Stochastic Boolean model of normal and aberrant cell cycles in budding yeast
Kittisak Taoma1,2, John J Tyson3, Teeraphan Laomettachit4,5
1Bioinformatics and Systems Biology Program, School of Bioresources and Technology, King Mongkut's University of Technology Thonburi, Bangkok, 10150, Thailand.
NPJ Systems Biology and Applications
|October 17, 2024
Summary
This study models the budding yeast cell cycle using a stochastic Boolean framework. The validated model accurately predicts phenotypes of numerous mutant strains, aiding understanding of cell cycle control.
Area of Science:
- Cell Biology
- Systems Biology
- Computational Biology
Background:
- The budding yeast cell cycle is regulated by a complex protein network.
- Dysregulation of this network can cause cell division errors and lethality.
- Understanding yeast cell cycle control provides insights into mammalian cell processes.
Purpose of the Study:
- To develop a Boolean model for simulating the budding yeast cell cycle.
- To validate the model against experimental data from mutant yeast strains.
- To explore the model's utility in simulating specific cell cycle anomalies.
Main Methods:
- Utilized a Boolean framework for stochastic simulations.
- Modeled the intricate protein regulatory network governing the cell cycle.
- Compared model predictions with experimental phenotypes of 40 mutant yeast strains.
Main Results:
- The model successfully accounted for the phenotypes of 83% of simulated mutant strains.
- The model accurately simulated endoreplicating and Cdc14 endocycles strains.
- The model replicated observed properties of wild-type and many mutant yeast cells.
Conclusions:
- The developed stochastic-Boolean model is a validated tool for studying yeast cell cycle control.
- The model serves as a foundation for more complex simulations of cell cycle anomalies.
- This approach may enhance understanding of cell cycle regulation in both yeast and mammalian cells.
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