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Systems strategies for developing industrial microbial strains

Nature Biotechnology volume 33, pages 1061–1072 (2015)Cite this article

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Abstract

Industrial strain development requires system-wide engineering and optimization of cellular metabolism while considering industrially relevant fermentation and recovery processes. It can be conceptualized as several strategies, which may be implemented in an iterative fashion and in different orders. The key challenges have been the time-, cost- and labor-intensive processes of strain development owing to the difficulties in understanding complex interactions among the metabolic, gene regulatory and signaling networks at the cell level, which are collectively represented as overall system performance under industrial fermentation conditions. These challenges can be overcome by taking systems approaches through the use of state-of-the-art tools of systems biology, synthetic biology and evolutionary engineering in the context of industrial bioprocess. Major systems metabolic engineering achievements in recent years include microbial production of amino acids (L-valine, L-threonine, L-lysine and L-arginine), bulk chemicals (1,4-butanediol, 1,4-diaminobutane, 1,5-diaminopentane, 1,3-propanediol, butanol, isobutanol and succinic acid) and drugs (artemisinin).

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Figure 1: Concept of the systems metabolic engineering framework.
Figure 2: General scheme of systems metabolic engineering and its case study on the overproduction of L-arginine using C. glutamicum15.
Figure 3: General scheme of systems metabolic engineering and its case study on the overproduction of 1,4-butanediol using E. coli11.
Figure 4: General scheme of systems metabolic engineering and its case study on the overproduction of L-lysine16 and bio-nylon17 using C. glutamicum.

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References

  1. Hong, K.K. & Nielsen, J. Metabolic engineering of Saccharomyces cerevisiae: a key cell factory platform for future biorefineries. Cell. Mol. Life Sci. 69, 2671–2690 (2012).

    Article  CAS  Google Scholar 

  2. Pronk, J.T. et al. How to set up collaborations between academia and industrial biotech companies. Nat. Biotechnol. 33, 237–240 (2015).

    Article  CAS  Google Scholar 

  3. Bailey, J.E. Toward a science of metabolic engineering. Science 252, 1668–1675 (1991).

    Article  CAS  Google Scholar 

  4. Lee, J.W. et al. Systems metabolic engineering of microorganisms for natural and non-natural chemicals. Nat. Chem. Biol. 8, 536–546 (2012).

    Article  CAS  Google Scholar 

  5. Sagt, C.M. Systems metabolic engineering in an industrial setting. Appl. Microbiol. Biotechnol. 97, 2319–2326 (2013).

    Article  CAS  Google Scholar 

  6. Park, J.H., Lee, K.H., Kim, T.Y. & Lee, S.Y. Metabolic engineering of Escherichia coli for the production of L-valine based on transcriptome analysis and in silico gene knockout simulation. Proc. Natl. Acad. Sci. USA 104, 7797–7802 (2007).

    Article  CAS  Google Scholar 

  7. Park, J.H., Kim, T.Y., Lee, K.H. & Lee, S.Y. Fed-batch culture of Escherichia coli for L-valine production based on in silico flux response analysis. Biotechnol. Bioeng. 108, 934–946 (2011).

    Article  CAS  Google Scholar 

  8. Park, J.H., Jang, Y.S., Lee, J.W. & Lee, S.Y. Escherichia coli W as a new platform strain for the enhanced production of L-valine by systems metabolic engineering. Biotechnol. Bioeng. 108, 1140–1147 (2011).

    Article  CAS  Google Scholar 

  9. Lee, K.H., Park, J.H., Kim, T.Y., Kim, H.U. & Lee, S.Y. Systems metabolic engineering of Escherichia coli for L-threonine production. Mol. Syst. Biol. 3, 149 (2007).

    Article  CAS  Google Scholar 

  10. Lee, J.W. et al. Development of sucrose-utilizing Escherichia coli K-12 strain by cloning β-fructofuranosidases and its application for L-threonine production. Appl. Microbiol. Biotechnol. 88, 905–913 (2010).

