicated that competition with endogenous metabolism may limit carbon flux into the pathway. Our group has recently developed an E. coli strain where phosphofructokinase (Pfk activity can be dynamically controlled and demonstrated its use for improving yields and titers of the glucaric acid precursor myo-inositol on glucose minimal medium. In this work, we have explored the further applicability of this strain for glucaric acid production in a supplemented medium more relevant for scale-up studies, both under batch conditions and with glucose feeding via in situ enzymatic starch hydrolysis. It was found that glucaric acid titers could be improved by up to 42% with appropriately timed knockdown of Pfk activity during glucose feeding. The glucose feeding protocol could also be used for reduction of acetate production in the wild type and modified E. coli strains.

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

    Science.gov (United States)

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

    2013-12-01

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

  19. Thermodynamics-based Metabolite Sensitivity Analysis in metabolic networks.

    Science.gov (United States)

    Kiparissides, A; Hatzimanikatis, V

    2017-01-01

    The increasing availability of large metabolomics datasets enhances the need for computational methodologies that can organize the data in a way that can lead to the inference of meaningful relationships. Knowledge of the metabolic state of a cell and how it responds to various stimuli and extracellular conditions can offer significant insight in the regulatory functions and how to manipulate them. Constraint based methods, such as Flux Balance Analysis (FBA) and Thermodynamics-based flux analysis (TFA), are commonly used to estimate the flow of metabolites through genome-wide metabolic networks, making it possible to identify the ranges of flux values that are consistent with the studied physiological and thermodynamic conditions. However, unless key intracellular fluxes and metabolite concentrations are known, constraint-based models lead to underdetermined problem formulations. This lack of information propagates as uncertainty in the estimation of fluxes and basic reaction properties such as the determination of reaction directionalities. Therefore, knowledge of which metabolites, if measured, would contribute the most to reducing this uncertainty can significantly improve our ability to define the internal state of the cell. In the present work we combine constraint based modeling, Design of Experiments (DoE) and Global Sensitivity Analysis (GSA) into the Thermodynamics-based Metabolite Sensitivity Analysis (TMSA) method. TMSA ranks metabolites comprising a metabolic network based on their ability to constrain the gamut of possible solutions to a limited, thermodynamically consistent set of internal states. TMSA is modular and can be applied to a single reaction, a metabolic pathway or an entire metabolic network. This is, to our knowledge, the first attempt to use metabolic modeling in order to provide a significance ranking of metabolites to guide experimental measurements.

  20. A proof for loop-law constraints in stoichiometric metabolic networks

    Directory of Open Access Journals (Sweden)

    Noor Elad

    2012-11-01

    Full Text Available Abstract Background Constraint-based modeling is increasingly employed for metabolic network analysis. Its underlying assumption is that natural metabolic phenotypes can be predicted by adding physicochemical constraints to remove unrealistic metabolic flux solutions. The loopless-COBRA approach provides an additional constraint that eliminates thermodynamically infeasible internal cycles (or loops from the space of solutions. This allows the prediction of flux solutions that are more consistent with experimental data. However, it is not clear if this approach over-constrains the models by removing non-loop solutions as well. Results Here we apply Gordan’s theorem from linear algebra to prove for the first time that the constraints added in loopless-COBRA do not over-constrain the problem beyond the elimination of the loops themselves. Conclusions The loopless-COBRA constraints can be reliably applied. Furthermore, this proof may be adapted to evaluate the theoretical soundness for other methods in constraint-based modeling.

  1. Flux balance analysis reveals acetate metabolism modulates cyclic electron flow and alternative glycolytic pathways in Chlamydomonas reinhardtii

    Directory of Open Access Journals (Sweden)

    Stephen Philip Chapman

    2015-06-01

    Full Text Available Cells of the green alga Chlamydomonas reinhardtii cultured in the presence of acetate perform mixotrophic growth, involving both photosynthesis and organic carbon assimilation. Under such conditions, cells exhibit a reduced capacity for photosynthesis but a higher growth rate, compared to phototrophic cultures. Better understanding of the downregulation of photosynthesis would enable more efficient conversion of carbon into valuable products like biofuels. In this study, Flux Balance Analysis (FBA and Flux Variability Analysis (FVA have been used with a genome scale model of C. reinhardtii to examine changes in intracellular flux distribution in order to explain their changing physiology. Additionally, a reaction essentiality analysis was performed to identify which reaction subsets are essential for a given growth condition. Our results suggest that exogenous acetate feeds into a modified tricarboxylic acid cycle, which bypasses the CO2 evolution steps, explaining increases in biomass, consistent with experimental data. In addition, reactions of the oxidative pentose phosphate and glycolysis pathways, inactive under phototrophic conditions, show substantial flux under mixotrophic conditions. Importantly, acetate addition leads to an increased flux through cyclic electron flow (CEF, but results in a repression of CO2 fixation via Rubisco, explaining the down regulation of photosynthesis. However, although CEF enhances growth on acetate, it is not essential – impairment of CEF results in alternative metabolic pathways being increased. We have demonstrated how the reactions of photosynthesis interconnect with carbon metabolism on a global scale, and how systems approaches play a viable tool in understanding complex relationships at the scale of the organism.

  2. Flux balance analysis reveals acetate metabolism modulates cyclic electron flow and alternative glycolytic pathways in Chlamydomonas reinhardtii.

    Science.gov (United States)

    Chapman, Stephen P; Paget, Caroline M; Johnson, Giles N; Schwartz, Jean-Marc

    2015-01-01

    Cells of the green alga Chlamydomonas reinhardtii cultured in the presence of acetate perform mixotrophic growth, involving both photosynthesis and organic carbon assimilation. Under such conditions, cells exhibit a reduced capacity for photosynthesis but a higher growth rate, compared to phototrophic cultures. Better understanding of the down regulation of photosynthesis would enable more efficient conversion of carbon into valuable products like biofuels. In this study, Flux Balance Analysis (FBA) and Flux Variability Analysis (FVA) have been used with a genome scale model of C. reinhardtii to examine changes in intracellular flux distribution in order to explain their changing physiology. Additionally, a reaction essentiality analysis was performed to identify which reaction subsets are essential for a given growth condition. Our results suggest that exogenous acetate feeds into a modified tricarboxylic acid (TCA) cycle, which bypasses the CO2 evolution steps, explaining increases in biomass, consistent with experimental data. In addition, reactions of the oxidative pentose phosphate and glycolysis pathways, inactive under phototrophic conditions, show substantial flux under mixotrophic conditions. Importantly, acetate addition leads to an increased flux through cyclic electron flow (CEF), but results in a repression of CO2 fixation via Rubisco, explaining the down regulation of photosynthesis. However, although CEF enhances growth on acetate, it is not essential-impairment of CEF results in alternative metabolic pathways being increased. We have demonstrated how the reactions of photosynthesis interconnect with carbon metabolism on a global scale, and how systems approaches play a viable tool in understanding complex relationships at the scale of the organism.

  3. Influence of the late winter bloom on migrant zooplankton metabolism and its implications on export fluxes

    Science.gov (United States)

    Putzeys, S.; Yebra, L.; Almeida, C.; Bécognée, P.; Hernández-León, S.

    2011-12-01

    Studies on carbon active fluxes due to diel migrants are scarce and critical for carbon flux models and biogeochemical estimates. We studied the temporal variability and vertical distribution of biomass, indices of feeding and respiration of the zooplanktonic community north off the Canary Islands during the end of the late winter bloom, in order to assess vertical carbon fluxes in this area. Biomass distribution during the day presented two dense layers of organisms at 0-200 m and around 500 m, whereas at night, most of the biomass concentrated in the epipelagic layer. The gut pigment flux (0.05-0.18 mgC·m - 2 ·d - 1 ) represented 0.22% of the estimated passive export flux (POC flux) while potential ingestion represented 3.91% of the POC (1.24-3.40 mgC·m - 2 ·d - 1 ). The active respiratory flux (0.50-1.36 mgC·m - 2 ·d - 1 ) was only 1.57% of the POC flux. The total carbon flux mediated by diel migrants (respiration plus potential ingestion) ranged between 3.37 and 9.22% of the POC flux; which is three-fold higher than calculating ingestion fluxes from gut pigments. Our results suggest that the fluxes by diel migrants play a small role in the downward flux of carbon in the open ocean during the post-bloom period.

  4. (13)C metabolic flux analysis of the extremely thermophilic, fast growing, xylose-utilizing Geobacillus strain LC300.

    Science.gov (United States)

    Cordova, Lauren T; Antoniewicz, Maciek R

    2016-01-01

    Thermophiles are increasingly used as versatile hosts in the biotechnology industry. One of the key advantages of thermophiles is the potential to achieve high rates of feedstock conversion at elevated temperatures. The recently isolated Geobacillus strain LC300 grows extremely fast on xylose, with a doubling time of less than 30 min. In the accompanying paper, the genome of Geobacillus LC300 was sequenced and annotated. In this work, we have experimentally validated the metabolic network model using parallel (13)C-labeling experiments and applied (13)C-metabolic flux analysis to quantify precise metabolic fluxes. Specifically, the complete set of singly labeled xylose tracers, [1-(13)C], [2-(13)C], [3-(13)C], [4-(13)C], and [5-(13)C]xylose, was used for the first time. Isotopic labeling of biomass amino acids was measured by gas chromatography mass spectrometry (GC-MS). Isotopic labeling of carbon dioxide in the off-gas was also measured by an on-line mass spectrometer. The (13)C-labeling data was then rigorously integrated for flux elucidation using the COMPLETE-MFA approach. The results provided important new insights into the metabolism of Geobacillus LC300, its efficient xylose utilization pathways, and the balance between carbon, redox and energy fluxes. The pentose phosphate pathway, glycolysis and TCA cycle were found to be highly active in Geobacillus LC300. The oxidative pentose phosphate pathway was also active and contributed significantly to NADPH production. No transhydrogenase activity was detected. Results from this work provide a solid foundation for future studies of this strain and its metabolic engineering and biotechnological applications.

  5. Quantitative Metabolomics and Instationary 13C-Metabolic Flux Analysis Reveals Impact of Recombinant Protein Production on Trehalose and Energy Metabolism in Pichia pastoris

    OpenAIRE

    Joel Jordà; Hugo Cueto Rojas; Marc Carnicer; Aljoscha Wahl; Pau Ferrer; Joan Albiol

    2014-01-01

    Pichia pastoris has been recognized as an effective host for recombinant protein production. In this work, we combine metabolomics and instationary 13C metabolic flux analysis (INST 13C-MFA) using GC-MS and LC-MS/MS to evaluate the potential impact of the production of a Rhizopus oryzae lipase (Rol) on P. pastoris central carbon metabolism. Higher oxygen uptake and CO2 production rates and slightly reduced biomass yield suggest an increased energy demand for the producing strain. This observa...

  6. Analysis of metabolic flux phenotypes for two Arabidopsis mutants with severe impairment in seed storage lipid synthesis

    Energy Technology Data Exchange (ETDEWEB)

    Lonien, J.; Schwender, J.

    2009-11-01

    Major storage reserves of Arabidopsis (Arabidopsis thaliana) seeds are triacylglycerols (seed oils) and proteins. Seed oil content is severely reduced for the regulatory mutant wrinkled1 (wri1-1; At3g54320) and for a double mutant in two isoforms of plastidic pyruvate kinase (pkp{beta}{sub 1}pkp{alpha}; At5g52920 and At3g22960). Both already biochemically well-characterized mutants were now studied by {sup 13}C metabolic flux analysis of cultured developing embryos based on comparison with their respective genetic wild-type backgrounds. For both mutations, in seeds as well as in cultured embryos, the oil fraction was strongly reduced while the fractions of proteins and free metabolites increased. Flux analysis in cultured embryos revealed changes in nutrient uptakes and fluxes into biomass as well as an increase in tricarboxylic acid cycle activity for both mutations. While in both wild types plastidic pyruvate kinase (PK{sub p}) provides most of the pyruvate for plastidic fatty acid synthesis, the flux through PK{sub p} is reduced in pkp{beta}{sub 1}pkp{alpha} by 43% of the wild-type value. In wri1-1, PK{sub p} flux is even more reduced (by 82%), although the genes PKp{beta}{sub 1} and PKp{alpha} are still expressed. Along a common paradigm of metabolic control theory, it is hypothesized that a large reduction in PK{sub p} enzyme activity in pkp{beta}{sub 1}pkp{alpha} has less effect on PK{sub p} flux than multiple smaller reductions in glycolytic enzymes in wri1-1. In addition, only in the wri1-1 mutant is the large reduction in PK{sub p} flux compensated in part by an increased import of cytosolic pyruvate and by plastidic malic enzyme. No such limited compensatory bypass could be observed in pkp{beta}{sub 1}pkp{alpha}.

  7. A metabolic and body-size scaling framework for parasite within-host abundance, biomass, and energy flux.

    Science.gov (United States)

    Hechinger, Ryan F

    2013-08-01

    Energetics may provide a useful currency for studying the ecology of parasite assemblages within individual hosts. Parasite assemblages may also provide powerful models to study general principles of ecological energetics. Yet there has been little ecological research on parasite-host energetics, probably due to methodological difficulties. However, the scaling relationships of individual metabolic rate with body or cell size and temperature may permit us to tackle the energetics of parasite assemblages in hosts. This article offers the foundations and initial testing of a metabolic theory of ecology (MTE) framework for parasites in hosts. I first provide equations to estimate energetic flux through observed parasite assemblages. I then develop metabolic scaling theory for parasite abundance, energetics, and biomass in individual hosts. In contrast to previous efforts, the theory factors in both host and parasite metabolic scaling, how parasites use host space, and whether energy or space dictates carrying capacity. Empirical tests indicate that host energetic flux can set parasite carrying capacity, which decreases as predicted considering the scaling of host and parasite metabolic rates. The theory and results also highlight that the phenomenon of "energetic equivalence" is not an assumption of MTE but a possible outcome contingent on how species partition resources. Hence, applying MTE to parasites can lend mechanistic, quantitative, predictive insight into the nature of parasitism and can inform general ecological theory.

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

    Science.gov (United States)

    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.

  9. Constraint-based scheduling applying constraint programming to scheduling problems

    CERN Document Server

    Baptiste, Philippe; Nuijten, Wim

    2001-01-01

    Constraint Programming is a problem-solving paradigm that establishes a clear distinction between two pivotal aspects of a problem: (1) a precise definition of the constraints that define the problem to be solved and (2) the algorithms and heuristics enabling the selection of decisions to solve the problem. It is because of these capabilities that Constraint Programming is increasingly being employed as a problem-solving tool to solve scheduling problems. Hence the development of Constraint-Based Scheduling as a field of study. The aim of this book is to provide an overview of the most widely used Constraint-Based Scheduling techniques. Following the principles of Constraint Programming, the book consists of three distinct parts: The first chapter introduces the basic principles of Constraint Programming and provides a model of the constraints that are the most often encountered in scheduling problems. Chapters 2, 3, 4, and 5 are focused on the propagation of resource constraints, which usually are responsibl...

  10. Constraint-Based Partial Evaluation for Imperative Languages

    Institute of Scientific and Technical Information of China (English)

    JIN Ying(金英); JIN Chengzhi(金成植)

    2002-01-01

    Constraint-based partial evaluation (CBPE) is a program optimization technique based on partial evaluation (PE) and constraint solving. Conventional PE only utilizes given parameter values to specialize programs. However, CBPE makes use of not only given values but also the following information: (a) the relationship between input parameters and program variables; (b) logical structure of a program to be evaluated. In this paper, a formal description of CBPE method for imperative languages is presented, and some related problems are discussed.

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

    Energy Technology Data Exchange (ETDEWEB)

    Tang, Yinjie J.; Sapra, Rajat; Joyner, Dominique; Hazen, Terry C.; Myers, Samuel; Reichmuth, David; Blanch, Harvey; Keasling, Jay D.

    2009-01-20

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

  12. Cutting the Gordian Knot: Identifiability of anaplerotic reactions in Corynebacterium glutamicum by means of (13) C-metabolic flux analysis.

    Science.gov (United States)

    Kappelmann, Jannick; Wiechert, Wolfgang; Noack, Stephan

    2016-03-01

    Corynebacterium glutamicum is the major workhorse for the microbial production of several amino and organic acids. As long as these derive from tricarboxylic acid cycle intermediates, the activity of anaplerotic reactions is pivotal for a high biosynthetic yield. To determine single anaplerotic activities (13) C-Metabolic Flux Analysis ((13) C-MFA) has been extensively used for C. glutamicum, however with different network topologies, inconsistent or poorly determined anaplerotic reaction rates. Therefore, in this study we set out to investigate whether a focused isotopomer model of the anaplerotic node can at all admit a unique solution for all fluxes. By analyzing different scenarios of active anaplerotic reactions, we show in full generality that for C. glutamicum only certain anaplerotic deletion mutants allow to uniquely determine the anaplerotic fluxes from (13) C-isotopomer data. We stress that the result of this analysis for different assumptions on active enzymes is directly transferable to other compartment-free organisms. Our results demonstrate that there exist biologically relevant metabolic network topologies for which the flux distribution cannot be inferred by classical (13) C-MFA.

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

    Science.gov (United States)

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

    2014-01-01

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

  14. TMX1 determines cancer cell metabolism as a thiol-based modulator of ER-mitochondria Ca2+ flux.

    Science.gov (United States)

    Raturi, Arun; Gutiérrez, Tomás; Ortiz-Sandoval, Carolina; Ruangkittisakul, Araya; Herrera-Cruz, Maria Sol; Rockley, Jeremy P; Gesson, Kevin; Ourdev, Dimitar; Lou, Phing-How; Lucchinetti, Eliana; Tahbaz, Nasser; Zaugg, Michael; Baksh, Shairaz; Ballanyi, Klaus; Simmen, Thomas

    2016-08-15

    The flux of Ca(2+) from the endoplasmic reticulum (ER) to mitochondria regulates mitochondria metabolism. Within tumor tissue, mitochondria metabolism is frequently repressed, leading to chemotherapy resistance and increased growth of the tumor mass. Therefore, altered ER-mitochondria Ca(2+) flux could be a cancer hallmark, but only a few regulatory proteins of this mechanism are currently known. One candidate is the redox-sensitive oxidoreductase TMX1 that is enriched on the mitochondria-associated membrane (MAM), the site of ER-mitochondria Ca(2+) flux. Our findings demonstrate that cancer cells with low TMX1 exhibit increased ER Ca(2+), accelerated cytosolic Ca(2+) clearance, and reduced Ca(2+) transfer to mitochondria. Thus, low levels of TMX1 reduce ER-mitochondria contacts, shift bioenergetics away from mitochondria, and accelerate tumor growth. For its role in intracellular ER-mitochondria Ca(2+) flux, TMX1 requires its thioredoxin motif and palmitoylation to target to the MAM. As a thiol-based tumor suppressor, TMX1 increases mitochondrial ATP production and apoptosis progression. Copyright © 2016 Raturi et al.

  15. Pathway-selective insulin resistance and metabolic disease: the importance of nutrient flux.

    Science.gov (United States)

    Otero, Yolanda F; Stafford, John M; McGuinness, Owen P

    2014-07-25

    Hepatic glucose and lipid metabolism are altered in metabolic disease (e.g. obesity, metabolic syndrome, and Type 2 diabetes). Insulin-dependent regulation of glucose metabolism is impaired. In contrast, lipogenesis, hypertriglyceridemia, and hepatic steatosis are increased. Because insulin promotes lipogenesis and liver fat accumulation, to explain the elevation in plasma and tissue lipids, investigators have suggested the presence of pathway-selective insulin resistance. In this model, insulin signaling to glucose metabolism is impaired, but insulin signaling to lipid metabolism is intact. We discuss the evidence for the differential regulation of hepatic lipid and glucose metabolism. We suggest that the primary phenotypic driver is altered substrate delivery to the liver, as well as the repartitioning of hepatic nutrient handling. Specific alterations in insulin signaling serve to amplify the alterations in hepatic substrate metabolism. Thus, hyperinsulinemia and its resultant increased signaling may facilitate lipogenesis, but are not the major drivers of the phenotype of pathway-selective insulin resistance.

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

    Science.gov (United States)

    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.

