We study populations of interacting cells with physics concepts and techniques. In this line, we have developed an injury-free technique inspired by wound-healing assays where free surface is released to a confluent epithelium. Under these conditions, they spread and migrate on the substrate while keeping strong cell-cell adhesions. This collective motility gives rise to unusual characteristics such as long-range correlations of the displacements within the monolayer and distinct “leader” cells at the tip of migration fingers. These fingers have striking similarities with some epithelial tumors.
In these situations, various parameters are dynamically mapped at different scales (forces developed by the cells, displacements and velocity fields, shapes or polarities…), and are correlated to the relevant biochemical signals (such as the activity of small G-proteins). This highly parallel and quantitative approach allows us to efficiently interact with theoreticians of several groups.
In the course of this study, we have developed an efficient fully automated correlation-based method to quantitatively monitor the main features of collective migration. This method, named AVeMap, can analyze many experiments in parallel from standard microscopy images. We have validated this approach on a wound-healing high-throughput siRNA screen.