    Article  CAS  Google Scholar 

  11. Yim, H. et al. Metabolic engineering of Escherichia coli for direct production of 1,4-butanediol. Nat. Chem. Biol. 7, 445–452 (2011).

    Article  CAS  Google Scholar 

  12. Paddon, C.J. et al. High-level semi-synthetic production of the potent antimalarial artemisinin. Nature 496, 528–532 (2013).

    Article  CAS  Google Scholar 

  13. Lee, S.J., Song, H. & Lee, S.Y. Genome-based metabolic engineering of Mannheimia succiniciproducens for succinic acid production. Appl. Environ. Microbiol. 72, 1939–1948 (2006).

    Article  CAS  Google Scholar 

  14. Becker, J. et al. Systems-wide analysis and engineering of metabolic pathway fluxes in bio-succinate producing Basfia succiniciproducens. Biotechnol. Bioeng. 110, 3013–3023 (2013).

    Article  CAS  Google Scholar 

  15. Park, S.H. et al. Metabolic engineering of Corynebacterium glutamicum for L-arginine production. Nat. Commun. 5, 4618 (2014).

    Article  CAS  Google Scholar 

  16. Becker, J., Zelder, O., Häfner, S., Schröder, H. & Wittmann, C. From zero to hero—design-based systems metabolic engineering of Corynebacterium glutamicum for L-lysine production. Metab. Eng. 13, 159–168 (2011).

    Article  CAS  Google Scholar 

  17. Kind, S. et al. From zero to hero—production of bio-based nylon from renewable resources using engineered Corynebacterium glutamicum. Metab. Eng. 25, 113–123 (2014).

    Article  CAS  Google Scholar 

  18. Lee, S.Y., Lee, D.Y. & Kim, T.Y. Systems biotechnology for strain improvement. Trends Biotechnol. 23, 349–358 (2005).

    Article  CAS  Google Scholar 

  19. Medema, M.H., van Raaphorst, R., Takano, E. & Breitling, R. Computational tools for the synthetic design of biochemical pathways. Nat. Rev. Microbiol. 10, 191–202 (2012).

    Article  CAS  Google Scholar 

  20. Paddon, C.J. & Keasling, J.D. Semi-synthetic artemisinin: a model for the use of synthetic biology in pharmaceutical development. Nat. Rev. Microbiol. 12, 355–367 (2014).

    Article  CAS  Google Scholar 

  21. Esvelt, K.M. & Wang, H.H. Genome-scale engineering for systems and synthetic biology. Mol. Syst. Biol. 9, 641 (2013).

    Article  Google Scholar 

  22. Yadav, V.G., De Mey, M., Lim, C.G., Ajikumar, P.K. & Stephanopoulos, G. The future of metabolic engineering and synthetic biology: towards a systematic practice. Metab. Eng. 14, 233–241 (2012).

    Article  CAS  Google Scholar 

  23. Cobb, R.E., Si, T. & Zhao, H. Directed evolution: an evolving and enabling synthetic biology tool. Curr. Opin. Chem. Biol. 16, 285–291 (2012).

    Article  CAS  Google Scholar 

  24. Lee, S.Y. High cell-density culture of Escherichia coli. Trends Biotechnol. 14, 98–105 (1996).

    Article  CAS  Google Scholar 

  25. Lee, B.R., Cho, S., Song, Y., Kim, S.C. & Cho, B.K. Emerging tools for synthetic genome design. Mol. Cells 35, 359–370 (2013).

    Article  CAS  Google Scholar 

  26. Song, C.W., Lee, J. & Lee, S.Y. Genome engineering and gene expression control for bacterial strain development. Biotechnol. J. 10, 56–68 (2015).

    Article  CAS  Google Scholar 

  27. Zhuang, K.H. & Herrgård, M.J. Multi-scale exploration of the technical, economic, and environmental dimensions of bio-based chemical production. Metab. Eng. 31, 1–12 (2015).

    Article  CAS  Google Scholar 

  28. Croughan, M.S., Konstantinov, K.B. & Cooney, C. The future of industrial bioprocessing: batch or continuous? Biotechnol. Bioeng. 112, 648–651 (2015).

