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In silico cell factory design driven by comprehensive genome-scale metabolic models: development and challenges

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Abstract

Genome-scale metabolic models (GEMs) have been widely used to design cell factories in silico. However, initial flux balance analysis only considers stoichiometry and reaction direction constraints, so it cannot accurately describe the distribution of metabolic flux under the control of various regulatory mechanisms. In the recent years, by introducing enzymology, thermodynamics, and other multiomics-based constraints into GEMs, the metabolic state of cells under different conditions was more accurately simulated and a series of algorithms have been presented for microbial phenotypic analysis. Herein, the development of multiconstrained GEMs was reviewed by taking the constraints of enzyme kinetics, thermodynamics, and transcriptional regulatory mechanisms as examples. This review focused on introducing and summarizing GEMs application tools and cases in cell factory design. The challenges and prospects of GEMs development were also discussed.

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Acknowledgements

This work was financially supported by the Key Research and Development Program of China (2020YFA0908300), the National Natural Science Foundation of China (31870069 and 32021005), and the Fundamental Research Funds for the Central Universities (USRP52019A, JUSRP121010, and JUSRP221013).

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  1. Key Laboratory of Carbohydrate Chemistry and Biotechnology, Ministry of Education, Jiangnan University, Wuxi, 214122, China

    Jiangong Lu, Xinyu Bi, Yanfeng Liu, Xueqin Lv, Jianghua Li, Guocheng Du & Long Liu

  2. Science Center for Future Foods, Jiangnan University, Wuxi, 214122, China

    Jiangong Lu, Xinyu Bi, Yanfeng Liu, Xueqin Lv, Jianghua Li, Guocheng Du & Long Liu

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JGL and XYB completed the collection and analysis of relevant literatures and the writing of the first draft. YFL, XQL, JHL, GCD and LL revised the manuscript. XQL and LL designed the manuscript. All authors contributed to the manuscript.

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Lu, J., Bi, X., Liu, Y. et al. In silico cell factory design driven by comprehensive genome-scale metabolic models: development and challenges. Syst Microbiol and Biomanuf 3, 207–222 (2023). https://doi.org/10.1007/s43393-022-00117-4

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