Active modulation of surfactant-driven flow instabilities by swarming bacteria.

Models based on surfactant-driven instabilities have been employed to describe pattern formation by swarming bacteria. However, by definition, such models cannot account for the effect of bacterial sensing and decision making. Here we present a more complete model for bacterial pattern formation which accounts for these effects by coupling active bacterial motility to the passive fluid dynamics. We experimentally identify behaviors which cannot be captured by previous models based on passive population dispersal and show that a more accurate description is provided by our model. It is seen that the coupling of bacterial motility to the fluid dynamics significantly alters the phase space of surfactant-driven pattern formation. We also show that our formalism is applicable across bacterial species.

Context-Specific Requirement of Forty-Four Two-Component Loci in Pseudomonas aeruginosa Swarming.

Swarming in Pseudomonas aeruginosa is a coordinated movement of bacteria over semisolid surfaces (0.5%-0.7% agar). On soft agar, P. aeruginosa exhibits a dendritic swarm pattern, with multiple levels of branching. However, the swarm patterns typically vary depending upon the experimental design. In the present study, we show that the pattern characteristics of P. aeruginosa swarm are highly environment dependent. We define several quantifiable, macroscale features of the swarm to study the plasticity of the swarm, observed across different nutrient formulations. Furthermore, through a targeted screen of 113 two-component system (TCS) loci of the P. aeruginosa strain PA14, we show that forty-four TCS genes regulate swarming in PA14 in a contextual fashion. However, only four TCS genes-fleR, fleS, gacS, and PA14_59770-were found essential for swarming. Notably, many swarming-defective TCS mutants were found highly efficient in biofilm formation, indicating opposing roles for many TCS loci.