Is cell segregation like oil and water: asymptotic versus transitory regime

TL;DR

This paper investigates whether the long-term asymptotic behavior of cell segregation models accurately reflects real biological processes, finding that transient regimes better match experimental data than asymptotic predictions.

Contribution

It establishes a direct comparison between experimental data and numerical models, revealing the importance of transient regimes over asymptotic ones in cell segregation.

Findings

Experimental data aligns with transient model regimes.

Asymptotic regimes are less relevant at biological scales.

Provides a new perspective on cell segregation modeling.

Abstract

Segregation of different cell types is a crucial process for the pattern formation in tissues, in particular during embryogenesis. Since the involved cell interactions are complex and difficult to measure individually in experiments, mathematical modelling plays an increasingly important role to unravel the mechanisms governing segregation. The analysis of these theoretical models focuses mainly on the asymptotic behavior at large times, in a steady regime and for large numbers of cells. Most famously, cell-segregation models based on the minimization of the total surface energy, a mechanism also driving the demixing of immiscible fluids, are known to exhibit asymptotically a particular algebraic scaling behavior. However, it is not clear, whether the asymptotic regime of the numerical models is relevant at the spatio-temporal scales of actual biological processes and in-vitro experiments. By developing a mapping between cell-based models and experimental settings, we are able to directly compare previous experimental data to numerical simulations of cell segregation quantitatively. We demonstrate that the experiments are reproduced by the transitory regime of the models rather than the asymptotic one. Our work puts a new perspective on previous model-driven conclusions on cell segregation mechanisms.