Emergent structures and dynamics of cell colonies by contact inhibition of locomotion

Abstract

Cells in tissues can organize into a broad spectrum of structures according to their function. Drastic changes of organization, such as epithelial-mesenchymal transitions or the formation of spheroidal aggregates, are often associated either to tissue morphogenesis or to cancer progression. Here, we study the organization of cell colonies by means of simulations of self-propelled particles with generic cell-like interactions. The interplay between cell softness, cell-cell adhesion, and contact inhibition of locomotion (CIL) yields structures and collective dynamics observed in several existing tissue phenotypes. These include regular distributions of cells, dynamic cell clusters, gel-like networks, collectively migrating monolayers, and 3D aggregates. We give analytical predictions for transitions between noncohesive, cohesive, and 3D cell arrangements. We explicitly show how CIL yields an effective repulsion that promotes cell dispersal, thereby hindering the formation of cohesive tissues. Yet, in continuous monolayers, CIL leads to collective cell motion, ensures tensile intercellular stresses, and opposes cell extrusion. Thus, our work highlights the prominent role of CIL in determining the emergent structures and dynamics of cell colonies.self-propelled particles | cell-cell adhesion | contact inhibition of locomotion | cell monolayers | collective motion C ell colonies exhibit a broad range of phenotypes. In terms of structure, collections of cells can arrange into distributions of single cells, assemble into continuous monolayers or multilayered tissues, or even form 3D agglomerates. In terms of dynamics, cell motility may simply be absent or produce random, directed, or collective migration of cells. Transitions between these states of tissue organization are characteristic of morphogenetic events and are also central to tumor formation and dispersal (1-4). Therefore, a physical understanding of the collective behavior of cell colonies will shed light on the regulation of many multicellular processes involved in development and disease.However, a complete physical picture of multicellular organization is not yet available, partly due to the challenge of modeling the complex interactions between cells. Here, we address this problem by means of large-scale simulations of self-propelled particles (SPP) endowed with interactions capturing generic cellular behaviors. Models of SPP with aligning interactions have been used to investigate collective cell motions in tissue monolayers (5-18). We extend this approach to unveil how the different structures and collective dynamics of cell colonies emerge from cell-cell interactions.In addition to an excluded-volume repulsion, cells generally feature a short-range attraction as a consequence of their active cortical contractility transmitted through cell-cell junctions. With no additional interactions, this attraction would typically lead to cohesive tissues. However, not all cell types form cohesive tissues. Whereas epithelial cells tend to form continuous monolayers...

Physical Models of Collective Cell Migration

“…With these interactions, a cell cluster can spontaneously polarize and undergo collective motion, as indicated by the center-of-mass velocity v. The color code indicates the cell polarity angle θi. Adapted from [123]. c, In growing tissues, CIL gives rise to tension profiles similar to experimental measurements.…”

“…Typically, the potential features a short-range repulsion, which usually includes a hard core to prevent cell overlaps (Section 2.2.3). However, to capture cell extrusion, a recent model proposed a soft-core repulsion with a finite energy plateau [123]. In addition to the repulsive part, the potential often features a mid-range attraction to account for cell-cell adhesion (Fig.…”

A Rho-GTPase based model explains spontaneous collective migration of neural crest cell clusters

“…However, it is challenging to represent intercellular interaction within the continuum formulation. Agent-based models address this concern by assigning rules on individual agents that recapitulate known cell-level behaviour [7,13,14,50]. While helpful when little is known about the underlying biology, these models tend simply to give back the behaviour designed for.…”

Compaction dynamics during progenitor cell self-assembly reveal granular mechanics

“…The IBM is derived from the model introduced by Delile et al (28), and is akin to Self-Propelled Particle (SPP) simulations (29,30), with the important difference that active forces are conser- Fig. (c-e) were simulated at w a = min −1 , D r = 0.5 min −1 .…”