Project properties
Title Modelling Toxicity dynamics in bioprocess design and optimization
Group Systems and Synthetic Biology
Project type thesis
Credits 36
Supervisor(s) Ivan Martin Martin, Jasper Koehorst, Maria Suarez Diez
Examiner(s) Prof. Maria Suarez Diez (SSB) Dr. Rob Smith
Contact info Robert1.smith@wur.nl
Begin date 2025/12/01
End date
Description Microbial cell factories (MCF) are important to design biobased synthesis processes to substitute fossil fuel based production procedures. However, the implementation and scale-up of these bioprocesses is technically challenging, since bioreactor operating conditions largely affect the production of microbial cell factories.
With this purpose, a tool has been developed (biosimul) to find the ideal production conditions for a certain bioprocess and microbial workhorse (e.g. production of p-coumaric acid by Pseudomonas putida). The tool uses constraint-based modelling to simulate the microbial dynamics in a bioreactor under a certain operating mode (e.g. batch or fed-batch), where reactor constraints are also considered. The tool extends previous work developed in [1].
In this context, the main goal of this project is to extend and test the current biosimul application to (mechanistically) consider toxicity dynamics (e.g. a product that becomes toxic for the MCF above certain concentrations, this should be modelled with an ODE). An example could be to model the production of ethanol by S. cerevisiae, for which high concentrations of this compound become toxic.
The thesis will most likely involve to (1) find a relevant dataset as experimental benchmark, (2) to code (in Python) and test different approaches (simple ODE simulations) to mimic the product toxicity within the biosimul application, (3) to generate results for a given MCF in a set of scenarios, (4) to compare these results with the experimental datasets and to draw some conclusions on why it works (or not) and what to improve.

References related to project: [1]
Used skills
Requirements Programming in Python. Basic knowledge of Ordinary Differential Equation (ODE) systems. Constraint based modelling of metabolism (such as what is seen in Metabolic Engineering of Industrial Microorganisms - MEIM, BPE34306) is highly recommended. Knowledge of Unix/Linux operating system is also welcomed but not required.