An agent-based model of the fission yeast cell cycle

Area of Science:

• Computational Biology
• Systems Biology
• Biophysics

Background:

• The cell cycle regulation in fission yeast (Schizosaccharomyces pombe) is complex, involving intricate protein interactions.
• Existing computational models often rely on kinetic parameters or differential equations, which can be difficult to obtain.
• Agent-based modeling (ABM) offers an alternative approach to simulate biological systems by representing individual components as agents.

Purpose of the Study:

• To develop a computational agent-based model (ABM) of the fission yeast (Schizosaccharomyces pombe) cell cycle.
• To investigate the sequence of protein states and cell cycle phase durations.
• To explore emergent behaviors and robustness of the cell cycle under varying conditions.

Main Methods:

• Utilized agent-based modeling (ABM) to represent each regulatory protein as an agent with activity and Brownian movement.
• The model is based on the conceptual regulatory network of the yeast cell cycle.
• Simulations were performed under biological and varied initial conditions to assess model behavior and emergent properties.

Main Results:

• The ABM successfully simulated the correct sequence of protein states and achieved cell cycle phase times comparable to mathematical models.
• The fission yeast cell reached the G1 stationary state in 94% of simulations under biological initial conditions.
• The model demonstrated robustness, reaching the G1 state in 87% of simulations across diverse initial conditions, indicating self-correction.

Conclusions:

• Agent-based modeling (ABM) is a suitable technique for studying yeast cell cycle dynamics and protein interactions without requiring kinetic parameters.
• The developed ABM provides a foundation for future research on fission yeast cell cycle, including cancer drug development.
• The model's ability to predict biological phenomena highlights the power of ABM in systems biology.