Related Experiment Video
Updated: Oct 11, 2025

Using Human Differentially Expressed Gene Lists to Perform Downstream Pathway Enrichment Analysis and Target Prioritization
Published on: October 3, 2025
A signaling pathway-driven bioinformatics pipeline for predicting therapeutics against emerging infectious diseases
Tiana M Scott1, Sam Jensen1, Brett E Pickett1
1Microbiology and Molecular Biology, Brigham Young University, Provo, Utah, 84602, USA.
Abstract:
Background: Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), the etiological agent of coronavirus disease-2019 (COVID-19), is a novel Betacoronavirus that was first reported in Wuhan, China in December of 2019. The virus has since caused a worldwide pandemic that highlights 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. To combat this problem, we constructed a computational pipeline that uniquely combines existing tools to predict drugs and biologics that could be repurposed to combat an emerging pathogen. Methods: Our 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 US Food and Drug Administration (FDA)-approved drugs that target human proteins within these pathways. We used this pipeline to perform a meta-analysis of RNA-seq data from cells infected with three Betacoronavirus species 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 and influenza A virus to identify therapeutics that could be used to treat COVID-19. Results: This analysis identified twelve existing drugs, most of which already have FDA-approval, that are predicted to counter the effects of SARS-CoV-2 infection. These results were cross-referenced with interventional clinical trials and other studies in the literature to identify drugs on our list that had previously been identified or used as treatments for COIVD-19 including canakinumab, anakinra, tocilizumab, sarilumab, and baricitinib. Conclusions: While the results reported here are specific to Betacoronaviruses, such as SARS-CoV-2, our bioinformatics pipeline can be used to quickly identify candidate therapeutics for future emerging infectious diseases.
Insights
A computational pipeline identified twelve existing drugs, including FDA-approved medications, that may treat COVID-19 by targeting SARS-CoV-2 infection pathways. This approach aids in rapid drug repurposing for emerging infectious diseases.
Area of Science:
- Computational biology
- Infectious disease research
- Drug discovery
Background:
- Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) causes COVID-19, a global pandemic.
- Rapid identification of treatments is crucial for novel infectious agents.
- Existing computational tools were combined to create a novel drug repurposing pipeline.
Purpose of the Study:
- To develop and utilize a computational pipeline for identifying potential therapeutics against emerging viral pathogens.
- To identify FDA-approved drugs that can be repurposed to treat COVID-19.
- To analyze transcriptomic data from infections with Betacoronaviruses and other respiratory viruses.
Main Methods:
- A bioinformatics pipeline was constructed to analyze RNA-sequencing data.
- The workflow identifies differentially expressed genes, enriched Gene Ontology terms, and dysregulated pathways.
- Meta-analysis of RNA-seq data from SARS-CoV, MERS-CoV, SARS-CoV-2, RSV, and influenza A virus-infected cells was performed.
Main Results:
- Twelve existing drugs, primarily FDA-approved, were predicted to counteract SARS-CoV-2 infection effects.
- Cross-referencing with clinical trials identified drugs like canakinumab, anakinra, tocilizumab, sarilumab, and baricitinib as potential COVID-19 treatments.
- The pipeline successfully identified known therapeutic candidates.
Conclusions:
- The developed bioinformatics pipeline can rapidly identify candidate therapeutics for emerging infectious diseases.
- Results are specific to Betacoronaviruses like SARS-CoV-2 but the method is broadly applicable.
- This strategy supports efficient drug repurposing against novel pathogens.

