Signaling networks and cell motility: a computational approach using a phase field description

Area of Science:

• Cell biology
• Biophysics
• Computational modeling

Background:

• Cell movement, involving protrusion and retraction, is crucial for biological processes.
• Actin cytoskeleton turnover and reorganization drive these dynamic cell shape changes.
• Existing models often simplify the complex interplay of internal and external cellular factors.

Purpose of the Study:

• To develop a comprehensive model simulating cell motility.
• To investigate the role of reaction-diffusion systems and Turing instability in establishing cell polarity.
• To integrate actin dynamics, GTPase activation, cell membrane mechanics, and cytoplasmic streaming.

Main Methods:

• A reaction-diffusion model incorporating cell membrane and cytoplasm processes.
• A Turing-type instability to generate cell polarity.
• A simplified GTPase activation network model accounting for dimensionality differences.
• Integration with a Helfrich-type model for membrane bending and stiffness.
• Inclusion of cytoplasmic and extracellular matrix streaming.
• Formulation within a phase field approach and solution via adaptive finite elements.

Main Results:

• The coupled model successfully simulates cell dynamics.
• The model reproduces key phenomenologies of cell motility, including protrusion and retraction.
• Turing instability effectively establishes cell polarity necessary for directional movement.

Conclusions:

• The developed model provides a unified framework for understanding cell motility.
• It highlights the importance of integrating multiple biophysical and biochemical processes.
• This approach offers a powerful tool for studying cell migration and related phenomena.