  17. Flux variability scanning based on enforced objective flux for identifying gene amplification targets

    Directory of Open Access Journals (Sweden)

    Park Jong

    2012-08-01

    Full Text Available Abstract Background In order to reduce time and efforts to develop microbial strains with better capability of producing desired bioproducts, genome-scale metabolic simulations have proven useful in identifying gene knockout and amplification targets. Constraints-based flux analysis has successfully been employed for such simulation, but is limited in its ability to properly describe the complex nature of biological systems. Gene knockout simulations are relatively straightforward to implement, simply by constraining the flux values of the target reaction to zero, but the identification of reliable gene amplification targets is rather difficult. Here, we report a new algorithm which incorporates physiological data into a model to improve the model’s prediction capabilities and to capitalize on the relationships between genes and metabolic fluxes. Results We developed an algorithm, flux variability scanning based on enforced objective flux (FVSEOF with grouping reaction (GR constraints, in an effort to identify gene amplification targets by considering reactions that co-carry flux values based on physiological omics data via “GR constraints”. This method scans changes in the variabilities of metabolic fluxes in response to an artificially enforced objective flux of product formation. The gene amplification targets predicted using this method were validated by comparing the predicted effects with the previous experimental results obtained for the production of shikimic acid and putrescine in Escherichia coli. Moreover, new gene amplification targets for further enhancing putrescine production were validated through experiments involving the overexpression of each identified targeted gene under condition-controlled batch cultivation. Conclusions FVSEOF with GR constraints allows identification of gene amplification targets for metabolic engineering of microbial strains in order to enhance the production of desired bioproducts. The algorithm

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

    Science.gov (United States)

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

    2014-07-08

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

  19. Flux balance analysis of genome-scale metabolic model of rice (Oryza sativa): Aiming to increase biomass

    Indian Academy of Sciences (India)

    Rahul Shaw; Sudip Kundu

    2015-10-01

    Due to socio-economic reasons, it is essential to design efficient stress-tolerant, more nutritious, high yielding rice varieties. A systematic understanding of the rice cellular metabolism is essential for this purpose. Here, we analyse a genome-scale metabolic model of rice leaf using Flux Balance Analysis to investigate whether it has potential metabolic flexibility to increase the biosynthesis of any of the biomass components. We initially simulate the metabolic responses under an objective to maximize the biomass components. Using the estimated maximum value of biomass synthesis as a constraint, we further simulate the metabolic responses optimizing the cellular economy. Depending on the physiological conditions of a cell, the transport capacities of intracellular transporters (ICTs) can vary. To mimic this physiological state, we randomly vary the ICTs’ transport capacities and investigate their effects. The results show that the rice leaf has the potential to increase glycine and starch in a wide range depending on the ICTs’ transport capacities. The predicted biosynthesis pathways vary slightly at the two different optimization conditions. With the constraint of biomass composition, the cell also has the metabolic plasticity to fix a wide range of carbon-nitrogen ratio.

  20. Annual benthic metabolism and organic carbon fluxes in a semi-enclosed Mediterranean bay dominated by the macroalgae Caulerpa prolifera.

    Directory of Open Access Journals (Sweden)

    Sergio eRuiz-Halpern

    2014-12-01

    Full Text Available Coastal areas play an important role on carbon cycling. Elucidating the dynamics on the production, transport and fate of organic carbon is relevant to gain a better understanding of the role coastal areas play in the global carbon budget. Here, we assess the metabolic status and associated organic carbon fluxes of a semi-enclosed Mediterranean bay supporting a meadow of Caulerpa prolifera. We test whether the EDOC pool is a significant component of the organic carbon pool and associated fluxes in this ecosystem. The Bay of Portocolom was in net metabolic balance on a yearly basis, but heterotrophic during the summer months. Community respiration (CR was positively correlated to C. prolifera biomass, while net community production (NCP had a negative correlation. The benthic compartment represented, on average, 72.6 ± 5.2 % of CR and 86.8 ± 4.5 % of gross primary production (GPP. Dissolved organic carbon (DOC production peaked in summer and was always positive, with the incubations performed in the dark almost doubling the flux of those performed in the light. Exchangeable dissolved organic carbon (EDOC, however, oscillated between production and uptake, being completely recycled within the system and representing around 14% of the DOC flux. The pools of bottom and surface DOC were high for an oligotrophic environment, and were positively correlated to the pool of EDOC. Thus, despite being in metabolic balance, this ecosystem acted as a conduit for organic carbon (OC, as it is able to export OC to adjacent areas derived from allochtonous inputs during heterotrophic conditions. These inputs likely come from groundwater discharge, human activity in the watershed, delivered to the sediments through the high capacity of C. prolifera to remove particles from the water column, and from the air-water exchange of EDOC, demonstrating that these communities are a major contributor to the cycling of OC in coastal embayments.

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

    Science.gov (United States)

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

    2014-01-01

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

  2. Revealing differences in metabolic flux distributions between a mutant strain and its parent strain Gluconacetobacter xylinus CGMCC 2955.

    Directory of Open Access Journals (Sweden)

    Cheng Zhong

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

  3. Constraint-Based Modeling of Carbon Fixation and the Energetics of Electron Transfer in Geobacter metallireducens

    Energy Technology Data Exchange (ETDEWEB)

    Feist, AM; Nagarajan, H; Rotaru, AE; Tremblay, PL; Zhang, T; Nevin, KP; Lovley, DR; Zengler, K

    2014-04-24

    Geobacter species are of great interest for environmental and biotechnology applications as they can carry out direct electron transfer to insoluble metals or other microorganisms and have the ability to assimilate inorganic carbon. Here, we report on the capability and key enabling metabolic machinery of Geobacter metallireducens GS-15 to carry out CO2 fixation and direct electron transfer to iron. An updated metabolic reconstruction was generated, growth screens on targeted conditions of interest were performed, and constraint-based analysis was utilized to characterize and evaluate critical pathways and reactions in G. metallireducens. The novel capability of G. metallireducens to grow autotrophically with formate and Fe(III) was predicted and subsequently validated in vivo. Additionally, the energetic cost of transferring electrons to an external electron acceptor was determined through analysis of growth experiments carried out using three different electron acceptors (Fe(III), nitrate, and fumarate) by systematically isolating and examining different parts of the electron transport chain. The updated reconstruction will serve as a knowledgebase for understanding and engineering Geobacter and similar species. Author Summary The ability of microorganisms to exchange electrons directly with their environment has large implications for our knowledge of industrial and environmental processes. For decades, it has been known that microbes can use electrodes as electron acceptors in microbial fuel cell settings. Geobacter metallireducens has been one of the model organisms for characterizing microbe-electrode interactions as well as environmental processes such as bioremediation. Here, we significantly expand the knowledge of metabolism and energetics of this model organism by employing constraint-based metabolic modeling. Through this analysis, we build the metabolic pathways necessary for carbon fixation, a desirable property for industrial chemical production. We

  4. Metabolic rates of ATP transfer through creatine kinase (CK Flux) predict clinical heart failure events and death.

    Science.gov (United States)

    Bottomley, Paul A; Panjrath, Gurusher S; Lai, Shenghan; Hirsch, Glenn A; Wu, Katherine; Najjar, Samer S; Steinberg, Angela; Gerstenblith, Gary; Weiss, Robert G

    2013-12-11

    Morbidity and mortality from heart failure (HF) are high, and current risk stratification approaches for predicting HF progression are imperfect. Adenosine triphosphate (ATP) is required for normal cardiac contraction, and abnormalities in creatine kinase (CK) energy metabolism, the primary myocardial energy reserve reaction, have been observed in experimental and clinical HF. However, the prognostic value of abnormalities in ATP production rates through CK in human HF has not been investigated. Fifty-eight HF patients with nonischemic cardiomyopathy underwent ³¹P magnetic resonance spectroscopy (MRS) to quantify cardiac high-energy phosphates and the rate of ATP synthesis through CK (CK flux) and were prospectively followed for a median of 4.7 years. Multiple-event analysis (MEA) was performed for HF-related events including all-cause and cardiac death, HF hospitalization, cardiac transplantation, and ventricular-assist device placement. Among baseline demographic, clinical, and metabolic parameters, MEA identified four independent predictors of HF events: New York Heart Association (NYHA) class, left ventricular ejection fraction (LVEF), African-American race, and CK flux. Reduced myocardial CK flux was a significant predictor of HF outcomes, even after correction for NYHA class, LVEF, and race. For each increase in CK flux of 1 μmol g⁻¹ s⁻¹, risk of HF-related composite outcomes decreased by 32 to 39%. These findings suggest that reduced CK flux may be a potential HF treatment target. Newer imaging strategies, including noninvasive ³¹P MRS that detect altered ATP kinetics, could thus complement risk stratification in HF and add value in conditions involving other tissues with high energy demands, including skeletal muscle and brain.

  5. Advances in the integration of transcriptional regulatory information into genome-scale metabolic models.

    Science.gov (United States)

    Vivek-Ananth, R P; Samal, Areejit

    2016-09-01

    A major goal of systems biology is to build predictive computational models of cellular metabolism. Availability of complete genome sequences and wealth of legacy biochemical information has led to the reconstruction of genome-scale metabolic networks in the last 15 years for several organisms across the three domains of life. Due to paucity of information on kinetic parameters associated with metabolic reactions, the constraint-based modelling approach, flux balance analysis (FBA), has proved to be a vital alternative to investigate the capabilities of reconstructed metabolic networks. In parallel, advent of high-throughput technologies has led to the generation of massive amounts of omics data on transcriptional regulation comprising mRNA transcript levels and genome-wide binding profile of transcriptional regulators. A frontier area in metabolic systems biology has been the development of methods to integrate the available transcriptional regulatory information into constraint-based models of reconstructed metabolic networks in order to increase the predictive capabilities of computational models and understand the regulation of cellular metabolism. Here, we review the existing methods to integrate transcriptional regulatory information into constraint-based models of metabolic networks.

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

    Science.gov (United States)

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

    2017-01-01

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

  7. Metabolic flux analysis of a phenol producing mutant of Pseudomonas putida S12: Verification and complementation of hypotheses derived from transcriptomics

    NARCIS (Netherlands)

    Wierckx, N.; Ruijssenaars, H.J.; Winde, J.H.de; Schmid, A.; Blank, L.M.

    2009-01-01

    The physiological effects of genetic and transcriptional changes observed in a phenol producing mutant of the solvent-tolerant Pseudomonas putida S12 were assessed with metabolic flux analysis. The upregulation of a malate/lactate dehydrogenase encoding gene could be connected to a flux increase fro

  8. Carbon-flux distribution within Streptomyces coelicolor metabolism: a comparison between the actinorhodin-producing strain M145 and its non-producing derivative M1146.

    Directory of Open Access Journals (Sweden)

    Fabien Coze

    Full Text Available Metabolic Flux Analysis is now viewed as essential to elucidate the metabolic pattern of cells and to design appropriate genetic engineering strategies to improve strain performance and production processes. Here, we investigated carbon flux distribution in two Streptomyces coelicolor A3 (2 strains: the wild type M145 and its derivative mutant M1146, in which gene clusters encoding the four main antibiotic biosynthetic pathways were deleted. Metabolic Flux Analysis and (13C-labeling allowed us to reconstruct a flux map under steady-state conditions for both strains. The mutant strain M1146 showed a higher growth rate, a higher flux through the pentose phosphate pathway and a higher flux through the anaplerotic phosphoenolpyruvate carboxylase. In that strain, glucose uptake and the flux through the Krebs cycle were lower than in M145. The enhanced flux through the pentose phosphate pathway in M1146 is thought to generate NADPH enough to face higher needs for biomass biosynthesis and other processes. In both strains, the production of NADPH was higher than NADPH needs, suggesting a key role for nicotinamide nucleotide transhydrogenase for redox homeostasis. ATP production is also likely to exceed metabolic ATP needs, indicating that ATP consumption for maintenance is substantial.Our results further suggest a possible competition between actinorhodin and triacylglycerol biosynthetic pathways for their common precursor, acetyl-CoA. These findings may be instrumental in developing new strategies exploiting S. coelicolor as a platform for the production of bio-based products of industrial interest.

  9. Flux analysis of central metabolic pathways in the Fe(III)-reducing organism Geobacter metallireducens via 13C isotopiclabeling

    Energy Technology Data Exchange (ETDEWEB)

    Tang, Yinjie J.; Chakraborty, Romy; Martin, Hector Garcia; Chu,Jeannie; Hazen, Terry C.; Keasling, Jay D.

    2007-08-13

    We analyzed the carbon fluxes in the central metabolism ofGeobacter metallireducens strain GS-15 using 13C isotopomer modeling.Acetate labeled in the 1st or 2nd position was the sole carbon source,and Fe-NTA was the sole terminal electron acceptor. The measured labeledacetate uptake rate was 21 mmol/gdw/h in the exponential growth phase.The resulting isotope labeling pattern of amino acids allowed an accuratedetermination of the in vivo global metabolic reaction rates (fluxes)through the central metabolic pathways using a computational isotopomermodel. The model indicated that over 90 percent of the acetate wascompletely oxidized to CO2 via a complete tricarboxylic acid (TCA) cyclewhile reducing iron. Pyruvate carboxylase and phosphoenolpyruvatecarboxykinase were present under these conditions, but enzymes in theglyoxylate shunt and malic enzyme were absent. Gluconeogenesis and thepentose phosphate pathway were mainly employed for biosynthesis andaccounted for less than 3 percent of total carbon consumption. The modelalso indicated surprisingly high reversibility in the reaction betweenoxoglutarate and succinate. This step operates close to the thermodynamicequilibrium possibly because succinate is synthesized via a transferasereaction, and its product, acetyl-CoA, inhibits the conversion ofoxoglutarate to succinate. These findings enable a better understandingof the relationship between genome annotation and extant metabolicpathways in G. metallireducens.

  10. Flux Balance Analysis Inspired Bioprocess Upgrading for Lycopene Production by a Metabolically Engineered Strain of Yarrowia lipolytica

    Science.gov (United States)

    Nambou, Komi; Jian, Xingxing; Zhang, Xinkai; Wei, Liujing; Lou, Jiajia; Madzak, Catherine; Hua, Qiang

    2015-01-01

    Genome-scale metabolic models embody a significant advantage of systems biology since their applications as metabolic flux simulation models enable predictions for the production of industrially-interesting metabolites. The biotechnological production of lycopene from Yarrowia lipolytica is an emerging scope that has not been fully scrutinized, especially for what concerns cultivation conditions of newly generated engineered strains. In this study, by combining flux balance analysis (FBA) and Plackett-Burman design, we screened chemicals for lycopene production from a metabolically engineered strain of Y. lipolytica. Lycopene concentrations of 126 and 242 mg/L were achieved correspondingly from the FBA-independent and the FBA-assisted designed media in fed-batch cultivation mode. Transcriptional studies revealed upregulations of heterologous genes in media designed according to FBA, thus implying the efficiency of model predictions. Our study will potentially support upgraded lycopene and other terpenoids production from existing or prospect bioengineered strains of Y. lipolytica and/or closely related yeast species. PMID:26703753

  11. Comparative 13C metabolic flux analysis of pyruvate dehydrogenase complex-deficient, L-valine-producing Corynebacterium glutamicum.

    Science.gov (United States)

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

    2011-09-01

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

  12. Effect of hypoxic acclimation on anoxia tolerance in Vitis roots: response of metabolic activity and K+ fluxes.

    Science.gov (United States)

    Mugnai, Sergio; Marras, Anna Maria; Mancuso, Stefano

    2011-06-01

    The effect of a hypoxic pre-treatment (HPT) on improving tolerance to prolonged anoxia conditions in two contrasting Vitis species (V. riparia, anoxia tolerant; V. rupestris, anoxia sensitive) was evaluated. The energy economy of root cells was studied by measuring heat production, the activity of pyruvate decarboxylase (PDC) and alcohol dehdrogenase (ADH), ethanol and ATP production, and K(+) fluxes. The results showed that HPT is an effective tool in order to maintain a sustainable metabolic performance in both the species under anoxia conditions, especially in sensitive species such as V. rupestris. Our results showed that the improved tolerance was mainly driven by: (i) an enhanced activity of key enzymes in alcohol fermentation (ADC and PDC); (ii) the capability to maintain a higher level of respiration, evidenced by a lesser decrease in heat development and ATP production; and (iii) the maintenance of a better ion homeostasis (highlighted by measurement of K(+) fluxes) and K(+) channel functionality.

  13. Dynamic Metabolic Flux Analysis Demonstrated on Cultures Where the Limiting Substrate Is Changed from Carbon to Nitrogen and Vice Versa

    Directory of Open Access Journals (Sweden)

    Gaspard Lequeux

    2010-01-01

    Full Text Available The main requirement for metabolic flux analysis (MFA is that the cells are in a pseudo-steady state, that there is no accumulation or depletion of intracellular metabolites. In the past, the applications of MFA were limited to the analysis of continuous cultures. This contribution introduces the concept of dynamic MFA and extends MFA so that it is applicable to transient cultures. Time series of concentration measurements are transformed into flux values. This transformation involves differentiation, which typically increases the noisiness of the data. Therefore, a noise-reducing step is needed. In this work, polynomial smoothing was used. As a test case, dynamic MFA is applied on Escherichia coli cultivations shifting from carbon limitation to nitrogen limitation and vice versa. After switching the limiting substrate from N to C, a lag phase was observed accompanied with an increase in maintenance energy requirement. This lag phase did not occur in the C- to N-limitation case.

  14. The Activity Reaction Core and Plasticity of Metabolic Networks.

    Directory of Open Access Journals (Sweden)

    2005-12-01

    Full Text Available Understanding the system-level adaptive changes taking place in an organism in response to variations in the environment is a key issue of contemporary biology. Current modeling approaches, such as constraint-based flux-balance analysis, have proved highly successful in analyzing the capabilities of cellular metabolism, including its capacity to predict deletion phenotypes, the ability to calculate the relative flux values of metabolic reactions, and the capability to identify properties of optimal growth states. Here, we use flux-balance analysis to thoroughly assess the activity of Escherichia coli, Helicobacter pylori, and Saccharomyces cerevisiae metabolism in 30,000 diverse simulated environments. We identify a set of metabolic reactions forming a connected metabolic core that carry non-zero fluxes under all growth conditions, and whose flux variations are highly correlated. Furthermore, we find that the enzymes catalyzing the core reactions display a considerably higher fraction of phenotypic essentiality and evolutionary conservation than those catalyzing noncore reactions. Cellular metabolism is characterized by a large number of species-specific conditionally active reactions organized around an evolutionary conserved, but always active, metabolic core. Finally, we find that most current antibiotics interfering with bacterial metabolism target the core enzymes, indicating that our findings may have important implications for antimicrobial drug-target discovery.

  15. In Silico Genome-Scale Reconstruction and Validation of the Corynebacterium glutamicum Metabolic Network

    DEFF Research Database (Denmark)

    Kjeldsen, Kjeld Raunkjær; Nielsen, J.

    2009-01-01

    A genome-scale metabolic model of the Gram-positive bacteria Corynebacterium glutamicum ATCC 13032 was constructed comprising 446 reactions and 411 metabolite, based on the annotated genome and available biochemical information. The network was analyzed using constraint based methods. The model...... and lactate. Comparable flux values between in silico model and experimental values were seen, although some differences in the phenotypic behavior between the model and the experimental data were observed,...

  16. Control of fluxes towards antibiotics and the role of primary metabolism in production of antibiotics

    DEFF Research Database (Denmark)

    Gunnarsson, Nina; Eliasson Lantz, Anna; Nielsen, Jacob

    2004-01-01

    Yield improvements in antibiotic-producing strains have classically been obtained through random mutagenesis and screening. An attractive alternative to this strategy is the rational design of producer strains via metabolic engineering, an approach that offers the possibility to increase yields...... while avoiding the problems of by-product formation and altered morphological properties, which frequently arise in mutagenized strains. An important aspect in the design of strains with improved yields by metabolic engineering is the identification of rate-controlling enzymatic reactions...... in the metabolic network. Here we describe and discuss available methods for identification of these steps, both in antibiotic biosynthesis pathways and in the primary metabolism, which serves as the supplier of precursors and cofactors for the secondary metabolism. Finally, the importance of precursor...

  17. Characterization of the role Rab25 in energy metabolism and cancer using extracellular flux analysis and material balance.

