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

Collins, Adam; Huett, Alan

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.

Citation

Collins, A., & Huett, A. (2018). A multi-phenotypic imaging screen to identify bacterial effectors by exogenous expression in a HeLa cell line. Scientific Data, 5, Article 180081. https://doi.org/10.1038/sdata.2018.81

• Journal Article Type: Article
• Acceptance Date: Jan 30, 2018
• Publication Date: May 15, 2018
• Deposit Date: May 18, 2018
• Publicly Available Date: May 18, 2018
• Journal: Scientific Data
• Electronic ISSN: 2052-4463
• Publisher: Nature Publishing Group
• Peer Reviewed: Peer Reviewed
• Volume: 5
• Article Number: 180081
• DOI: https://doi.org/10.1038/sdata.2018.81
• Public URL: https://nottingham-repository.worktribe.com/output/932703
• Publisher URL: https://www.nature.com/articles/sdata201881