Skip to main content
SpringerLink
Log in

Comparative metabolomic analysis reveals different evolutionary mechanisms for branched-chain amino acids production

  • Research Paper
  • Published:
Bioprocess and Biosystems Engineering Aims and scope Submit manuscript

Abstract

Evolution is a powerful tool for the breeding of microorganisms, while the connection between the changes of intracellular metabolism and different evolution directions is still unclear, which once clarified, will greatly expand the application of evolutionary engineering. We aim to clarify the correlation between metabolism changes and evolution directions in two Corynebacterium glutamicum strains for l-valine and l-leucine overproducing originated from the same parental strain by repeated random mutagenesis and selection. GC–MS metabolomics was performed to identify and quantify intracellular metabolites of the evolved and wild-type C. glutamicum strains. Time-series comparison of the fermentation processes was performed. The metabolism differences of three strains mainly exist in central carbon metabolism and the stress-resisting modes. C. glutamicum XV developed an overall “pyruvate-saving” mode for l-valine synthesis, and adopted a trehalose accumulating strategy to resist environmental stresses. C. glutamicum CP depended on an enhanced “pyruvate-producing” mode, together with certain “pyruvate-saving” strategies, for efficient l-leucine synthesis, and accumulated proline, my-inositol, and inositol as the stress-resisting measure. These elaborate regulation strategies could be used in future metabolic engineering, making evolution more informative and applicable.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  1. Dragosits M, Mattanovich D (2013) Adaptive laboratory evolution—principles and applications for biotechnology. Microb Cell Fact 12(1):64. https://doi.org/10.1186/1475-2859-12-64

    Article  PubMed  PubMed Central  Google Scholar 

  2. Peris D, Moriarty RV, Alexander WG, Baker E, Sylvester K, Sardi M, Langdon QK, Libkind D, Wang QM, Bai FY, Leducq JB, Charron G, Landry CR, Sampaio JP, Gonçalves P, Hyma KE, Fay JC, Sato TK, Hittinger CT (2017) Hybridization and adaptive evolution of diverse Saccharomyces species for cellulosic biofuel production. Biotechnol Biofuels 10(1):78. https://doi.org/10.1186/s13068-017-0763-7

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Zhu Z, Zhang J, Ji X, Fang Z, Wu Z, Chen J, Du G (2018) Evolutionary engineering of industrial microorganisms-strategies and applications. Appl Microbiol Biotechnol 102(11):4615–4627. https://doi.org/10.1007/s00253-018-8937-1

    Article  CAS  PubMed  Google Scholar 

  4. Lee JW, Na D, Park JM, Lee J, Choi S, Lee SY (2012) Systems metabolic engineering of microorganisms for natural and non-natural chemicals. Nat Chem Biol 8:536. https://doi.org/10.1038/nchembio.970

    Article  CAS  PubMed  Google Scholar 

  5. Ma Q, Zhang Q, Xu Q, Zhang C, Li Y, Fan X, Xie X, Chen N (2017) Systems metabolic engineering strategies for the production of amino acids. Synthetic Syst Biotechnol 2(2):87–96. https://doi.org/10.1016/j.synbio.2017.07.003

    Article  Google Scholar 

  6. Lee SY, Kim HU (2015) Systems strategies for developing industrial microbial strains. Nat Biotechnol 33(10):1061–1072. https://doi.org/10.1038/nbt.3365

    Article  CAS  PubMed  Google Scholar 

  7. Zhu L, Li Y, Cai Z (2015) Development of a stress-induced mutagenesis module for autonomous adaptive evolution of Escherichia coli to improve its stress tolerance. Biotechnol Biofuels 8(1):93. https://doi.org/10.1186/s13068-015-0276-1

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Liu W, Jiang R (2015) Combinatorial and high-throughput screening approaches for strain engineering. Appl Microbiol Biotechnol 99(5):2093–2104. https://doi.org/10.1007/s00253-015-6400-0

    Article  CAS  PubMed  Google Scholar 

  9. Lin JL, Wagner JM, Alper HS (2017) Enabling tools for high-throughput detection of metabolites: metabolic engineering and directed evolution applications. Biotechnol Adv 35(8):950–970. https://doi.org/10.1016/j.biotechadv.2017.07.005

    Article  CAS  PubMed  Google Scholar 

  10. Mahr R, Gätgens C, Gätgens J, Polen T, Kalinowski J, Frunzke J (2015) Biosensor-driven adaptive laboratory evolution of l-valine production in Corynebacterium glutamicum. Metab Eng 32:184–194. https://doi.org/10.1016/j.ymben.2015.09.017

    Article  CAS  PubMed  Google Scholar 

  11. Zhang J, Jensen MK, Keasling JD (2015) Development of biosensors and their application in metabolic engineering. Curr Opin Chem Biol 28:1–8. https://doi.org/10.1016/j.cbpa.2015.05.013

