Title: Modelling Collective Gradient Sensing with Leader and Follower Cells
Abstract: Cells in clusters can cooperate to improve sensing chemical gradients. Recent experiments suggest that in some cell clusters there are cells which try to sense and follow a chemical gradient (leader cells) and other cells that follow their neighbors (follower cells). Single cell experiments have indicated that a cell can more effectively follow steeper chemical gradients, and information theory approaches have shown that a steeper chemical gradient can reduce the error in a cell's measurement of the gradient's direction. In light of these results, we have developed models of cluster chemotaxis that include leader cells and follower cells. In the models, the accuracy of the leader cells depends on gradient steepness, number of chemical receptors on each cell, and the dissociation constant of the ligand-receptor interaction. We simulate cluster chemotaxis in an environment with a transition between high and low chemoattractant. In a steep gradient, a cell cluster with leaders and followers can be guided by leaders near the transition, which have more information about the gradient's direction. If the follower cells perfectly follow the cluster's direction, a few leaders alone can successfully guide the cluster. However, as the followers become noisy, the number of leaders for optimal chemotaxis increases. At a fixed follower noise level, the optimal number of leaders changes as a function of the width of the gradient transition. As the width increases, the optimal number of leaders initially increases since more cells are within the transition region and have sufficient information to effectively lead. However, as the gradient widens further, it becomes too shallow for even some cells within the transition region to accurately sense, and the optimal number of leaders decreases.