Data from: Inferring single cell behavior from large-scale epithelial sheet migration patterns

Abstract

Cell migration plays an important role in a wide variety of biological processes and can incorporate both individual cell motion and collective behavior. The emergent properties of collective migration are receiving increasing attention as collective motion’s role in diseases such as metastatic cancer becomes clear. Yet, how individual cell behavior influences large-scale, multi-cell collective motion remains unclear. In our study, we provided insight into the mechanisms behind collective migration by studying cell migration in a spreading monolayer of epithelial MCF10A cells. We quantify migration using particle image velocimetry and find that cell groups have features of motion that span multiple length scales. Comparing our experimental results to a model of collective cell migration, we find that cell migration within the monolayer can be affected in qualitatively different ways by cell motion at the boundary, yet it is not necessary to introduce leader cells at the boundary or specify other large-scale features to recapitulate this large-scale phenotype in simulations. Instead, in our model, collective motion can be enhanced by increasing the overall activity of the cells or by giving the cells a stronger coupling between their motion and polarity. This suggests that investigating the activity and polarity persistence of individual cells will add insight into the collective migration phenotypes observed during development and disease. This dataset provides microscopy images and analysis to support the article in the Journal of the Royal Society Interface (doi 10.1098/rsif.2017.0147) describing these migration behaviors.