Team:Jilin China/Model

General Overview

For project modelling, our aim was to estimate the growth of the engineered bacteria and to develop a method to fit the kinetic parameters in the progress of phenol degradation. Our project was based on a feedback adjustment mechanism – engineered bacteria growth was supposed to recover when phenol was detected, and phenol would be degraded by the engineered bacteria. In this year’s modelling part, we separated this feedback network into two parts: one part was the engineered bacteria population modelling (as the feedback on phenol concentration changes). And another part was phenol degradation kinetics modelling (as the functional part). By combining these two models, we set up the whole feedback adjustment network. All the codes are available on our GitHub

For the population modelling part, safety was our first concern, which means that E. coli growth could be under control. We set up two growth models – a population growth model free from toxin protein (CbtA) and a growth model affected by CbtA. By comparing the parameter in these two models, we saw clear changes after the expression of CbtA. The general growth was supposed to be a weighted average of these two models and the weights would change as the feedback on phenol concentration changes. Read more...

For the phenol degradation kinetic modelling part, we developed a method to fit the models. Since our monooxygenase (TfdB-JLU) was supposed to function on a wide range of substrates (such as 2,4-dichlorophenol, phenol, indole, etc.), there was too much work for us to test all the substrates. Though not all the experiments were finished, we developed this fitting method for our future work. Read more...

Finally, the E. coli population model and the chlorophenol degrading model were combined. Since the population of E. coli was closely related with the concentration of chlorophenol (the anti-toxin which affects the growth of E. coli is controlled by chlorophenol), this combination would draw a clear picture of how our engineered bacteria works. This model took the population changes into account and could help us understand more about the rate of the degradation. Read more...