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CartoCell, a high-content pipeline for 3D image analysis, unveils cell morphology patterns in epithelia

Andrés-San Román, Jesús A; Gordillo-Vázquez, Carmen; Franco-Barranco, Daniel; Morato, Laura; Fernández-Espartero, Cecilia H; Baonza, Gabriel; Tagua, Antonio; ... Escudero, Luis M; + view all (2023) CartoCell, a high-content pipeline for 3D image analysis, unveils cell morphology patterns in epithelia. Cell Rep Methods , Article 100597. 10.1016/j.crmeth.2023.100597. (In press). Green open access

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Abstract

Decades of research have not yet fully explained the mechanisms of epithelial self-organization and 3D packing. Single-cell analysis of large 3D epithelial libraries is crucial for understanding the assembly and function of whole tissues. Combining 3D epithelial imaging with advanced deep-learning segmentation methods is essential for enabling this high-content analysis. We introduce CartoCell, a deep-learning-based pipeline that uses small datasets to generate accurate labels for hundreds of whole 3D epithelial cysts. Our method detects the realistic morphology of epithelial cells and their contacts in the 3D structure of the tissue. CartoCell enables the quantification of geometric and packing features at the cellular level. Our single-cell cartography approach then maps the distribution of these features on 2D plots and 3D surface maps, revealing cell morphology patterns in epithelial cysts. Additionally, we show that CartoCell can be adapted to other types of epithelial tissues.

Type: Article
Title: CartoCell, a high-content pipeline for 3D image analysis, unveils cell morphology patterns in epithelia
Location: United States
Open access status: An open access version is available from UCL Discovery
DOI: 10.1016/j.crmeth.2023.100597
Publisher version: https://doi.org/10.1016/j.crmeth.2023.100597
Language: English
Additional information: © 2023 The Authors. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Keywords: 3D epithelia, CP: Imaging, CP: Systems biology, deep learning segmentation, high-content, image analysis, single-cell cartography
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
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
URI: https://discovery.ucl.ac.uk/id/eprint/10178024
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