Bridging the gap between single-cell migration and collective dynamics
- Ludwig-Maximilians-Universität München, Germany
Abstract
Motivated by the wealth of experimental data recently available, we present a cellular-automaton-based modeling framework focussing on high-level cell functions and their concerted effect on cellular migration patterns. Specifically, we formulate a coarse-grained description of cell polarity through self-regulated actin organization and its response to mechanical cues. Furthermore, we address the impact of cell adhesion on collective migration in cell cohorts. The model faithfully reproduces typical cell shapes and movements down to the level of single cells, yet allows for the efficient simulation of confluent tissues. In confined circular geometries, we find that specific properties of individual cells (polarizability; contractility) influence the emerging collective motion of small cell cohorts. Finally, we study the properties of expanding cellular monolayers (front morphology; stress and velocity distributions) at the level of extended tissues.
Data availability
We have uploaded the source code used in the main part of our study as well as the one used in the appendix. Furthermore, we have provided the full list of parameters in the figure captions, as well as exemplary parameter files for all applicable figures.
Article and author information
Author details
Funding
German Excellence Initiative (NanoSystems Initiative Munich (NIM))
- Erwin Frey
Deutsche Forschungsgemeinschaft (Collaborative Research Center (SFB) 1032 (project B02))
- Erwin Frey
Deutsche Forschungsgemeinschaft (Graduate School of Quantitative Biosciences Munich (QBM))
- Andriy Goychuk
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2019, Thüroff et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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Bridging the gap between single-cell migration and collective dynamics
eLife 8:e46842.
https://doi.org/10.7554/eLife.46842
