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Establishment of a morphological atlas of the Caenorhabditis elegans embryo using deep-learning-based 4D segmentation

The invariant development and transparent body of the nematode Caenorhabditis elegans enables complete delineation of cell lineages throughout development. Despite extensive studies of cell division, cell migration and cell fate differentiation, cell morphology during development has not yet been sy...

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Autores principales: Cao, Jianfeng, Guan, Guoye, Ho, Vincy Wing Sze, Wong, Ming-Kin, Chan, Lu-Yan, Tang, Chao, Zhao, Zhongying, Yan, Hong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7721714/
https://www.ncbi.nlm.nih.gov/pubmed/33288755
http://dx.doi.org/10.1038/s41467-020-19863-x
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author Cao, Jianfeng
Guan, Guoye
Ho, Vincy Wing Sze
Wong, Ming-Kin
Chan, Lu-Yan
Tang, Chao
Zhao, Zhongying
Yan, Hong
author_facet Cao, Jianfeng
Guan, Guoye
Ho, Vincy Wing Sze
Wong, Ming-Kin
Chan, Lu-Yan
Tang, Chao
Zhao, Zhongying
Yan, Hong
author_sort Cao, Jianfeng
collection PubMed
description The invariant development and transparent body of the nematode Caenorhabditis elegans enables complete delineation of cell lineages throughout development. Despite extensive studies of cell division, cell migration and cell fate differentiation, cell morphology during development has not yet been systematically characterized in any metazoan, including C. elegans. This knowledge gap substantially hampers many studies in both developmental and cell biology. Here we report an automatic pipeline, CShaper, which combines automated segmentation of fluorescently labeled membranes with automated cell lineage tracing. We apply this pipeline to quantify morphological parameters of densely packed cells in 17 developing C. elegans embryos. Consequently, we generate a time-lapse 3D atlas of cell morphology for the C. elegans embryo from the 4- to 350-cell stages, including cell shape, volume, surface area, migration, nucleus position and cell-cell contact with resolved cell identities. We anticipate that CShaper and the morphological atlas will stimulate and enhance further studies in the fields of developmental biology, cell biology and biomechanics.
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spelling pubmed-77217142020-12-11 Establishment of a morphological atlas of the Caenorhabditis elegans embryo using deep-learning-based 4D segmentation Cao, Jianfeng Guan, Guoye Ho, Vincy Wing Sze Wong, Ming-Kin Chan, Lu-Yan Tang, Chao Zhao, Zhongying Yan, Hong Nat Commun Article The invariant development and transparent body of the nematode Caenorhabditis elegans enables complete delineation of cell lineages throughout development. Despite extensive studies of cell division, cell migration and cell fate differentiation, cell morphology during development has not yet been systematically characterized in any metazoan, including C. elegans. This knowledge gap substantially hampers many studies in both developmental and cell biology. Here we report an automatic pipeline, CShaper, which combines automated segmentation of fluorescently labeled membranes with automated cell lineage tracing. We apply this pipeline to quantify morphological parameters of densely packed cells in 17 developing C. elegans embryos. Consequently, we generate a time-lapse 3D atlas of cell morphology for the C. elegans embryo from the 4- to 350-cell stages, including cell shape, volume, surface area, migration, nucleus position and cell-cell contact with resolved cell identities. We anticipate that CShaper and the morphological atlas will stimulate and enhance further studies in the fields of developmental biology, cell biology and biomechanics. Nature Publishing Group UK 2020-12-07 /pmc/articles/PMC7721714/ /pubmed/33288755 http://dx.doi.org/10.1038/s41467-020-19863-x Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Cao, Jianfeng
Guan, Guoye
Ho, Vincy Wing Sze
Wong, Ming-Kin
Chan, Lu-Yan
Tang, Chao
Zhao, Zhongying
Yan, Hong
Establishment of a morphological atlas of the Caenorhabditis elegans embryo using deep-learning-based 4D segmentation
title Establishment of a morphological atlas of the Caenorhabditis elegans embryo using deep-learning-based 4D segmentation
title_full Establishment of a morphological atlas of the Caenorhabditis elegans embryo using deep-learning-based 4D segmentation
title_fullStr Establishment of a morphological atlas of the Caenorhabditis elegans embryo using deep-learning-based 4D segmentation
title_full_unstemmed Establishment of a morphological atlas of the Caenorhabditis elegans embryo using deep-learning-based 4D segmentation
title_short Establishment of a morphological atlas of the Caenorhabditis elegans embryo using deep-learning-based 4D segmentation
title_sort establishment of a morphological atlas of the caenorhabditis elegans embryo using deep-learning-based 4d segmentation
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7721714/
https://www.ncbi.nlm.nih.gov/pubmed/33288755
http://dx.doi.org/10.1038/s41467-020-19863-x
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