Experimental investigation into indole production using passaging of E. coli and B. subtilis along with unstructured modeling and parameter estimation using dynamic optimization: An integrated framework

Abstract

Greener process synthesis for drug production focuses on the replacement of chemical processes with biological processes. However, optimization of these processes remains challenging due to lack of experimental data, particularly for long term passaging and suitable parameter estimation techniques. In this context, we propose a mixed passaging scheme containing the co-culture of E. coli and B. subtilis that can be used to produce indole. The cell growth and product profiles obtained from fermenter corresponding to pure culture and individual culture obtained after passaging of E. coli and B. subtilis were used for unstructured model selection. Kinetic parameter estimation was performed using a hybrid technique combining classical and evolutionary algorithms. The dynamic interaction between the two organisms in long term passaging was captured by implementing optimal control for estimating time-varying parameters. The proposed unstructured model is capable of emulating the mixed culture effect on cell growth, product formation, and substrate depletion. This is the first instance where an integrated framework combining experimental and computational methodology is used to estimate and analyse model parameters in a mixed culture of E. coli and B. subtilis towards indole production. A similar framework can be used for optimizing the process parameters to improve the indole production.