Non-linear dynamics in contact-based pattern formation

Developing tissues are active matter systems in which the constituting cells exchange information to self-organize into distinct patterns. When cells communicate through direct physical contact, they form a signaling network with a topology that can be dynamic depending on the rheological properties of the system. To study patterning arising from feedback effects between signaling and cellular dynamics, we rely on a statistical physics approach. We consider spatial probability distributions that represent the chance of encountering and exchanging signals with a given cell. Complemented by a minimal model of the molecular signaling pathway [Corson et al. 2017], we obtain a set of coupled, nonlinear differential equations with a rich patterning landscape. We apply our theory to predict patterning dynamics in the zebrafish neuromast, a highly regenerative mechanosensory epithelium, in which cells are in a “fluid-like” state. To quantify patterning of this organ, we exploit 3D life fluorescence microscopy and an integrated approach combining experimental observations and theory.