Learning the dynamics of cell-cell interactions in confined cell migration
ORAL
Abstract
In many physiological processes, contact-mediated cell-cell interactions play a key role in shaping the stochastic trajectories of migrating cells. However, a quantitative framework to describe the stochastic dynamics of interacting cells in remains elusive. Here, we monitor stochastic cell trajectories in a minimal experimental cell collider: a dumbbell-shaped micropattern on which pairs of cells perform repeated cellular collisions. We observe different characteristic behaviors, including cells reversing, following and sliding past each other upon collision. Capitalizing on this large experimental data set of coupled cell trajectories, we infer an interacting stochastic equation of motion that accurately predicts the observed interaction behaviors. Our approach reveals that interacting non-cancerous MCF10A cells can be described by repulsion and friction interactions. In contrast, cancerous MDA-MB-231 cells exhibit novel and surprising attraction and anti-friction interactions, promoting the predominant relative sliding behavior observed for these cells. Based on these experimentally inferred interactions, we show how this framework may generalize to provide a unifying theoretical description of the diverse cellular interaction behaviors of distinct cell types.
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Presenters
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David Brückner
- Ludwig Maximilian University of Munich
- Ludwig-Maximilian-University Munich