Large-scale simulations of biological cell sorting driven by differential adhesion follow diffusion-limited domain coalescence regime

TL;DR

This study uses large-scale simulations to investigate the kinetics of cell sorting driven by differential adhesion, revealing a diffusion-limited domain coalescence process with a specific power-law growth.

Contribution

The paper introduces an efficient modified Cellular Potts Model for large-scale simulations and identifies the diffusion-limited coalescence as the dominant kinetic regime in cell sorting.

Findings

Domain size grows as a power-law with exponent 1/4

Sorting dynamics are dominated by diffusion and coalescence of domains

Boundary conditions influence observed scaling behaviors

Abstract

Cell sorting, whereby a heterogeneous cell mixture segregates and forms distinct homogeneous tissues, is one of the main collective cell behaviors at work during development. Although differences in interfacial energies are recognized to be a possible driving source for cell sorting, no clear consensus has emerged on the kinetic law of cell sorting driven by differential adhesion. Using a modified Cellular Potts Model algorithm that allows for efficient simulations while preserving the connectivity of cells, we numerically explore cell-sorting dynamics over very large scales in space and time. For a binary mixture of cells surrounded by a medium, increase of domain size follows a power-law with exponent $n=1/4$ independently of the mixture ratio, revealing that the kinetics is dominated by the diffusion and coalescence of rounded domains. We compare these results with recent numerical studies on cell sorting, and discuss the importance of algorithmic differences as well as boundary conditions on the observed scaling.