Effects of cell-cell communication on bacterial chemotaxis

TL;DR

This study investigates whether cell-cell communication via a secreted co-attractant can enhance bacterial chemotaxis. A one-dimensional Keller-Segel-type continuum model with fold-change sensing and optional adaptive secretion is developed, yielding analytic drift-speed expressions via Gaussian moment closure. The main findings are that constant co-attractant secretion slows chemotaxis, whereas adaptive secretion speeds it up when the adaptation strength satisfies η > η_c, with V = V0 (1+η)/[1+(α-1) D_b/(2 D_a)]. A key prediction is that partial receptor inactivation can increase chemotaxis speed while complete inactivation slows it, highlighting the importance of coupling signaling modules; the results extend to higher dimensions and offer experimentally testable implications for communication in gradient sensing systems.

Abstract

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.

Figures (3)

• Figure 1: Schematic of chemotaxis with communication. A population of bacteria (green) migrates up the gradient of an external chemical (gray) and secretes a diffusing chemical (blue) to which it is also attracted. (a) Bacteria secrete the co-attractant at a constant rate. (b) The secretion rate increases with external chemical concentration, which we term adaptive communication.
• Figure 2: Effects of constant communication on chemotaxis. (a) Both the bacterial population and co-attractant profile maintain a finite width in steady state for $\alpha > 1$. Here there is no external attractant ($c=0$). (b) Constant communication slows down chemotaxis. Here $V_0 \equiv D_b\gamma g$. In both panels, circles are numerical results, and curves are the analytic expressions (Eqs. \ref{['var']} and \ref{['V']}, respectively).
• Figure 3: Effects of adaptive communication on chemotaxis. (a) Adaptation (increasing $\eta$) increases chemotaxis speed. Circles are numerical results, and curves are Eq. \ref{['Va']}. (b) Communication speeds up chemotaxis for $\eta > \eta_c$. Color map is numerical results, and black line is Eq. \ref{['etac']}. (c) Schematic of the mechanism: for $\eta < \eta_c$, the co-attractant lags behind the bacteria, slowing down chemotaxis; for $\eta > \eta_c$, the co-attractant leads the bacteria, speeding up chemotaxis.