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?:abstract
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Background Severe Acute Respiratory Syndrome (SARS) corona virus (SARS-CoV) infections are a serious public health threat because of their pandemic-causing potential. This work uses mRNA expression data to predict genes associated with SARS-CoV infection through an innovative meta-analysis examining gene signatures (i.e., gene lists ranked by differential gene expression between SARS and mock infection). Methods This work defines 29 gene signatures representing SARS infection across seven strains with established mutations that vary virulence (infectious clone SARS (icSARS), Urbani, MA15, ΔORF6, BAT-SRBD, ΔNSP16, and ExoNI) and host (human lung cultures and/or mouse lung samples) and examines them through Gene Set Enrichment Analysis (GSEA). To do this, first positive and negative icSARS gene panels were defined from GSEA-identified leading-edge genes between 500 genes from positive or negative tails of the GSE47960-derived icSARSvsmock signature and the GSE47961-derived icSARSvsmock signature, both from human cultures. GSEA then was used to assess enrichment and identify leading-edge icSARS panel genes in the other 27 signatures. Genes associated with SARS-CoV infection are predicted by examining membership in GSEA-identified leading-edges across signatures. Results Significant enrichment (GSEA p<0.001) was observed between GSE47960-derived and GSE47961-derived signatures, and those leading-edges defined the positive (233 genes) and negative (114 genes) icSARS panels. Non-random (null distribution p<0.001) significant enrichment (p<0.001) was observed between icSARS panels and all verification icSARSvsmock signatures derived from human cultures, from which 51 over- and 22 under-expressed genes were shared across leading-edges with 10 over-expressed genes already being associated with icSARS infection. For the icSARSvsmock mouse signature, significant, non-random enrichment (both p<0.001) held for only the positive icSARS panel, from which nine genes were shared with icSARS infection in human cultures. Considering other SARS strains, significant (p<0.01), non-random (p<0.002) enrichment was observed across signatures derived from other SARS strains for the positive icSARS panel. Five positive icSARS panel genes, CXCL10, OAS3, OASL, IFIT3, and XAF1, were found in mice and human signatures. Conclusion The GSEA-based meta-analysis approach used here identified genes with and without reported associations with SARS-CoV infections, highlighting this approach’s predictability and usefulness in identifying genes that have potential as therapeutic targets to preclude or overcome SARS infections.
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