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A multi-phenotypic imaging screen to identify bacterial effectors by exogenous expression in a HeLa cell line
We present a high-content screen (HCS) for the simultaneous analysis of multiple phenotypes in HeLa cells expressing an autophagy reporter (mcherry-LC3) and one of 224 GFP-fused proteins from the Crohn’s Disease (CD)-associated bacterium, Adherent Invasive E. coli (AIEC) strain LF82. Using automated...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5952863/ https://www.ncbi.nlm.nih.gov/pubmed/29762554 http://dx.doi.org/10.1038/sdata.2018.81 |
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author | Collins, Adam Huett, Alan |
author_facet | Collins, Adam Huett, Alan |
author_sort | Collins, Adam |
collection | PubMed |
description | We present a high-content screen (HCS) for the simultaneous analysis of multiple phenotypes in HeLa cells expressing an autophagy reporter (mcherry-LC3) and one of 224 GFP-fused proteins from the Crohn’s Disease (CD)-associated bacterium, Adherent Invasive E. coli (AIEC) strain LF82. Using automated confocal microscopy and image analysis (CellProfiler), we localised GFP fusions within cells, and monitored their effects upon autophagy (an important innate cellular defence mechanism), cellular and nuclear morphology, and the actin cytoskeleton. This data will provide an atlas for the localisation of 224 AIEC proteins within human cells, as well as a dataset to analyse their effects upon many aspects of host cell morphology. We also describe an open-source, automated, image-analysis workflow to identify bacterial effectors and their roles via the perturbations induced in reporter cell lines when candidate effectors are exogenously expressed. |
format | Online Article Text |
id | pubmed-5952863 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-59528632018-05-30 A multi-phenotypic imaging screen to identify bacterial effectors by exogenous expression in a HeLa cell line Collins, Adam Huett, Alan Sci Data Data Descriptor We present a high-content screen (HCS) for the simultaneous analysis of multiple phenotypes in HeLa cells expressing an autophagy reporter (mcherry-LC3) and one of 224 GFP-fused proteins from the Crohn’s Disease (CD)-associated bacterium, Adherent Invasive E. coli (AIEC) strain LF82. Using automated confocal microscopy and image analysis (CellProfiler), we localised GFP fusions within cells, and monitored their effects upon autophagy (an important innate cellular defence mechanism), cellular and nuclear morphology, and the actin cytoskeleton. This data will provide an atlas for the localisation of 224 AIEC proteins within human cells, as well as a dataset to analyse their effects upon many aspects of host cell morphology. We also describe an open-source, automated, image-analysis workflow to identify bacterial effectors and their roles via the perturbations induced in reporter cell lines when candidate effectors are exogenously expressed. Nature Publishing Group 2018-05-15 /pmc/articles/PMC5952863/ /pubmed/29762554 http://dx.doi.org/10.1038/sdata.2018.81 Text en Copyright © 2018, The Author(s) http://creativecommons.org/licenses/by/4.0/ 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/ The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ applies to the metadata files made available in this article. |
spellingShingle | Data Descriptor Collins, Adam Huett, Alan A multi-phenotypic imaging screen to identify bacterial effectors by exogenous expression in a HeLa cell line |
title | A multi-phenotypic imaging screen to identify bacterial effectors by exogenous expression in a HeLa cell line |
title_full | A multi-phenotypic imaging screen to identify bacterial effectors by exogenous expression in a HeLa cell line |
title_fullStr | A multi-phenotypic imaging screen to identify bacterial effectors by exogenous expression in a HeLa cell line |
title_full_unstemmed | A multi-phenotypic imaging screen to identify bacterial effectors by exogenous expression in a HeLa cell line |
title_short | A multi-phenotypic imaging screen to identify bacterial effectors by exogenous expression in a HeLa cell line |
title_sort | multi-phenotypic imaging screen to identify bacterial effectors by exogenous expression in a hela cell line |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5952863/ https://www.ncbi.nlm.nih.gov/pubmed/29762554 http://dx.doi.org/10.1038/sdata.2018.81 |
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