    Science.gov (United States)

    Mitra, Shreya; Molina, Jennifer; Mills, Gordon B; Dennison, Jennifer B

    2015-01-01

    Rab25, by altering trafficking of critical cellular resources, influences cell metabolism and survival during stress conditions. Overall, perturbations in the vesicular trafficking machinery change cellular bioenergetics that can be directly measured in real time as Oxygen Consumption Rate, OCR (mitochondrial respiration) and Extracellular Acidification Rate, ECAR (glycolysis) by an extracellular flux analyzer (XF96, Seahorse Biosciences, MA). Additionally, overall turnover of glucose, lactate, as well as glutamine and glutamate can be measured biochemically using the YSI2900 Biochemistry Analyzer (YSI Incorporated, Life Sciences, OH). A combination of these two methods allows a precise and quantitative approach to interrogate the role of Rab25 as well as other Rab GTPases in central carbon energy metabolism.

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

    Science.gov (United States)

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

    2013-09-01

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

  19. Signal transduction and metabolic flux of beta-thujaplicin and monoterpene biosynthesis in elicited Cupressus lusitanica cell cultures.

    Science.gov (United States)

    Zhao, Jian; Matsunaga, Yoko; Fujita, Koki; Sakai, Kokki

    2006-01-01

    beta-Thujaplicin is an antimicrobial tropolone derived from geranyl pyrophosphate(GPP) and monoterpene intermediate. Yeast elicitor-treated Cupressus lusitanica cell cultures accumulate high levels of beta-thujaplicin at early stages and other monoterpenes at later stages post-elicitation. The different regulation of beta-thujaplicin and monoterpene biosynthesis and signal transduction directing metabolic flux to beta-thujaplicin firstly and then shifting metabolic flow from beta-thujaplicin to other monoterpene biosynthesis were investigated. The earlier rapid induction of beta-thujaplicin accumulation and a later stimulation of monoterpene biosynthesis by yeast elicitor are in well agreement with elicitor-induced changes in activity of three monoterpene biosynthetic enzymes including isopentenyl pyrophosphate isomerase, GPP synthase, and monoterpene synthase. Yeast elicitor induces an earlier and stronger beta-thujaplicin production and monoterpene biosynthetic enzyme activity than methyl jasmonate (MeJA) does. Profiling all monoterpenes produced by C. lusitanica cell cultures under different conditions reveals that beta-thujaplicin biosynthesis parallels with other monoterpenes and competes for common precursor pools. Yet beta-thujaplicin is produced pre-dominantly at early stage of elicitation whereas other monoterpenes are mainly accumulated at late stage while beta-thujaplicin is metabolized. It is suggested that yeast elicitor-treated C. lusitanica cells preferentially accumulate beta-thujaplicin as a primary defense and other monoterpenes as a secondary defense. Inhibitor treatments suggest that immediate production of beta-thujaplicin post-elicitation largely depends on pre-existing enzymes and translation of pre-existing transcripts as well as recruitment of precursor pools from both the cytosol and plastids. The later beta-thujaplicin and other monoterpene accumulation strictly depends on active transcription and translation. Induction of beta

  20. (13)C dynamic nuclear polarization for measuring metabolic flux in endothelial progenitor cells

    DEFF Research Database (Denmark)

    Nielsen, Nathalie; Laustsen, Christoffer; Bertelsen, Lotte Bonde

    2016-01-01

    system with EPCs either adhered to 3D printed scaffolds or kept in cell suspension. The pyruvate-to-lactate conversion was elevated in suspension of EPCs compared to the EPCs adhered to scaffolds. Furthermore in the setup with EPCs in suspension, an increase in lactate production was seen over time...... suspension show a metabolism with higher lactate production consistent with cells senescence processes compared to cells grown first at 2D culture and subsequent in the 3D printed scaffolds method, where metabolism shows no sign of metabolic shifting during the monitored period....

  1. Alterations in cancer cell metabolism: the Warburg effect and metabolic adaptation.

    Science.gov (United States)

    Asgari, Yazdan; Zabihinpour, Zahra; Salehzadeh-Yazdi, Ali; Schreiber, Falk; Masoudi-Nejad, Ali

    2015-05-01

    The Warburg effect means higher glucose uptake of cancer cells compared to normal tissues, whereas a smaller fraction of this glucose is employed for oxidative phosphorylation. With the advent of high throughput technologies and computational systems biology, cancer cell metabolism has been reinvestigated over the last decades toward identifying various events underlying "how" and "why" a cancer cell employs aerobic glycolysis. Significant progress has been shaped to revise the Warburg effect. In this study, we have integrated the gene expression of 13 different cancer cells with the genome-scale metabolic network of human (Recon1) based on the E-Flux method, and analyzed them based on constraint-based modeling. Results show that regardless of significant up- and down-regulated metabolic genes, the distribution of metabolic changes is similar in different cancer types. These findings support the theory that the Warburg effect is a consequence of metabolic adaptation in cancer cells. Copyright © 2015 Elsevier Inc. All rights reserved.

  2. Network reconstruction of platelet metabolism identifies metabolic signature for aspirin resistance

    Science.gov (United States)

    Thomas, Alex; Rahmanian, Sorena; Bordbar, Aarash; Palsson, Bernhard Ø.; Jamshidi, Neema

    2014-01-01

    Recently there has not been a systematic, objective assessment of the metabolic capabilities of the human platelet. A manually curated, functionally tested, and validated biochemical reaction network of platelet metabolism, iAT-PLT-636, was reconstructed using 33 proteomic datasets and 354 literature references. The network contains enzymes mapping to 403 diseases and 231 FDA approved drugs, alluding to an expansive scope of biochemical transformations that may affect or be affected by disease processes in multiple organ systems. The effect of aspirin (ASA) resistance on platelet metabolism was evaluated using constraint-based modeling, which revealed a redirection of glycolytic, fatty acid, and nucleotide metabolism reaction fluxes in order to accommodate eicosanoid synthesis and reactive oxygen species stress. These results were confirmed with independent proteomic data. The construction and availability of iAT-PLT-636 should stimulate further data-driven, systems analysis of platelet metabolism towards the understanding of pathophysiological conditions including, but not strictly limited to, coagulopathies.

  3. Metabolic flux pattern of glucose utilization by Xanthomonas campestris pv. campestris: prevalent role of the Entner-Doudoroff pathway and minor fluxes through the pentose phosphate pathway and glycolysis.

    Science.gov (United States)

    Schatschneider, Sarah; Huber, Claudia; Neuweger, Heiko; Watt, Tony Francis; Pühler, Alfred; Eisenreich, Wolfgang; Wittmann, Christoph; Niehaus, Karsten; Vorhölter, Frank-Jörg

    2014-10-01

    The well-studied plant pathogenic bacterium Xanthomonas campestris pv. campestris (Xcc) synthesizes the biotechnologically important polysaccharide xanthan gum, which is also regarded as a virulence factor in plant interactions. In Xcc, sugars like glucose are utilized as a source to generate energy and biomass for growth and pathogenicity. In this study, we used [1-(13)C]glucose as a tracer to analyze the fluxes in the central metabolism of the bacterium growing in a minimal medium. (13)C-Metabolic flux analysis based on gas chromatography-mass spectrometry (GC-MS) confirmed the prevalent catabolic role of the Entner-Doudoroff pathway. Comparative nuclear magnetic resonance (NMR)-based isotopologue profiling of a mutant deficient in glycolysis gave evidence for a moderate flux via glycolysis in the wild-type. In addition to reconfirming the Entner-Doudoroff pathway as a catabolic main route, this approach affirmed a numerically minor but important flux via the pentose phosphate pathway.

  4. Contribution of gene expression to metabolic fluxes in hypermetabolic livers induced through burn injury and cecal ligation and puncture in rats.

    Science.gov (United States)

    Banta, Scott; Vemula, Murali; Yokoyama, Tadaaki; Jayaraman, Arul; Berthiaume, François; Yarmush, Martin L

    2007-05-01

    Severe injury activates many stress-related and inflammatory pathways that can lead to a systemic hypermetabolic state. Prior studies using perfused hypermetabolic rat livers have identified intrinsic metabolic flux changes that were not dependent upon the continual presence of elevated stress hormones and substrate loads. We investigated the hypothesis that such changes may be due to persistent alterations in gene expression. A systemic hypermetabolic response was induced in rats by applying a moderate burn injury followed 2 days later by cecum ligation and puncture (CLP) to produce sepsis. Control animals received a sham-burn followed by CLP, or a sham-burn followed by sham-CLP. Two days after CLP, livers were analyzed for gene expression changes using DNA microarrays and for metabolism alterations by ex vivo perfusion coupled with Metabolic Flux Analysis. Burn injury prior to CLP increased fluxes while decreases in gene expression levels were observed. Conversely, CLP alone significantly increased metabolic gene expression, but decreased many of the corresponding metabolic fluxes. Burn injury combined with CLP led to the most dramatic changes, where concurrent changes in fluxes and gene expression levels occurred in about 1/3 of the reactions. The data are consistent with the notion that in this model, burn injury prior to CLP increased fluxes through post-translational mechanisms with little contribution of gene expression, while CLP treatment up-regulated the metabolic machinery by transcriptional mechanisms. Overall, these data show that mRNA changes measured at a single time point by DNA microarray analysis do not reliably predict metabolic flux changes in perfused livers.

  5. A Constraint-Based Understanding of Design Spaces

    DEFF Research Database (Denmark)

    Biskjaer, Michael Mose; Dalsgaard, Peter; Halskov, Kim

    2014-01-01

    space schema, can identify the properties of the prospective product that s/he can form. Through a case study, we show how design space schemas can support designers in various ways, including gaining an overview of the design process, documenting it, reflecting on it, and developing design concepts......This paper suggests a framework for understanding and manoeuvring design spaces based on insights from research into creativity constraints. We define the design space as a conceptual space, which in addition to being co-constituted, explored and developed by the designer encompasses the creativity...... constraints governing the design process. While design spaces can be highly complex, our constraint-based understanding enables us to argue for the benefits of a systematic approach to mapping and manipulating aspects of the design space. We discuss how designers by means of a simple representation, a design...

  6. A Constraint-based Case Frame Lexicon Architecture

    CERN Document Server

    Oflazer, K; Oflazer, Kemal; Yilmaz, Okan

    1995-01-01

    In Turkish, (and possibly in many other languages) verbs often convey several meanings (some totally unrelated) when they are used with subjects, objects, oblique objects, adverbial adjuncts, with certain lexical, morphological, and semantic features, and co-occurrence restrictions. In addition to the usual sense variations due to selectional restrictions on verbal arguments, in most cases, the meaning conveyed by a case frame is idiomatic and not compositional, with subtle constraints. In this paper, we present an approach to building a constraint-based case frame lexicon for use in natural language processing in Turkish, whose prototype we have implemented under the TFS system developed at Univ. of Stuttgart. A number of observations that we have made on Turkish have indicated that we need something beyond the traditional transitive and intransitive distinction, and utilize a framework where verb valence is considered as the obligatory co-existence of an arbitrary subset of possible arguments along with the...

  7. Cofactor engineering through heterologous expression of an NADH oxidase and its impact on metabolic flux redistribution in Klebsiella pneumoniae

    Directory of Open Access Journals (Sweden)

    Ji Xiao-Jun

    2013-01-01

    Full Text Available Abstract Background Acetoin is an important bio-based platform chemical. However, it is usually existed as a minor byproduct of 2,3-butanediol fermentation in bacteria. Results The present study reports introducing an exogenous NAD+ regeneration sysytem into a 2,3-butanediol producing strain Klebsiella pneumoniae to increse the accumulation of acetoin. Batch fermentation suggested that heterologous expression of the NADH oxidase in K. pneumoniae resulted in large decreases in the intracellular NADH concentration (1.4 fold and NADH/NAD+ ratio (2.0 fold. Metabolic flux analysis revealed that fluxes to acetoin and acetic acid were enhanced, whereas, production of lactic acid and ethanol were decreased, with the accumualation of 2,3-butanediol nearly unaltered. By fed-batch culture of the recombinant, the highest reported acetoin production level (25.9 g/L by Klebsiella species was obtained. Conclusions The present study indicates that microbial production of acetoin could be improved by decreasing the intracellular NADH/NAD+ ratio in K. pneumoniae. It demonstrated that the cofactor engineering method, which is by manipulating the level of intracellular cofactors to redirect cellular metabolism, could be employed to achieve a high efficiency of producing the NAD+-dependent microbial metabolite.

  8. Whole-system metabolism and CO2 fluxes in a Mediterranean Bay dominated by seagrass beds (Palma Bay, NW Mediterranean

    Directory of Open Access Journals (Sweden)

    A. V. Borges

    2004-10-01

    Full Text Available The relationship between whole-system metabolism estimates based on planktonic and benthic incubations (bare sediments and seagrass, Posidonia oceanica meadows, and CO2 fluxes across the air-sea interface were examined in the Bay of Palma (Mallorca, Spain during two cruises in March and June 2002. Moreover, planktonic and benthic incubations were performed at monthly intervals from March 2001 to October 2002 in a seagrass vegetated area of the bay. From the annual study, results showed a contrast between the planktonic compartment, which was heterotrophic during most of the year, except for occasional bloom episodes, and the benthic compartment, which was slightly autotrophic. Whereas the seagrass community was autotrophic, the excess organic carbon production therein could only balance the excess respiration of the planktonic compartment in shallow waters (2 fields and fluxes across the bay observed during the two extensive cruises in 2002. Finally, dissolved inorganic carbon and oxygen budgets provided NEP estimates in fair agreement with those derived from direct metabolic estimates based on incubated samples over the Posidonia oceanica meadow.

  9. Disruption of lactate dehydrogenase and alcohol dehydrogenase for increased hydrogen production and its effect on metabolic flux in Enterobacter aerogenes.

    Science.gov (United States)

    Zhao, Hongxin; Lu, Yuan; Wang, Liyan; Zhang, Chong; Yang, Cheng; Xing, Xinhui

    2015-10-01

    Hydrogen production by Enterobacter aerogenes from glucose was enhanced by deleting the targeted ldhA and adh genes responsible for two NADH-consuming pathways which consume most NADH generated from glycolysis. Compared with the wild-type, the hydrogen yield of IAM1183-ΔldhA increased 1.5 fold. Metabolic flux analysis showed both IAM1183-ΔldhA and IAM1183-Δadh exhibited significant changes in flux, including enhanced flux towards the hydrogen generation. The lactate production of IAM1183-ΔldhA significantly decreased by 91.42%, while the alcohol yield of IAM1183-Δadh decreased to 30%. The mutant IAM1183-ΔldhA with better hydrogen-producing performance was selected for further investigation in a 5-L fermentor. The hydrogen production of IAM1183-ΔldhA was 2.3 times higher than the wild-type. Further results from the fermentation process showed that the pH decreased to 5.39 levels, then gradually increased to 5.96, indicating that some acidic metabolites might be degraded or uptaken by cells.

  10. Metabolomic and (13)C-metabolic flux analysis of a xylose-consuming Saccharomyces cerevisiae strain expressing xylose isomerase.

    Science.gov (United States)

    Wasylenko, Thomas M; Stephanopoulos, Gregory

    2015-03-01

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

  11. Computational Methods for Modification of Metabolic Networks

    Directory of Open Access Journals (Sweden)

    Takeyuki Tamura

    2015-01-01

    Full Text Available In metabolic engineering, modification of metabolic networks is an important biotechnology and a challenging computational task. In the metabolic network modification, we should modify metabolic networks by newly adding enzymes or/and knocking-out genes to maximize the biomass production with minimum side-effect. In this mini-review, we briefly review constraint-based formalizations for Minimum Reaction Cut (MRC problem where the minimum set of reactions is deleted so that the target compound becomes non-producible from the view point of the flux balance analysis (FBA, elementary mode (EM, and Boolean models. Minimum Reaction Insertion (MRI problem where the minimum set of reactions is added so that the target compound newly becomes producible is also explained with a similar formalization approach. The relation between the accuracy of the models and the risk of overfitting is also discussed.

  12. CeCaFDB: a curated database for the documentation, visualization and comparative analysis of central carbon metabolic flux distributions explored by 13C-fluxomics.

    Science.gov (United States)

    Zhang, Zhengdong; Shen, Tie; Rui, Bin; Zhou, Wenwei; Zhou, Xiangfei; Shang, Chuanyu; Xin, Chenwei; Liu, Xiaoguang; Li, Gang; Jiang, Jiansi; Li, Chao; Li, Ruiyuan; Han, Mengshu; You, Shanping; Yu, Guojun; Yi, Yin; Wen, Han; Liu, Zhijie; Xie, Xiaoyao

    2015-01-01

    The Central Carbon Metabolic Flux Database (CeCaFDB, available at http://www.cecafdb.org) is a manually curated, multipurpose and open-access database for the documentation, visualization and comparative analysis of the quantitative flux results of central carbon metabolism among microbes and animal cells. It encompasses records for more than 500 flux distributions among 36 organisms and includes information regarding the genotype, culture medium, growth conditions and other specific information gathered from hundreds of journal articles. In addition to its comprehensive literature-derived data, the CeCaFDB supports a common text search function among the data and interactive visualization of the curated flux distributions with compartmentation information based on the Cytoscape Web API, which facilitates data interpretation. The CeCaFDB offers four modules to calculate a similarity score or to perform an alignment between the flux distributions. One of the modules was built using an inter programming algorithm for flux distribution alignment that was specifically designed for this study. Based on these modules, the CeCaFDB also supports an extensive flux distribution comparison function among the curated data. The CeCaFDB is strenuously designed to address the broad demands of biochemists, metabolic engineers, systems biologists and members of the -omics community.

  13. Connecting extracellular metabolomic measurements to intracellular flux states in yeast

    Directory of Open Access Journals (Sweden)

    Herrgård Markus J

    2009-03-01

    Full Text Available Abstract Background Metabolomics has emerged as a powerful tool in the quantitative identification of physiological and disease-induced biological states. Extracellular metabolome or metabolic profiling data, in particular, can provide an insightful view of intracellular physiological states in a noninvasive manner. Results We used an updated genome-scale metabolic network model of Saccharomyces cerevisiae, iMM904, to investigate how changes in the extracellular metabolome can be used to study systemic changes in intracellular metabolic states. The iMM904 metabolic network was reconstructed based on an existing genome-scale network, iND750, and includes 904 genes and 1,412 reactions. The network model was first validated by comparing 2,888 in silico single-gene deletion strain growth phenotype predictions to published experimental data. Extracellular metabolome data measured in response to environmental and genetic perturbations of ammonium assimilation pathways was then integrated with the iMM904 network in the form of relative overflow secretion constraints and a flux sampling approach was used to characterize candidate flux distributions allowed by these constraints. Predicted intracellular flux changes were consistent with published measurements on intracellular metabolite levels and fluxes. Patterns of predicted intracellular flux changes could also be used to correctly identify the regions of the metabolic network that were perturbed. Conclusion Our results indicate that integrating quantitative extracellular metabolomic profiles in a constraint-based framework enables inferring changes in intracellular metabolic flux states. Similar methods could potentially be applied towards analyzing biofluid metabolome variations related to human physiological and disease states.

  14. Maximal sum of metabolic exchange fluxes outperforms biomass yield as a predictor of growth rate of microorganisms.

    Directory of Open Access Journals (Sweden)

    Raphy Zarecki

    Full Text Available Growth rate has long been considered one of the most valuable phenotypes that can be measured in cells. Aside from being highly accessible and informative in laboratory cultures, maximal growth rate is often a prime determinant of cellular fitness, and predicting phenotypes that underlie fitness is key to both understanding and manipulating life. Despite this, current methods for predicting microbial fitness typically focus on yields [e.g., predictions of biomass yield using GEnome-scale metabolic Models (GEMs] or notably require many empirical kinetic constants or substrate uptake rates, which render these methods ineffective in cases where fitness derives most directly from growth rate. Here we present a new method for predicting cellular growth rate, termed SUMEX, which does not require any empirical variables apart from a metabolic network (i.e., a GEM and the growth medium. SUMEX is calculated by maximizing the SUM of molar EXchange fluxes (hence SUMEX in a genome-scale metabolic model. SUMEX successfully predicts relative microbial growth rates across species, environments, and genetic conditions, outperforming traditional cellular objectives (most notably, the convention assuming biomass maximization. The success of SUMEX suggests that the ability of a cell to catabolize substrates and produce a strong proton gradient enables fast cell growth. Easily applicable heuristics for predicting growth rate, such as what we demonstrate with SUMEX, may contribute to numerous medical and biotechnological goals, ranging from the engineering of faster-growing industrial strains, modeling of mixed ecological communities, and the inhibition of cancer growth.

