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A quantitative biophysical principle to explain the 3D cellular connectivity in curved epithelia

Gómez-Gálvez, P; Vicente-Munuera, P; Anbari, S; Tagua, A; Gordillo-Vázquez, C; Andrés-San Román, JA; Franco-Barranco, D; ... Escudero, LM; + view all (2022) A quantitative biophysical principle to explain the 3D cellular connectivity in curved epithelia. Cell Systems , 13 (8) 631-643.e8. 10.1016/j.cels.2022.06.003. Green open access

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Abstract

Epithelial cell organization and the mechanical stability of tissues are closely related. In this context, it has been recently shown that packing optimization in bended or folded epithelia is achieved by an energy minimization mechanism that leads to a complex cellular shape: the “scutoid”. Here, we focus on the relationship between this shape and the connectivity between cells. We use a combination of computational, experimental, and biophysical approaches to examine how energy drivers affect the three-dimensional (3D) packing of tubular epithelia. We propose an energy-based stochastic model that explains the 3D cellular connectivity. Then, we challenge it by experimentally reducing the cell adhesion. As a result, we observed an increment in the appearance of scutoids that correlated with a decrease in the energy barrier necessary to connect with new cells. We conclude that tubular epithelia satisfy a quantitative biophysical principle that links tissue geometry and energetics with the average cellular connectivity.

Type: Article
Title: A quantitative biophysical principle to explain the 3D cellular connectivity in curved epithelia
Location: United States
Open access status: An open access version is available from UCL Discovery
DOI: 10.1016/j.cels.2022.06.003
Publisher version: https://doi.org/10.1016/j.cels.2022.06.003
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Tissue/Cellular Biophysics, Computational geometry, Developmental Systems Biology, Mathematical/Biophysical modeling, Bioimage Analysis
UCL classification: UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > Lab for Molecular Cell Bio MRC-UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL
URI: https://discovery-pp.ucl.ac.uk/id/eprint/10155692
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