    Article  CAS  Google Scholar 

  29. Van Dien, S. From the first drop to the first truckload: commercialization of microbial processes for renewable chemicals. Curr. Opin. Biotechnol. 24, 1061–1068 (2013).

    Article  CAS  Google Scholar 

  30. Choi, S. et al. Production of 4-hydroxybutyric acid by metabolically engineered Mannheimia succiniciproducens and its conversion to γ-butyrolactone by acid treatment. Metab. Eng. 20, 73–83 (2013).

    Article  CAS  Google Scholar 

  31. Anbarasan, P. et al. Integration of chemical catalysis with extractive fermentation to produce fuels. Nature 491, 235–239 (2012).

    Article  CAS  Google Scholar 

  32. Guan, Y., Dunham, M., Caudy, A. & Troyanskaya, O. Systematic planning of genome-scale experiments in poorly studied species. PLOS Comput. Biol. 6, e1000698 (2010).

    Article  Google Scholar 

  33. Cobb, R.E., Wang, Y. & Zhao, H. High-efficiency multiplex genome editing of Streptomyces species using an engineered CRISPR/Cas system. ACS Synth. Biol. 4, 723–728 (2015).

    Article  CAS  Google Scholar 

  34. Tong, Y., Charusanti, P., Zhang, L., Weber, T. & Lee, S.Y. CRISPR-Cas9 based engineering of actinomycetal genomes. ACS Synth. Biol. 10.1021/acssynbio.5b00038 (25 March 2015).

  35. Shin, J.H., Kim, H.U., Kim, D.I. & Lee, S.Y. Production of bulk chemicals via novel metabolic pathways in microorganisms. Biotechnol. Adv. 31, 925–935 (2013).

    Article  CAS  Google Scholar 

  36. Lee, J.W., Kim, T.Y., Jang, Y.S., Choi, S. & Lee, S.Y. Systems metabolic engineering for chemicals and materials. Trends Biotechnol. 29, 370–378 (2011).

    Article  CAS  Google Scholar 

  37. Lee, J.W., Kim, H.U., Choi, S., Yi, J. & Lee, S.Y. Microbial production of building block chemicals and polymers. Curr. Opin. Biotechnol. 22, 758–767 (2011).

    Article  CAS  Google Scholar 

  38. Choi, Y.J. & Lee, S.Y. Microbial production of short-chain alkanes. Nature 502, 571–574 (2013).

    Article  CAS  Google Scholar 

  39. Dellomonaco, C., Clomburg, J.M., Miller, E.N. & Gonzalez, R. Engineered reversal of the β-oxidation cycle for the synthesis of fuels and chemicals. Nature 476, 355–359 (2011).

    Article  CAS  Google Scholar 

  40. Yu, J.L., Xia, X.X., Zhong, J.J. & Qian, Z.G. Direct biosynthesis of adipic acid from a synthetic pathway in recombinant Escherichia coli. Biotechnol. Bioeng. 111, 2580–2586 (2014).

    Article  CAS  Google Scholar 

  41. Borodina, I. et al. Establishing a synthetic pathway for high-level production of 3-hydroxypropionic acid in Saccharomyces cerevisiae via β-alanine. Metab. Eng. 27, 57–64 (2015).

    Article  CAS  Google Scholar 

  42. Jiang, M. & Pfeifer, B.A. Metabolic and pathway engineering to influence native and altered erythromycin production through E. coli. Metab. Eng. 19, 42–49 (2013).

    Article  CAS  Google Scholar 

  43. Zhang, K., Li, H., Cho, K.M. & Liao, J.C. Expanding metabolism for total biosynthesis of the nonnatural amino acid L-homoalanine. Proc. Natl. Acad. Sci. USA 107, 6234–6239 (2010).

    Article  CAS  Google Scholar 

  44. Smanski, M.J. et al. Functional optimization of gene clusters by combinatorial design and assembly. Nat. Biotechnol. 32, 1241–1249 (2014).

