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13C metabolite profiling to compare the central metabolic flux in two yeast strains

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Abstract

13C metabolite profiling to quantify the dynamic changes of central carbon metabolites was attempted using mass isotopomer distribution analysis in two yeast strains, Saccharomyces cerevisiae and Kluyveromyces marxianus. Mass and isotopomer balances of the intermediates were examined and calculated in both yeast species and central carbon metabolic fluxes were successfully determined. Metabolic fluxes of pentose phosphate pathway in K. marxianus were 1.66 times higher than S. cerevisiae. The flux difference was also supported by relatively high abundance of partially labeled fructose 6-phosphate and 3-phosphoglycerate as well as an increased concentration of labeled L-valine in K. marxianus. Metabolic flux analysis combined with dynamic metabolite profiling has provided better understanding in the central carbon metabolic pathways of two model organisms and can be applied as a method to analyze more complicated metabolic networks in other organisms.

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References

  1. Toya, Y. and H. Shimizu (2013) Flux analysis and metabolomics for systematic metabolic engineering of microorganisms. Biotechnol. Adv. 31: 818–826.

    Article  CAS  Google Scholar 

  2. Dauner, M. (2010) From fluxes and isotope labeling patterns towards in silico cells. Curr. Opin. Biotech. 21: 55–62.

    Article  CAS  Google Scholar 

  3. Wiechert, W. (2001) 13C metabolic flux analysis. Metab. Eng. 3: 195–206.

    Article  CAS  Google Scholar 

  4. Wittmann, C. (2007) Fluxome analysis using GC-MS. Microb. Cell Fact 6: 1.

    Article  Google Scholar 

  5. Crown, S. B. and M. R. Antoniewicz (2012) Selection of tracers for 13 C-metabolic flux analysis using elementary metabolite units (EMU) basis vector methodology. Metab. Eng. 14: 150–161.

    Article  CAS  Google Scholar 

  6. Dauner, M. and U. Sauer (2000) GC?MS analysis of amino acids rapidly provides rich information for isotopomer balancing. Biotechnol. Prog. 16: 642–649.

    Article  CAS  Google Scholar 

  7. Wiechert, W., M. Möllney, N. Isermann, M. Wurzel, and A. A. de Graaf (1999) Bidirectional reaction steps in metabolic networks: III. Explicit solution and analysis of isotopomer labeling systems. Biotechnol. Bioeng. 66: 69–85.

    Article  CAS  Google Scholar 

  8. Antoniewicz, M. R., J. K. Kelleher, and G. Stephanopoulos (2007) Elementary metabolite units (EMU): A novel framework for modeling isotopic distributions. Metab. Eng. 9: 68–86.

    Article  CAS  Google Scholar 

  9. Antoniewicz, M. R., D. F. Kraynie, L. A. Laffend, J. González-Lergier, J. K. Kelleher, and G. Stephanopoulos (2007) Metabolic flux analysis in a nonstationary system: Fed-batch fermentation of a high yielding strain of E. coli producing 1, 3-propanediol. Metab. Eng, 9: 277–292.

    Article  CAS  Google Scholar 

  10. Shirai, T., K. Fujimura, C, Furusawa, K. Nagahisa, S. Shioya, and H. Shimizu (2007) Study on roles of anaplerotic pathways in glutamate overproduction of Corynebacterium glutamicum by metabolic flux analysis. Microb. Cell Fact. 6: 1.

    Article  Google Scholar 

  11. Lu, S., M. A. Eiteman, and E. Altman (2009) Effect of CO2 on succinate production in dual-phase Escherichia coli fermentations. J. Biotechnol. 143: 213–223.

    Article  CAS  Google Scholar 

  12. Umakoshi, M., T. Hirasawa, C. Furusawa, Y. Takenaka, Y. Kikuchi, and H. Shimizu (2011) Improving protein secretion of a transglutaminase-secreting Corynebacterium glutamicum recombinant strain on the basis of 13C metabolic flux analysis. J. Biosci. Bioeng. 112: 595–601.

    Article  CAS  Google Scholar 

  13. Wiechert, W. and K. Nöh (2005) From stationary to instationary metabolic flux analysis. Adv. Biochem. Eng. Biotechnol. 92: 145–172.

    CAS  Google Scholar 

  14. Young, J. D., J. L. Walther, M. R. Antoniewicz, H. Yoo, and G. Stephanopoulos (2008) An elementary metabolite unit (EMU) based method of isotopically nonstationary flux analysis. Biotechnol. Bioeng. 99: 686–699.

    Article  CAS  Google Scholar 

  15. Wahl, S. A., K. Nöh, and W. Wiechert (2008) 13C labeling experiments at metabolic nonstationary conditions: An exploratory study. BMC Bioinformat. 9: 1.

    Article  Google Scholar 

  16. Aboka, F. O., J. J. Heijnen, and W. A. Van Winden (2009) Dynamic 13C-tracer study of storage carbohydrate pools in aerobic glucose-limited Saccharomyces cerevisiae confirms a rapid steady-state turnover and fast mobilization during a modest stepup in the glucose uptake rate. FEMS Yeast Res. 9: 191–201.

