Dataset Information

Evaluation of 13C isotopic tracers for metabolic flux analysis in mammalian cells.

ABSTRACT: (13)C metabolic flux analysis (MFA) is the most comprehensive means of characterizing cellular metabolic states. Uniquely labeled isotopic tracers enable more focused analyses to probe specific reactions within the network. As a result, the choice of tracer largely determines the precision with which one can estimate metabolic fluxes, especially in complex mammalian systems that require multiple substrates. Here we have experimentally determined metabolic fluxes in a tumor cell line, successfully recapitulating the hallmarks of cancer cell metabolism. Using these data, we computationally evaluated specifically labeled (13)C glucose and glutamine tracers for their ability to precisely and accurately estimate fluxes in central carbon metabolism. These methods enabled us to identify the optimal tracer for analyzing individual fluxes, specific pathways, and central carbon metabolism as a whole. [1,2-(13)C(2)]glucose provided the most precise estimates for glycolysis, the pentose phosphate pathway, and the overall network. Tracers such as [2-(13)C]glucose and [3-(13)C]glucose also outperformed the more commonly used [1-(13)C]glucose. [U-(13)C(5)]glutamine emerged as the preferred isotopic tracer for the analysis of the tricarboxylic acid (TCA) cycle. These results provide valuable, quantitative information on the performance of (13)C-labeled substrates and can aid in the design of more informative MFA experiments in mammalian cell culture.

SUBMITTER: Metallo CM

PROVIDER: S-EPMC3026314 | biostudies-literature | 2009 Nov

REPOSITORIES: biostudies-literature

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Evaluation of 13C isotopic tracers for metabolic flux analysis in mammalian cells.

Metallo Christian M CM Walther Jason L JL Stephanopoulos Gregory G

Journal of biotechnology 20090719 3

(13)C metabolic flux analysis (MFA) is the most comprehensive means of characterizing cellular metabolic states. Uniquely labeled isotopic tracers enable more focused analyses to probe specific reactions within the network. As a result, the choice of tracer largely determines the precision with which one can estimate metabolic fluxes, especially in complex mammalian systems that require multiple substrates. Here we have experimentally determined metabolic fluxes in a tumor cell line, successfull ...[more]

PMID: 19622376

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Project description: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 (<20 sec). CONCLUSION: We have developed a fast, accurate application to perform steady-state 13C metabolic flux analysis. OpenFLUX will strongly facilitate and enhance the design, calculation and interpretation of metabolic flux studies. By providing the software open source, we hope it will evolve with the rapidly growing field of fluxomics.

Dataset Information

Evaluation of 13C isotopic tracers for metabolic flux analysis in mammalian cells.

Publications

Evaluation of 13C isotopic tracers for metabolic flux analysis in mammalian cells.

Similar Datasets

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