We report quantitative measurements of the velocity field of collectively migrating cells in a motile epithelium. The migration is triggered by presenting free surface to an initially confluent monolayer by using a microstencil technique that does not damage the cells. To avoid the technical difficulties inherent in the tracking of single cells, the field is mapped using the technique of particle image velocimetry. The main relevant parameters, such as the velocity module, the order parameter, and the velocity correlation function, are then extracted from this cartography. These quantities are dynamically measured on two types of cells (collectively migrating Madin-Darby canine kidney (MDCK) cells and fibroblastlike normal rat kidney (NRK) cells), first as they approach confluence, and then when the geometrical constraints are released. In particular, for MDCK cells filling up the patterns, we observe a sharp decrease in the average velocity after the point of confluence, whereas the densification of the monolayer is much more regular. After the peeling off of the stencil, a velocity correlation length of approximately 200 microm is measured for MDCK cells versus only approximately 40 microm for the more independent NRK cells. Our conclusions are supported by parallel single-cell tracking experiments. By using the biorthogonal decomposition of the velocity field, we conclude that the velocity field of MDCK cells is very coherent in contrast with the NRK cells. The displacements in the fingers arising from the border of MDCK epithelia are very oriented along their main direction. They influence the velocity field in the epithelium over a distance of approximately 200 microm.

Modelling the displacement of thousands of cells that move in a collective way is required for the simulation and the theoretical analysis of various biological processes. Here, we tackle this question in the controlled setting where the motion of Madin-Darby Canine Kidney (MDCK) cells in a confluent epithelium is triggered by the unmasking of free surface. We develop a simple model in which cells are described as point particles with a dynamic based on the two premises that, first, cells move in a stochastic manner and, second, tend to adapt their motion to that of their neighbors. Detailed comparison to experimental data show that the model provides a quantitatively accurate description of cell motion in the epithelium bulk at early times. In addition, inclusion of model “leader” cells with modified characteristics, accounts for the digitated shape of the interface which develops over the subsequent hours, providing that leader cells invade free surface more easily than other cells and coordinate their motion with their followers. The previously-described progression of the epithelium border is reproduced by the model and quantitatively explained.