Cellular automaton model of the actin cytoskeleton

Area of Science:

• Biophysics
• Cell Biology
• Computational Biology

Background:

• The actin cytoskeleton is crucial for cellular structure and function, operating under complex viscous nonequilibrium conditions.
• Understanding the spatial and temporal dynamics of actin polymerization and associated proteins is essential for cell biology.

Purpose of the Study:

• To develop a cellular automaton model of the actin cytoskeleton that incorporates macromolecular spatial and temporal behavior.
• To simulate actin polymerization, cross-linking, severing, and gelation dynamics under various cellular conditions.

Main Methods:

• Developed a cellular automaton model incorporating actin monomer binding, polymerization, cross-linking (alpha-actinin), sequestration (profilin), severing/capping (gelsolin), and PIP2 binding.
• Derived equations for molecular translation/rotation probabilities and binding probabilities based on physical parameters and reaction rate constants.
• Simulated gelation and sol-gel transitions, analyzing the distribution and organization of actin-binding proteins using fractal dimension.

Main Results:

• The model accurately replicates actin polymerization and ATP hydrolysis under varying cation and nucleotide conditions.
• Calcium regulation of alpha-actinin and gelsolin predicts inhomogeneous distributions of bound alpha-actinin and F-actin, with distinct bunching patterns.
• Simulation of gel-sol transitions aligns with existing polymer gel theories, and actin/alpha-actinin gels show phase shifts upon filament shortening.

Conclusions:

• The developed cellular automaton model provides a robust framework for studying the complex spatial and temporal properties of the actin cytoskeleton.
• The model's accurate predictions suggest its pertinence to understanding in vivo cytoskeletal dynamics and regulatory mechanisms.
• The study quantifies protein organization using fractal dimensions and predicts phase transitions in actin-based gels.