Self-generated chemotaxis of mixed cell populations - Ucar, Mehmet Can; Alsberga, Zane; Alanko, Jonna; Sixt, Michael; Hannezo, Edouard (Proceedings of the National Academy of Sciences, 2026)
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 directed by self-generated signaling gradients rather than long-range, prepatterned cues. However, how heterogeneous mixtures of cells interact nonreciprocally 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 the relative chemotactic sensitivities of different cell populations control their long-time coupling and comigration dynamics, with boundary conditions such as external cell and attractant reservoirs substantially influencing the migration patterns. Our model predicts an optimal parameter regime that enables robust and colocalized migration. We test our theoretical predictions with in vitro experiments demonstrating the comigration of distinct immune cell populations, and quantitatively reproduce observed migration patterns under wild-type and perturbed conditions. Interestingly, immune cell comigration occurs close to the predicted optimal regime. Finally, we incorporate mechanical interactions into our framework, revealing a nontrivial interplay between chemotactic and mechanical nonreciprocity in driving collective migration. Together, our findings suggest that self-generated chemotaxis is a robust strategy for the navigation of mixed cell populations.