ABSTRACTCell migration is astoundingly diverse. Molecular signatures, cell-cell and cell-matrix interactions, and environmental structures each play their part in shaping cell motion, yielding numerous different cell morphologies and migration modes. Nevertheless, in recent years, a simple unifying law was found to describe cell migration across many different cell types and contexts: faster cells turn less frequently. Given this universal coupling between speed and persistence (UCSP), from a modelling perspective it is important to know whether computational models of cell migration capture this speed-persistence link. Here, we present an in-depth characterisation of an existing Cellular Potts Model (CPM). We first show that this model robustly reproduces the UCSP without having been designed for this task. Instead, we show that this fundamental law of migration emerges spontaneously through a crosstalk of intracellular mechanisms, cell shape, and environmental constraints, resembling the dynamic nature of cell migration in vivo. Our model also reveals how cell shape dynamics can further constrain cell motility by limiting both the speed and persistence a cell can reach, and how a rigid environment such as the skin can restrict cell motility even further. Our results further validate the CPM as a model of cell migration, and shed new light on the speed-persistence coupling that has emerged as a fundamental property of migrating cells.SIGNIFICANCEThe universal coupling between speed and persistence (UCSP) is the first general quantitative law describing motility patterns across the versatile spectrum of migrating cells. Here, we show – for the first time – that this migration law emerges spontaneously in an existing, highly popular computational model of cell migration. Studying the UCSP in entirely different model frameworks, not explicitly built with this law in mind, can help uncover how intracellular dynamics, cell shape, and environment interact to produce the diverse motility patterns observed in migrating cells.
A minimum energy optimization approach for simulations of the droplet wetting modes using the cellular Potts model