Statistical dynamics of spatial-order formation by communicating cells

TL;DR

This paper develops a statistical mechanics framework to understand how communicating cells self-organize into spatial patterns from disorder, using concepts like energy landscapes and metastability.

Contribution

It introduces a novel theoretical approach modeling cellular communication as particles on energy landscapes, explaining pattern formation and metastability in cell populations.

Findings

Cells can form stable spatial patterns from disorder.

The framework predicts metastable configurations.

Cellular communication dynamics resemble particles rolling on energy landscapes.

Abstract

Communicating cells can coordinate their gene expressions to form spatial patterns. 'Secrete-and-sense cells' secrete and sense the same molecule to do so and are ubiquitous. Here we address why and how these cells, from disordered beginnings, can form spatial order through a statistical mechanics-type framework for cellular communication. Classifying cellular lattices by 'macrostate' variables - 'spatial order paramete' and average gene-expression level - reveals a conceptual picture: cellular lattices act as particles rolling down on 'pseudo-energy landscapes' shaped by a 'Hamiltonian' for cellular communication. Particles rolling down represent cells' spatial order increasing. Particles trapped on the landscapes represent metastable spatial configurations. The gradient of the Hamiltonian and a 'trapping probability' determine the particle's equation of motion. This framework is extendable to more complex forms of cellular communication.