An agent-based model of the fission yeast cell cycle

• Published in: Current genetics Vol. 65; no. 1; pp. 193 - 200
• Main Authors: Castro, Carlos, Flores, Dora-Luz, Cervantes-Vásquez, David, Vargas-Viveros, Eunice, Gutiérrez-López, Everardo, Muñoz-Muñoz, Franklin
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01-02-2019; Springer Nature B.V
• Subjects: Agent-based models; Biochemistry; Biological activity; Biological models (mathematics); Biomedical and Life Sciences; Cancer; Cell Biology; Cell cycle; Computer applications; Computer simulation; Differential equations; Fission; G1 Phase - physiology; Initial conditions; Life Sciences; Mathematical models; Microbial Genetics and Genomics; Microbiology; Models, Biological; Original Article; Plant Sciences; Protein interaction; Proteins; Proteomics; Schizosaccharomyces - physiology; Schizosaccharomyces pombe Proteins - physiology; Stochasticity; Yeast; Yeasts; Agent-based modeling; Fission yeast; Cell cycle; Cancer
• ISSN: 0172-8083; 1432-0983
• DOI: 10.1007/s00294-018-0859-z

The objective of this paper is to develop a computational model of the fission yeast (
Schizosaccharomyces pombe
) cell cycle using agent-based modeling (ABM), to study the sequence of states of the proteins and time of the cell cycle phases, under the action of proteins that regulate its cell cycle. The model relies only on the conceptual model of the yeast cell cycle regulatory network, where each protein has been represented as an agent with a property called activity that represents its biological function and a stochastic Brownian movement. The results indicate that the simulated phase time did have similar results in comparison with other models using mathematical approaches. Similarly, the correct sequence of states was achieved, and the model was run under different initial states to understand its emergent behaviors. The cell reached the G1 stationary state 94% of the times when running the model under biological initial conditions and 87% of the times when running the model through all the different combinations of initial states. Such results imply that the cell was capable to fix toward the biological expected phenomena. These results show that ABM is a suitable technique to study protein–protein interactions without using, often unavailable, kinetic parameters, or differential equations. This model sets as a base for further studies that involve the cell cycle of the fission yeast, with a special attention to studies and development of drug treatments for specific types of cancer.