Author: Rietdijk, Jonne; Tampere, Marianna; Pettke, Aleksandra; Georgieva, Polina; Lapins, Maris; Berglund, Ulrika Warpman; Spjuth, Ola; Puumalainen, Marjo-Riitta; Carreras-Puigvert, Jordi
Title: A phenomics approach for in vitro antiviral drug discovery Cord-id: qj6ux1yb Document date: 2021_3_24
ID: qj6ux1yb
Snippet: Background 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. Result
Document: Background 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. Results 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. Conclusions The method can be used in drug discovery for morphological profiling of novel antiviral compounds on both infected and non-infected cells.
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