The role of positional information in collective gradient sensing

Eukaryotic cells sense chemical gradients to decide where and when to move. While individual cells struggle to sense shallow gradients, clusters of cells increase their sensing accuracy by integrating measurements of concentration made across the cluster. However, the integration of these measurements may be constrained in the case where cells have limited information on their position within the cluster. We apply maximum likelihood estimation to study gradient sensing accuracy when cells have limited positional information. We compare our results with a tug-of-war model in which cells respond to the gradient by a collective guidance mechanism without relying on their positional information, but only using cells at the edge of the cluster. As cell positional uncertainties increase, a trade-off occurs in which the tug-of-war model responds more accurately to the chemical gradient despite using fewer cells. However, for sufficiently large cell groups or shallow chemical gradients, the tug-of-war model will always be suboptimal to one that integrates information from all cells, even if positional uncertainty is high.