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Project properties |
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| Title | Impact of regulation on enzyme-constrained genome scale metabolic models |
| Group | Systems and Synthetic Biology |
| Project type | thesis |
| Credits | 36 |
| Supervisor(s) | María Suárez Diez, David Saque Henriques |
| Examiner(s) | Prof. Maria Suarez Diez; Dr. Rob Smith |
| Contact info | robert1.smith@wur.nl |
| Begin date | 2024/11/01 |
| End date | |
| Description | Genome scale metabolic models (GEMs) are mathematical representations of cell metabolism based on genome annotation. Their enzyme-constrained versions (ecGEMs) include a constraint that represents the limitation of protein content in a cell. These models are solely based on reaction stoichiometry, they do not include regulation at the gene or protein level, and they assume steady state1.
GEMs and ecGEMs can be simulated under dynamic conditions using dynamic flux balance analysis (dFBA). Besides, ecGEMs can predict metabolic changes such as ethanol production of Saccharomyces cerevisiae cells grown aerobically with glucose excess (Crabtree effect)2. In this project, you will investigate whether the addition of regulation to ecGEMs can improve predictions on protein usage during the Crabtree effect. This project starts by estimating parameters to match dFBA simulations of an ecGEM of S. cerevisiae to experimental data. Then, model predictions on enzyme usage will be compared to proteomic datasets. Finally, the effect of additional constraints on ecGEM mimicking known gene regulation will be studied. With this, you will be able to understand if the characteristic protein constraint of ecGEMs is enough to substitute the effect of regulation. Bibliography 1. Sánchez BJ, Zhang C, Nilsson A, Lahtvee P-J, Kerkhoven EJ, Nielsen J. Improving the phenotype predictions of a yeast genome-scale metabolic model by incorporating enzymatic constraints. Mol Syst Biol. 2017;13:935. doi:10.15252/msb.20167411 2. Moreno-Paz S, Schmitz J, Martins dos Santos VAP, Suarez-Diez M. Enzyme-constrained models predict the dynamics of Saccharomyces cerevisiae growth in continuous, batch and fed-batch bioreactors. Microb Biotechnol. 2022;15(5):1434-1445. doi:10.1111/1751-7915.13995 |
| Used skills | • Working with enzyme-constrained genome scale models and dynamic models
• Integration of dynamic flux balance analysis and regulation • Microbial metabolism and its regulation |
| Requirements | basic knowledge of python, basic knowledge of microbial models of metabolism (for instance BPE-34306 or SSB-50806). |