    Article  CAS  PubMed  Google Scholar 

  12. Shi S, Ang EL, Zhao H (2018) In vivo biosensors: mechanisms, development, and applications. J Ind Microbiol Biotechnol 45(7):491–516. https://doi.org/10.1007/s10295-018-2004-x

    Article  CAS  PubMed  Google Scholar 

  13. Becker J, Wittmann C (2012) Systems and synthetic metabolic engineering for amino acid production: the heartbeat of industrial strain development. Curr Opin Biotechnol 23(5):718–726. https://doi.org/10.1016/j.copbio.2011.12.025

    Article  CAS  PubMed  Google Scholar 

  14. Park JH, Lee SY (2008) Towards systems metabolic engineering of microorganisms for amino acid production. Curr Opin Biotechnol 19(5):454–460. https://doi.org/10.1016/j.copbio.2008.08.007

    Article  CAS  PubMed  Google Scholar 

  15. Becker J, Wittmann C (2012) Bio-based production of chemicals, materials and fuels—Corynebacterium glutamicum as versatile cell factory. Curr Opin Biotechnol 23(4):631–640. https://doi.org/10.1016/j.copbio.2011.11.012

    Article  CAS  PubMed  Google Scholar 

  16. Duan Y, Guo Q, Wen C, Wang W, Li Y, Tan B, Li F, Yin Y (2016) Free amino acid profile and expression of genes implicated in protein metabolism in skeletal muscle of growing pigs fed low-protein diets supplemented with branched-chain amino acids. J Agric Food Chem 64(49):9390–9400. https://doi.org/10.1021/acs.jafc.6b03966

    Article  CAS  PubMed  Google Scholar 

  17. Schwentner A, Feith A, Münch E, Busche T, Rückert C, Kalinowski J, Takors R, Blombach B (2018) Metabolic engineering to guide evolution—creating a novel mode for l-valine production with Corynebacterium glutamicum. Metab Eng 47:31–41. https://doi.org/10.1016/j.ymben.2018.02.015

    Article  CAS  PubMed  Google Scholar 

  18. Wang X (2019) Strategy for improving l-isoleucine production efficiency in Corynebacterium glutamicum. Appl Microbiol Biotechnol 103(5):2101–2111. https://doi.org/10.1007/s00253-019-09632-2

    Article  CAS  PubMed  Google Scholar 

  19. Gui Y, Ma Y, Xu Q, Zhang C, Xie X, Chen N (2016) Complete genome sequence of Corynebacterium glutamicum CP, a Chinese l-leucine producing strain. J Biotechnol 220:64–65. https://doi.org/10.1016/j.jbiotec.2016.01.010

    Article  CAS  PubMed  Google Scholar 

  20. Ma YC, Ma Q, Cui Y, Du LH, Xie XX, Chen N (2019) Transcriptomic and metabolomics analyses reveal metabolic characteristics of l-leucine- and l-valine-producing Corynebacterium glutamicum mutants. Annals of Microbiology 69:457–468. https://doi.org/10.1007/s13213-018-1431-2

    Article  CAS  Google Scholar 

  21. Ding MZ, Zhou X, Yuan YJ (2010) Metabolome profiling reveals adaptive evolution of Saccharomyces cerevisiae during repeated vacuum fermentations. Metabolomics 6(1):42–55. https://doi.org/10.1007/s11306-009-0173-3

    Article  CAS  Google Scholar 

  22. Soma Y, Tsuruno K, Wada M, Yokota A, Hanai T (2014) Metabolic flux redirection from a central metabolic pathway toward a synthetic pathway using a metabolic toggle switch. Metab Eng 23:175–184. https://doi.org/10.1016/j.ymben.2014.02.008

    Article  CAS  PubMed  Google Scholar 

  23. Noh MH, Lim HG, Park S, Seo SW, Jung GY (2017) Precise flux redistribution to glyoxylate cycle for 5-aminolevulinic acid production in Escherichia coli. Metab Eng 43:1–8. https://doi.org/10.1016/j.ymben.2017.07.006

    Article  CAS  PubMed  Google Scholar 

  24. Kim SC, Min BE, Hwang HG, Seo SW, Jung GY (2015) Pathway optimization by re-design of untranslated regions for l-tyrosine production in Escherichia coli. Sci Rep 5:13853–13853. https://doi.org/10.1038/srep13853

    Article  PubMed  Google Scholar 

  25. Gupta A, Reizman IMB, Reisch CR, Prather KLJ (2017) Dynamic regulation of metabolic flux in engineered bacteria using a pathway-independent quorum-sensing circuit. Nat Biotechnol 35:273–279. https://doi.org/10.1038/nbt.3796

