DOI: 10.17044/scilifelab.14188403
title: A phenomics approach for antiviral drug discovery - Images, analysis pipelines and feature data

description: Abstract:<br><br>The current COVID-19 pandemic has highlighted the need for new and fast methods to identify novel or repurposed therapeutic drugs. Here we present a method for untargeted phenotypic drug screening of virus-infected cells, combining Cell Painting with antibody-based detection of viral infection in a single assay. We designed an image analysis pipeline for segmentation and classification of virus-infected and non-infected cells, followed by extraction of morphological properties. We show that the methodology can successfully capture virus-induced phenotypic signatures of MRC-5 human lung fibroblasts infected with Human coronavirus 229E (CoV-229E). Moreover, we demonstrate that our method can be used in phenotypic drug screening using a panel of nine host- and virus-targeting antivirals. Treatment with effective antiviral compounds reversed the morphological profile of the host cells towards a non-infected state. The method can be used in drug discovery for morphological profiling of novel antiviral compounds on both infected and non-infected cells. <br><br>Screen description: <br>The images are of MRC-5 human lung fibroblasts infected with Human coronavirus 229E (CoV-229E) and treated with a panel of nine host- and virus-targeting antivirals. Cells are labelled with five labels that characterise seven cellular components (from the "Cell Painting" assay) as well as with a Coronavirus pan monoclonal antibody combined with a secondary antibody. This experiment consists of 5 plates. Each plate has 60 wells, and 9 fields of view per well. Each field was imaged in five channels (detection wavelengths), and each channel is stored as a separate, grayscale image file in TIFF format.The channel names (w1-w5) correspond to the following stains: w1 = Hoechst 33342 (HOECHST); w2= Coronavirus pan Monoclonal Antibody (FIPV3-70) + Goat Anti-Mouse IgG H&L secondary antibody (MITO); w3= Wheat Germ Agglutinin/Alexa Fluor 555 + Phalloidin/Alexa Fluor 568 (PHAandWGA); w4= SYTO 14 green (SYTO); w5= Concanavalin A/Alexa Fluor 488 (CONC)<br>Organization of files:<br>1) Raw image data:<br>- MRC5_HCoV229_Plate1.tar.gz <br>- MRC5_HCoV229_Plate2.tar.gz - MRC5_Plate3.tar.gz - MRC5_Plate4.tar.gz - MRC5_HCoV229_Plate5.tar.gz <br>2) Image analysis pipelines (CellProfiler 4.0.7):<br>Cell Profiler project with a subset of images to try out the analysis pipeline:- Example_PipelineAndData.tar.gz <br>Quality control, illumination correction and feature extraction pipelines:- AnalysisPipelines.tar.gz<br><br>3) Extracted feature data:<br>- features_MRC5_HCoV229_Plate1.tar.gz<br>- features_MRC5_HCoV229_Plate2.tar.gz- features_MRC5_Plate3.tar.gz- features_MRC5_Plate4.tar.gz- features_MRC5_HCoV229_Plate5.tar.gz<br>Metadata:<br>The file “Metadata_MRC5_HCoV229E_plate1-5.csv“ contains the metadata in CSV format, with the following fields:<br>- Plate_id: corresponds to the experimental plate<br>- Well: well allocation in the 96-well plate<br>- virus: "virus +" when cells are exposed to virus, and "virus -' for non-infected controls- Compound: name of compound<br>- Dose [μM]: dose of compound<br>For full information, see the manuscript to which this data is linked.<br>