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Robustness analysis and identification for an enzyme-catalytic complex metabolic network in batch culture

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Abstract

Bioconversion of glycerol to 1,3-propanediol is a promising way to mitigate the shortage of energy. To maximize the production of 1,3-propanediol, it needs to control precisely microbial fermentation process. However, it might consume lots of human and material resources when conducting experimental tests many times. In this study, a nonlinear enzyme-catalytic dynamical system is developed to describe the bioconversion process of glycerol to 1,3-propanediol, especially continuous piecewise linear functions are used as identification parameters. The existence, uniqueness and continuity of solutions are also discussed. Then, considering the fact that the concentration of intracellular substances is difficult to measure in experiments, a new quantitative definition of biological robustness is introduced as a performance index to determine the identification parameters related to intracellular substances. Meanwhile, a two-phase optimization algorithm is constructed to solve the identification model. By comparison with the experimental data, it can be found that the present nonlinear dynamical system can describe the fermentation process very well. Finally, the present nonlinear dynamical system and the corresponding optimal identification parameters might be useful in future studies on the batch culture of glycerol to 1,3-propanediol.

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Acknowledgements

This work was supported by the National Natural Science Foundation of China (Grant Nos. 11171050, 11901075 and 72061007), the Fundamental Research Funds for Central Universities in China (Grant No. DUT15LK25), the Guangxi Key Laboratory of Cryptography and Information Security at Guilin University of Electronic Technology (Grant No. GCIS201929) and Guangxi Young Scholar Research Ability Enhancement Program (Grant No. 2020KY05017).

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Authors and Affiliations

  1. School of Mathematics and Computing Science, Guilin University of Electronic Technology, Guilin, 541004, Guangxi, People’s Republic of China

    Qi Yang & Qunbin Chen

  2. School of Mathematical Sciences, Dalian University of Technology, Dalian, 116024, Liaoning, People’s Republic of China

    Teng Niu & Enmin Feng

  3. Department of Mathematics, School of Science, Dalian Maritime University, Dalian, 116026, Liaoning, People’s Republic of China

    Jinlong Yuan

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  1. Qi Yang
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Correspondence to Qunbin Chen.

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Yang, Q., Chen, Q., Niu, T. et al. Robustness analysis and identification for an enzyme-catalytic complex metabolic network in batch culture. Bioprocess Biosyst Eng 44, 1511–1524 (2021). https://doi.org/10.1007/s00449-021-02535-5

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