Self-generated chemotaxis of mixed cell populations

Abstract

Cell and tissue movement in development, cancer invasion, and immune response relies on chemical or mechanical guidance cues. In many systems, this behavior is locally guided by self-generated signaling gradients rather than long-range, pre-patterned cues. However, how heterogeneous mixtures of cells interact non-reciprocally and navigate through self-generated gradients remains largely unexplored. Here we introduce a theoretical framework for the self-organized chemotaxis of heterogeneous cell populations. We find that relative chemotactic sensitivity of cell populations controls their long-time coupling and co-migration dynamics, with boundary conditions such as external cell- and attractant reservoirs substantially influencing the migration patterns. We further predict an optimal parameter regime that leads to robust and colocalized migration. We test our theoretical predictions with in vitro experiments demonstrating the co-migration of different immune cell populations, and quantitatively reproduce observed migration patterns under wild-type and perturbed conditions. Interestingly, immune cell co-migration appears close to the predicted optimal regime. Finally, we incorporate mechanical interactions into our framework, revealing a phase diagram that illustrates non-trivial interplays between chemotactic and mechanical non-reciprocity in driving collective migration. Together, our findings suggest that self-generated chemotaxis is a robust strategy for emergent multicellular navigation.