Mathematical and Computational Modeling of Amoeboid Cell Crawling

TL;DR

This review discusses recent advances in mathematical and computational models of amoeboid cell crawling, emphasizing biochemical signaling, mechanical interactions, and complex environment navigation.

Contribution

It provides a comprehensive overview of modeling frameworks for amoeboid motion, integrating chemical and mechanical cues, and highlights future challenges in the field.

Findings

Various modeling approaches capture cell shape deformations.

Models incorporate chemotaxis and curvotaxis guidance cues.

Emerging challenges include complex topography interactions.

Abstract

Amoeboid motion is a dynamic mode of cell motility essential for processes such as the immune response and wound healing. This review examines recent developments in the mathematical and computational modeling of amoeboid crawling, focusing on the interplay between intracellular biochemical signaling and the physical mechanics of the cell membrane. We discuss the core components of cell motility and the integration of chemical and mechanical guidance cues suchg as chemotaxis and curvotaxis. We evaluate a range of modeling frameworks, from simple stochastic descriptions of center of mass motion to more complicated phase-field, finite-element methods and Potts models that capture complex cell shape deformations. Finally, we highlight emerging challenges, such as modeling interactions with complex topographies and large-scale multicellular coordination, as important steps toward a better understanding of cell locomotion.