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Live-cell imaging and analysis reveal cell phenotypic transition dynamics inherently missing in snapshot data
Recent advances in single-cell techniques catalyze an emerging field of studying how cells convert from one phenotype to another, in a step-by-step process. Two grand technical challenges, however, impede further development of the field. Fixed cell–based approaches can provide snapshots of high-dim...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Association for the Advancement of Science
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7473671/ https://www.ncbi.nlm.nih.gov/pubmed/32917609 http://dx.doi.org/10.1126/sciadv.aba9319 |
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author | Wang, Weikang Douglas, Diana Zhang, Jingyu Kumari, Sangeeta Enuameh, Metewo Selase Dai, Yan Wallace, Callen T. Watkins, Simon C. Shu, Weiguo Xing, Jianhua |
author_facet | Wang, Weikang Douglas, Diana Zhang, Jingyu Kumari, Sangeeta Enuameh, Metewo Selase Dai, Yan Wallace, Callen T. Watkins, Simon C. Shu, Weiguo Xing, Jianhua |
author_sort | Wang, Weikang |
collection | PubMed |
description | Recent advances in single-cell techniques catalyze an emerging field of studying how cells convert from one phenotype to another, in a step-by-step process. Two grand technical challenges, however, impede further development of the field. Fixed cell–based approaches can provide snapshots of high-dimensional expression profiles but have fundamental limits on revealing temporal information, and fluorescence-based live-cell imaging approaches provide temporal information but are technically challenging for multiplex long-term imaging. We first developed a live-cell imaging platform that tracks cellular status change through combining endogenous fluorescent labeling that minimizes perturbation to cell physiology and/or live-cell imaging of high-dimensional cell morphological and texture features. With our platform and an A549 VIM-RFP epithelial-to-mesenchymal transition (EMT) reporter cell line, live-cell trajectories reveal parallel paths of EMT missing from snapshot data due to cell-cell dynamic heterogeneity. Our results emphasize the necessity of extracting dynamical information of phenotypic transitions from multiplex live-cell imaging. |
format | Online Article Text |
id | pubmed-7473671 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | American Association for the Advancement of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-74736712020-09-17 Live-cell imaging and analysis reveal cell phenotypic transition dynamics inherently missing in snapshot data Wang, Weikang Douglas, Diana Zhang, Jingyu Kumari, Sangeeta Enuameh, Metewo Selase Dai, Yan Wallace, Callen T. Watkins, Simon C. Shu, Weiguo Xing, Jianhua Sci Adv Research Articles Recent advances in single-cell techniques catalyze an emerging field of studying how cells convert from one phenotype to another, in a step-by-step process. Two grand technical challenges, however, impede further development of the field. Fixed cell–based approaches can provide snapshots of high-dimensional expression profiles but have fundamental limits on revealing temporal information, and fluorescence-based live-cell imaging approaches provide temporal information but are technically challenging for multiplex long-term imaging. We first developed a live-cell imaging platform that tracks cellular status change through combining endogenous fluorescent labeling that minimizes perturbation to cell physiology and/or live-cell imaging of high-dimensional cell morphological and texture features. With our platform and an A549 VIM-RFP epithelial-to-mesenchymal transition (EMT) reporter cell line, live-cell trajectories reveal parallel paths of EMT missing from snapshot data due to cell-cell dynamic heterogeneity. Our results emphasize the necessity of extracting dynamical information of phenotypic transitions from multiplex live-cell imaging. American Association for the Advancement of Science 2020-09-04 /pmc/articles/PMC7473671/ /pubmed/32917609 http://dx.doi.org/10.1126/sciadv.aba9319 Text en Copyright © 2020 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC). https://creativecommons.org/licenses/by-nc/4.0/ https://creativecommons.org/licenses/by-nc/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial license (https://creativecommons.org/licenses/by-nc/4.0/) , which permits use, distribution, and reproduction in any medium, so long as the resultant use is not for commercial advantage and provided the original work is properly cited. |
spellingShingle | Research Articles Wang, Weikang Douglas, Diana Zhang, Jingyu Kumari, Sangeeta Enuameh, Metewo Selase Dai, Yan Wallace, Callen T. Watkins, Simon C. Shu, Weiguo Xing, Jianhua Live-cell imaging and analysis reveal cell phenotypic transition dynamics inherently missing in snapshot data |
title | Live-cell imaging and analysis reveal cell phenotypic transition dynamics inherently missing in snapshot data |
title_full | Live-cell imaging and analysis reveal cell phenotypic transition dynamics inherently missing in snapshot data |
title_fullStr | Live-cell imaging and analysis reveal cell phenotypic transition dynamics inherently missing in snapshot data |
title_full_unstemmed | Live-cell imaging and analysis reveal cell phenotypic transition dynamics inherently missing in snapshot data |
title_short | Live-cell imaging and analysis reveal cell phenotypic transition dynamics inherently missing in snapshot data |
title_sort | live-cell imaging and analysis reveal cell phenotypic transition dynamics inherently missing in snapshot data |
topic | Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7473671/ https://www.ncbi.nlm.nih.gov/pubmed/32917609 http://dx.doi.org/10.1126/sciadv.aba9319 |
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