Neighbor-enhanced diffusivity in dense, cohesive cell populations

Hyun Gyu Lee, Kyoung J. Lee

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)

Abstract

The dispersal or mixing of cells within cellular tissue is a crucial property for diverse biological processes, ranging from morphogenesis, immune action, to tumor metastasis. With the phenomenon of 'contact inhibition of locomotion,' it is puzzling how cells achieve such processes within a densely packed cohesive population. Here we demonstrate that a proper degree of cell-cell adhesiveness can, intriguingly, enhance the super-diffusive nature of individual cells. We systematically characterize the migration trajectories of crawling MDA-MB- 231 cell lines, while they are in several different clustering modes, including freely crawling singles, cohesive doublets of two cells, quadruplets, and confluent population on two-dimensional substrate. Following data analysis and computer simulation of a simple cellular Potts model, which faithfully recapitulated all key experimental observations such as enhanced diffusivity as well as periodic rotation of cell-doublets and cell-quadruplets with mixing events, we found that proper combination of active self-propelling force and cell-cell adhesion is sufficient for generating the observed phenomena. Additionally, we found that tuning parameters for these two factors covers a variety of different collective dynamic states.

Original languageEnglish
Article numbere1009447
JournalPLoS Computational Biology
Volume17
Issue number9
DOIs
Publication statusPublished - 2021 Sept

Bibliographical note

Funding Information:
This work was supported by the National Research Foundation of Korea (NRF) grant funded to KJL by the Korea government(MEST) (No. 2019R1A2C2005989). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Publisher Copyright:
© 2021 Lee, Lee. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

ASJC Scopus subject areas

  • Ecology, Evolution, Behavior and Systematics
  • Modelling and Simulation
  • Ecology
  • Molecular Biology
  • Genetics
  • Cellular and Molecular Neuroscience
  • Computational Theory and Mathematics

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