CHSU Discovery

SARS-CoV-2 early infection signature identified potential key infection mechanisms and drug targets.

BMC genomics Peer reviewed publication
volume 22 issue 1 pages 125
February 2021
DOI: 10.1186/s12864-021-07433-4 PMID: 33602138
EISSN: 1471-2164 KB-ID: 13203 CHSU: Faculty LN: Khalafalla
  1. https://www.ncbi.nlm.nih.gov/pubmed/33602138
  2. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7889713/
  3. https://doi.org/10.1186/s12864-021-07433-4

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Description

BACKGROUND

The ongoing COVID-19 outbreak has caused devastating mortality and posed a significant threat to public health worldwide. Despite the severity of this illness and 2.3 million worldwide deaths, the disease mechanism is mostly unknown. Previous studies that characterized differential gene expression due to SARS-CoV-2 infection lacked robust validation. Although vaccines are now available, effective treatment options are still out of reach.

RESULTS

To characterize the transcriptional activity of SARS-CoV-2 infection, a gene signature consisting of 25 genes was generated using a publicly available RNA-Sequencing (RNA-Seq) dataset of cultured cells infected with SARS-CoV-2. The signature estimated infection level accurately in bronchoalveolar lavage fluid (BALF) cells and peripheral blood mononuclear cells (PBMCs) from healthy and infected patients (mean 0.001 vs. 0.958; P < 0.0001). These signature genes were investigated in their ability to distinguish the severity of SARS-CoV-2 infection in a single-cell RNA-Sequencing dataset. TNFAIP3, PPP1R15A, NFKBIA, and IFIT2 had shown bimodal gene expression in various immune cells from severely infected patients compared to healthy or moderate infection cases. Finally, this signature was assessed using the publicly available ConnectivityMap database to identify potential disease mechanisms and drug repurposing candidates. Pharmacological classes of tricyclic antidepressants, SRC-inhibitors, HDAC inhibitors, MEK inhibitors, and drugs such as atorvastatin, ibuprofen, and ketoconazole showed strong negative associations (connectivity score < - 90), highlighting the need for further evaluation of these candidates for their efficacy in treating SARS-CoV-2 infection.

CONCLUSIONS

Thus, using the 25-gene SARS-CoV-2 infection signature, the SARS-CoV-2 infection status was captured in BALF cells, PBMCs and postmortem lung biopsies. In addition, candidate SARS-CoV-2 therapies with known safety profiles were identified. The signature genes could potentially also be used to characterize the COVID-19 disease severity in patients' expression profiles of BALF cells.

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Subjects

Affiliations

  1. College of Pharmacy,
  2. College of Pharmacy, California Health Sciences University, Clovis, CA 93612 USA
  3. School of Pharmacy,

Publisher

BioMed Central (England)

Languages

English

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