Presenter: Tiana Scott, College of Life Sciences, Microbiology and Molecular Biology
Authors: Tiana M. Scott, Sam Jensen, Brett E. Pickett
Faculty Advisor: Brett Pickett, College of Life Sciences, Microbiology and Molecular Biology
Institution: Brigham Young University
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a novel Betacoronavirus that was first reported in Wuhan, China in December of 2019. Its associated disease has been named coronavirus disease-2019 (COVID-19), which has now become associated with a worldwide pandemic. The devastating effects of this pandemic have highlighted the need to quickly identify potential prophylactic or therapeutic treatments that can reduce the signs, symptoms, and/or spread of disease when dealing with a novel infectious agent. We constructed a novel computational pipeline that predicts drugs and biologics that could be repurposed to combat a novel infectious disease. Specifically, this workflow analyzes RNA sequencing data to determine differentially expressed genes, enriched Gene Ontology (GO) terms, and dysregulated pathways in infected cells, which can then be used to identify FDA-approved drugs that target proteins within these pathways. We used this pipeline to perform a meta-analysis of RNA sequencing data from cells infected with three Betacoronaviruses including severe acute respiratory syndrome coronavirus (SARS-CoV; SARS), Middle East respiratory syndrome coronavirus (MERS-CoV; MERS), and SARS-CoV-2, as well as respiratory syncytial virus (RSV) and influenza A virus (IAV) to identify therapeutics that could be used to treat COVID-19. This analysis identified twenty-seven existing drugs, most of which already have FDA-approval, that are predicted to counter the effects of SARS-CoV-2 infection. These results are validated by separate studies involving canakinumab, anakinra, tocilizumab, sarilumab, baricitinib, and others. While the results reported here are specific to Betacoronaviruses, such as SARS-CoV-2, our bioinformatics pipeline can be used to quickly identify candidate drugs for treating future emerging infectious diseases.