David Bruekner

In many key physiological processes, cells migrate through structured and confining environments. However, a quantitative framework for the dynamics of confined migration has remained elusive. To provide such a framework, we employ a data-driven approach to infer the dynamics of cell movement, morphology and interactions of cells confined in two-state micropatterns. In this confinement, cells stochastically migrate back and forth between two square adhesion sites connected by a thin bridge. By inferring a stochastic equation of motion directly from the experimentally determined short time-scale dynamics, we show that cells exhibit intricate non-linear deterministic dynamics that adapt to the geometry of confinement [1,2]. This approach reveals that different cell lines exhibit distinct classes of dynamical systems, ranging from bistable to limit cycle behavior. We extend this dynamical systems framework to experiments of interacting cell pairs, revealing that cancerous (MDA-MB-231) cells exhibit qualitatively different interactions to non-cancerous (MCF10A) cells [3]. Our approach yields a conceptual framework for confined cell migration and a novel quantitative classification scheme for cell-cell interactions.