A Data-Driven Model of Polarity Reversal in Migrating Cells

We study how motile cells can reverse their polarity when exposed to changing stimuli, using mathematical modeling alongside extensive experimental data from optogenetic assays carried out by our collaborators in the Orion Weiner lab (UCSF). These experiments revealed an unexpected phenomenon: when a localized input is followed by a global stimulus, cells often reverse their direction of turning. To explain this, our collaborators hypothesized the existence of a slow-acting, locally produced inhibitor downstream of Rac, a signaling molecule known to promote actin assembly and front-edge protrusion. We test this idea by adapting an existing reaction diffusion model that, under certain conditions, produces a stable spatial pattern: a polarized distribution with a clear front and back. This modeling framework, often referred to as wave-pinning, has not previously been fitted directly to experimental data. Here, we calibrate the model’s reaction terms to time-dependent Rac activity data, introducing a novel approach that embraces cellular heterogeneity by fitting a distribution of parameters across multiple cells. While the Rac-inhibitor circuit captures several key features of the response, it fails to reproduce reversal. Incorporating PIP3, an upstream regulator of Rac, allows the model to recover reversal dynamics and reproduce the full range of observed behaviours. In this presentation, we will show the development of our modeling framework from its earliest steps, including how data fitting informed model refinement. Our results validate the experimental hypothesis and yield new predictions about the molecular timing and feedback logic underlying flexible polarity control.