    Article  CAS  Google Scholar 

  17. Juminaga, D., E. E. K. Baidoo, A. M. Redding-Johanson, T. S. Batth, H. Burd, A. Mukhopadhyay, C. J. Petzold, and J. D. Keasling (2012) Modular engineering of L-tyrosine production in Escherichia coli. Appl. Environ. Microbiol. 78: 89–98.

    Article  CAS  Google Scholar 

  18. Yamamoto, S., W. Gunji, H. Suzuki, H. Toda, M. Suda, T. Jojima, M. Inui, and H. Yukawa (2012) Overexpression of genes encoding glycolytic enzymes in Corynebacterium glutamicum enhances glucose metabolism and alanine production under oxygen deprivation conditions. Appl. Environ. Microbiol. 78: 4447–4457.

    Article  CAS  Google Scholar 

  19. Büscher, J. M., D. Czernik, J. C. Ewald, U. Sauer, and N. Zamboni (2009) Cross-platform comparison of methods for quantitative metabolomics of primary metabolism. Anal. Chem. 81: 2135–2143.

    Article  Google Scholar 

  20. Vielhauer, O., M. Zakhartsev, T. Horn, R. Takors, and M. Reuss (2011) Simplified absolute metabolite quantification by gas chromatography–isotope dilution mass spectrometry on the basis of commercially available source material. J. Chromatogr. B Biomed. Sci. Appl. 879: 3859–3870.

    CAS  Google Scholar 

  21. van Gulik, W. M. (2010) Fast sampling for quantitative microbial metabolomics. Curr. Opin. Biotechnol. 21: 27–34.

    Article  Google Scholar 

  22. Jung, J. Y., T. Y. Kim, C. Y. Ng, and M. K. Oh (2012) Characterization of GCY1 in Saccharomyces cerevisiae by metabolic profiling. J. Appl. Microbiol. 113: 1468–1478.

    Article  CAS  Google Scholar 

  23. Nikerel, I. E., W. A. van Winden, P. J. Verheijen, and J. J. Heijnen (2009) Model reduction and a priori kinetic parameter identifiability analysis using metabolome time series for metabolic reaction networks with linlog kinetics. Metab. Eng. 11: 20–30.

    Article  CAS  Google Scholar 

  24. Yuan, J., W. U. Fowler, E. Kimball, W. Lu, and J. D. Rabinowitz (2006) Kinetic flux profiling of nitrogen assimilation in Escherichia coli. Nat. Chem. Biol. 2: 529–530.

    Article  CAS  Google Scholar 

  25. Shlomi, T., J. Fan, B. Tang, W. D. Kruger, and J. D. Rabinowitz (2014) Quantitation of cellular metabolic fluxes of methionine. Anal. Chem. 86: 1583–1591.

    Article  CAS  Google Scholar 

  26. Fan, J., J. Ye, J. J. Kamphorst, T. Shlomi, C. B. Thompson, and J. D. Rabinowitz (2014) Quantitative flux analysis reveals folatedependent NADPH production. Nature 510: 298–302.

    Article  CAS  Google Scholar 

  27. Kim, T. Y., S. W. Lee, and M. K. Oh (2014) Biosynthesis of 2-phenylethanol from glucose with genetically engineered Kluyveromyces marxianus. Enz. Microb. Technol. 61: 44–47.

    Article  Google Scholar 

  28. Wittmann, C. and E. Heinzle (2001) Modeling and experimental design for metabolic flux analysis of lysine-producing Corynebacteria by mass spectrometry. Metab. Eng. 3: 173–191.

    Article  CAS  Google Scholar 

  29. Wittmann, C., P. Kiefer, and O. Zelder (2004) Metabolic fluxes in Corynebacterium glutamicum during lysine production with sucrose as carbon source. Appl. Environ. Microbiol. 70: 7277–7287.

    Article  CAS  Google Scholar 

  30. Jung, J. Y. and M. K. Oh (2015) Isotope labeling pattern study of central carbon metabolites using GC/MS. J. Chromatogr. B Biomed. Sci. Appl. 974: 101–108.

    CAS  Google Scholar 

  31. Cipollina, C., A. ten Pierick, A. B. Canelas, R. M. Seifar, A. J. van Maris, J. C. van Dam, and J. J. Heijnen (2009) A comprehensive method for the quantification of the non-oxidative pentose phosphate pathway intermediates in Saccharomyces cerevisiae by GC–IDMS. J. Chromatogr. B Biomed. Sci. Appl. 877: 3231–3236.

    CAS  Google Scholar 

  32. Bartek, T., B. Blombach, S. Lang, B. J. Eikmanns, W. Wiechert, M. Oldiges, K. Nöh, and S. Noack (2011) Comparative 13C metabolic flux analysis of pyruvate dehydrogenase complex-deficient, L-valine-producing Corynebacterium glutamicum. Appl. Environ. Microbiol. 77: 6644–6652.

    Article  CAS  Google Scholar 

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Correspondence to Jinwon Lee or Min-Kyu Oh.

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First two authors have contributed equally to this work.

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Jung, JY., Yun, S.H., Im, DK. et al. 13C metabolite profiling to compare the central metabolic flux in two yeast strains. Biotechnol Bioproc E 21, 814–822 (2016). https://doi.org/10.1007/s12257-016-0536-3

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  • DOI: https://doi.org/10.1007/s12257-016-0536-3

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