Experimental and natural evidence of SARS-CoV-2 infection-induced activation of type I interferon responses
Two highly pathogenic human coronaviruses that cause severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS) have evolved proteins that can inhibit host antiviral responses, likely contributing to disease progression and high case-fatality rates. SARS-CoV-2 emerged in December 2019 to cause a global pandemic. Recent studies have shown that SARS-CoV-2 is unable to induce a robust type I interferon (IFN) response in human cells, leading to speculations about the ability of SARS-CoV-2 to inhibit innate antiviral responses. However, innate antiviral responses are dynamic in nature and gene expression levels rapidly change within minutes to hours. In this study, we have performed a time series RNA-seq analysis to identify early virus-host processes. SARS-CoV-2 infection upregulated transcripts for type I IFNs and interferon stimulated genes (ISGs) after 12 hours. Furthermore, we analyzed the ability of SARS-CoV-2 to inhibit type I IFN production and downstream antiviral signaling in human cells. Using exogenous stimuli, we discovered that SARS-CoV-2 is unable to modulate IFNb production and downstream expression of ISGs, such as IRF7 and IFIT1. Thus, data from our study indicate that SARS-CoV-2 may have evolved additional mechanisms, such as masking its nucleic acid from cellular immune response sensors to mount a dampened innate antiviral response. Further studies are required to fully identify the range of immune-modulatory strategies of SARS-CoV-2. Overall design: We infected triplicated human lung epithelial cells (Calu-3) at a multiplicity of infection (MOI) for SARS-CoV-2 of 2, with comparison to triplicated uninfected controls. One hour post infection, the inoculum was removed and the clock was set to zero. We extracted and sequenced poly-A enriched RNA at 0, 1, 2, 3, 6 and 12 hours post infection (hpi) using an Illumina HiSeq 2500 with 2 x 50 bp chemistry to a minimum of 21.9 million clusters per replicate. Paired-end sequencing reads were mapped to the human reference transcriptome (GRCh37.67) obtained from the ENSEMBL database using the 'quant' function of Salmon, transcript counts summarized at the gene-level using the corresponding transcriptome GTF file mappings obtained from ENSEMBL, and count data normalized using DeSeq2's 'estimateSizeFactors' function using the default 'median ratio method'.