Self-organisation of bacteria through swarming
Swarming is a unique example of social behaviour in bacteria. They represent the collective effort of bacteria to translocate on moist substrates. The bacteria extract fluid from the substrate through osmosis and produces surfactants to ease the spreading of the extracted fluid, thereby colonising the substrate. The spreading colony forms distinct patterns specific to the swarming species. We are interested in understanding the local interaction that leads to colony-level patterns. In specific we study the self-organisation of Pseudomonas aeruginosa into long sparse branches as they swarm. We probe the swarm behaviour in complex environments such as physical obstacles, multiple colonies in close proximity, antibiotics and foreign bacteria. We propose a complete model for bacterial pattern formation by coupling active bacterial motility to passive fluid dynamics. We have verified the qualitative similarity of the patterns obtained in the simulations with that of experiments implying the model captures most of the dominant forces that determine the swarm behaviour. We have studied the variation of patterns in different nutrient and substrate conditions and have verified that the model can account for such changes. We also study the behaviour of swarm on inclined surfaces. The swarm behaves like a fluid drop that quickly de-pins to slide down the surface, exhibiting how bacteria can use gravity to transport themselves on inclined surfaces quickly. We experimentally show that the osmosis dynamics plays a major role here and agrees well with the simulation using our model. The swarms' response to the antibiotic in preliminary experiments showed that the bacteria in the swarm could steer the direction of the branch, possibly away from the antibiotic. In addition to the change in direction, we observe that the bacterial tips merge to form aggregates of high cell density. The aggregation, instead of escaping from the region of high concentration of antibiotic, is non-intuitive. We study the response for different classes of antibiotics and see that the response may be unique to the aminoglycosides. We find that there are live bacteria in the aggregate, and the individual bacteria are not resistant to the antibiotic, which tells us that the aggregation is offering the group a survival advantage and questions the efficacy of antibiotic in the presence of such social behaviour of the swarm. We propose a plausible mechanism to explain the enhanced survivability of the high-density bacterial aggregations. We inspect the swarm at the single-cell level to understand the hydrodynamic forces at play. The high density of bacteria in a swarm makes it difficult to track the behaviour of cells at this level for a long duration and using a laser beam for fluorescence needed for tagging the bacteria also affects the swarm adversely to the extent of inhibiting this behaviour. The singlecell studies have thus only been used to measure a few experimental parameters and verify the assumptions used in our model. We have therefore studied the swarm in different environmental conditions and have verified that our model can predict its behaviour in most of the conditions. We also show scenarios where our model fails and suggest ways to improve the model for future work.