A multi-phenotypic imaging screen to identify bacterial effectors by exogenous expression in a HeLa cell line.
Adam CollinsAlan HuettPublished in: Scientific data (2018)
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.
Keyphrases
- cell cycle arrest
- cell death
- induced apoptosis
- high throughput
- endoplasmic reticulum stress
- signaling pathway
- single cell
- oxidative stress
- immune response
- deep learning
- machine learning
- pi k akt
- electronic health record
- poor prognosis
- escherichia coli
- diabetic rats
- endothelial cells
- photodynamic therapy
- drug induced
- nk cells