  15. Metabolic flux analysis model for optimizing xylose conversion into ethanol by the natural C5-fermenting yeast Candida shehatae.

    Science.gov (United States)

    Bideaux, Carine; Montheard, Julie; Cameleyre, Xavier; Molina-Jouve, Carole; Alfenore, Sandrine

    2016-02-01

    A metabolic flux analysis (MFA) model was developed to optimize the xylose conversion into ethanol using Candida shehatae strain. This metabolic model was compartmented and constructed with xylose as carbon substrate integrating the enzymatic duality of the first step of xylose degradation via an algebraic coefficient. The model included the pentose phosphate pathway, glycolysis, synthesis of major metabolites like ethanol, acetic acid and glycerol, the tricarboxylic acid cycle as well as the respiratory chain, the cofactor balance, and the maintenance. The biomass composition and thus production were integrated considering the major biochemical synthesis reactions from monomers to each constitutive macromolecule (i.e., proteins, lipids, polysaccharides, nucleic acids). The construction of the model resulted into a 122-linear equation system to be resolved. A first experiment allowed was to verify the accuracy of the model by comparing calculated and experimental data. The metabolic model was utilized to determine the theoretical yield taking into account oxido-reductive balance and to optimize ethanol production. The maximal theoretical yield was calculated at 0.62 Cmolethanol/Cmolxylose for an oxygen requirement of 0.33 moloxygen/molxylose linked to the cofactors of the xylose reductase. Cultivations in chemostat mode allowed the fine tuning of both xylose and oxygen uptakes and showed that lower was the oxygen/xylose ratio, higher was the ethanol production yield. The best experimental ethanol production yield (0.51 Cmolethanol/Cmolxylose) was obtained for an oxygen supply of 0.47 moloxygen/molxylose.

  16. The key to acetate: metabolic fluxes of acetic acid bacteria under cocoa pulp fermentation-simulating conditions.

    Science.gov (United States)

    Adler, Philipp; Frey, Lasse Jannis; Berger, Antje; Bolten, Christoph Josef; Hansen, Carl Erik; Wittmann, Christoph

    2014-08-01

    Acetic acid bacteria (AAB) play an important role during cocoa fermentation, as their main product, acetate, is a major driver for the development of the desired cocoa flavors. Here, we investigated the specialized metabolism of these bacteria under cocoa pulp fermentation-simulating conditions. A carefully designed combination of parallel 13C isotope labeling experiments allowed the elucidation of intracellular fluxes in the complex environment of cocoa pulp, when lactate and ethanol were included as primary substrates among undefined ingredients. We demonstrate that AAB exhibit a functionally separated metabolism during coconsumption of two-carbon and three-carbon substrates. Acetate is almost exclusively derived from ethanol, while lactate serves for the formation of acetoin and biomass building blocks. Although this is suboptimal for cellular energetics, this allows maximized growth and conversion rates. The functional separation results from a lack of phosphoenolpyruvate carboxykinase and malic enzymes, typically present in bacteria to interconnect metabolism. In fact, gluconeogenesis is driven by pyruvate phosphate dikinase. Consequently, a balanced ratio of lactate and ethanol is important for the optimum performance of AAB. As lactate and ethanol are individually supplied by lactic acid bacteria and yeasts during the initial phase of cocoa fermentation, respectively, this underlines the importance of a well-balanced microbial consortium for a successful fermentation process. Indeed, AAB performed the best and produced the largest amounts of acetate in mixed culture experiments when lactic acid bacteria and yeasts were both present.

  17. Maximal sum of metabolic exchange fluxes outperforms biomass yield as a predictor of growth rate of microorganisms.

    Science.gov (United States)

    Zarecki, Raphy; Oberhardt, Matthew A; Yizhak, Keren; Wagner, Allon; Shtifman Segal, Ella; Freilich, Shiri; Henry, Christopher S; Gophna, Uri; Ruppin, Eytan

    2014-01-01

    Growth rate has long been considered one of the most valuable phenotypes that can be measured in cells. Aside from being highly accessible and informative in laboratory cultures, maximal growth rate is often a prime determinant of cellular fitness, and predicting phenotypes that underlie fitness is key to both understanding and manipulating life. Despite this, current methods for predicting microbial fitness typically focus on yields [e.g., predictions of biomass yield using GEnome-scale metabolic Models (GEMs)] or notably require many empirical kinetic constants or substrate uptake rates, which render these methods ineffective in cases where fitness derives most directly from growth rate. Here we present a new method for predicting cellular growth rate, termed SUMEX, which does not require any empirical variables apart from a metabolic network (i.e., a GEM) and the growth medium. SUMEX is calculated by maximizing the SUM of molar EXchange fluxes (hence SUMEX) in a genome-scale metabolic model. SUMEX successfully predicts relative microbial growth rates across species, environments, and genetic conditions, outperforming traditional cellular objectives (most notably, the convention assuming biomass maximization). The success of SUMEX suggests that the ability of a cell to catabolize substrates and produce a strong proton gradient enables fast cell growth. Easily applicable heuristics for predicting growth rate, such as what we demonstrate with SUMEX, may contribute to numerous medical and biotechnological goals, ranging from the engineering of faster-growing industrial strains, modeling of mixed ecological communities, and the inhibition of cancer growth.

  18. Radiation Promptly Alters Cancer Live Cell Metabolic Fluxes: An In Vitro Demonstration

    NARCIS (Netherlands)

    Campos, D.; Peeters, W.; Nickel, K.; Burkel, B.; Bussink, J.; Kimple, R.J.; Kogel, A. van der; Eliceiri, K.W.; Kissick, M.W.

    2016-01-01

    Quantitative data is presented that shows significant changes in cellular metabolism in a head and neck cancer cell line 30 min after irradiation. A head and neck cancer cell line (UM-SCC-22B) and a comparable normal cell line, normal oral keratinocyte (NOK) were each separately exposed to 10 Gy and

  19. 14C-labeled propionate metabolism in vivo and estimates of hepatic gluconeogenesis relative to Krebs cycle flux.

    Science.gov (United States)

    Landau, B R; Schumann, W C; Chandramouli, V; Magnusson, I; Kumaran, K; Wahren, J

    1993-10-01

    Purposes of this study were 1) to estimate in humans, using 14C-labeled propionate, the rate of hepatic gluconeogenesis relative to the rate of Krebs cycle flux; 2) to compare those rates with estimates previously made using [3-14C]lactate and [2-14C]acetate; 3) to determine if the amount of ATP required for that rate of gluconeogenesis could be generated in liver, calculated from that rate of Krebs cycle flux and splanchnic balance measurements, previously made, and 4) to test whether hepatic succinyl-CoA is channeled during its metabolism through the Krebs cycle. [2-14C]propionate, [3-14C]-propionate, and [2,3-14C]succinate were given along with phenyl acetate to normal subjects, fasted 60 h. Distributions of 14C were determined in the carbons of blood glucose and of glutamate from excreted phenylacetylglutamine. Corrections to the distributions for 14CO2 fixation were made from the specific activities of urinary urea and the specific activities in glucose, glutamate, and urea previously found on administering [14C]-bicarbonate. Uncertainties in the corrections and in the contributions of pyruvate and Cori cyclings limit the quantitations. The rate of gluconeogenesis appears to be two or more times the rate of Krebs cycle flux and pyruvate's decarboxylation to acetyl-CoA, metabolized in the cycle, less than one-twenty-fifth the rate of its decarboxylation. Such estimates were previously made using [3-14C]lactate. The findings support the use of phenyl acetate to sample hepatic alpha-ketoglutarate. Ratios of specific activities of glucose to glutamate and glucose to urinary urea and expired CO2 indicate succinate's extensive metabolism when presented in trace amounts to liver. Utilizations of the labeled compounds by liver relative to other tissues were in the order succinate = lactate > propionate > acetate. ATP required for gluconeogenesis and urea formation was approximately 40% of the amount of ATP generated in liver. There was no channeling of succinyl-CoA in

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

    Energy Technology Data Exchange (ETDEWEB)

    Nault, Rance, E-mail: naultran@msu.edu [Ottawa-Carleton Institute of Biology, Department of Biology and Centre for Advanced Research in Environmental Genomics, University of Ottawa, Ottawa, Ontario, K1N 6N5 (Canada); Abdul-Fattah, Hiba [Ottawa-Carleton Institute of Biology, Department of Biology and Centre for Advanced Research in Environmental Genomics, University of Ottawa, Ottawa, Ontario, K1N 6N5 (Canada); Mironov, Gleb G.; Berezovski, Maxim V. [Ottawa-Carleton Institute of Biology, Department of Biology and Centre for Advanced Research in Environmental Genomics, University of Ottawa, Ottawa, Ontario, K1N 6N5 (Canada); Department of Chemistry, University of Ottawa, Ottawa, Ontario, K1N 6N5 (Canada); Moon, Thomas W. [Ottawa-Carleton Institute of Biology, Department of Biology and Centre for Advanced Research in Environmental Genomics, University of Ottawa, Ottawa, Ontario, K1N 6N5 (Canada)

    2013-08-15

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

  1. The metabolic flux regulation of Klebsiella pneumoniae based on quorum sensing system

    Science.gov (United States)

    Sun, Shujing; Zhang, Haiyang; Lu, Shuyi; Lai, Chunfen; Liu, Huijun; Zhu, Hu

    2016-01-01

    Quorum-sensing (QS) systems exist universally in bacteria to regulate multiple biological functions. Klebsiella pneumoniae, an industrially important bacterium that produces bio-based chemicals such as 2,3-butanediol and acetoin, can secrete a furanosyl borate diester (AI-2) as the signalling molecule mediating a QS system, which plays a key regulatory role in the biosynthesis of secondary metabolites. In this study, the molecular regulation and metabolic functions of a QS system in K. pneumoniae were investigated. The results showed that after the disruption of AI-2-mediated QS by the knockout of luxS, the production of acetoin, ethanol and acetic acid were relatively lower in the K. pneumoniae mutant than in the wild type bacteria. However, 2,3-butanediol production was increased by 23.8% and reached 54.93 g/L. The observed enhancement may be attributed to the improvement of the catalytic activity of 2,3-butanediol dehydrogenase (BDH) in transforming acetoin to 2,3-butanediol. This possibility is consistent with the RT-PCR-verified increase in the transcriptional level of budC, which encodes BDH. These results also demonstrated that the physiological metabolism of K. pneumoniae was adversely affected by a QS system. This effect was reversed through the addition of synthetic AI-2. This study provides the basis for a QS-modulated metabolic engineering study of K. pneumoniae. PMID:27924940

  2. Metabolic Flux Distribution during Defatting of Steatotic Human Hepatoma (HepG2) Cells.

    Science.gov (United States)

    Yarmush, Gabriel; Santos, Lucas; Yarmush, Joshua; Koundinyan, Srivathsan; Saleem, Mubasher; Nativ, Nir I; Schloss, Rene S; Yarmush, Martin L; Maguire, Timothy J; Berthiaume, Francois

    2016-01-04

    Methods that rapidly decrease fat in steatotic hepatocytes may be helpful to recover severely fatty livers for transplantation. Defatting kinetics are highly dependent upon the extracellular medium composition; however, the pathways involved are poorly understood. Steatosis was induced in human hepatoma cells (HepG2) by exposure to high levels of free fatty acids, followed by defatting using plain medium containing no fatty acids, or medium supplemented with a cocktail of defatting agents previously described before. We measured the levels of 28 extracellular metabolites and intracellular triglyceride, and fed the data into a steady-state mass balance model to estimate strictly intracellular fluxes. We found that during defatting, triglyceride content decreased, while beta-oxidation, the tricarboxylic acid cycle, and the urea cycle increased. These fluxes were augmented by defatting agents, and even more so by hyperoxic conditions. In all defatting conditions, the rate of extracellular glucose uptake/release was very small compared to the internal supply from glycogenolysis, and glycolysis remained highly active. Thus, in steatotic HepG2 cells, glycolysis and fatty acid oxidation may co-exist. Together, these pathways generate reducing equivalents that are supplied to mitochondrial oxidative phosphorylation.

  3. Metabolic Flux Distribution during Defatting of Steatotic Human Hepatoma (HepG2 Cells

    Directory of Open Access Journals (Sweden)

    Gabriel Yarmush

    2016-01-01

    Full Text Available Methods that rapidly decrease fat in steatotic hepatocytes may be helpful to recover severely fatty livers for transplantation. Defatting kinetics are highly dependent upon the extracellular medium composition; however, the pathways involved are poorly understood. Steatosis was induced in human hepatoma cells (HepG2 by exposure to high levels of free fatty acids, followed by defatting using plain medium containing no fatty acids, or medium supplemented with a cocktail of defatting agents previously described before. We measured the levels of 28 extracellular metabolites and intracellular triglyceride, and fed the data into a steady-state mass balance model to estimate strictly intracellular fluxes. We found that during defatting, triglyceride content decreased, while beta-oxidation, the tricarboxylic acid cycle, and the urea cycle increased. These fluxes were augmented by defatting agents, and even more so by hyperoxic conditions. In all defatting conditions, the rate of extracellular glucose uptake/release was very small compared to the internal supply from glycogenolysis, and glycolysis remained highly active. Thus, in steatotic HepG2 cells, glycolysis and fatty acid oxidation may co-exist. Together, these pathways generate reducing equivalents that are supplied to mitochondrial oxidative phosphorylation.

  4. Metabolic flux analysis in complex isotopolog space. Recycling of glucose in tobacco plants.

    Science.gov (United States)

    Ettenhuber, Christian; Radykewicz, Tanja; Kofer, Waltraud; Koop, Hans-Ulrich; Bacher, Adelbert; Eisenreich, Wolfgang

    2005-02-01

    Tobacco plants grown in vitro were supplied with a mixture of [U-13C6]glucose and unlabelled sucrose via the root system. After 20 days, leaves were harvested and extracted with water. Glucose was isolated from the extract and was analysed by 13C NMR spectroscopy. All 13C signals appeared as complex multiplets due to 13C-13C coupling. The abundance of 21 isotopologous glucose species was determined from the 13C NMR signal integrals by numerical deconvolution using a genetic algorithm. The relative fractions of specific isotopologs in the overall excess of 13C-labelled specimens establish flux contributions via glycolysis/glucogenesis, pentose phosphate pathway, citric acid cycle and Calvin cycle including 13CO2 refixation. The fluxes were modelled and reconstructed in silico by a novel rule-based approach yielding the contributions of circular pathways and the degree of multiple cycling events. The data indicate that the vast majority of the proffered [U-13C6]glucose molecules had been modified by catabolism and subsequent glucogenesis from catabolic fragments, predominantly via passage through the citric acid cycle and the pentose phosphate pathway.

  5. Research on constraint-based virtual assembly technologies

    Institute of Scientific and Technical Information of China (English)

    YANG Rundang; WU Dianliang; FAN Xiumin; YAN Juanqi

    2007-01-01

    To realize a constraint-based virtual assembly operation,the unified representations of the assembly constraint,the equivalent relation between the constraint and the degree of freedom(DOF),and the movement DOF reduction in a virtual environment are proposed.Several algorithms about the constraint treatment are submitted.First,the automatic recognition algorithm based on the assembly relation is used to determine the position and orientation relation between two geometry elements of constraint whether they meet the given errors.Second,to satisfy the new constraint,according to the positing solving algorithm,the position and orientation of an active part are modified with minimal adjustment after the part has satisfied the affirmed constraints.Finally,the algorithm of movement navigation based on the generalized coordinate system is put forward,and the part movement is guided.These algorithms have been applied to the integrated virtual assembly environment(IVAE)system.Experiments have indicated that these algorithms have well supported constraint treatments in the IVAE and realized the closer combination of the virtual and the real assembly processes.

  6. Constraint-based soft tissue simulation for virtual surgical training.

    Science.gov (United States)

    Tang, Wen; Wan, Tao Ruan

    2014-11-01

    Most of surgical simulators employ a linear elastic model to simulate soft tissue material properties due to its computational efficiency and the simplicity. However, soft tissues often have elaborate nonlinear material characteristics. Most prominently, soft tissues are soft and compliant to small strains, but after initial deformations they are very resistant to further deformations even under large forces. Such material characteristic is referred as the nonlinear material incompliant which is computationally expensive and numerically difficult to simulate. This paper presents a constraint-based finite-element algorithm to simulate the nonlinear incompliant tissue materials efficiently for interactive simulation applications such as virtual surgery. Firstly, the proposed algorithm models the material stiffness behavior of soft tissues with a set of 3-D strain limit constraints on deformation strain tensors. By enforcing a large number of geometric constraints to achieve the material stiffness, the algorithm reduces the task of solving stiff equations of motion with a general numerical solver to iteratively resolving a set of constraints with a nonlinear Gauss-Seidel iterative process. Secondly, as a Gauss-Seidel method processes constraints individually, in order to speed up the global convergence of the large constrained system, a multiresolution hierarchy structure is also used to accelerate the computation significantly, making interactive simulations possible at a high level of details. Finally, this paper also presents a simple-to-build data acquisition system to validate simulation results with ex vivo tissue measurements. An interactive virtual reality-based simulation system is also demonstrated.

  7. Processing scalar implicature: a constraint-based approach.

    Science.gov (United States)

    Degen, Judith; Tanenhaus, Michael K

    2015-05-01

    Three experiments investigated the processing of the implicature associated with some using a "gumball paradigm." On each trial, participants saw an image of a gumball machine with an upper chamber with 13 gumballs and an empty lower chamber. Gumballs then dropped to the lower chamber and participants evaluated statements, such as "You got some of the gumballs." Experiment 1 established that some is less natural for reference to small sets (1, 2, and 3 of the 13 gumballs) and unpartitioned sets (all 13 gumballs) compared to intermediate sets (6-8). Partitive some of was less natural than simple some when used with the unpartitioned set. In Experiment 2, including exact number descriptions lowered naturalness ratings for some with small sets but not for intermediate size sets and the unpartitioned set. In Experiment 3, the naturalness ratings from Experiment 2 predicted response times. The results are interpreted as evidence for a Constraint-Based account of scalar implicature processing and against both two-stage, Literal-First models and pragmatic Default models.

  8. Hybrid metabolic flux analysis and recombinant protein prediction in Pichia pastoris X-33 cultures expressing a single-chain antibody fragment.

    Science.gov (United States)

    Isidro, Inês A; Portela, Rui M; Clemente, João J; Cunha, António E; Oliveira, Rui

    2016-09-01

    Despite the growing importance of the Pichia pastoris expression system as industrial workhorse, the literature is almost absent in systematic studies on how culture medium composition affects central carbon fluxes and heterologous protein expression. In this study we investigate how 26 variations of the BSM+PTM1 medium impact central carbon fluxes and protein expression in a P. pastoris X-33 strain expressing a single-chain antibody fragment. To achieve this goal, we adopted a hybrid metabolic flux analysis (MFA) methodology, which is a modification of standard MFA to predict the rate of synthesis of recombinant proteins. Hybrid MFA combines the traditional parametric estimation of central carbon fluxes with non-parametric statistical modeling of product-related quantitative or qualitative measurements as a function of central carbon fluxes. It was observed that protein yield variability was 53.6 % (relative standard deviation) among the different experiments. Protein yield is much more sensitive to medium composition than biomass growth, which is mainly determined by the carbon source availability and main salts. Hybrid MFA was able to describe accurately the protein yield with normalized RMSE of 6.3 % over 5 independent experiments. The metabolic state that promotes high protein yields is characterized by high overall metabolic rates through main central carbon pathways concomitantly with a relative shift of carbon flux from biosynthetic towards energy generating pathways.

