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Project properties |
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| Title | A practical approach for bioreactor parameter optimization |
| Group | Systems and Synthetic Biology |
| Project type | thesis |
| Credits | 36 |
| Supervisor(s) | Iván Martín Martín, Jasper Koehorst, Maria Suarez Diez |
| Examiner(s) | Dr Jasper Koehorst; Prof. Dr Maria Suarez Diez |
| Contact info | Robert1.smith@wur.nl |
| Begin date | 2024/12/01 |
| 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.
The aim of this MSc project is to model microbial metabolism through a parameter optimization framework (Python application already available, called Bioprocess simulator) 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]. The main goal of this project is to test the tool and find the ideal combination of values for the parameters in a certain reactor operating mode (e.g. fed, gas flow, initial carbon and nitrogen concentration, reactor volume, etc.) and the most suitable GEM for the microbe of choice, to maximize a certain performance measure in a specific production process of interest. In this work the student will use already available models to simulate the behaviour of MCFs such as P. putida, Saccharomyces cerevisiae, Yarrowia lipolytica or Escherichia coli. References [1] Moreno-Paz, S., Schmitz, J., Martins dos Santos, V. A. P., Suarez-Diez, M. (2022). Enzyme-constrained models predict the dynamics of Saccharomyces cerevisiae growth in continuous, batch and fed-batch bioreactors. Microbial Biotechnology. https://doi.org/10.1111/1751-7915.13995. |
| Used skills | Modelling of microbial metabolism using genome scale models (GEMs) and enzyme constraint models (ecGEMs), and dynamic flux balance analysis.
Python for data analysis and basic software tool development. User knowledge on statistical optimization frameworks. |
| Requirements | Programming in Python. 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. |