Mathematical Modeling of Chemotaxis Guided Amoeboid Cell Swimming

TL;DR

This paper presents a mathematical model for amoeboid cell swimming driven by chemotaxis, revealing how cells can follow chemoattractants and how bacteria can evade predators, expanding understanding of cell motility beyond crawling.

Contribution

The study introduces a novel modeling framework for chemotaxis-induced amoeboid swimming, incorporating deformable cell dynamics and low Reynolds number flows.

Findings

Chemotaxis guides amoeboid cells to follow bacteria.

Bacterial rheotaxis can help bacteria escape predators.

Model demonstrates cell-bacteria interactions in a fluid environment.

Abstract

Cells and microorganisms adopt various strategies to migrate in response to different environmental stimuli. To date, many modeling research has focused on the crawling-based Dictyostelium discoideum (Dd) cells migration induced by chemotaxis, yet recent experimental results reveal that even without adhesion or contact to a substrate, Dd cells can still swim to follow chemoattractant signals. In this paper, we develop a modeling framework to investigate the chemotaxis induced amoeboid cell swimming dynamics. A minimal swimming system consists of one deformable Dd amoeboid cell and a dilute suspension of bacteria, and the bacteria produce chemoattractant signals that attract the Dd cell. We use the mathematical amoeba model to generate Dd cell deformation and solve the resulting low Reynolds number flows, and use a moving mesh based finite volume method to solve the reaction-diffusion-convection equation. Using the computational model, we show that chemotaxis guides a swimming Dd cell to follow and catch bacteria, while on the other hand, bacterial rheotaxis may help the bacteria to escape from the predator Dd cell.