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Successful Downsizing for High-Throughput 13C-MFA Applications

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Metabolic Flux Analysis

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1191))

Abstract

13C label-based metabolic flux analysis is a powerful technique for the determination of intracellular reaction rates and is used in such different research fields as quantitative physiology, metabolic engineering, and systems biology. Metabolic fluxes can be determined at high quality using (pseudo)-steady-state cultures and advanced mathematical models for data interpretation. Here, we describe a protocol for parallel metabolic flux analysis that consists of downsized microbial (yeast) cultivation, miniaturized sample preparation, and semiautomated analytics and data evaluation. With this protocol dozens of metabolic flux analyses can be carried out in 1 week, thereby enabling for example the analysis of genetic and environmental perturbations on the operation of metabolic networks.

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References

  1. Fischer E, Sauer U (2003) Metabolic flux profiling of Escherichia coli mutants in central carbon metabolism using GC-MS. Eur J Biochem 270:880–891

    Article  CAS  PubMed  Google Scholar 

  2. Nöh K, Gronke K, Luo B, Takors R, Oldiges M, Wiechert W (2007) Metabolic flux analysis at ultra short time scale: isotopically non-stationary 13C labeling experiments. J Biotechnol 129:249–267

    Article  PubMed  Google Scholar 

  3. Quek LE, Wittmann C, Nielsen LK, Krömer JO (2009) OpenFLUX: efficient modelling software for 13C-based metabolic flux analysis. Microb Cell Fact 8:25

    Article  PubMed Central  PubMed  Google Scholar 

  4. Zamboni N, Fischer E, Sauer U (2005) FiatFlux—a software for metabolic flux analysis from 13C-glucose experiments. BMC Bioinformatics 6:209

    Article  PubMed Central  PubMed  Google Scholar 

  5. Wiechert W, Mollney M, Petersen S, de Graaf AA (2001) A universal framework for 13C metabolic flux analysis. Metab Eng 3:265–283

    Article  CAS  PubMed  Google Scholar 

  6. Ebert BE, Lamprecht A-L, Steffen B, Blank LM (2012) Flux-P: automating metabolic flux analysis. Metabolites 2:872–890

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  7. Sauer U, Lasko DR, Fiaux J, Hochuli M, Glaser R, Szyperski T, Wuthrich K, Bailey JE (1999) Metabolic flux ratio analysis of genetic and environmental modulations of Escherichia coli central carbon metabolism. J Bacteriol 181:6679–6688

    CAS  PubMed Central  PubMed  Google Scholar 

  8. Lamprecht AL, Margaria T, Steffen B (2008) Seven variations of an alignment workflow—an illustration of agile process design and management in Bio-jETI. Bioinformatics Res Appl 4983:445–456

    Article  Google Scholar 

  9. Steffen B, Margaria T, Nagel R, Jörges S, Kubczak C (2007) Model-driven development with the jABC. In: Bin E, Ziv A, Ur S (eds) Hardware and Software, Verification and Testing. Springer Berlin, Heidelberg, pp 92–108

    Google Scholar 

  10. Nanchen A, Fuhrer T, Sauer U (2007) Determination of metabolic flux ratios from 13C-experiments and gas chromatography-mass spectrometry data: protocol and principles. Methods Mol Biol 358:177–197

    Article  CAS  PubMed  Google Scholar 

  11. Verduyn C, Postma E, Scheffers WA, Vandijken JP (1992) Effect of benzoic acid on metabolic fluxes in yeasts—a continuous culture study on the regulation of respiration and alcoholic fermentation. Yeast 8:501–517

    Article  CAS  PubMed  Google Scholar 

  12. Duetz WA, Ruedi L, Hermann R, O’Connor K, Büchs J, Witholt B (2000) Methods for intense aeration, growth, storage, and replication of bacterial strains in microtiter plates. Appl Environ Microbiol 66:2641–2646

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  13. Droste P, Miebach S, Niedenfuhr S, Wiechert W, Nöh K (2011) Visualizing multi-omics data in metabolic networks with the software Omix—a case study. Biosystems 105:154–161

    Article  CAS  PubMed  Google Scholar 

  14. Fischer E, Zamboni N, Sauer U (2004) High-throughput metabolic flux analysis based on gas chromatography-mass spectrometry derived 13C constraints. Anal Biochem 325:308–316

    Article  CAS  PubMed  Google Scholar 

  15. Wittmann C (2007) Fluxome analysis using GC-MS. Microb Cell Fact 6:6

    Article  PubMed Central  PubMed  Google Scholar 

  16. Blank LM, Kuepfer L, Sauer U (2005) Large-scale 13C-flux analysis reveals mechanistic principles of metabolic network robustness to null mutations in yeast. Genome Biol 6:R49

    Article  PubMed Central  PubMed  Google Scholar 

  17. Samorski M, Muller-Newen G, Büchs J (2005) Quasi-continuous combined scattered light and fluorescence measurements: a novel measurement technique for shaken microtiter plates. Biotechnol Bioeng 92:61–68

    Article  CAS  PubMed  Google Scholar 

  18. Kensy F, Zang E, Faulhammer C, Tan RK, Büchs J (2009) Validation of a high-throughput fermentation system based on online monitoring of biomass and fluorescence in continuously shaken microtiter plates. Microb Cell Fact 8:31

    Article  PubMed Central  PubMed  Google Scholar 

  19. Poskar CH, Huege J, Krach C, Franke M, Shachar-Hill Y, Junker BH (2012) iMS2Flux—a high-throughput processing tool for stable isotope labeled mass spectrometric data used for metabolic flux analysis. BMC Bioinformatics 13:295

    Article  PubMed Central  PubMed  Google Scholar 

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Acknowledgement

This work was supported by the Cluster of Excellence “Tailor-Made Fuels from Biomass,” which is funded by the Excellence Initiative of the German federal and state governments to promote science and research at German universities.

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Correspondence to Lars M. Blank .

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© 2014 Springer Science+Business Media New York

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Ebert, B.E., Blank, L.M. (2014). Successful Downsizing for High-Throughput 13C-MFA Applications. In: Krömer, J., Nielsen, L., Blank, L. (eds) Metabolic Flux Analysis. Methods in Molecular Biology, vol 1191. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-1170-7_8

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  • DOI: https://doi.org/10.1007/978-1-4939-1170-7_8

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  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-1169-1

  • Online ISBN: 978-1-4939-1170-7

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