  9. Metabolite essentiality elucidates robustness of Escherichia coli metabolism

    CERN Document Server

    Kim, Pan-Jun; Kim, Tae Yong; Lee, Kwang Ho; Jeong, Hawoong; Lee, Sang Yup; Park, Sunwon

    2007-01-01

    Complex biological systems are very robust to genetic and environmental changes at all levels of organization. Many biological functions of Escherichia coli metabolism can be sustained against single-gene or even multiple-gene mutations by using redundant or alternative pathways. Thus, only a limited number of genes have been identified to be lethal to the cell. In this regard, the reaction-centric gene deletion study has a limitation in understanding the metabolic robustness. Here, we report the use of flux-sum, which is the summation of all incoming or outgoing fluxes around a particular metabolite under pseudo-steady state conditions, as a good conserved property for elucidating such robustness of E. coli from the metabolite point of view. The functional behavior, as well as the structural and evolutionary properties of metabolites essential to the cell survival, was investigated by means of a constraints-based flux analysis under perturbed conditions. The essential metabolites are capable of maintaining a...

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

    Science.gov (United States)

    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.

  11. Characterizing the roles of changing population size and selection on the evolution of flux control in metabolic pathways.

    Science.gov (United States)

    Orlenko, Alena; Chi, Peter B; Liberles, David A

    2017-05-25

    Understanding the genotype-phenotype map is fundamental to our understanding of genomes. Genes do not function independently, but rather as part of networks or pathways. In the case of metabolic pathways, flux through the pathway is an important next layer of biological organization up from the individual gene or protein. Flux control in metabolic pathways, reflecting the importance of mutation to individual enzyme genes, may be evolutionarily variable due to the role of mutation-selection-drift balance. The evolutionary stability of rate limiting steps and the patterns of inter-molecular co-evolution were evaluated in a simulated pathway with a system out of equilibrium due to fluctuating selection, population size, or positive directional selection, to contrast with those under stabilizing selection. Depending upon the underlying population genetic regime, fluctuating population size was found to increase the evolutionary stability of rate limiting steps in some scenarios. This result was linked to patterns of local adaptation of the population. Further, during positive directional selection, as with more complex mutational scenarios, an increase in the observation of inter-molecular co-evolution was observed. Differences in patterns of evolution when systems are in and out of equilibrium, including during positive directional selection may lead to predictable differences in observed patterns for divergent evolutionary scenarios. In particular, this result might be harnessed to detect differences between compensatory processes and directional processes at the pathway level based upon evolutionary observations in individual proteins. Detecting functional shifts in pathways reflects an important milestone in predicting when changes in genotypes result in changes in phenotypes.

  12. In silico analysis of Clostridium acetobutylicum ATCC 824 metabolic response to an external electron supply.

    Science.gov (United States)

    Gallardo, Roberto; Acevedo, Alejandro; Quintero, Julián; Paredes, Ivan; Conejeros, Raúl; Aroca, Germán

    2016-02-01

    The biological production of butanol has become an important research field and thanks to genome sequencing and annotation; genome-scale metabolic reconstructions have been developed for several Clostridium species. This work makes use of the iCAC490 model of Clostridium acetobutylicum ATCC 824 to analyze its metabolic capabilities and response to an external electron supply through a constraint-based approach using the Constraint-Based Reconstruction Analysis Toolbox. Several analyses were conducted, which included sensitivity, production envelope, and phenotypic phase planes. The model showed that the use of an external electron supply, which acts as co-reducing agent along with glucose-derived reducing power (electrofermentation), results in an increase in the butanol-specific productivity. However, a proportional increase in the butyrate uptake flux is required. Besides, the uptake of external butyrate leads to the coupling of butanol production and growth, which coincides with results reported in literature. Phenotypic phase planes showed that the reducing capacity becomes more limiting for growth at high butyrate uptake fluxes. An electron uptake flux allows the metabolism to reach the growth optimality line. Although the maximum butanol flux does not coincide with the growth optimality line, a butyrate uptake combined with an electron uptake flux would result in an increased butanol volumetric productivity, being a potential strategy to optimize the production of butanol by C. acetobutylicum ATCC 824.

  13. Constraint-based modeling of carbon fixation and the energetics of electron transfer in Geobacter metallireducens.

    Science.gov (United States)

    Feist, Adam M; Nagarajan, Harish; Rotaru, Amelia-Elena; Tremblay, Pier-Luc; Zhang, Tian; Nevin, Kelly P; Lovley, Derek R; Zengler, Karsten

    2014-04-01

    Geobacter species are of great interest for environmental and biotechnology applications as they can carry out direct electron transfer to insoluble metals or other microorganisms and have the ability to assimilate inorganic carbon. Here, we report on the capability and key enabling metabolic machinery of Geobacter metallireducens GS-15 to carry out CO2 fixation and direct electron transfer to iron. An updated metabolic reconstruction was generated, growth screens on targeted conditions of interest were performed, and constraint-based analysis was utilized to characterize and evaluate critical pathways and reactions in G. metallireducens. The novel capability of G. metallireducens to grow autotrophically with formate and Fe(III) was predicted and subsequently validated in vivo. Additionally, the energetic cost of transferring electrons to an external electron acceptor was determined through analysis of growth experiments carried out using three different electron acceptors (Fe(III), nitrate, and fumarate) by systematically isolating and examining different parts of the electron transport chain. The updated reconstruction will serve as a knowledgebase for understanding and engineering Geobacter and similar species.

  14. Constraint-based modeling of carbon fixation and the energetics of electron transfer in Geobacter metallireducens.

    Directory of Open Access Journals (Sweden)

    Adam M Feist

    2014-04-01

    Full Text Available Geobacter species are of great interest for environmental and biotechnology applications as they can carry out direct electron transfer to insoluble metals or other microorganisms and have the ability to assimilate inorganic carbon. Here, we report on the capability and key enabling metabolic machinery of Geobacter metallireducens GS-15 to carry out CO2 fixation and direct electron transfer to iron. An updated metabolic reconstruction was generated, growth screens on targeted conditions of interest were performed, and constraint-based analysis was utilized to characterize and evaluate critical pathways and reactions in G. metallireducens. The novel capability of G. metallireducens to grow autotrophically with formate and Fe(III was predicted and subsequently validated in vivo. Additionally, the energetic cost of transferring electrons to an external electron acceptor was determined through analysis of growth experiments carried out using three different electron acceptors (Fe(III, nitrate, and fumarate by systematically isolating and examining different parts of the electron transport chain. The updated reconstruction will serve as a knowledgebase for understanding and engineering Geobacter and similar species.

  15. Contribution of Gene Expression to Metabolic Fluxes in Hypermetabolic Livers Induced Through Burn Injury and Cecal Ligation and Puncture in Rats

    OpenAIRE

    Banta, Scott; Vemula, Murali; Yokoyama, Tadaaki; Jayaraman, Arul; Berthiaume, François; Yarmush, Martin L.

    2007-01-01

    Severe injury activates many stress-related and inflammatory pathways that can lead to a systemic hyper-metabolic state. Prior studies using perfused hypermetabolic rat livers have identified intrinsic metabolic flux changes that were not dependent upon the continual presence of elevated stress hormones and substrate loads. We investigated the hypothesis that such changes may be due to persistent alterations in gene expression. A systemic hypermetabolic response was induced in rats by applyin...

  16. Modeling the diversion of primary carbon flux into secondary metabolism under variable nitrate and light/dark conditions.

    Science.gov (United States)

    Larbat, Romain; Robin, Christophe; Lillo, Cathrine; Drengstig, Tormod; Ruoff, Peter

    2016-08-01

    In plants, the partitioning of carbon resources between growth and defense is detrimental for their development. From a metabolic viewpoint, growth is mainly related to primary metabolism including protein, amino acid and lipid synthesis, whereas defense is based notably on the biosynthesis of a myriad of secondary metabolites. Environmental factors, such as nitrate fertilization, impact the partitioning of carbon resources between growth and defense. Indeed, experimental data showed that a shortage in the nitrate fertilization resulted in a reduction of the plant growth, whereas some secondary metabolites involved in plant defense, such as phenolic compounds, accumulated. Interestingly, sucrose, a key molecule involved in the transport and partitioning of carbon resources, appeared to be under homeostatic control. Based on the inflow/outflow properties of sucrose homeostatic regulation we propose a global model on how the diversion of the primary carbon flux into the secondary phenolic pathways occurs at low nitrate concentrations. The model can account for the accumulation of starch during the light phase and the sucrose remobilization by starch degradation during the night. Day-length sensing mechanisms for variable light-dark regimes are discussed, showing that growth is proportional to the length of the light phase. The model can describe the complete starch consumption during the night for plants adapted to a certain light/dark regime when grown on sufficient nitrate and can account for an increased accumulation of starch observed under nitrate limitation.

  17. Metabolism

    Science.gov (United States)

    ... Surgery? Choosing the Right Sport for You Shyness Metabolism KidsHealth > For Teens > Metabolism Print A A A ... food through a process called metabolism. What Is Metabolism? Metabolism (pronounced: meh-TAB-uh-lih-zem) is ...

  18. Linking planktonic biomass and metabolism to net gas fluxes in northern temperate lakes

    Energy Technology Data Exchange (ETDEWEB)

    Giorgio, P.A. del [Univ. of Maryland Center for Environmental Science, Cambridge, MD (United States). Horn Point Lab.; Cole, J.J.; Caraco, N.F. [Inst. of Ecosystem Studies, Millbrook, NY (United States); Peters, R.H. [McGill Univ., Montreal, Quebec (Canada). Dept. of Biology

    1999-06-01

    Plankton communities in oligotrophic waters are characteristically dominated by the biomass of heterotrophs, including bacteria, micro-, and macrozooplankton. It has been generally assumed that these inverted biomass pyramids are the direct result of high specific production rates of phytoplankton and a tight coupling between producers and consumers. There are, however, at least two alternative hypotheses: (1) heterotrophic biomass turnover is much slower in oligotrophic than eutrophic systems; and (2) oligotrophic planktonic communities are significantly subsidized by allochthonous organic matter. In this study the authors assessed these hypotheses by establishing the relationship between plankton biomass structure, plankton function, and whole-lake gas (O{sub 2} and CO{sub 2}) fluxes in 20 temperate lakes that span a large range in primary production. The authors show that the balance of phytoplankton production and community respiration (P/R ratio) is always below unity in unproductive lakes where heterotrophic biomass (H) is high relative to autotrophic biomass (A), suggesting that these planktonic food webs function as heterotrophic systems and must be subsidized by allochthonous organic matter. Further, rates of phytoplankton specific production are not highest in communities characterized by dominance of heterotrophic biomass. All except the most productive lakes were supersaturated in CO{sub 2} and undersaturated in O{sub 2}.

  19. Metabolic Flux Analysis of Lipid Biosynthesis in the Yeast Yarrowia lipolytica Using 13C-Labled Glucose and Gas Chromatography-Mass Spectrometry.

    Directory of Open Access Journals (Sweden)

    Huaiyuan Zhang

    Full Text Available The oleaginous yeast Yarrowia lipolytica has considerable potential for producing single cell oil, which can be converted to biodiesel, a sustainable alternative to fossil fuels. However, extensive fundamental and engineering efforts must be carried out before commercialized production become cost-effective. Therefore, in this study, metabolic flux analysis of Y. lipolytica was performed using 13C-labeled glucose as a sole carbon source in nitrogen sufficient and insufficient media. The nitrogen limited medium inhibited cell growth while promoting lipid accumulation (from 8.7% of their biomass to 14.3%. Metabolic flux analysis showed that flux through the pentose phosphate pathway was not significantly regulated by nitrogen concentration, suggesting that NADPH generation is not the limiting factor for lipid accumulation in Y. lipolytica. Furthermore, metabolic flux through malic enzyme was undetectable, confirming its non-regulatory role in lipid accumulation in this yeast. Nitrogen limitation significantly increased flux through ATP:citrate lyase (ACL, implying that ACL plays a key role in providing acetyl-CoA for lipid accumulation in Y. lipolytica.

  20. Metabolic Flux Analysis of Lipid Biosynthesis in the Yeast Yarrowia lipolytica Using 13C-Labled Glucose and Gas Chromatography-Mass Spectrometry.

    Science.gov (United States)

    Zhang, Huaiyuan; Wu, Chao; Wu, Qingyu; Dai, Junbiao; Song, Yuanda

    2016-01-01

    The oleaginous yeast Yarrowia lipolytica has considerable potential for producing single cell oil, which can be converted to biodiesel, a sustainable alternative to fossil fuels. However, extensive fundamental and engineering efforts must be carried out before commercialized production become cost-effective. Therefore, in this study, metabolic flux analysis of Y. lipolytica was performed using 13C-labeled glucose as a sole carbon source in nitrogen sufficient and insufficient media. The nitrogen limited medium inhibited cell growth while promoting lipid accumulation (from 8.7% of their biomass to 14.3%). Metabolic flux analysis showed that flux through the pentose phosphate pathway was not significantly regulated by nitrogen concentration, suggesting that NADPH generation is not the limiting factor for lipid accumulation in Y. lipolytica. Furthermore, metabolic flux through malic enzyme was undetectable, confirming its non-regulatory role in lipid accumulation in this yeast. Nitrogen limitation significantly increased flux through ATP:citrate lyase (ACL), implying that ACL plays a key role in providing acetyl-CoA for lipid accumulation in Y. lipolytica.

  1. Simultaneous investigation of cardiac pyruvate dehydrogenase flux, Krebs cycle metabolism and pH, using hyperpolarized [1,2-(13)C2]pyruvate in vivo.

    Science.gov (United States)

    Chen, Albert P; Hurd, Ralph E; Schroeder, Marie A; Lau, Angus Z; Gu, Yi-ping; Lam, Wilfred W; Barry, Jennifer; Tropp, James; Cunningham, Charles H

    2012-02-01

    (13)C MR spectroscopy studies performed on hearts ex vivo and in vivo following perfusion of prepolarized [1-(13)C]pyruvate have shown that changes in pyruvate dehydrogenase (PDH) flux may be monitored non-invasively. However, to allow investigation of Krebs cycle metabolism, the (13)C label must be placed on the C2 position of pyruvate. Thus, the utilization of either C1 or C2 labeled prepolarized pyruvate as a tracer can only afford a partial view of cardiac pyruvate metabolism in health and disease. If the prepolarized pyruvate molecules were labeled at both C1 and C2 positions, then it would be possible to observe the downstream metabolites that were the results of both PDH flux ((13)CO(2) and H(13)CO(3)(-)) and Krebs cycle flux ([5-(13)C]glutamate) with a single dose of the agent. Cardiac pH could also be monitored in the same experiment, but adequate SNR of the (13)CO(2) resonance may be difficult to obtain in vivo. Using an interleaved selective RF pulse acquisition scheme to improve (13)CO(2) detection, the feasibility of using dual-labeled hyperpolarized [1,2-(13)C(2)]pyruvate as a substrate for dynamic cardiac metabolic MRS studies to allow simultaneous investigation of PDH flux, Krebs cycle flux and pH, was demonstrated in vivo.

  2. Dissolved organic matter and lake metabolism: Biogeochemistry and controls of nutrient flux dynamics to fresh waters. Technical progress report, January 1, 1990--December 31, 1991

    Energy Technology Data Exchange (ETDEWEB)

    Wetzel, R.G.

    1992-12-31

    The land-water interface region consists of two major components: the wetland, and the down-gradient adjacent littoral floating-leaved and submersed, macrophyte communities. Because of the importance of very high production and nutrient turnover of attached microbiota, a major emphasis of this investigation was placed upon these biota and their metabolic capacities for assimilation and release of organic compounds and nutrient retention and cycling. Examination of the capacities of wetland littoral communities to regulate fluxes of nutrients and organic compounds often has been limited to input-output analyses. These input-output data are an integral part of these investigations, but most of the research effort concentrated on the biotic and metabolic mechanisms that control fluxes and retention capacities and their effects upon biota in the down-gradient waters. The important regulatory capacities of dissolved organic compounds on enzyme reactivity was examined experimentally and coupled to the wetland-littoral organic carbon flux budgets.

  3. Systems biology of bacterial nitrogen fixation: High-throughput technology and its integrative description with constraint-based modeling

    Directory of Open Access Journals (Sweden)

    Resendis-Antonio Osbaldo

    2011-07-01

    Full Text Available Abstract Background Bacterial nitrogen fixation is the biological process by which atmospheric nitrogen is uptaken by bacteroids located in plant root nodules and converted into ammonium through the enzymatic activity of nitrogenase. In practice, this biological process serves as a natural form of fertilization and its optimization has significant implications in sustainable agricultural programs. Currently, the advent of high-throughput technology supplies with valuable data that contribute to understanding the metabolic activity during bacterial nitrogen fixation. This undertaking is not trivial, and the development of computational methods useful in accomplishing an integrative, descriptive and predictive framework is a crucial issue to decoding the principles that regulated the metabolic activity of this biological process. Results In this work we present a systems biology description of the metabolic activity in bacterial nitrogen fixation. This was accomplished by an integrative analysis involving high-throughput data and constraint-based modeling to characterize the metabolic activity in Rhizobium etli bacteroids located at the root nodules of Phaseolus vulgaris (bean plant. Proteome and transcriptome technologies led us to identify 415 proteins and 689 up-regulated genes that orchestrate this biological process. Taking into account these data, we: 1 extended the metabolic reconstruction reported for R. etli; 2 simulated the metabolic activity during symbiotic nitrogen fixation; and 3 evaluated the in silico results in terms of bacteria phenotype. Notably, constraint-based modeling simulated nitrogen fixation activity in such a way that 76.83% of the enzymes and 69.48% of the genes were experimentally justified. Finally, to further assess the predictive scope of the computational model, gene deletion analysis was carried out on nine metabolic enzymes. Our model concluded that an altered metabolic activity on these enzymes induced

  4. Ecosystem Metabolism and Air-Water Fluxes of Greenhouse Gases in High Arctic Wetland Ponds

    Science.gov (United States)

    Lehnherr, I.; Venkiteswaran, J.; St. Louis, V. L.; Emmerton, C.; Schiff, S. L.

    2012-12-01

    Freshwater lakes and wetlands can be very productive systems on the Arctic landscape compared to terrestrial tundra ecosystems and provide valuable resources to many organisms, including waterfowl, fish and humans. Rates of ecosystem productivity dictate how much energy flows through food webs, impacting the abundance of higher-level organisms (e.g., fish), as well as the net carbon balance, which determines whether a particular ecosystem is a source or sink of carbon. Climate change is predicted to result in warmer temperatures, increased precipitation and permafrost melting in the Arctic and is already altering northern ecosystems at unprecedented rates; however, it is not known how freshwater systems are responding to these changes. To predict how freshwater systems will respond to complex environmental changes, it is necessary to understand the key processes, such as primary production and ecosystem respiration, that are driving these systems. We sampled wetland ponds (n=8) and lakes (n=2) on northern Ellesmere Island (81° N, Nunavut, Canada) during the open water season for a suite of biogeochemical parameters, including concentrations of dissolved gases (O2, CO2, CH4, N2O) as well as stable-isotope ratios of dissolved inorganic carbon (δ13C-DIC), dissolved oxygen (δ18O-DO), and water (δ18O-H2O). We will present rates of primary production and ecosystem respiration, modeled from the concentration and stable isotope ratios of DIC and DO, as well as air-water gas exchange of greenhouse gases in these high Arctic ponds and lakes. Preliminary results demonstrate that ecosystem metabolism in these ponds was high enough to result in significant deviations in the isotope ratios of DIC and DO from atmospheric equilibrium conditions. In other words ecosystem rates of primary production and respiration were faster than gas exchange even in these small, shallow, well-mixed ponds. Furthermore, primary production was elevated enough at all sites except Lake Hazen, a

  5. Controlling the feed rate of glucose and propanol for the enhancement of erythromycin production and exploration of propanol metabolism fate by quantitative metabolic flux analysis.

