# A stochastic model for bacteria-driven micro-swimmers

## TL;DR

This paper develops a stochastic fluid dynamic model for bacteria-driven micro-swimmers, analyzing their motion, diffusion, and chemotaxis, with implications for designing biomedical micro-robots.

## Contribution

It introduces a novel analytical and computational model for bacteria-driven micro-swimmers, including effects of run-and-tumble motion and chemotaxis, validated by simulations.

## Key findings

- Mean squared displacement scales with swimming speed and number of bacteria at short times.
- At long times, MSD depends on particle size, not bacteria count.
- Micro-swimmers can perform chemotaxis with drift velocity proportional to chemical gradient.

## Abstract

Experiments have recently shown the feasibility of utilising bacteria as micro-scale robotic devices, with special attention paid to the development of bacteria-driven micro-swimmers taking advantage of built-in actuation and sensing mechanisms of cells. Here we propose a stochastic fluid dynamic model to describe analytically and computationally the dynamics of microscopic particles driven by the motion of surface-attached bacteria undergoing run-and-tumble motion. We compute analytical expressions for the rotational diffusion coefficient, the swimming speed and the effective diffusion coefficient. At short times, the mean squared displacement (MSD) is proportional to the square of the swimming speed, which is independent of the particle size (for fixed density of attached bacteria) and scales linearly with the number of attached bacteria; in contrast, at long times the MSD scales quadratically with the size of the swimmer and is independent of the number of bacteria. We then extend our result to the situation where the surface-attached bacteria undergo chemotaxis within the linear response regime. We demonstrate that bacteria-driven particles are capable of performing artificial chemotaxis, with a chemotactic drift velocity linear in the chemical concentration gradient and independent of the size of the particle. Our results are validated against numerical simulations in the Brownian dynamics limit and will be relevant to the optimal design of micro-swimmers for biomedical applications.