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Area of Science:

  • Microbiology
  • Physics
  • Biophysics

Background:

  • Bacterial motility is crucial in natural and engineered systems.
  • Modeling bacterial movement in complex environments is challenging due to cell-surface interactions and unknown geometries.

Purpose of the Study:

  • To develop a method for deriving bacterial diffusion coefficients in disordered media.
  • To provide analytical predictions for bacterial motility based on cell and environmental parameters.

Main Methods:

  • Abstracting bacterial dynamics to "surface states" that describe cell-surface interactions.
  • Deriving a long-time diffusion equation analytically from the state model.
  • Applying the method to a run-and-tumble particle in a 2D Lorentz gas environment and comparing with simulations.

Main Results:

  • Analytical predictions showed good agreement with particle simulations.
  • Diffusivity was found to depend non-monotonically on bacterial run length.
  • An optimal run length was derived, showing dependence on environmental length scales.
  • Rescaling length and time by average event intervals collapsed all diffusivities onto a single, analytically derived curve.

Conclusions:

  • The approach successfully extracts interpretable, macroscopic diffusive behavior from complex microscopic dynamics.
  • The method provides tools and intuitions for understanding bacterial diffusion in disordered media.
  • This work offers a framework for predicting and controlling bacterial motility in structured environments.