Abstract

Bacterial swarming resulting in collective navigation over surfaces provides a valuable example of cooperative colonization of new territories. The social bacterium Paenibacillus vortex exhibits successful and diverse swarming strategies. When grown on hard agar surfaces with peptone, P. vortex develops complex colonies of vortices (rotating bacterial aggregates). In contrast, during growth on Mueller–Hinton broth gelled into a soft agar surface, a new strategy of multi-level organization is revealed: the colonies are organized into a special network of swarms (or ‘snakes’ of a fraction of millimeter in width) with intricate internal traffic. More specifically, cell movement is organized in two or three lanes of bacteria traveling between the back and the front of the swarm. This special form of cellular logistics suggests new methods in which bacteria can share resources and risk while searching for food or migrating into new territories. While the vortices-based organization on hard agar surfaces has been modeled before, here, we introduce a new multi-agent bacterial swarming model devised to capture the swarms-based organization on soft surfaces. We test two putative generic mechanisms that may underlie the observed swarming logistics: (i) chemo-activated taxis in response to chemical cues and (ii) special align-and-push interactions between the bacteria and the boundary of the layer of lubricant collectively generated by the swarming bacteria. Using realistic parameters, the model captures the observed phenomena with semi-quantitative agreement in terms of the velocity as well as the dynamics of the swarm and its envelope. This agreement implies that the bacteria interactions with the swarm boundary play a crucial role in mediating the interplay between the collective movement of the swarm and the internal traffic dynamics.

Highlights

  • Swarming is a method of movement in which bacteria use flagella to migrate rapidly over surfaces en masse [1]

  • The dynamics of bacteria moving inside a branch was characterized and investigated using three quantitative measures from physics and fluid mechanics—the velocity profile across the swarm, the flow vorticity and an order parameter

  • The lesson learned from the simulations is that the special interaction between the bacteria and the swarm envelope mediates a coupling between the internal swarming traffic and the swarm propagation and navigation

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Summary

Introduction

Swarming is a method of movement in which bacteria use flagella to migrate rapidly over surfaces en masse [1]. The current model incorporates the effect of chemical cues in a special way devised to fit the observations: the influence of increased rate of change in the concentration of a chemical signal (or equivalently a decreased concentration of nutrients) is to shorten the time to reach the maximal velocity This dependence can be explained as the result of increased coordination between bacteria. By incorporating the new features described above, the model reproduces a large part of the observed behavior in advancing P. vortex It offers a putative mechanism in which bacteria navigate and effectively steer the swarm by rearranging the internal dynamics

Swarm dynamics and collective navigation
Quantification of self-organized traffic
Velocity profile
Modeling agents with a self-generated moving envelope
Agent propulsion
Chemo-activated taxis
Collective orientation interactions
The simulation steps
Modeling the envelope dynamics
The agents-envelop align-and-push interactions
Remarks on the modeling approach
Lane formation and forward motion
Swarm–swarm interactions
Conclusions
Findings
Looking ahead
Full Text
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