Data to accompany the manuscript "A phenomics approach for antiviral drug discovery".

DOI:
https://doi.org/10.1101/2021.01.13.423947

Authors:
Jonne Rietdijk, Marianna Tampere, Aleksandra Pettke, Polina Georgieva, Maris Lapins, Ulrika Warpman Berglund, Ola Spjuth, Marjo-Riitta Puumalainen and Jordi Carreras Puigvert

Categories:
Virology, Cell Biology

Item type:
Dataset

Keywords:
Phenomics, morphological profiling, cell painting, drug discovery, antiviral

Description: 

Abstract:

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.

Screen description:

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). 

Organization of files:

1) Raw image data:

- MRC5_HCoV229_Plate1.tar.gz
- MRC5_HCoV229_Plate2.tar.gz
- MRC5_Plate3.tar.gz
- MRC5_Plate4.tar.gz
- MRC5_HCoV229_Plate5.tar.gz

2) Image analysis pipelines (CellProfiler 4.0.7):

Example_pipeline project with example dataset:
- Example_PipelineAndData.tar.gz 

Quality control, Illumination correction and feature extraction pipelines:
- AnalysisPipelines.tar.gz

3) Extracted feature data:
- features_MRC5_HCoV229_Plate1.tar.gz
- features_MRC5_HCoV229_Plate2.tar.gz
- features_MRC5_Plate3.tar.gz
- features_MRC5_Plate4.tar.gz
- features_MRC5_HCoV229_Plate5.tar.gz

Metadata:

The file ÒMetadata_MRC5_HCoV229E_plate1-5Ò contains the metadata in CSV format, with the following fields:
- Plate_id: corresponds to the experimental plate
- Well: well allocation in the 96-well plate
- virus: virus+ when cells are exposed to virus, and virus- for non-infected controls
- Compound: name of compound
- Dose [uM]: dose of compound

For full information, see the article to which this data is linked.

Funding: 
This project received funding within the SciLifeLab National COVID-19 Research Program and Knut och Alice Wallenbergs stiftelse (KAW 2020.0182). This project also received funding from the Swedish Research Council (2017-05631 for M-R.P; 2020-03731 for OS and JCP), FORMAS (2018-00924 for OS and JR) and the European UnionÕs Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement no 722729. M.T. was supported by SSF (FID15-0010). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Licence:
CC BY 4.0

Publisher:
Uppsala University

Contact:
jordi.carreras.puigvert@farmbio.uu.se