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

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.