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Ma Y, Cui Y, Du L, Liu X, Xie X, Chen N (2018) Identification and application of a growth-regulated promoter for improving l-valine production in Corynebacterium glutamicum. Microb Cell Fact 17(1):185. https://doi.org/10.1186/s12934-018-1031-7

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Andrade-Linares DR, Lehmann A, Rillig MC (2016) Microbial stress priming: a meta-analysis. Environ Microbiol 18(4):1277–1288. https://doi.org/10.1111/1462-2920.13223

    Article  PubMed  Google Scholar 

  28. Wu Q, Zhu L, Xu Q, Huang H, Jiang L, Yang S-T (2017) Tailoring the oxidative stress tolerance of Clostridium tyrobutyricum CCTCC W428 by introducing trehalose biosynthetic capability. J Agric Food Chem 65(40):8892–8901. https://doi.org/10.1021/acs.jafc.7b03172

    Article  CAS  PubMed  Google Scholar 

  29. Iordachescu M, Imai R (2008) Trehalose biosynthesis in response to abiotic stresses. J Integr Plant Biol 50(10):1223–1229. https://doi.org/10.1111/j.1744-7909.2008.00736.x

    Article  CAS  PubMed  Google Scholar 

  30. Tan Z, Yoon JM, Nielsen DR, Shanks JV, Jarboe LR (2016) Membrane engineering via trans unsaturated fatty acids production improves Escherichia coli robustness and production of biorenewables. Metab Eng 35:105–113. https://doi.org/10.1016/j.ymben.2016.02.004

    Article  CAS  PubMed  Google Scholar 

  31. Kavi Kishor PB, Sreenivasulu N (2014) Is proline accumulation per se correlated with stress tolerance or is proline homeostasis a more critical issue? Plant Cell Environ 37(2):300–311. https://doi.org/10.1111/pce.12157

    Article  CAS  PubMed  Google Scholar 

  32. Wang X, Bai X, Chen DF, Chen FZ, Li BZ, Yuan YJ (2015) Increasing proline and myo-inositol improves tolerance of Saccharomyces cerevisiae to the mixture of multiple lignocellulose-derived inhibitors. Biotechnol Biofuels 8(1):142. https://doi.org/10.1186/s13068-015-0329-5

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

This study was supported by the National Key Research and Development Program of China (2018YFA090039), Natural Science Foundation of Tianjin (17JCQNJC09500), National Natural Science Foundation of China (21808168, 31470211), Tianjin Municipal Science and Technology Commission (17YFZCSY01050), Public Service Platform Project of Industrial Microbial Breeding and Fermentation Technology (17PTGCCX00190).

Author information

Author notes

  1. Qian Ma and Xiaolin Mo contributed equally to this work.

Authors and Affiliations

  1. Key Laboratory of Industrial Fermentation Microbiology, Tianjin University of Science and Technology, Ministry of Education, Tianjin, 300457, People’s Republic of China

    Qian Ma, Xixian Xie & Ning Chen

  2. Tianjin Key Laboratory of Industrial Microbiology, Tianjin University of Science and Technology, Tianjin, 300457, People’s Republic of China

    Qian Ma, Xixian Xie & Ning Chen

  3. College of Biotechnology, Tianjin University of Science and Technology, Tianjin, 300457, People’s Republic of China

    Qian Ma, Xiaolin Mo, Quanwei Zhang, Zhengjie Hou, Miao Tan, Li Xia, Quanwei Sun, Xixian Xie & Ning Chen

  4. National and Local United Engineering Lab of Metabolic Control Fermentation Technology, Tianjin University of Science and Technology, Tianjin, 300457, People’s Republic of China

    Qian Ma, Xixian Xie & Ning Chen

  5. Tianjin Engineering Research Center of Microbial Metabolism and Fermentation Process Control, Tianjin, 300457, People’s Republic of China

    Ning Chen

Authors
  1. Qian Ma
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Xiaolin Mo
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Quanwei Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Zhengjie Hou
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Miao Tan
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Li Xia
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Quanwei Sun
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Xixian Xie
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Ning Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

The manuscript was written through contributions of all authors. QM and XLM collected samples, conducted experiments, performed data analysis, and wrote the manuscript. QWZ, ZJH, MT, and QWS contributed in collection of samples. XLM and LX did the omics analysis; XXX and CN supervised the whole research and revised the manuscript.

Corresponding authors

Correspondence to Xixian Xie or Ning Chen.

Ethics declarations

Conflict of interest

The authors declare no competing financial interests.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ma, Q., Mo, X., Zhang, Q. et al. Comparative metabolomic analysis reveals different evolutionary mechanisms for branched-chain amino acids production. Bioprocess Biosyst Eng 43, 85–95 (2020). https://doi.org/10.1007/s00449-019-02207-5

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00449-019-02207-5

Keywords

Search

Navigation