    Science.gov (United States)

    Chen, Yong; Huang, Mingzhi; Wang, Zejian; Chu, Ju; Zhuang, Yingping; Zhang, Siliang

    2013-10-01

    In this paper, several different fermentation experiments were designed to address whether modulating glucose and propanol feeds could benefit the production level of erythromycin during pilot plant (30 L) fermentation. Results showed that glucose feed rate (determined by a set high or low culture pH) had no effect on erythromycin production, indicating that glucose was not the limiting factor for erythromycin biosynthesis under these conditions. It was found that decreasing glucose feed could stimulate the consumption of propanol, and the high erythromycin production (12.49 ± 0.50 mg ml⁻¹) was achieved by controlling the feed rates of glucose and propanol. The quantitative metabolic flux analysis disclosed that high propanol consumption increased the pool size of propionyl-CoA (~2.147 mmol g⁻¹ day⁻¹) and methylmalonyl-CoA (~1.708 mmol g⁻¹ day⁻¹). It was also found that 45-77 % of the propanol went into the TCA cycle which strengthened the conclusion that blocking the propionate pathway to TCA cycle could lead to a significant increase in erythromycin production in carbohydrate-based media (Reeves et al. Ind Microbiol Biotechnol 7:600-609, 2006). In addition, the results also suggested that a relative low intracellular ATP level resulting from low glucose feed did not limit the erythromycin biosynthesis, and a relatively high NADPH should be beneficial for erythromycin biosynthesis.

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

    Science.gov (United States)

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

    2012-12-01

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

  7. The short-chain fatty acid uptake fluxes by mice on a guar gum supplemented diet associate with amelioration of major biomarkers of the metabolic syndrome.

    Science.gov (United States)

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

    2014-01-01

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

  8. The short-chain fatty acid uptake fluxes by mice on a guar gum supplemented diet associate with amelioration of major biomarkers of the metabolic syndrome.

    Directory of Open Access Journals (Sweden)

    Gijs den Besten

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

  9. Validation of the doubly-labeled water (H/sup 3/H/sup 18/O) method for measuring water flux and energy metabolism in tenebrionid beetles

    Energy Technology Data Exchange (ETDEWEB)

    Cooper, P.D.

    1981-01-01

    Doubly-labeled water (H/sup 3/H/sup 18/O) has been used to determine water flux and energy metabolism in a variety of vertebrates. This study examines the applicability of this technique to arthropods. The theory of the technique depends upon the assumption that doubly-labeled water introduced into the animal's body water equilibrates with water and carbon dioxide by the action of carbonic anhydrase. Tritium (/sup 3/H) is lost from the animal only with water while oxygen-18 is lost with both water and carbon dioxide. The difference bwtween the rates of loss of the two isotopes is proportional to CO/sub 2/ loss rate. Validation of the use of tritiated water for measuring water flux was accomplished by comparing gravimetric measurements of water gain with flux rates determined by loss of tritiated water. At room humidity, an overestimate for influx calculated from labeled water calculations was found, averaging 12 mg H/sub 2/O (g.d)/sup -1/. Comparison of CO/sub 2/ loss rate determined isotopically with rates of CO/sub 2/ loss determined by standard metabolic rates also yielded overestimates for the isotopic technique, overestimates ranging between 20 and 30%. The relevance of this for studies using labeled water for studying water fluxes and free metabolism of free-ranging arthropods is discussed.

  10. Gill lipid metabolism and unidirectional Na+ flux in the European eel (Anguilla anguilla) after transfer to dilute media

    DEFF Research Database (Denmark)

    Hansen, H.J.M.; Grosell, M.; Rosenkilde, P.

    1999-01-01

    positive linear correlation of percentage (14C) wax alcohols with log [22Na efflux]. Based on the observed parallel between Naf flux and gill lipid metabolism, it is suggested that the eel reacts at first to a loss of Na+ by synthesizing wax alcohols that can tighten the gill membrane. (C) 1999 Elsevier......+ uptake rate was 12 mu mol kg(-1) h(-1), i.e., the general picture in DW was a net Na+ loss. In another similar experiment, groups of three FW-adapted eels were incubated in vivo for up to 24 h with (C-14) acetate added as lipid precursor to the ambient water. Incubation in FW showed about 20......% of the total C-14-activity incorporated into gill lipids as (C-14) wax alcohols (WA; octadecanol and eicosanol). This percentage went up to 50% shortly after transfer to DW and came down again to about 20% after 2 weeks in DW. Single eels labelled with Na-22 in the plasma showed a statistically significant...

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

    Science.gov (United States)

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

    2016-02-01

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

  12. Metabolic profiling and flux analysis of MEL-2 human embryonic stem cells during exponential growth at physiological and atmospheric oxygen concentrations.

    Science.gov (United States)

    Turner, Jennifer; Quek, Lake-Ee; Titmarsh, Drew; Krömer, Jens O; Kao, Li-Pin; Nielsen, Lars; Wolvetang, Ernst; Cooper-White, Justin

    2014-01-01

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

  13. A Constraint-Based Geospatial Data Integration System for Wildfire Management Project

    Data.gov (United States)

    National Aeronautics and Space Administration — We propose to develop a constraint-based system for automatically integrating online, heterogeneous data sources with geospatial data produced by NASA in order to...

  14. A Constraint-Based Geospatial Data Integration System for Wildfire Management Project

    Data.gov (United States)

    National Aeronautics and Space Administration — We propose to implement a constraint-based data integration system for wildfire intelligence, for use during both the pre-planning and event response phases of...

  15. ¹³C metabolic flux analysis identifies an unusual route for pyruvate dissimilation in mycobacteria which requires isocitrate lyase and carbon dioxide fixation.

    Directory of Open Access Journals (Sweden)

    Dany J V Beste

    2011-07-01

    Full Text Available Mycobacterium tuberculosis requires the enzyme isocitrate lyase (ICL for growth and virulence in vivo. The demonstration that M. tuberculosis also requires ICL for survival during nutrient starvation and has a role during steady state growth in a glycerol limited chemostat indicates a function for this enzyme which extends beyond fat metabolism. As isocitrate lyase is a potential drug target elucidating the role of this enzyme is of importance; however, the role of isocitrate lyase has never been investigated at the level of in vivo fluxes. Here we show that deletion of one of the two icl genes impairs the replication of Mycobacterium bovis BCG at slow growth rate in a carbon limited chemostat. In order to further understand the role of isocitrate lyase in the central metabolism of mycobacteria the effect of growth rate on the in vivo fluxes was studied for the first time using ¹³C-metabolic flux analysis (MFA. Tracer experiments were performed with steady state chemostat cultures of BCG or M. tuberculosis supplied with ¹³C labeled glycerol or sodium bicarbonate. Through measurements of the ¹³C isotopomer labeling patterns in protein-derived amino acids and enzymatic activity assays we have identified the activity of a novel pathway for pyruvate dissimilation. We named this the GAS pathway because it utilizes the Glyoxylate shunt and Anapleurotic reactions for oxidation of pyruvate, and Succinyl CoA synthetase for the generation of succinyl CoA combined with a very low flux through the succinate--oxaloacetate segment of the tricarboxylic acid cycle. We confirm that M. tuberculosis can fix carbon from CO₂ into biomass. As the human host is abundant in CO₂ this finding requires further investigation in vivo as CO₂ fixation may provide a point of vulnerability that could be targeted with novel drugs. This study also provides a platform for further studies into the metabolism of M. tuberculosis using ¹³C-MFA.

  16. Enhanced production of resveratrol derivatives in tobacco plants by improving the metabolic flux of intermediates in the phenylpropanoid pathway.

    Science.gov (United States)

    Jeong, Yu Jeong; An, Chul Han; Woo, Su Gyeong; Park, Ji Hye; Lee, Ki-Won; Lee, Sang-Hoon; Rim, Yeonggil; Jeong, Hyung Jae; Ryu, Young Bae; Kim, Cha Young

    2016-09-01

    The biosynthesis of flavonoids such as anthocyanin and stilbenes has attracted increasing attention because of their potential health benefits. Anthocyanins and stilbenes share common phenylpropanoid precursor pathways. We previously reported that the overexpression of sweetpotato IbMYB1a induced anthocyanin pigmentation in transgenic tobacco (Nicotiana tabacum) plants. In the present study, transgenic tobacco (Nicotiana tabacum SR1) plants (STS-OX and ROST-OX) expressing the RpSTS gene encoding stilbene synthase from rhubarb (Rheum palmatum L. cv. Jangyeop) and the RpSTS and VrROMT genes encoding resveratrol O-methyltransferase from frost grape (Vitis riparia) were generated under the control of 35S promoter. Phenotypic alterations in floral organs, such as a reduction in floral pigments and male sterility, were observed in STS-OX transgenic tobacco plants. However, we failed to obtain STS-OX and ROST-OX plants with high levels of resveratrol compounds. Therefore, to improve the production of resveratrol derivatives in plants, we cross-pollinated flowers of STS-OX or ROST-OX and IbMYB1a-OX transgenic lines (SM and RSM). Phenotypic changes in vegetative and reproductive development of SM and RSM plants were observed. Furthermore, by HPLC and LC-MS analyses, we found enhanced production of resveratrol derivatives such as piceid, piceid methyl ether, resveratrol methyl ether O-hexoside, and 5-methyl resveratrol-3,4'-O-β-D-diglucopyranoside in SM and RSM cross-pollinated lines. Here, total contents of trans- and cis-piceids ranged from approximately 104-240 µg/g fresh weight in SM (F2). Collectively, we suggest that coexpression of RpSTS and IbMYB1a via cross-pollination can induce enhanced production of resveratrol compounds in plants by increasing metabolic flux into stilbenoid biosynthesis.

  17. 13C-metabolic flux ratio and novel carbon path analyses confirmed that Trichoderma reesei uses primarily the respirative pathway also on the preferred carbon source glucose

    Directory of Open Access Journals (Sweden)

    Saloheimo Markku

    2009-10-01

    Full Text Available Abstract Background The filamentous fungus Trichoderma reesei is an important host organism for industrial enzyme production. It is adapted to nutrient poor environments where it is capable of producing large amounts of hydrolytic enzymes. In its natural environment T. reesei is expected to benefit from high energy yield from utilization of respirative metabolic pathway. However, T. reesei lacks metabolic pathway reconstructions and the utilization of the respirative pathway has not been investigated on the level of in vivo fluxes. Results The biosynthetic pathways of amino acids in T. reesei supported by genome-level evidence were reconstructed with computational carbon path analysis. The pathway reconstructions were a prerequisite for analysis of in vivo fluxes. The distribution of in vivo fluxes in both wild type strain and cre1, a key regulator of carbon catabolite repression, deletion strain were quantitatively studied by performing 13C-labeling on both repressive carbon source glucose and non-repressive carbon source sorbitol. In addition, the 13C-labeling on sorbitol was performed both in the presence and absence of sophorose that induces the expression of cellulase genes. Carbon path analyses and the 13C-labeling patterns of proteinogenic amino acids indicated high similarity between biosynthetic pathways of amino acids in T. reesei and yeast Saccharomyces cerevisiae. In contrast to S. cerevisiae, however, mitochondrial rather than cytosolic biosynthesis of Asp was observed under all studied conditions. The relative anaplerotic flux to the TCA cycle was low and thus characteristic to respiratory metabolism in both strains and independent of the carbon source. Only minor differences were observed in the flux distributions of the wild type and cre1 deletion strain. Furthermore, the induction of the hydrolytic gene expression did not show altered flux distributions and did not affect the relative amino acid requirements or relative anabolic

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

    Science.gov (United States)

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

    2017-08-29

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

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

    Directory of Open Access Journals (Sweden)

    Sugimoto Masahiro

    2006-07-01

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

  20. Consequences of phosphoenolpyruvate:sugar phosphotranferase system and pyruvate kinase isozymes inactivation in central carbon metabolism flux distribution in Escherichia coli

    Directory of Open Access Journals (Sweden)

    Meza Eugenio

    2012-09-01

    Full Text Available Abstract Background In Escherichia coli phosphoenolpyruvate (PEP is a key central metabolism intermediate that participates in glucose transport, as precursor in several biosynthetic pathways and it is involved in allosteric regulation of glycolytic enzymes. In this work we generated W3110 derivative strains that lack the main PEP consumers PEP:sugar phosphotransferase system (PTS- and pyruvate kinase isozymes PykA and PykF (PTS-pykA- and PTS-pykF-. To characterize the effects of these modifications on cell physiology, carbon flux distribution and aromatics production capacity were determined. Results When compared to reference strain W3110, strain VH33 (PTS- displayed lower specific rates for growth, glucose consumption and acetate production as well as a higher biomass yield from glucose. These phenotypic effects were even more pronounced by the additional inactivation of PykA or PykF. Carbon flux analysis revealed that PTS inactivation causes a redirection of metabolic flux towards biomass formation. A cycle involving PEP carboxylase (Ppc and PEP carboxykinase (Pck was detected in all strains. In strains W3110, VH33 (PTS- and VH35 (PTS-, pykF-, the net flux in this cycle was inversely correlated with the specific rate of glucose consumption and inactivation of Pck in these strains caused a reduction in growth rate. In the PTS- background, inactivation of PykA caused a reduction in Ppc and Pck cycling as well as a reduction in flux to TCA, whereas inactivation of PykF caused an increase in anaplerotic flux from PEP to OAA and an increased flux to TCA. The wild-type and mutant strains were modified to overproduce L-phenylalanine. In resting cells experiments, compared to reference strain, a 10, 4 and 7-fold higher aromatics yields from glucose were observed as consequence of PTS, PTS PykA and PTS PykF inactivation. Conclusions Metabolic flux analysis performed on strains lacking the main activities generating pyruvate from PEP revealed the high

  1. ToMI-FBA: A genome-scale metabolic flux based algorithm to select optimum hosts and media formulations for expressing pathways of interest

    Directory of Open Access Journals (Sweden)

    Hadi Nazem-Bokaee

    2015-09-01

    Full Text Available The Total Membrane Influx constrained Flux Balance Analysis (ToMI-FBA algorithm was developed in this research as a new tool to help researchers decide which microbial host and medium formulation are optimal for expressing a new metabolic pathway. ToMI-FBA relies on genome-scale metabolic flux modeling and a novel in silico cell membrane influx constraint that specifies the flux of atoms (not molecules into the cell through all possible membrane transporters. The ToMI constraint is constructed through the addition of an extra row and column to the stoichiometric matrix of a genome-scale metabolic flux model. In this research, the mathematical formulation of the ToMI constraint is given along with four case studies that demonstrate its usefulness. In Case Study 1, ToMI-FBA returned an optimal culture medium formulation for the production of isobutanol from Bacillus subtilis. Significant levels of L-valine were recommended to optimize production, and this result has been observed experimentally. In Case Study 2, it is demonstrated how the carbon to nitrogen uptake ratio can be specified as an additional ToMI-FBA constraint. This was investigated for maximizing medium chain length polyhydroxyalkanoates (mcl-PHA production from Pseudomonas putida KT2440. In Case Study 3, ToMI-FBA revealed a strategy of adding cellobiose as a means to increase ethanol selectivity during the stationary growth phase of Clostridium acetobutylicum ATCC 824. This strategy was also validated experimentally. Finally, in Case Study 4, B. subtilis was identified as a superior host to Escherichia coli, Saccharomyces cerevisiae, and Synechocystis PCC6803 for the production of artemisinate.

  2. Constraint-based probabilistic learning of metabolic pathways from tomato volatiles

    NARCIS (Netherlands)

    Gavai, A.K.; Tikunov, Y.M.; Ursem, R.A.; Bovy, A.G.; Eeuwijk, van F.A.; Nijveen, H.; Lucas, P.J.F.; Leunissen, J.A.M.

    2009-01-01

    Clustering and correlation analysis techniques have become popular tools for the analysis of data produced by metabolomics experiments. The results obtained from these approaches provide an overview of the interactions between objects of interest. Often in these experiments, one is more interested i

  3. Modelling microbial metabolic rewiring during growth in a complex medium.

    Science.gov (United States)

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

    2016-11-24

    In their natural environment, bacteria face a wide range of environmental conditions that change over time and that impose continuous rearrangements at all the cellular levels (e.g. gene expression, metabolism). When facing a nutritionally rich environment, for example, microbes first use the preferred compound(s) and only later start metabolizing the other one(s). A systemic re-organization of the overall microbial metabolic network in response to a variation in the composition/concentration of the surrounding nutrients has been suggested, although the range and the entity of such modifications in organisms other than a few model microbes has been scarcely described up to now. We used multi-step constraint-based metabolic modelling to simulate the growth in a complex medium over several time steps of the Antarctic model organism Pseudoalteromonas haloplanktis TAC125. As each of these phases is characterized by a specific set of amino acids to be used as carbon and energy source our modelling framework describes the major consequences of nutrients switching at the system level. The model predicts that a deep metabolic reprogramming might be required to achieve optimal biomass production in different stages of growth (different medium composition), with at least half of the cellular metabolic network involved (more than 50% of the metabolic genes). Additionally, we show that our modelling framework is able to capture metabolic functional association and/or common regulatory features of the genes embedded in our reconstruction (e.g. the presence of common regulatory motifs). Finally, to explore the possibility of a sub-optimal biomass objective function (i.e. that cells use resources in alternative metabolic processes at the expense of optimal growth) we have implemented a MOMA-based approach (called nutritional-MOMA) and compared the outcomes with those obtained with Flux Balance Analysis (FBA). Growth simulations under this scenario revealed the deep impact of

  4. The human metabolic reconstruction Recon 1 directs hypotheses of novel human metabolic functions

    Directory of Open Access Journals (Sweden)

    Thiele Ines

    2011-10-01

    Full Text Available Abstract Background Metabolic network reconstructions formalize our knowledge of metabolism. Gaps in these networks pinpoint regions of metabolism where biological components and functions are "missing." At the same time, a major challenge in the post genomic era involves characterisation of missing biological components to complete genome annotation. Results We used the human metabolic network reconstruction RECON 1 and established constraint-based modelling tools to uncover novel functions associated with human metabolism. Flux variability analysis identified 175 gaps in RECON 1 in the form of blocked reactions. These gaps were unevenly distributed within metabolic pathways but primarily found in the cytosol and often caused by compounds whose metabolic fate, rather than production, is unknown. Using a published algorithm, we computed gap-filling solutions comprised of non-organism specific metabolic reactions capable of bridging the identified gaps. These candidate solutions were found to be dependent upon the reaction environment of the blocked reaction. Importantly, we showed that automatically generated solutions could produce biologically realistic hypotheses of novel human metabolic reactions such as of the fate of iduronic acid following glycan degradation and of N-acetylglutamate in amino acid metabolism. Conclusions The results demonstrate how metabolic models can be utilised to direct hypotheses of novel metabolic functions in human metabolism; a process that we find is heavily reliant upon manual curation and biochemical insight. The effectiveness of a systems approach for novel biochemical pathway discovery in mammals is demonstrated and steps required to tailor future gap filling algorithms to mammalian metabolic networks are proposed.

  5. Metabolism

    Science.gov (United States)

    ... Are More Common in People With Type 1 Diabetes Metabolic Syndrome Your Child's Weight Healthy Eating Endocrine System Blood Test: Basic Metabolic Panel (BMP) Activity: Endocrine System Growth Disorders Diabetes Center Thyroid Disorders Your Endocrine System Movie: Endocrine ...

  6. Metabolism

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    2008255 Serum adiponectin level declines in the elderly with metabolic syndrome.WU Xiaoyan(吴晓琰),et al.Dept Geriatr,Huashan Hosp,Fudan UnivShanghai200040.Chin J Geriatr2008;27(3):164-167.Objective To investigate the correlation between ser-um adiponectin level and metabolic syndrome in the elderly·Methods Sixty-one subjects with metabolic syndrome and140age matched subjects without metabolic

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

    Directory of Open Access Journals (Sweden)

    Ahmad A Mannan

    Full Text Available 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.

  8. Tagging French comparing a statistical and a constraint-based method

    CERN Document Server

    Chanod, J P; Chanod, Jean-Pierre; Tapanainen, Pasi

    1995-01-01

    In this paper we compare two competing approaches to part-of-speech tagging, statistical and constraint-based disambiguation, using French as our test language. We imposed a time limit on our experiment: the amount of time spent on the design of our constraint system was about the same as the time we used to train and test the easy-to-implement statistical model. We describe the two systems and compare the results. The accuracy of the statistical method is reasonably good, comparable to taggers for English. But the constraint-based tagger seems to be superior even with the limited time we allowed ourselves for rule development.

