Effects of cell-cell communication on bacterial chemotaxis

Bacteria track chemical gradients using a biased random walk, a process called chemotaxis. Experiments suggest that bacteria also communicate during this process. Using a mathematical model, we find that sufficiently strong communication succeeds in keeping a population of bacteria together but slows down chemotaxis. However, if the secretion of the communication molecule is coupled to the detection of the external chemoattractant, chemotaxis can be faster than without communication. Intriguingly, in this regime we predict that, even though blocking the communication receptors should slow down chemotaxis, partially blocking or underexpressing them should speed it up. Our work provides physical insights on how communication and chemotaxis are connected and may help explain why chemotaxing bacteria communicate.

💡 Research Summary

This research investigates the complex interplay between cell-cell communication and the efficiency of bacterial chemotaxis, a fundamental survival mechanism where bacteria navigate chemical gradients through a biased random walk. While traditional studies often focus on the sensory capabilities of individual cells, this paper employs a mathematical modeling approach to explore how collective signaling influences the dynamics of bacterial populations.

The study utilizes a continuum modeling framework based on the Keller-Segel-type equations. By describing the bacterial density $b(x,t)$ and the concentration of a co-attractant $a(x,t)$ through diffusion-advection equations, the authors are able to simulate the macroscopic behavior of a population emerging from microscopic individual movements. The core of the investigation lies in analyzing how the strength and the mechanism of signal secretion affect the trade-off between population cohesion and chemotactic velocity.

The researchers identified two distinct operational regimes. In the first regime, characterized by “strong communication,” the high level of signaling leads to significant population cohesion. While this keeps the bacterial group together, the intense intercellular interactions act as a form of resistance, effectively slowing down the overall chemotactic speed. This suggests that excessive communication can be detrimental to the rapid navigation of the population.

In the second, more complex regime, “coupled communication,” the secretion of the signaling molecule is intrinsically linked to the detection of the external chemoattractant. The model reveals a profound discovery: when signaling is coupled with environmental sensing, the communication can actually accelerate chemotaxis, making the group move faster than if the cells were acting in isolation. This implies that communication serves as a functional mechanism for synchronizing and enhancing the collective response to environmental stimuli.

Perhaps the most striking and counter-intuitive finding of this study is the prediction regarding receptor regulation. The model suggests that in the coupled regime, partially blocking or underexpressing the communication receptors can lead to an increase in chemotactic speed. This non-monotonic relationship challenges the conventional assumption that higher receptor density always leads to better sensing and movement. It provides a physical basis for the idea that bacteria may have evolved to “tune” their receptor expression to an optimal level that balances sensitivity with the need for rapid, unhindered movement.

In conclusion, this work provides significant physical insights into the evolutionary purpose of bacterial communication. By demonstrating that communication can be a driver of enhanced chemotactic efficiency through coupling mechanisms, the study offers a new perspective on why bacteria communicate. These findings have broader implications for understanding self-organizing biological systems and the evolutionary optimization of collective behavior in various microbial ecosystems.