Small-scale demixing in confluent biological tissues

Abstract

Surface tension governed by differential adhesion can drive fluid particle mixtures to sort into separate regions, i.e., demix. Does the same phenomenon occur in confluent biological tissues? We begin to answer this question for epithelial monolayers with a combination of theory via a vertex model and experiments on keratinocyte monolayers. Vertex models are distinct from particle models in that the interactions between the cells are shape-based, as opposed to distance-dependent. We investigate whether a disparity in cell shape or size alone is sufficient to drive demixing in bidisperse vertex model fluid mixtures. Surprisingly, we observe that both types of bidisperse systems robustly mix on large lengthscales. On the other hand, shape disparity generates slight demixing over a few cell diameters, a phenomenon we term micro-demixing. This result can be understood by examining the differential energy barriers for neighbor exchanges (T1 transitions). Experiments with mixtures of wild-type and E-cadherin-deficient keratinocytes on a substrate are consistent with the predicted phenomenon of micro-demixing, which biology may exploit to create subtle patterning. The robustness of mixing at large scales, however, suggests that despite some differences in cell shape and size, progenitor cells can readily mix throughout a developing tissue until acquiring means of recognizing cells of different types.

arXiv comment32 pages, 17 figures

References in corpus (10)

• A density-independent glass transition in biological tissues
• Motility-driven glass and jamming transitions in biological tissues
• Scaling of Traction Forces with Size of Cohesive Cell Colonies
• The critical probability for random Voronoi percolation in the plane is 1/2
• Correlating Cell Shape and Cellular Stress in Motile Confluent Tissues
• cellGPU: massively parallel simulations of dynamic vertex models
• Soft yet sharp interfaces in a vertex model of confluent tissue
• Anomalous glassy dynamics in simple models of dense biological tissue
• Geometric frustration and solid-solid transitions in model 2D tissue
• Clustering-induced attraction in granular mixtures of rods and spheres