    Article  CAS  Google Scholar 

  45. Ling, H., Teo, W., Chen, B., Leong, S.S. & Chang, M.W. Microbial tolerance engineering toward biochemical production: from lignocellulose to products. Curr. Opin. Biotechnol. 29, 99–106 (2014).

    Article  CAS  Google Scholar 

  46. Utrilla, J. et al. Engineering and adaptive evolution of Escherichia coli for D-lactate fermentation reveals GatC as a xylose transporter. Metab. Eng. 14, 469–476 (2012).

    Article  CAS  Google Scholar 

  47. Dunlop, M.J. et al. Engineering microbial biofuel tolerance and export using efflux pumps. Mol. Syst. Biol. 7, 487 (2011).

    Article  Google Scholar 

  48. Lam, F.H., Ghaderi, A., Fink, G.R. & Stephanopoulos, G. Biofuels. Engineering alcohol tolerance in yeast. Science 346, 71–75 (2014).

    Article  CAS  Google Scholar 

  49. Na, D. et al. Metabolic engineering of Escherichia coli using synthetic small regulatory RNAs. Nat. Biotechnol. 31, 170–174 (2013).

    Article  CAS  Google Scholar 

  50. Yoo, S.M., Na, D. & Lee, S.Y. Design and use of synthetic regulatory small RNAs to control gene expression in Escherichia coli. Nat. Protoc. 8, 1694–1707 (2013).

    Article  CAS  Google Scholar 

  51. King, Z.A. & Feist, A.M. Optimal cofactor swapping can increase the theoretical yield for chemical production in Escherichia coli and Saccharomyces cerevisiae. Metab. Eng. 24, 117–128 (2014).

    Article  CAS  Google Scholar 

  52. Rellos, P., Ma, J. & Scopes, R.K. Alteration of substrate specificity of Zymomonas mobilis alcohol dehydrogenase-2 using in vitro random mutagenesis. Protein Expr. Purif. 9, 83–90 (1997).

    Article  CAS  Google Scholar 

  53. Kim, J. & Copley, S.D. Inhibitory cross-talk upon introduction of a new metabolic pathway into an existing metabolic network. Proc. Natl. Acad. Sci. USA 109, E2856–E2864 (2012).

    Article  CAS  Google Scholar 

  54. Jantama, K. et al. Eliminating side products and increasing succinate yields in engineered strains of Escherichia coli C. Biotechnol. Bioeng. 101, 881–893 (2008).

    Article  CAS  Google Scholar 

  55. Kim, T.Y., Park, J.M., Kim, H.U., Cho, K.M. & Lee, S.Y. Design of homo-organic acid producing strains using multi-objective optimization. Metab. Eng. 28, 63–73 (2015).

    Article  CAS  Google Scholar 

  56. Lewis, N.E., Nagarajan, H. & Palsson, B.O. Constraining the metabolic genotype-phenotype relationship using a phylogeny of in silico methods. Nat. Rev. Microbiol. 10, 291–305 (2012).

    Article  CAS  Google Scholar 

  57. Wang, H.H. et al. Programming cells by multiplex genome engineering and accelerated evolution. Nature 460, 894–898 (2009).

    Article  CAS  Google Scholar 

  58. Wang, H.H. et al. Genome-scale promoter engineering by coselection MAGE. Nat. Methods 9, 591–593 (2012).

    Article  Google Scholar 

  59. Warner, J.R., Reeder, P.J., Karimpour-Fard, A., Woodruff, L.B. & Gill, R.T. Rapid profiling of a microbial genome using mixtures of barcoded oligonucleotides. Nat. Biotechnol. 28, 856–862 (2010).

    Article  CAS  Google Scholar 

  60. Hollinshead, W., He, L. & Tang, Y.J. Biofuel production: an odyssey from metabolic engineering to fermentation scale-up. Front. Microbiol. 5, 344 (2014).

