Effective run-and-tumble dynamics of bacteria baths

Area of Science:

• Microbiology
• Statistical Physics
• Computational Biology

Background:

• * Escherichia coli (E. coli) bacteria exhibit run-and-tumble motility, generating random walks.
• * Analytical models for bacterial density fluctuations are accurate only at very low concentrations.
• * Bacterial interactions become significant at higher, practically relevant concentrations.

Purpose of the Study:

• * To investigate the dynamic structure factor of a model bacterial bath at increasing densities.
• * To determine if a simplified model can capture the complex dynamics of interacting bacteria.
• * To analyze how bacterial motility parameters are affected by high concentrations.

Main Methods:

• * Employed molecular dynamics simulations to model a bacterial bath.
• * Studied the dynamic structure factor across a range of bacterial densities.
• * Utilized a free run-and-tumble model with adjustable parameters.

Main Results:

• * The dynamics of density fluctuations in dense bacterial systems can be reproduced using a run-and-tumble model.
• * Effective fitting parameters in the model were found to depend on bacterial density.
• * Key parameters like tumbling rate, tumbling time, and self-propulsion velocity were analyzed in relation to density.

Conclusions:

• * A simplified run-and-tumble model is sufficient to describe E. coli dynamics in dense environments.
• * Bacterial motility parameters are density-dependent and require effective adjustments in models.
• * This work provides insights into the collective behavior of microorganisms in concentrated suspensions.