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).
Preview |
Text
Vicente Munuera_1-s2.0-S2667237523002497-main.pdf Download (4MB) | Preview |
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-pp.ucl.ac.uk/id/eprint/10178024 |
Archive Staff Only
 |
View Item |
