A distributed stochastic perception-action loop model of cell motility

In this paper, we present a novel framework for the modeling of cell-migration, and more specifically the migration of human keratinocytes. The model decouples the embodiment of an artificial cell into two elements. A cell-body is implemented by two sets of springs forming a membrane and a supporting cortical-cytoskeleton, which allows for cell-body rigidity and flexibility. The leading-edge, a structure spreading around the cell-body, is simulated with a stochastic cellular-automata. It defines the migratory forces that pull the cell-body according to its local spread around the cell. The overall movement of the leading-edge depends on stochastic interaction with the environment and guides the whole cell movement through spatiotemporal integration of local forces. We demonstrate that our cell migration model allows for spontaneous symmetry-breaking and directed cell movement and has in-built obstacle-avoidance, closely mimicking the migration of living cells. The model is extended to simulate chemotactic behavior, the artificial cell can sense and move along a gradient with its trajectory depending on the cell shape, stiffness and leading-edge dynamics. In summary, we have developed a novel cell migration model with emergent properties, wherein local forces create an integrated cell movement. The presented interplay of the distributed physical and an informational embodiment is not limited in reach to the example of cell migration, but can of interest for design of perception-action loops and sensor evolution in general.