Two Cell Types Move in Sync express
A colony of cells resembles a squad blazing a trail through unknown terrain. In living tissue, this role is often played by chemotaxis — movement along a gradient of a chemical that the cells themselves secrete. Earlier models described homogeneous groups, but in reality, different cell types interact.
The authors generalized the self-generated chemotaxis model to the case of two cell populations and discovered an effect of "propagating terraces"—two coupled waves running at different speeds. Ahead goes a pure front of sensors, followed by a mixed front where consumers slow the motion. The speeds of these waves were expressed analytically in terms of model parameters and measurable quantities.
It turned out that heterogeneity helps sensors migrate farther: consumers, by destroying the signal, create a steeper gradient that propels the scouts. Consumers, on the other hand, benefit from moving in the company of their own kind: this way they are more efficient.
Original abstract
as written by the authors arXiv:2607.09296
Chemotaxis underlies the collective migration of cell populations in developmental processes and immune responses. While the theoretical investigation of single-cell-type collective chemotaxis has received considerable attention, heterogeneous chemotaxis involving multiple interacting cell types remains poorly understood. Here, we generalise a model of heterogeneous self-generated chemotaxis and analyse the resulting collective migration patterns. We show that coupled migration between two cell types gives rise to \emph{propagating terraces} -- coupled travelling fronts moving at different speeds. While a sensor-only population leads the migrating collective, a slower mixed sensor-consumer population follows. Our analysis reveals that these fronts are coupled via the dynamics of the self-generated chemoattractant gradients. We derive analytical expressions for the migration speeds of the two fronts just in term of model parameters and experimentally measurable quantities. Our analytical results reveal that heterogeneity can enhance long-range migration via self-generated chemotaxis for sensor cells. While sensor cells can leverage benefit from mixing with consumer cells, the latter migrate more efficiently when mixing with cells of the same type. Together, our results provide a comprehensive theoretical framework for understanding heterogeneous self-generated chemotaxis.
Consumer cells, by eating the chemical signal, inadvertently create a clearer "trail" for the scouts, along which they move faster.