Simulating invasion with cellular automata: connecting cell-scale and population-scale properties

Area of Science:

• Computational Biology
• Biophysics
• Cell Biology

Background:

• Cell invasion is crucial in development and disease, involving motility and proliferation.
• Existing models struggle to integrate data across population and individual cell scales.
• Multiscale experimental data requires integrated modeling approaches.

Purpose of the Study:

• To develop a discrete cellular automata model for cell invasion.
• To link cell-scale parameters to population-scale invasion dynamics.
• To provide a tool for interpreting and predicting cell invasion processes.

Main Methods:

• Development of a discrete cellular automata model with experimentally motivated rules.
• Simulation on a two-dimensional lattice to observe invasion waves.
• Averaging simulation results to determine population-scale wave speed.
• Analysis of individual cell trajectories within simulated invasion waves.

Main Results:

• Simulations show invasion waves propagating at a constant speed.
• A clear relationship between population-scale wave speed and cell-scale parameters was established.
• Model-generated cell trajectories align with experimental observations.
• The model successfully predicts both population and cell-scale invasion properties.

Conclusions:

• The discrete cellular automata model effectively captures multiscale aspects of cell invasion.
• This approach overcomes limitations of continuum models for studying cell motility.
• The model serves as a valuable tool for understanding and predicting biological invasion phenomena.