Small-scale demixing in confluent biological tissues

Abstract

Surface tension governed by differential adhesion can drive fluid particle mixtures to segregate into distinct regions, i.e., demix. Does the same phenomenon occur in vertex models of confluent epithelial monolayers? Vertex models are different from particle models in that the interactions between the cells are shape-based, as opposed to metric-based. 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, i.e. micro-demixing. This result, can be understood by examining the differential energy barriers for neighbor exchanges (T1 transitions). The robustness of mixing at large scales 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.

Investigating the nature of active forces in tissues reveals how contractile cells can form extensile monolayers

“…In the latter case, we could even observe E-cad KO colonies surrounded by WT cells which could not be simply explained by the differential adhesion hypothesis and was not observed in previous adhesion based studies governed by cortical/line tension. 43,[45][46][47][48][49] We were able to replicate this in our simulations (Figure 6b). Moreover, to further test the unmixing phase we thought to probe the unmixing of two cell types with and without E-cadherin, but both showing extensile behaviour.…”

“…To this end, we first quantified the degree of phase separation by measuring the mixing-index of a mixture of WT and E-cad KO cells defined as the number of homotypic neighbours over the total number of cells. 46,47 In the segregation mechanism based on differential line tension this mixing-index grows with a power-law exponent with time and approaches one. 47 However, as evident from both experiments and simulations, the mixing-index in our system saturates and complete phase separation is never obtained (Figure 5a and b).…”

Viscoelastic Networks: Forming Cells and Tissues

“…Vertex models have recently received a lot of attention due to their potential in describing a wide range of tissue properties [25, 27, 36, 111-115, 117-119, 121-123]. Moreover, the accurate study of their mathematical properties revealed a plethora of interesting physical properties [27,28], such as second order rigidity [121], that could play a relevant role in the modeling of biological tissues. Importantly, these properties may imply an interesting departure from the framework proposed by inanimate material science, and proposes a theoretical framework that extends to biological materials.…”

“…Arguably, the response to an external stress will be, at least partially, driven by the possibility of cell rearrangements which, in turn, depend on the ease of movements of cells within the tissue. The energetic contributions that configure the overall energy of the tissue come from the resistance against compression and the departure from some preferred shape in cells which, in most cases, is introduced as the preferred relation perimeter/area in 2D projections [27,113,121,122]. Having N cells, the functional accounting for the energy of the (2D) system reads:…”

“…Consistently, one would expect that the shear modulus goes hand in hand with the energy barriers. Remarkably, this is not the case, and for values 3.71 < s 0 < 3.81, the tissue has zero linear response but non-zero high-order response [121]. In consequence, this phenomenon has been called "second order rigidity" and the material regime has been named "soft solid" regime [126].…”