A multi-phenotypic imaging screen to identify bacterial effectors by exogenous expression in a HeLa cell line

Collins, Adam and Huett, Alan (2018) A multi-phenotypic imaging screen to identify bacterial effectors by exogenous expression in a HeLa cell line. Scientific Data, 5 . 180081/1-180081/12. ISSN 2052-4463

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Abstract

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 209 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 209 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.

Item Type: Article
RIS ID: https://nottingham-repository.worktribe.com/output/932703
Schools/Departments: University of Nottingham, UK > Faculty of Medicine and Health Sciences > School of Life Sciences
Identification Number: https://doi.org/10.1038/sdata.2018.81
Depositing User: Eprints, Support
Date Deposited: 18 May 2018 09:45
Last Modified: 04 May 2020 19:36
URI: http://eprints.nottingham.ac.uk/id/eprint/51012

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