A SARS-CoV-2 cytopathicity dataset generated by high-content screening of a large drug repurposing collection

Coronaviridae is a family of encapsulated single-stranded positive-sense RNA viruses that typically cause mild respiratory diseases such as the common cold in humans. However, several β coronavirus strains have emerged over the last two decades that cause acute respiratory infections associated with high mortality, particularly in individuals with underlying health conditions. Three major outbreaks have occurred, the first caused by Severe acute respiratory syndrome coronavirus (SARS-CoV) in 2002/2003, the second caused by Middle East respiratory syndrome coronavirus (MERS-CoV) in 2012, and the latest caused by Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which was first recorded in December 2019 and was declared pandemic in March 2020. At the time of writing (9th December 2020), more than 69 million confirmed SARS-CoV-2 infections have been reported worldwide and more than 1.6 million people have died from the associated disease, COVID-19.

As a complement to the safe and effective vaccines against SARS-CoV-2, the repurposing of existing drugs represents a pragmatic strategy for the treatment of COVID-19 patients. Drug repurposing (drug repositioning) is advantageous in the face of rapidly-spreading emerging diseases because the pathway to approval is facilitated by pre-existing preclinical (and often clinical or post-marketing) data, existing production capacity and supply chains can be used, and new mechanisms of action can be discovered that may suggest potential drug combinations for enhanced efficacy by exploiting synergistic effects. Furthermore, bioinformatics analysis has identified 66 druggable proteins based on the SARS-CoV-2/human host cell interactome, which will allow the selection of compounds that interfere with interactions essential in the viral replication cycle. Regardless of the origin of drugs against SARS-CoV-2, properly controlled clinical safety and efficacy studies are still needed before the approval of pharmacological treatments for COVID-19.

Multiple interventional clinical trials have been initiated in the search for effective treatments against SARS-CoV-2. The individual drugs or combination treatments for these studies have often been selected based on known activities against SARS-CoV, Ebola virus, HIV or Plasmodiumspp., hence the drugs under investigation include remdesivir, interferon β and ribavirin and lopinavir/ritonavir. However, the search for effective drugs against SARS-CoV-2 could extend beyond known antivirals and anti-infectives if suitable high-throughput assays are used to identify candidates.

figure1

Fig. : Cytopathicity assay workflow. To test for compound cytotoxicity, Caco-2 cells were grown to confluence and incubated with test compounds for 48 h. To test whether the compounds influenced the cytopathic effect of SARS-CoV-2, Caco-2 cells were grown to confluence and incubated with the test compounds and SARS-CoV-2 for 48 h. For image acquisition, the cells were fixed to comply with BSL1 requirements and imaged by digital phase contrast (DPC) microscopy. Upper image set shows the primary screen to determine cytotoxicity and cytopathic effect. Top two rows are representative wells of the compound area including three active molecules. Bottom row shows four positive control wells (virus treated, no compounds) and four negative control wells (no virus, no compounds). Lower image set shows the dose-response screen used to measure the anti-cytopathic effects of each compound at eight concentrations, allowing the calculation of IC50 values. Scale bar = 500 µm.

 

Here we describe a high-content imaging dataset generated by screening a well-defined collection of 5632 compounds including 3488 with clinical or post-marketing data across 600 indications. The compounds were screened for their ability to inhibit the cytopathic effect of SARS-CoV-2 in the human epithelial colorectal adenocarcinoma cell line Caco-2 using the assay design shown in Fig . The compounds we used are well annotated in terms of primary and secondary targets and we therefore hope the data and meta-data presented herein will be combined with our results and the findings of other researchers to identify additional treatment options for COVID-19, including drug combinations. One important avenue for reuse is to determine whether any of these clinical-stage compounds or related molecules could safely achieve active concentrations at the principal SARS-CoV-2 infection site, the human lung epithelium. In this manner, the combination of our in vitro activity data with information about tissue distribution may help to determine the most promising avenues for future COVID-19 preclinical and clinical studies.

Ellinger, B., Bojkova, D., Zaliani, A. et al. A SARS-CoV-2 cytopathicity dataset generated by high-content screening of a large drug repurposing collection. Sci Data 8, 70 (2021). https://doi.org/10.1038/s41597-021-00848-4

Leave a Reply

Your email address will not be published. Required fields are marked *