Deformability and collision-induced reorientation enhance cell topotaxis in dense microenvironments

Area of Science:

• Cellular dynamics and biophysics
• Computational biology and modeling

Background:

• Cells navigate complex environments using cues like obstacle density gradients, a phenomenon termed topotaxis.
• Previous active Brownian particle (ABP) models predicted topotactic drifts lower than experimentally observed.

Purpose of the Study:

• To investigate discrepancies in topotaxis prediction by incorporating cell deformability and complex cell-pillar interactions.
• To develop and validate a more detailed model for cell navigation in topographic environments.

Main Methods:

• Utilized the cellular Potts model (CPM) with the Act model (mimicking actin-driven motility) and a hybrid CPM-ABP model.
• Fitted model parameters to experimental Dictyostelium discoideum motion on a flat surface.
• Simulated topotaxis in pillared grids with varying pillar densities.

Main Results:

• CPM variants predicted higher topotactic drifts than ABPs, aligning better with experimental data for starved Dictyostelium discoideum.
• The Act model demonstrated superior topotactic efficiency due to greater reduction in persistence time in dense pillar grids.
• Pillar adhesion reduced cell speed and topotaxis; less persistent vegetative cells showed minimal drift.

Conclusions:

• Deformable cell volume enhances topotactic drift compared to ABPs.
• Feedback from cell-pillar collisions on cell persistence increases drift, particularly in highly persistent cells.
• CPM-based models provide a more accurate representation of cell topotaxis in complex environments.