Information Integration and Collective Motility in Phototactic Cyanobacteria
Cells in microbial colonies integrate information across multiple spatial and temporal scales while sensing environmental cues. A number of photosynthetic cyanobacteria respond in a directional manner to incident light, resulting in the phototaxis of individual cells. Colonies of such bacteria exhibit large-scale changes in morphology, arising from cell-cell interactions, during phototaxis. These interactions occur through type IV pili-mediated physical contacts between cells, as well as through the secretion of complex polysaccharides ( slime) that facilitates cell motion. Here, we describe a computational model for such collective behaviour in colonies of the cyanobacterium Synechocystis. The model is designed to replicate observations from recent experiments on the emergent response of the colonies to varied light regimes. It predicts the complex colony morphologies that arise as a result. We ask if changes in colony morphology during phototaxis can be used to infer if cells integrate information from multiple light sources simultaneously, or respond to these light sources separately at each instant of time. We find that these two scenarios cannot be distinguished from the shapes of colonies alone. However, we show that tracking the trajectories of individual cyanobacteria provides a way of determining their mode of response. Our model allows us to address the emergent nature of this class of collective bacterial motion, linking individual cell response to the dynamics of colony shape.\n\nStatement of SignificanceMicrobial colonies in the wild often consist of large groups of heterogeneous cells that coordi-nate and integrate information across multiple spatio-temporal scales. We describe a computational model for one such collective behaviour, phototaxis, in colonies of the cyanobacterium Synechocystis that move in response to light. The model replicates experimental observations the response of cyanobacterial colonies to varied light regimes, and predicts the complex colony morphologies that arise as a result. The results suggest that tracking the trajectories of individual cyanobacteria may provide a way of determining their mode of information integration. Our model allows us to address the emergent nature of this class of collective bacterial motion, linking individual cell response to the large scale dynamics of the colony.