Crawling migration under chemical signalling: a stochastic particle model

TL;DR

This paper introduces a stochastic particle model for cell migration influenced by external chemical signals, extending previous models by incorporating time-varying signals and analyzing their impact on cell trajectories.

Contribution

It presents a novel non-homogeneous Markovian model for cell migration under chemical signals, capturing the influence of dynamic external cues on protrusion activity.

Findings

Model is well-posed and mathematically rigorous.

Chemical signals significantly alter long-term cell trajectories.

Trajectories vary with different signal configurations.

Abstract

Cell migration is a fundamental process involved in physiological phenomena such as the immune response and morphogenesis, but also in pathological processes, such as the development of tumor metastasis. These functions are effectively ensured because cells are active systems that adapt to their environment. In this work, we consider a migrating cell as an active particle, where its intracellular activity is responsible for motion. Such system was already modeled in a previous model where the protrusion activity of the cell was described by a stochastic Markovian jump process. The model was proven able to capture the diversity in observed trajectories. Here, we add a description of the effect of an external chemical attractive signal on the protrusion dynamics, that may vary in time. We show that the resulting stochastic model is a well-posed non-homogeneous Markovian process, and provide cell trajectories in different settings, illustrating the effects of the signal on long-term trajectories.