    Article  Google Scholar 

  61. Dahl, R.H. et al. Engineering dynamic pathway regulation using stress-response promoters. Nat. Biotechnol. 31, 1039–1046 (2013).

    Article  CAS  Google Scholar 

  62. Galanie, S., Thodey, K., Trenchard, I.J., Filsinger, I.M. & Smolke, C.D. Complete biosynthesis of opioids in yeast. Science 349, 1095–1100 (2015).

    Article  CAS  Google Scholar 

  63. Karr, J.R. et al. A whole-cell computational model predicts phenotype from genotype. Cell 150, 389–401 (2012).

    Article  CAS  Google Scholar 

  64. Hsiao, T.Y., Glatz, C.E. & Glatz, B.A. Broth recycle in a yeast fermentation. Biotechnol. Bioeng. 44, 1228–1234 (1994).

    Article  CAS  Google Scholar 

  65. Yin, J., Fu, X.Z., Wu, Q., Chen, J.C. & Chen, G.Q. Development of an enhanced chromosomal expression system based on porin synthesis operon for halophile Halomonas sp. Appl. Microbiol. Biotechnol. 98, 8987–8997 (2014).

    Article  CAS  Google Scholar 

  66. Caspeta, L. et al. Biofuels. Altered sterol composition renders yeast thermotolerant. Science 346, 75–78 (2014).

    Article  CAS  Google Scholar 

  67. Bonneau, R. et al. A predictive model for transcriptional control of physiology in a free living cell. Cell 131, 1354–1365 (2007).

    Article  CAS  Google Scholar 

  68. Xia, J., Yamaji, N. & Ma, J.F. An appropriate concentration of arginine is required for normal root growth in rice. Plant Signal. Behav. 9, e28717 (2014).

    Article  Google Scholar 

  69. Burgard, A.P., Pharkya, P. & Maranas, C.D. Optknock: a bilevel programming framework for identifying gene knockout strategies for microbial strain optimization. Biotechnol. Bioeng. 84, 647–657 (2003).

    Article  CAS  Google Scholar 

  70. Antoniewicz, M.R. 13C metabolic flux analysis: optimal design of isotopic labeling experiments. Curr. Opin. Biotechnol. 24, 1116–1121 (2013).

    Article  CAS  Google Scholar 

  71. Trinh, C.T., Wlaschin, A. & Srienc, F. Elementary mode analysis: a useful metabolic pathway analysis tool for characterizing cellular metabolism. Appl. Microbiol. Biotechnol. 81, 813–826 (2009).

    Article  CAS  Google Scholar 

  72. Kim, H.U., Kim, T.Y. & Lee, S.Y. Metabolic flux analysis and metabolic engineering of microorganisms. Mol. Biosyst. 4, 113–120 (2008).

    Article  Google Scholar 

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Acknowledgements

We thank Seok Hyun Park, Sol Choi, Joungmin Lee, Chan Woo Song, Jae Ho Shin and Won Jun Kim for thoughtful discussions. This work was supported by the Technology Development Program to Solve Climate Changes on Systems Metabolic Engineering for Biorefineries (NRF-2012M1A2A2026556) and by Intelligent Synthetic Biology Center through the Global Frontier Project (2011-0031963) from the Ministry of Science, ICT and Future Planning (MSIP) through the National Research Foundation (NRF) of Korea. This work was also supported by the Novo Nordisk Foundation.

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Authors and Affiliations

  1. Department of Chemical and Biomolecular Engineering (BK21 Plus Program), Metabolic and Biomolecular Engineering National Research Laboratory, Center for Systems and Synthetic Biotechnology, Institute for the BioCentury, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea

    Sang Yup Lee & Hyun Uk Kim

  2. BioInformatics Research Center, KAIST, Daejeon, Republic of Korea

    Sang Yup Lee & Hyun Uk Kim

  3. BioProcess Engineering Research Center, KAIST, Daejeon, Republic of Korea

    Sang Yup Lee

  4. The Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Hørsholm, Denmark

    Sang Yup Lee & Hyun Uk Kim

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Correspondence to Sang Yup Lee.

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

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