Modeling the Interplay of Oscillatory Synchronization and Aggregation via Cell-Cell Adhesion

TL;DR

This paper introduces a mathematical model for cell systems with internal oscillators, exploring how cell adhesion and synchronization interact to produce diverse spatial and temporal patterns, relevant to developmental biology.

Contribution

It develops a PDE model linking cell adhesion, oscillatory synchronization, and aggregation, and classifies resulting patterns through stability analysis and simulations.

Findings

Identification of conditions for synchronized clustering and aggregation.

Discovery of phase wave patterns with spatial phase gradients.

Confirmation of results via a 2D Cellular Automaton simulation.

Abstract

We present a model of systems of cells with intracellular oscillators (`clocks'). This is motivated by examples from developmental biology and from the behavior of organisms on the threshold to multicellularity. Cells undergo random motion and adhere to each other. The adhesion strength between neighbors depends on their clock phases in addition to a constant baseline strength. The oscillators are linked via Kuramoto-type local interactions. The model is an advection-diffusion partial differential equation with nonlocal advection terms. We demonstrate that synchronized states correspond to Dirac-delta measure solutions of a weak version of the equation. To analyze the complex interplay of aggregation and synchronization, we then perform a linear stability analysis of the incoherent, spatially uniform state. This lets us classify possibly emerging patterns depending on model parameters. Combining these results with numerical simulations, we determine a range of possible far-from equilibrium patterns when baseline adhesion strength is zero: There is aggregation into separate synchronized clusters with or without global synchrony; global synchronization without aggregation; or unexpectedly a ``phase wave" pattern characterized by spatial gradients of clock phases. A 2D Lattice-Gas Cellular Automaton model confirms and illustrates these results.