Host transcriptional response to SARS-CoV-2 infection in COVID-19 patients

Singh, Nitesh Kumar; Srivastava, Surabhi; Zaveri, Lamuk; Bingi, Thrilok Chander; Mesipogu, Rajarao; Kumar, Santosh; Gaur, Namami; Hajirnis, Nikhil; Maccha, Pratheusa; Shambhavi, Sakshi; Khan, Shagufta; Soujanya, Mamilla; Nagabandi, Tulasi; Mishra, Rakesh K.; Tallapaka, Karthik Bharadwaj; Sowpati, Divya Tej

Background One of the most perplexing aspects of infection with the SARS-CoV-2 virus has been the variable response elicited in its human hosts. Investigating the transcriptional changes in individuals affected by COVID-19 can help understand and predict the degree of illness and guide clinical outcomes in diverse backgrounds. Methods Analysis of host transcriptome variations via RNA sequencing from naso/oropharyngeal swabs of COVID-19 patients. Results We report strong upregulation of the innate immune response, especially type I interferon pathway, upon SARS-CoV-2 infection. Upregulated genes were subjected to a comparative meta-analysis using global datasets to identify a common network of interferon stimulated and viral response genes that mediate the host response and resolution of infection. A large proportion of mis-regulated genes showed a reduction in expression level, suggesting an overall decrease in host mRNA production. Significantly downregulated genes included those encoding olfactory, taste and neuro-sensory receptors. Many pro-inflammatory markers and cytokines were also downregulated or remained unchanged in the COVID-19 patients. Finally, a large number of non-coding RNAs were identified as down-regulated, with a few of the lncRNAs associated with functional roles in directing the response to viral infection. Conclusions SARS-CoV-2 infection results in the robust activation of the body’s innate immunity. Reduction of gene expression is well correlated with the clinical manifestations and symptoms of COVID-19 such as the loss of smell and taste, and myocardial and neurological complications. This study provides a critical dataset of genes that will enhance our understanding of the nature and prognosis of COVID-19.