Data-driven theory reveals protrusion and polarity interactions governing collision behavior of distinct motile cells
Abstract
The migration behavior of colliding cells is critically determined by transient contact-interactions. During these interactions, the motility machinery, including the front-rear polarization of the cell, dynamically responds to surface protein-mediated transmission of forces and biochemical signals between cells. While biomolecular details of such contact-interactions are increasingly well understood, it remains unclear what biophysical interaction mechanisms govern the cell-level dynamics of colliding cells and how these mechanisms vary across cell types. Here, we develop a phenomenological theory based on 14 candidate contact-interaction mechanisms coupling cell position, protrusion, and polarity. Using high-throughput micropattern experiments, we detect which of these phenomenological contact-interactions captures the interaction behaviors of cells. We find that various cell types - ranging from mesenchymal to epithelial cells - are accurately captured by a single model with only two interaction mechanisms: polarity-protrusion coupling and polarity-polarity coupling. The qualitatively different interaction behaviors of distinct cells, as well as cells subject to molecular perturbations of surface protein-mediated signaling, can all be quantitatively captured by varying the strength and sign of the polarity-polarity coupling mechanism. Altogether, our data-driven phenomenological theory of cell-cell interactions reveals polarity-polarity coupling as a versatile and general contact-interaction mechanism, which may underlie diverse collective migration behavior of motile cells.
Keywords
Cite
@article{arxiv.2407.17268,
title = {Data-driven theory reveals protrusion and polarity interactions governing collision behavior of distinct motile cells},
author = {Tom Brandstätter and Emily Brieger and David B. Brückner and Georg Ladurner and Joachim Rädler and Chase P. Broedersz},
journal= {arXiv preprint arXiv:2407.17268},
year = {2024}
}