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

    DEFF Research Database (Denmark)

    DiNuzzo, Mauro; Giove, Federico; Maraviglia, Bruno

    2016-01-01

    utilization. In order to examine the participation of astrocytic energy metabolism in brain ion homeostasis, here we attempted to devise a simple stoichiometric relation linking glutamatergic neurotransmission to Na(+) and K(+) ionic currents. To this end, we took into account ion pumps and voltage....../ligand-gated channels using the stoichiometry derived from available energy budget for neocortical signaling and incorporated this stoichiometric relation into a computational metabolic model of neuron-astrocyte interactions. We aimed at reproducing the experimental observations about rates of metabolic pathways...

  10. 13C based proteinogenic amino acid (PAA and metabolic flux ratio analysis of Lactococcus lactis reveals changes in pentose phosphate (PP pathway in response to agitation and temperature related stresses

    Directory of Open Access Journals (Sweden)

    Kamalrul Azlan Azizan

    2017-07-01

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

  11. Flux control exerted by mitochondrial outer membrane carnitine palmitoyltransferase over beta-oxidation, ketogenesis and tricarboxylic acid cycle activity in hepatocytes isolated from rats in different metabolic states.

    Science.gov (United States)

    Drynan, L; Quant, P A; Zammit, V A

    1996-08-01

    The Flux Control Coefficients of mitochondrial outer membrane carnitine palmitoyltransferase (CPT I) with respect to the overall rates of beta-oxidation, ketogenesis and tricarboxylic acid cycle activity were measured in hepatocytes isolated from rats in different metabolic states (fed, 24 h-starved, starved-refed and starved/insulin-treated). These conditions were chosen because there is controversy as to whether, when significant control ceases to be exerted by CPT I over the rate of fatty oxidation [Moir and Zammit (1994) Trends Biochem. Sci. 19, 313-317], this is transferred to one or more steps proximal to acylcarnitine synthesis (e.g. decreased delivery of fatty acids to the liver) or to the reaction catalysed by mitochondrial 3-hydroxy-3-methyl-glutaryl-CoA synthase [Hegardt (1995) Biochem. Soc. Trans. 23, 486-490]. Therefore isolated hepatocytes were used in the present study to exclude the involvement of changes in the rate of delivery of non-esterified fatty acids (NEFA) to the liver, such as occur in vivo, and to ascertain whether, under conditions of constant supply of NEFA, CPT I retains control over the relevant fluxes of fatty acid oxidation to ketones and carbon dioxide, or whether control is transferred to another (intrahepatocytic) site. The results clearly show that the Flux Control Coefficients of CPT I with respect to overall beta-oxidation and ketogenesis are very high under all conditions investigated, indicating that control is not lost to another intrahepatic site during the metabolic transitions studied. The control of CPT I over tricarboxylic acid cycle activity was always very low. The significance of these findings for the integration of fatty acid and carbohydrate metabolism in the liver is discussed.

  12. Photobioreactor design for isotopic non-stationary 13C-metabolic flux analysis (INST 13C-MFA) under photoautotrophic conditions.

    Science.gov (United States)

    Martzolff, Arnaud; Cahoreau, Edern; Cogne, Guillaume; Peyriga, Lindsay; Portais, Jean-Charles; Dechandol, Emmanuel; Le Grand, Fabienne; Massou, Stéphane; Gonçalves, Olivier; Pruvost, Jérémy; Legrand, Jack

    2012-12-01

    Adaptive metabolic behavior of photoautotrophic microorganisms toward genetic and environmental perturbations can be interpreted in a quantitative depiction of carbon flow through a biochemical reaction network using isotopic non-stationary (13) C-metabolic flux analysis (INST (13) C-MFA). To evaluate (13) C-metabolic flux maps for Chlamydomonas reinhardtii, an original experimental framework was designed allowing rapid, reliable collection of high-quality isotopomer data against time. It involved (i) a short-time (13) C labeling injection device based on mixing control in a torus-shaped photobioreactor with plug-flow hydrodynamics allowing a sudden step-change in the (13) C proportion in the substrate feed and (ii) a rapid sampling procedure using an automatic fast filtration method coupled to a manual rapid liquid nitrogen quenching step. (13) C-substrate labeling enrichment was controlled through the total dissolved inorganic carbon concentration in the pulsed solution. First results were obtained from steady-state continuous culture measurements allowing the characterization of the kinetics of label incorporation into light-limited growing cells cultivated in a photobioreactor operating at the maximal biomass productivity for an incident photon flux density of 200 µmol m(-2) s(-1). (13)C label incorporation was measured for 21 intracellular metabolites using IC-MS/MS in 58 samples collected across a labeling experiment duration of 7 min. The fastest labeling rate was observed for 2/3-phosphoglycerate with an apparent isotopic stationary state reached after 300 s. The labeling rate was consistent with the optimized mixing time of about 4.9 s inside the reactor and the shortest reliable sampling period assessed at 5 s.

  13. GC-MS/MS survey of collision-induced dissociation of tert-butyldimethylsilyl-derivatized amino acids and its application to (13)C-metabolic flux analysis of Escherichia coli central metabolism.

    Science.gov (United States)

    Okahashi, Nobuyuki; Kawana, Shuichi; Iida, Junko; Shimizu, Hiroshi; Matsuda, Fumio

    2016-09-01

    Stable isotope labeling experiments using mass spectrometry have been employed to investigate carbon flow levels (metabolic flux) in mammalian, plant, and microbial cells. To achieve a more precise (13)C-metabolic flux analysis ((13)C-MFA), novel fragmentations of tert-butyldimethylsilyl (TBDMS)-amino acids were investigated by gas chromatography-tandem mass spectrometry (GC-MS/MS). The product ion scan analyses of 15 TBDMS-amino acids revealed 24 novel fragment ions. The amino acid-derived carbons included in the five fragment ions were identified by the analyses of (13)C-labeled authentic standards. The identification of the fragment ion at m/z 170 indicated that the isotopic abundance of S-methyl carbon in methionine could be determined from the cleavage of C5 in the precursor of [M-159](+) (m/z 218). It was also confirmed that the precision of (13)C-MFA in Escherichia coli central carbon metabolism could be improved by introducing (13)C-labeling data derived from novel fragmentations. Graphical Abstract Novel collision-induced dissociation fragmentations of tert-butyldimethylsilyl amino acids were investigated and identified by GC-MS/MS.

  14. Enzyme oscillation can enhance the thermodynamic efficiency of cellular metabolism: consequence of anti-phase coupling between reaction flux and affinity

    Science.gov (United States)

    Himeoka, Yusuke; Kaneko, Kunihiko

    2016-04-01

    Cells generally convert nutrient resources to products via energy transduction. Accordingly, the thermodynamic efficiency of this conversion process is one of the most essential characteristics of living organisms. However, although these processes occur under conditions of dynamic metabolism, most studies of cellular thermodynamic efficiency have been restricted to examining steady states; thus, the relevance of dynamics to this efficiency has not yet been elucidated. Here, we develop a simple model of metabolic reactions with anabolism-catabolism coupling catalyzed by enzymes. Through application of external oscillation in the enzyme abundances, the thermodynamic efficiency of metabolism was found to be improved. This result is in strong contrast with that observed in the oscillatory input, in which the efficiency always decreased with oscillation. This improvement was effectively achieved by separating the anabolic and catabolic reactions, which tend to disequilibrate each other, and taking advantage of the temporal oscillations so that each of the antagonistic reactions could progress near equilibrium. In this case, anti-phase oscillation between the reaction flux and chemical affinity through oscillation of enzyme abundances is essential. This improvement was also confirmed in a model capable of generating autonomous oscillations in enzyme abundances. Finally, the possible relevance of the improvement in thermodynamic efficiency is discussed with respect to the potential for manipulation of metabolic oscillations in microorganisms.

  15. Enzyme oscillation can enhance the thermodynamic efficiency of cellular metabolism: consequence of anti-phase coupling between reaction flux and affinity.

    Science.gov (United States)

    Himeoka, Yusuke; Kaneko, Kunihiko

    2016-04-05

    Cells generally convert nutrient resources to products via energy transduction. Accordingly, the thermodynamic efficiency of this conversion process is one of the most essential characteristics of living organisms. However, although these processes occur under conditions of dynamic metabolism, most studies of cellular thermodynamic efficiency have been restricted to examining steady states; thus, the relevance of dynamics to this efficiency has not yet been elucidated. Here, we develop a simple model of metabolic reactions with anabolism-catabolism coupling catalyzed by enzymes. Through application of external oscillation in the enzyme abundances, the thermodynamic efficiency of metabolism was found to be improved. This result is in strong contrast with that observed in the oscillatory input, in which the efficiency always decreased with oscillation. This improvement was effectively achieved by separating the anabolic and catabolic reactions, which tend to disequilibrate each other, and taking advantage of the temporal oscillations so that each of the antagonistic reactions could progress near equilibrium. In this case, anti-phase oscillation between the reaction flux and chemical affinity through oscillation of enzyme abundances is essential. This improvement was also confirmed in a model capable of generating autonomous oscillations in enzyme abundances. Finally, the possible relevance of the improvement in thermodynamic efficiency is discussed with respect to the potential for manipulation of metabolic oscillations in microorganisms.

  16. Constraint-Based Modeling: From Cognitive Theory to Computer Tutoring--and Back Again

    Science.gov (United States)

    Ohlsson, Stellan

    2016-01-01

    The ideas behind the constraint-based modeling (CBM) approach to the design of intelligent tutoring systems (ITSs) grew out of attempts in the 1980's to clarify how declarative and procedural knowledge interact during skill acquisition. The learning theory that underpins CBM was based on two conceptual innovations. The first innovation was to…

  17. Experience Report: Constraint-Based Modelling and Simulation of Railway Emergency Response Plans

    DEFF Research Database (Denmark)

    Debois, Søren; Hildebrandt, Thomas; Sandberg, Lene

    2016-01-01

    We report on experiences from a case study applying a constraint-based process-modelling and -simulation tool, dcrgraphs.net, to the modelling and rehearsal of railway emergency response plans with domain experts. The case study confirmed the approach as a viable means for domain experts to analyse...... and security processes in the danish public transport sector and their dependency on ICT....

  18. ASPIRE: An Authoring System and Deployment Environment for Constraint-Based Tutors

    Science.gov (United States)

    Mitrovic, Antonija; Martin, Brent; Suraweera, Pramuditha; Zakharov, Konstantin; Milik, Nancy; Holland, Jay; McGuigan, Nicholas

    2009-01-01

    Over the last decade, the Intelligent Computer Tutoring Group (ICTG) has implemented many successful constraint-based Intelligent Tutoring Systems (ITSs) in a variety of instructional domains. Our tutors have proven their effectiveness not only in controlled lab studies but also in real classrooms, and some of them have been commercialized.…

  19. An Improved Constraint-based system for the verification of security protocols

    NARCIS (Netherlands)

    Corin, R.J.; Etalle, Sandro; Hermenegildo, Manuel V.; Puebla, German

    We propose a constraint-based system for the verification of security protocols that improves upon the one developed by Millen and Shmatikov. Our system features (1) a significantly more efficient implementation, (2) a monotonic behavior, which also allows to detect aws associated to partial runs

  20. Constraint-based solver for the Military unit path finding problem

    CSIR Research Space (South Africa)

    Leenen, L

    2010-04-01

    Full Text Available -based approach because it requires flexibility in modelling. The authors formulate the MUPFP as a constraint satisfaction problem and a constraint-based extension of the search algorithm. The concept demonstrator uses a provided map, for example taken from Google...

  1. An Improved Constraint-based system for the verification of security protocols

    NARCIS (Netherlands)

    Corin, Ricardo; Etalle, Sandro; Hermenegildo, Manuel V.; Puebla, German

    2002-01-01

    We propose a constraint-based system for the verification of security protocols that improves upon the one developed by Millen and Shmatikov. Our system features (1) a significantly more efficient implementation, (2) a monotonic behavior, which also allows to detect aws associated to partial runs an

  2. Identification of enzymes and quantification of metabolic fluxes in the wild type and in a recombinant Aspergillus oryzae strain

    DEFF Research Database (Denmark)

    Pedersen, Henrik; Carlsen, Morten; Nielsen, Jens Bredal

    1999-01-01

    Two alpha-amylase-producing strains of Aspergillus oryzae, a wild-type strain and a recombinant containing additional copies of the alpha-amylase gene, were characterized,vith respect to enzyme activities, localization of enzymes to the mitochondria or cytosol, macromolecular composition...... or nitrate as the nitrogen source. The flux through the pentose phosphate pathway increased with increasing specific growth rate. The fluxes through the pentose phosphate pathway were 15 to 26% higher for the recombinant strain than for the wild-type strain....

  3. Effect of iclR and arcA knockouts on biomass formation and metabolic fluxes in Escherichia coli K12 and its implications on understanding the metabolism of Escherichia coli BL21 (DE3

    Directory of Open Access Journals (Sweden)

    Charlier Daniel

    2011-04-01

    Full Text Available Abstract Background Gene expression is regulated through a complex interplay of different transcription factors (TFs which can enhance or inhibit gene transcription. ArcA is a global regulator that regulates genes involved in different metabolic pathways, while IclR as a local regulator, controls the transcription of the glyoxylate pathway genes of the aceBAK operon. This study investigates the physiological and metabolic consequences of arcA and iclR deletions on E. coli K12 MG1655 under glucose abundant and limiting conditions and compares the results with the metabolic characteristics of E. coli BL21 (DE3. Results The deletion of arcA and iclR results in an increase in the biomass yield both under glucose abundant and limiting conditions, approaching the maximum theoretical yield of 0.65 c-mole/c-mole glucose under glucose abundant conditions. This can be explained by the lower flux through several CO2 producing pathways in the E. coli K12 ΔarcAΔiclR double knockout strain. Due to iclR gene deletion, the glyoxylate pathway is activated resulting in a redirection of 30% of the isocitrate molecules directly to succinate and malate without CO2 production. Furthermore, a higher flux at the entrance of the TCA was noticed due to arcA gene deletion, resulting in a reduced production of acetate and less carbon loss. Under glucose limiting conditions the flux through the glyoxylate pathway is further increased in the ΔiclR knockout strain, but this effect was not observed in the double knockout strain. Also a striking correlation between the glyoxylate flux data and the isocitrate lyase activity was observed for almost all strains and under both growth conditions, illustrating the transcriptional control of this pathway. Finally, similar central metabolic fluxes were observed in E. coli K12 ΔarcA ΔiclR compared to the industrially relevant E. coli BL21 (DE3, especially with respect to the pentose pathway, the glyoxylate pathway, and the TCA

  4. Molecular System Bioenergics of the Heart: Experimental Studies of Metabolic Compartmentation and Energy Fluxes versus Computer Modeling

    Directory of Open Access Journals (Sweden)

    Valdur Saks

    2011-12-01

    Full Text Available In this review we analyze the recent important and remarkable advancements in studies of compartmentation of adenine nucleotides in muscle cells due to their binding to macromolecular complexes and cellular structures, which results in non-equilibrium steady state of the creatine kinase reaction. We discuss the problems of measuring the energy fluxes between different cellular compartments and their simulation by using different computer models. Energy flux determinations by 18O transfer method have shown that in heart about 80% of energy is carried out of mitochondrial intermembrane space into cytoplasm by phosphocreatine fluxes generated by mitochondrial creatine kinase from adenosine triphosphate (ATP, produced by ATP Synthasome. We have applied the mathematical model of compartmentalized energy transfer for analysis of experimental data on the dependence of oxygen consumption rate on heart workload in isolated working heart reported by Williamson et al. The analysis of these data show that even at the maximal workloads and respiration rates, equal to 174 µmol O2 per min per g dry weight, phosphocreatine flux, and not ATP, carries about 80–85% percent of energy needed out of mitochondria into the cytosol. We analyze also the reasons of failures of several computer models published in the literature to correctly describe the experimental data.

  5. Nitrate addition to groundwater impacted by ethanol-blended fuel accelerates ethanol removal and mitigates the associated metabolic flux dilution and inhibition of BTEX biodegradation.

    Science.gov (United States)

    Corseuil, Henry Xavier; Gomez, Diego E; Schambeck, Cássio Moraes; Ramos, Débora Toledo; Alvarez, Pedro J J

    2015-03-01

    A comparison of two controlled ethanol-blended fuel releases under monitored natural attenuation (MNA) versus nitrate biostimulation (NB) illustrates the potential benefits of augmenting the electron acceptor pool with nitrate to accelerate ethanol removal and thus mitigate its inhibitory effects on BTEX biodegradation. Groundwater concentrations of ethanol and BTEX were measured 2 m downgradient of the source zones. In both field experiments, initial source-zone BTEX concentrations represented less than 5% of the dissolved total organic carbon (TOC) associated with the release, and measurable BTEX degradation occurred only after the ethanol fraction in the multicomponent substrate mixture decreased sharply. However, ethanol removal was faster in the nitrate amended plot (1.4 years) than under natural attenuation conditions (3.0 years), which led to faster BTEX degradation. This reflects, in part, that an abundant substrate (ethanol) can dilute the metabolic flux of target pollutants (BTEX) whose biodegradation rate eventually increases with its relative abundance after ethanol is preferentially consumed. The fate and transport of ethanol and benzene were accurately simulated in both releases using RT3D with our general substrate interaction module (GSIM) that considers metabolic flux dilution. Since source zone benzene concentrations are relatively low compared to those of ethanol (or its degradation byproduct, acetate), our simulations imply that the initial focus of cleanup efforts (after free-product recovery) should be to stimulate the degradation of ethanol (e.g., by nitrate addition) to decrease its fraction in the mixture and speed up BTEX biodegradation.

  6. Lipid Metabolic Versatility in Malassezia spp. Yeasts Studied through Metabolic Modeling.

    Science.gov (United States)

    Triana, Sergio; de Cock, Hans; Ohm, Robin A; Danies, Giovanna; Wösten, Han A B; Restrepo, Silvia; González Barrios, Andrés F; Celis, Adriana

    2017-01-01

    Malassezia species are lipophilic and lipid-dependent yeasts belonging to the human and animal microbiota. Typically, they are isolated from regions rich in sebaceous glands. They have been associated with dermatological diseases such as seborrheic dermatitis, pityriasis versicolor, atopic dermatitis, and folliculitis. The genomes of Malassezia globosa, Malassezia sympodialis, and Malassezia pachydermatis lack the genes related to fatty acid synthesis. Here, the lipid-synthesis pathways of these species, as well as of Malassezia furfur, and of an atypical M. furfur variant were reconstructed using genome data and Constraints Based Reconstruction and Analysis. To this end, the genomes of M. furfur CBS 1878 and the atypical M. furfur 4DS were sequenced and annotated. The resulting Enzyme Commission numbers and predicted reactions were similar to the other Malassezia strains despite the differences in their genome size. Proteomic profiling was utilized to validate flux distributions. Flux differences were observed in the production of steroids in M. furfur and in the metabolism of butanoate in M. pachydermatis. The predictions obtained via these metabolic reconstructions also suggested defects in the assimilation of palmitic acid in M. globosa, M. sympodialis, M. pachydermatis, and the atypical variant of M. furfur, but not in M. furfur. These predictions were validated via physiological characterization, showing the predictive power of metabolic network reconstructions to provide new clues about the metabolic versatility of Malassezia.

  7. Inferring Metabolic States in Uncharacterized Environments Using Gene-Expression Measurements

    Science.gov (United States)

    Rossell, Sergio; Huynen, Martijn A.; Notebaart, Richard A.

    2013-01-01

    The large size of metabolic networks entails an overwhelming multiplicity in the possible steady-state flux distributions that are compatible with stoichiometric constraints. This space of possibilities is largest in the frequent situation where the nutrients available to the cells are unknown. These two factors: network size and lack of knowledge of nutrient availability, challenge the identification of the actual metabolic state of living cells among the myriad possibilities. Here we address this challenge by developing a method that integrates gene-expression measurements with genome-scale models of metabolism as a means of inferring metabolic states. Our method explores the space of alternative flux distributions that maximize the agreement between gene expression and metabolic fluxes, and thereby identifies reactions that are likely to be active in the culture from which the gene-expression measurements were taken. These active reactions are used to build environment-specific metabolic models and to predict actual metabolic states. We applied our method to model the metabolic states of Saccharomyces cerevisiae growing in rich media supplemented with either glucose or ethanol as the main energy source. The resulting models comprise about 50% of the reactions in the original model, and predict environment-specific essential genes with high sensitivity. By minimizing the sum of fluxes while forcing our predicted active reactions to carry flux, we predicted the metabolic states of these yeast cultures that are in large agreement with what is known about yeast physiology. Most notably, our method predicts the Crabtree effect in yeast cells growing in excess glucose, a long-known phenomenon that could not have been predicted by traditional constraint-based modeling approaches. Our method is of immediate practical relevance for medical and industrial applications, such as the identification of novel drug targets, and the development of biotechnological processes that

  8. Synoptic evaluation of carbon cycling in the Beaufort Sea during summer: contrasting river inputs, ecosystem metabolism and air-sea CO2 fluxes

    Science.gov (United States)

    Forest, A.; Coupel, P.; Else, B.; Nahavandian, S.; Lansard, B.; Raimbault, P.; Papakyriakou, T.; Gratton, Y.; Fortier, L.; Tremblay, J.-É.; Babin, M.

