How Swarming Bacteria Actively Use Physics to Avoid Danger

“Bacteria always find new ways to manipulate their environment to protect themselves,” says Harshitha Kotian, a PhD candidate at the Indian Institute of Science.

Like many physics students, Kotian once thought research on bacteria and antibiotics should be left to the biologists and chemists. Now she’s part of an interdisciplinary research team that recently uncovered how the multidrug resistant bacteria Pseudomonas aeruginosa use basic physics to avoid antibiotics.

P. aeruginosa is known for its ability to cause sepsis and other serious infections when a person’s immune system is already compromised. They can colonize in many different environments, including on the surfaces of hospital equipment, and they’re dangerously resistant to many different antibiotics.

Gram-stained P. aeruginosa bacteria (pink-red rods). Credit: GFDL, (CC BY-SA 3.0).

This new research, published in the American Physical Society’s journal Physical Review E, investigates the collective motion of the bacteria. Individual P. aeruginosa bacterium can swim, but as a group they overtake moisture-rich surfaces by swarming–moving as a coordinated pack in a way that maximizes resources and speeds up growth of the colony. While liquid is necessary for swarming, the bacteria need less than you might expect. That’s because they produce a surfactant, a substance that lowers the surface tension of the liquid, as they swim. Essentially, the surfactant thins out the liquid so that it can spread over a larger area.

To study swarming in the lab, the team observed the behavior of P. aeruginosa bacteria on agar plates. The bacteria extract water from the agar that, in conjunction with the surfactant they produce, forms a thin film on top of the agar through which the bacteria swarm. Left alone, a swarming colony of the bacteria forms long, straight tendrils that extend outward symmetrically.

Previous research has demonstrated that swarming tendrils swerve to avoid physical obstacles and the tendrils of nearby colonies. You can orchestrate some pretty fascinating patterns by designing obstacle courses, but what most captured Kotian’s attention was the fact that tendrils of the same colony rarely intersect. She began looking at existing mathematical models of swarming behavior to see how well they reproduce all of the possible patterns.

The most comprehensive model–the one that best resembled the full range of possible outcomes–was proposed in just 2018. The thing is, that model is completely surfactant-driven. In other words, it considers bacteria as passive passengers whose destination is determined by the surface tension of the liquid and its surroundings. The bacteria don’t make any decisions about what happens.

To find out if the bacteria could actively control swarming, given the opportunity, the team set out to design a situation where a tendril encountered an obstacle that didn’t interfere with the flow of the liquid. After some experimentation, they landed on antibiotics.

The team placed a drop of the antibiotic gentamicin near the tip of a tendril. To their surface, the tendril not only swerved, it actually intersected with a neighboring tendril–something that rarely happens. Control experiments revealed that the response was not surfactant-driven, wasn’t the result of the antibiotic killing nearby bacteria, and only occurred with bacteria that could swim independently.

Swarm colony of Pseudom onas aeruginosa (a) just before addition of antibiotic and (b) after 8 h from the addition of antibiotic. P1 and p2 represent the positions at which the antibiotic was added. Credit: Kotian, et al., Physical Review

These results suggest that individual bacteria constantly scan their local environments for chemical signals of trouble. If a bacterium detects trouble, it modifies its swimming direction. If a critical number of individuals detect trouble and change direction, the collective change in surfactant production alters the direction in which the liquid spreads–and therefore the course of a tendril.

Traditional swarming models treat bacteria as passive entities that grow and multiply but don’t actively control their motion. However, those models can’t reproduce this outcome. “[Bacteria] are more capable of manipulating the flow than they were earlier credited for,” says Kotian.

In light of their findings, the team expanded the surfactant-driven model to incorporate this behavior. Then they demonstrated that it can reproduce the full span of behaviors observed in P. aeruginosa and other surfactant-producing bacteria.

Equipped with a model that addresses the how, now Kotian wants to know the why. Why do tendrils rarely intersect except in the case of antibiotic avoidance? Why is this grouping advantageous? Armed with this knowledge, researchers may be able to develop more targeted treatment plans and simultaneously slow the rise of antimicrobial resistance. “Along with the dosage rationalization there has to be consideration for the environment in which the antibiotic is expected to act,” says Kotian.

Kendra Redmond

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