Artículo
CartoCell, a high-content pipeline for 3D image analysis, unveils cell morphology patterns in epithelia
Autor/es | Andrés San Román, Jesús Ángel
Gordillo Vázquez, Carmen María Franco Barranco, Daniel Morato Concejero, Laura Huertas Fernández-Espartero, Cecilia Baonza, Gabriel Tagua Jáñez, Antonio Jesús Vicente Munuera, Pablo Palacios Barea, Ana María Gavilán Dorronzoro, María de la Paz Martín Belmonte, Fernando Annese, Valentina Gómez Gálvez, Pedro Arganda Carreras, Ignacio Escudero Cuadrado, Luis María |
Departamento | Universidad de Sevilla. Departamento de Biología Celular |
Fecha de publicación | 2023 |
Fecha de depósito | 2023-11-02 |
Publicado en |
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Resumen | 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 ... 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. |
Agencias financiadoras | Ministerio de Ciencia e Innovación (MICIN). España Junta de Andalucía Ministerio de Economía y Competitividad (MINECO). España |
Identificador del proyecto | PID2019-103900GB-I00
PID2020-120367GB-I00 PID2021-126701OB-I00 US-1380953 PY18-631 BES-2022-077789 |
Cita | Andrés San Román, J.Á., Gordillo Vázquez, C.M., Franco Barranco, D., Morato Concejero, L., Huertas Fernández-Espartero, C., Baonza, G.,...,Escudero Cuadrado, L.M. (2023). CartoCell, a high-content pipeline for 3D image analysis, unveils cell morphology patterns in epithelia. Cell Reports Methods, 3 (10), 100597. https://doi.org/10.1016/j.crmeth.2023.100597. |
Ficheros | Tamaño | Formato | Ver | Descripción |
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CartoCell.pdf | 4.269Mb | [PDF] | Ver/ | |