Dynamics of cell ensembles on Aadhesive micropatterns: bridging the gap between single cell spreading and collective cell migration
The collective dynamics of multicellular systems arise from the interplay of a few fundamental elements: growth, division and apoptosis of single cells; their mechanical and adhesive interactions with neighboring cells and the extracellular matrix; and the tendency of polarized cells to move. Microp...
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| Main Authors: | , |
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| Format: | Article (Journal) |
| Language: | English |
| Published: |
April 7, 2016
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| In: |
PLoS Computational Biology
Year: 2016, Volume: 12, Issue: 4 |
| ISSN: | 1553-7358 |
| DOI: | 10.1371/journal.pcbi.1004863 |
| Online Access: | Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1371/journal.pcbi.1004863 Verlag, lizenzpflichtig, Volltext: https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1004863 
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| Author Notes: | Philipp J. Albert, Ulrich S. Schwarz |
| Summary: | The collective dynamics of multicellular systems arise from the interplay of a few fundamental elements: growth, division and apoptosis of single cells; their mechanical and adhesive interactions with neighboring cells and the extracellular matrix; and the tendency of polarized cells to move. Micropatterned substrates are increasingly used to dissect the relative roles of these fundamental processes and to control the resulting dynamics. Here we show that a unifying computational framework based on the cellular Potts model can describe the experimentally observed cell dynamics over all relevant length scales. For single cells, the model correctly predicts the statistical distribution of the orientation of the cell division axis as well as the final organisation of the two daughters on a large range of micropatterns, including those situations in which a stable configuration is not achieved and rotation ensues. Large ensembles migrating in heterogeneous environments form non-adhesive regions of inward-curved arcs like in epithelial bridge formation. Collective migration leads to swirl formation with variations in cell area as observed experimentally. In each case, we also use our model to predict cell dynamics on patterns that have not been studied before. |
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| Item Description: | Gesehen am 12.08.2020 |
| Physical Description: | Online Resource |
| ISSN: | 1553-7358 |
| DOI: | 10.1371/journal.pcbi.1004863 |