    2014-05-01

    The accelerated decline in Arctic sea ice and an ongoing trend toward more energetic atmospheric and oceanic forcings are modifying carbon cycling in the Arctic Ocean. A critical issue is to understand how net community production (NCP; the balance between gross primary production and community respiration) responds to changes and modulates air-sea CO2 fluxes. Using data collected as part of the ArcticNet-Malina 2009 expedition in the southeastern Beaufort Sea (Arctic Ocean), we synthesize information on sea ice, wind, river, water column properties, metabolism of the planktonic food web, organic carbon fluxes and pools, as well as air-sea CO2 exchange, with the aim of documenting the ecosystem response to environmental changes. Data were analyzed to develop a non-steady-state carbon budget and an assessment of NCP against air-sea CO2 fluxes. During the field campaign, the mean wind field was a mild upwelling-favorable wind (~ 5 km h-1) from the NE. A decaying ice cover ( 600 mg C m-2 d-1) over the shelf prior to our survey, (2) freshwater dilution by river runoff and ice melt, and (3) the presence of cold surface waters offshore. Only the Mackenzie River delta and localized shelf areas directly affected by upwelling were identified as substantial sources of CO2 to the atmosphere (> 10 mmol C m-2 d-1). Daily PP rates were generally Arctic transits to a new state.

  9. How important is thermodynamics for identifying elementary flux modes?

    Science.gov (United States)

    Peres, Sabine; Jolicœur, Mario; Moulin, Cécile

    2017-01-01

    We present a method for computing thermodynamically feasible elementary flux modes (tEFMs) using equilibrium constants without need of internal metabolite concentrations. The method is compared with the method based on a binary distinction between reversible and irreversible reactions. When all reactions are reversible, adding the constraints based on equilibrium constants reduces the number of elementary flux modes (EFMs) by a factor of two. Declaring in advance some reactions as irreversible, based on reliable biochemical expertise, can in general reduce the number of EFMs by a greater factor. But, even in this case, computing tEFMs can rule out some EFMs which are biochemically irrelevant. We applied our method to two published models described with binary distinction: the monosaccharide metabolism and the central carbon metabolism of Chinese hamster ovary cells. The results show that the binary distinction is in good agreement with biochemical observations. Moreover, the suppression of the EFMs that are not consistent with the equilibrium constants appears to be biologically relevant. PMID:28222104

  10. Physiological characterization of recombinant Saccharomyces cerevisiae expressing the Aspergillus nidulans phosphoketolase pathway: validation of activity through 13C-based metabolic flux analysis.

    Science.gov (United States)

    Papini, Marta; Nookaew, Intawat; Siewers, Verena; Nielsen, Jens

    2012-08-01

    Several bacterial species and filamentous fungi utilize the phosphoketolase pathway (PHK) for glucose dissimilation as an alternative to the Embden-Meyerhof-Parnas pathway. In Aspergillus nidulans, the utilization of this metabolic pathway leads to increased carbon flow towards acetate and acetyl CoA. In the first step of the PHK, the pentose phosphate pathway intermediate xylulose-5-phosphate is converted into acetylphosphate and glyceraldehyde-3-phosphate through the action of xylulose-5-phosphate phosphoketolase, and successively acetylphosphate is converted into acetate by the action of acetate kinase. In the present work, we describe a metabolic engineering strategy used to express the fungal genes of the phosphoketolase pathway in Saccharomyces cerevisiae and the effects of the expression of this recombinant route in yeast. The phenotype of the engineered yeast strain MP003 was studied during batch and chemostat cultivations, showing a reduced biomass yield and an increased acetate yield during batch cultures. To establish whether the observed effects in the recombinant strain MP003 were due directly or indirectly to the expression of the phosphoketolase pathway, we resolved the intracellular flux distribution based on (13)C labeling during chemostat cultivations. From flux analysis it is possible to conclude that yeast is able to use the recombinant pathway. Our work indicates that the utilization of the phosphoketolase pathway does not interfere with glucose assimilation through the Embden-Meyerhof-Parnas pathway and that the expression of this route can contribute to increase the acetyl CoA supply, therefore holding potential for future metabolic engineering strategies having acetyl CoA as precursor for the biosynthesis of industrially relevant compounds.

  11. Mathematical models for determining metabolic fluxes through the citric acid and the glyoxylate cycles in Saccharomyces cerevisiae by 13C-NMR spectroscopy.

    Science.gov (United States)

    Tran-Dinh, S; Bouet, F; Huynh, Q T; Herve, M

    1996-12-15

    We propose, first, a practical method for studying the isotopic transformation of glutamate or any other metabolite isotopomers in the citric acid and the glyoxylate cycles; second, two mathematical models, one for evaluating the flux through the citric acid cycle and the other for evaluating the flux through the latter coupled to the glyoxylate cycle in yeast. These models are based on the analysis of 13C-NMR spectra of glutamate obtained from Saccharomyces cerevisiae, NCYC strain, fed with 100% enriched [2-13C]acetate. The population of each glutamate isotopomer, the change in intensity of each multiplet component or the enrichment of any glutamate carbon is expressed by a specific analytical equation from which the flux in the citric acid and the glyoxylate cycles can be deduced. The aerobic metabolism of 100% [2-13C]acetate in acetate-grown S. cerevisiae cells was studied as a function of time using 13C-NMR. 1H-NMR and biochemical techniques. The C1 and C6 doublet and singlet of labeled trehalose increase continuously with time indicating that there is no isotopic transformation between trehalose isotopomers even though the corresponding formation rates are different. By contrast, the glutamate C4 singlet increases then decreases with time. The C4 doublet, which is lower than the singlet for t 90 min. A similar observation was made for the C2 resonance singlet and doublet. In addition, the glutamate C2 multiplet consists of only seven instead of nine peaks as in random labeling. These results agree well with our models and demonstrate that, in the presence of acetate, anaplerotic carbon sources involved in the synthesis of acetyl-CoA are negligible in yeast. The flux in the citric acid cycle was deduced from a plot of the C4 area versus incubation time, while the flux within the glyoxylate cycle was determined from the relative intensity of the glutamate C4 doublet and singlet. The fluxes in the citric acid and the glyoxylate cycles were found to be comparable

  12. Clarifying the regulation of NO/N2O production in Nitrosomonas europaea during anoxic-oxic transition via flux balance analysis of a metabolic network model.

    Science.gov (United States)

    Perez-Garcia, Octavio; Villas-Boas, Silas G; Swift, Simon; Chandran, Kartik; Singhal, Naresh

    2014-09-01

    The metabolic mechanism regulating the production of nitric and nitrous oxide (NO, N2O) in ammonia oxidizing bacteria (AOB) was characterized by flux balance analysis (FBA) of a stoichiometric metabolic network (SMN) model. The SMN model was created using 51 reactions and 44 metabolites of the energy metabolism in Nitrosomonas europaea, a widely studied AOB. FBA of model simulations provided estimates for reaction rates and yield ratios of intermediate metabolites, substrates, and products. These estimates matched well, deviating on average by 15% from values for 17 M yield ratios reported for non-limiting oxygen and ammonium concentrations. A sensitivity analysis indicated that the reactions catalysed by cytochromes aa3 and P460 principally regulate the pathways of NO and N2O production (hydroxylamine oxidoreductase mediated and nitrifier denitrification). FBA of simulated N. europaea exposure to oxic-anoxic-oxic transition indicated that NO and N2O production primarily resulted from an intracellular imbalance between the production and consumption of electron equivalents during NH3 oxidation, and that NO and N2O are emitted when the sum of their production rates is greater than half the rate of NO oxidation by cytochrome P460.

  13. Changes of in vivo fluxes through central metabolic pathways during the production of nystatin by Streptomyces noursei in batch culture

    DEFF Research Database (Denmark)

    Jonsbu, E.; Christensen, Bjarke; Nielsen, Jens

    2001-01-01

    The central carbon metabolism of the nystatin-producing strain Streptomyces noursei ATCC 11455 was evaluated by C-13-labelling experiments. A batch fermentation was examined during the idiophase by GC-MS measurements of the labelling patterns of amino acids in the biomass. The labelling patterns...

  14. Metabolism

    Science.gov (United States)

    ... a particular food provides to the body. A chocolate bar has more calories than an apple, so ... acid phenylalanine, needed for normal growth and protein production). Inborn errors of metabolism can sometimes lead to ...

  15. Consonant-vowel interactions in Modern Standard Latvian: a representational and constraint-based account

    Directory of Open Access Journals (Sweden)

    Olga Urek

    2016-07-01

    Full Text Available In this article I provide a representational and a constraint-based analysis of four interacting palatalization processes operative in Modern Standard Latvian: velar affrication, velar palatalization, yod-palatalization and front vowel raising. The main advantage of the representational account developed here is that it treats all of the mentioned Latvian processes as strictly assimilatory, and at the same time avoids purely stipulative mechanisms characteristic of many feature-geometric approaches to cross-category interactions. The article also contributes to the debate on the role of geometric subsegmental representations in constraint-based computational models, by demonstrating that a principled account of locality, transparency and blocking effects in Latvian palatalization requires the reference to hierarchical autosegmental structures.

  16. ParallelPC: an R package for efficient constraint based causal exploration

    OpenAIRE

    Le, Thuc Duy; Hoang, Tao; Li, Jiuyong; Liu, Lin; Hu, Shu

    2015-01-01

    Discovering causal relationships from data is the ultimate goal of many research areas. Constraint based causal exploration algorithms, such as PC, FCI, RFCI, PC-simple, IDA and Joint-IDA have achieved significant progress and have many applications. A common problem with these methods is the high computational complexity, which hinders their applications in real world high dimensional datasets, e.g gene expression datasets. In this paper, we present an R package, ParallelPC, that includes th...

  17. Constraint-based modeling and kinetic analysis of the Smad dependent TGF-beta signaling pathway.

    Directory of Open Access Journals (Sweden)

    Zhike Zi

    Full Text Available BACKGROUND: Investigation of dynamics and regulation of the TGF-beta signaling pathway is central to the understanding of complex cellular processes such as growth, apoptosis, and differentiation. In this study, we aim at using systems biology approach to provide dynamic analysis on this pathway. METHODOLOGY/PRINCIPAL FINDINGS: We proposed a constraint-based modeling method to build a comprehensive mathematical model for the Smad dependent TGF-beta signaling pathway by fitting the experimental data and incorporating the qualitative constraints from the experimental analysis. The performance of the model generated by constraint-based modeling method is significantly improved compared to the model obtained by only fitting the quantitative data. The model agrees well with the experimental analysis of TGF-beta pathway, such as the time course of nuclear phosphorylated Smad, the subcellular location of Smad and signal response of Smad phosphorylation to different doses of TGF-beta. CONCLUSIONS/SIGNIFICANCE: The simulation results indicate that the signal response to TGF-beta is regulated by the balance between clathrin dependent endocytosis and non-clathrin mediated endocytosis. This model is useful to be built upon as new precise experimental data are emerging. The constraint-based modeling method can also be applied to quantitative modeling of other signaling pathways.

  18. CELL SCALE HOST-PATHOGEN MODELING: ANOTHER BRANCH IN THE EVOLUTION OF CONSTRAINT-BASED METHODS

    Directory of Open Access Journals (Sweden)

    Neema eJamshidi

    2015-10-01

    Full Text Available Constraint-based models have become popular methods for systems biology as they enable the integration of complex, disparate datasets in a biologically cohesive framework that also supports the description of biological processes in terms of basic physicochemical constraints and relationships. The scope, scale, and application of genome scale models have grown from single cell bacteria to multi-cellular interaction modeling; host-pathogen modeling represents one of these examples at the current horizon of constraint-based methods. There are now a small number of examples of host-pathogen constraint-based models in the literature, however there has not yet been a definitive description of the methodology required for the functional integration of genome scale models in order to generate simulation capable host-pathogen models. Herein we outline a systematic procedure to produce functional host-pathogen models, highlighting steps which require debugging and iterative revisions in order to successfully build a functional model. The construction of such models will enable the exploration of host-pathogen interactions by leveraging the growing wealth of omic data in order to better understand mechanism of infection and identify novel therapeutic strategies.

  19. Soft sensor control of metabolic fluxes in a recombinant Escherichia coli fed-batch cultivation producing green fluorescence protein.

    Science.gov (United States)

    Gustavsson, Robert; Mandenius, Carl-Fredrik

    2013-10-01

    A soft sensor approach is described for controlling metabolic overflow from mixed-acid fermentation and glucose overflow metabolism in a fed-batch cultivation for production of recombinant green fluorescence protein (GFP) in Escherichia coli. The hardware part of the sensor consisted of a near-infrared in situ probe that monitored the E. coli biomass and an HPLC analyzer equipped with a filtration unit that measured the overflow metabolites. The computational part of the soft sensor used basic kinetic equations and summations for estimation of specific rates and total metabolite concentrations. Two control strategies for media feeding of the fed-batch cultivation were evaluated: (1) controlling the specific rates of overflow metabolism and mixed-acid fermentation metabolites at a fixed pre-set target values, and (2) controlling the concentration of the sum of these metabolites at a set level. The results indicate that the latter strategy was more efficient for maintaining a high titer and low variability of the produced recombinant GFP protein.

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

    Science.gov (United States)

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

    2010-06-07

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

  1. Metabolic flux analysis of Escherichia coli creB and arcA mutants reveals shared control of carbon catabolism under microaerobic growth conditions.

    Science.gov (United States)

    Nikel, Pablo I; Zhu, Jiangfeng; San, Ka-Yiu; Méndez, Beatriz S; Bennett, George N

    2009-09-01

    Escherichia coli has several elaborate sensing mechanisms for response to availability of oxygen and other electron acceptors, as well as the carbon source in the surrounding environment. Among them, the CreBC and ArcAB two-component signal transduction systems are responsible for regulation of carbon source utilization and redox control in response to oxygen availability, respectively. We assessed the role of CreBC and ArcAB in regulating the central carbon metabolism of E. coli under microaerobic conditions by means of (13)C-labeling experiments in chemostat cultures of a wild-type strain, DeltacreB and DeltaarcA single mutants, and a DeltacreB DeltaarcA double mutant. Continuous cultures were conducted at D = 0.1 h(-1) under carbon-limited conditions with restricted oxygen supply. Although all experimental strains metabolized glucose mainly through the Embden-Meyerhof-Parnas pathway, mutant strains had significantly lower fluxes in both the oxidative and the nonoxidative pentose phosphate pathways. Significant differences were also found at the pyruvate branching point. Both pyruvate-formate lyase and the pyruvate dehydrogenase complex contributed to acetyl-coenzyme A synthesis from pyruvate, and their activity seemed to be modulated by both ArcAB and CreBC. Strains carrying the creB deletion showed a higher biomass yield on glucose compared to the wild-type strain and its DeltaarcA derivative, which also correlated with higher fluxes from building blocks to biomass. Glyoxylate shunt and lactate dehydrogenase were active mainly in the DeltaarcA strain. Finally, it was observed that the tricarboxylic acid cycle reactions operated in a rather cyclic fashion under our experimental conditions, with reduced activity in the mutant strains.

  2. ANALYSIS OF METABOLIC FLUXES IN BATCH CULTURES OF INOSINE-OVERPRODUCING Bacillus subtillis%肌苷产生菌枯草芽孢杆菌分批发酵的代谢流分析

    Institute of Scientific and Technical Information of China (English)

    张蓓; 张克旭; 陈宁; 徐咏全

    2003-01-01

    It is well recognized that metabolic fluxes are the key variables that must be determined in orderto understand metabolic regulation and patterns. However, owing to difficulties in measuring the flux values,evaluation of metabolic fluxes has not been an integral part of the most metabolic studies. Flux values formetabolites of glycolysis (EMP), tricarboxylic acid (TCA) cycle, and hexose monophosphate (HMP) pathwaywas obtained for batch cultures of inosine overproducing Bacilus subtilis by combining the information from thestoichiometry of key biosynthetic reactions with the experimental data on uptake rate of glucose and formationrates of metabolic product and byproducts.%为了更好地掌握代谢规律和代谢方式,代谢流作为一个关键而重要的变量需要测定.然而,由于代谢流测定的困难,在许多代谢研究中代谢流并没有被完全应用.在肌苷高产菌枯草芽孢杆菌中,利用得到的实验数据包括葡萄糖的消耗速率和代谢主产物以及副产物的形成速率,利用代谢通量平衡模型,得到糖酵解、三羟酸循环及磷酸戊糖途径的代谢流,并对其进行了分析.

  3. Effect of Resveratrol on Metabolic Network Flux in Rats%白藜芦醇对大鼠代谢网络通量的影响

    Institute of Scientific and Technical Information of China (English)

    胥连杰; 王会松; 庞广昌

    2016-01-01

    本研究设置了对照组以及白藜芦醇低、中、高3个剂量(2、20、200 mg/kg)实验组,每组各6只雄性大鼠,对灌胃后的大鼠建立代谢网络模型,进行乳酸代谢网络通量的研究。结果表明:在给大鼠喂食2 mg/kg的白藜芦醇时,机体分解代谢降低,但当白藜芦醇的剂量为20 mg/kg时,机体分解代谢增加,当白藜芦醇剂量为200 mg/kg时,机体分解代谢增加趋势更为明显。在白藜芦醇剂量为2 mg/kg时,机体分解代谢最低,低剂量的白藜芦醇可能有助于现代文明病的预防和治疗。当剂量达到200 mg/kg时,机体分解代谢明显增强,说明它可能会对机体造成毒副作用。显然,白藜芦醇只能在一定的剂量范围内发挥保健作用。%A large number of studies have shown that lactic acid metabolism flux can be used to quantitatively describe the state of the body in the condition of normal life. When it is reduced, the body is in good shape; in contrast, when it is increased, the body is in the state of inflammation or detoxification. In recent years, a number of reports have demonstrated the prevention of diseases of modern civilization by resveratrol and it is evident that this effect is closely related to lactate metabolism flux. However, studies on its metabolism in the body have rarely been reported. In the present study, one control group and three resveratrol treatment groups at low, medium and high doses (2, 20 and 200 mg/kg), each consisting of 6 male rats were designed. After the rats were administered by gavage, a metabolic network model for metabolic flux analysis was established. The results showed that the body catabolism was reduced by administration of 2 mg/kg of resveratrol, but it was increased dose-dependently when the dose was over 20 mg/kg. Based on these results, resveratrol at 2 mg/kg could result in the lowest body catabolism, suggesting that it can help prevent and treat diseases of modern

  4. Metabolic control analysis of the penicillin biosynthetic pathway: the influence of the LLD-ACV:bisACV ratio on the flux control.

    Science.gov (United States)

    Theilgaard, H A; Nielsen, J

    1999-01-01

    An extended kinetic model for the first two steps of the penicillin biosynthetic pathway in Penicillium chrysogenum is set up. It includes the formation and reduction of the dimer bis-delta-(L-alpha-aminoadipyl)-L-cysteinyl-D-valine (bisACV) from the first pathway intermediate LLD-ACV and their parallel inhibition of the enzyme ACV synthetase (ACVS). The kinetic model is based on Michaelis-Menten type kinetics, with non-competitive inhibition of the ACVS by both LLD-ACV and bisACV, and competitive inhibition of the isopenicillin N synthetase (IPNS) by glutathione. The inhibition constant of LLD-ACV, KACV is determined to be 0.54 mm. With the kinetic model metabolic control analysis is performed to identify the di