NSUN2-mediated M5c methylation of IRF3 mRNA negatively regulates type I interferon responses during various viral infections.

5-Methylcytosine (m5C) is a widespread post-transcriptional RNA modification and is reported to be involved in manifold cellular responses and biological processes through regulating RNA metabolism. However, its regulatory role in antiviral innate immunity has not yet been elucidated. Here, we report that NSUN2, a typical m5C methyltransferase, negatively regulates type I interferon responses during various viral infections, including SARS-CoV-2. NSUN2 specifically mediates m5C methylation of IRF3 mRNA and accelerates its degradation, resulting in low levels of IRF3 and downstream IFN-ß production. Knockout or knockdown of NSUN2 enhanced type I interferon and downstream ISGs during various viral infection in vitro. And in vivo, the antiviral innate response is more dramatically enhanced in Nsun2+/- mice than in Nsun2+/+ mice. The highly m5C methylated cytosines in IRF3 mRNA were identified, and their mutation enhanced cellular IRF3 mRNA levels. Moreover, infection with Sendai virus (SeV), vesicular stomatitis virus (VSV), herpes simplex virus 1 (HSV-1), or Zika virus (ZIKV) resulted in a reduction of endogenous NSUN2 levels. Especially, SARS-CoV-2 infection (WT strain and BA.1 omicron variant) also decreased endogenous levels of NSUN2 in COVID-19 patients and K18-hACE2 KI mice, further increasing type I interferon and downstream ISGs. Together, our findings reveal that NSUN2 serves as a negative regulator of interferon response by accelerating the fast turnover of IRF3 mRNA, while endogenous NSUN2 levels decrease during SARS-CoV-2 and various viral infections to boost antiviral responses for effective elimination of viruses.

The SARS-CoV-2 subgenome landscape and its novel regulatory features.

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is currently a global pandemic. CoVs are known to generate negative subgenomes (subgenomic RNAs [sgRNAs]) through transcription-regulating sequence (TRS)-dependent template switching, but the global dynamic landscapes of coronaviral subgenomes and regulatory rules remain unclear. Here, using next-generation sequencing (NGS) short-read and Nanopore long-read poly(A) RNA sequencing in two cell types at multiple time points after infection with SARS-CoV-2, we identified hundreds of template switches and constructed the dynamic landscapes of SARS-CoV-2 subgenomes. Interestingly, template switching could occur in a bidirectional manner, with diverse SARS-CoV-2 subgenomes generated from successive template-switching events. The majority of template switches result from RNA-RNA interactions, including seed and compensatory modes, with terminal pairing status as a key determinant. Two TRS-independent template switch modes are also responsible for subgenome biogenesis. Our findings reveal the subgenome landscape of SARS-CoV-2 and its regulatory features, providing a molecular basis for understanding subgenome biogenesis and developing novel anti-viral strategies.

Analytical comparisons of SARS-COV-2 detection by qRT-PCR and ddPCR with multiple primer/probe sets.

Different primers/probes sets have been developed all over the world for the nucleic acid detection of SARS-CoV-2 by quantitative real time polymerase chain reaction (qRT-PCR) as a standard method. In our recent study, we explored the feasibility of droplet digital PCR (ddPCR) for clinical SARS-CoV-2 nucleic acid detection compared with qRT-PCR using the same primer/probe sets issued by Chinese Center for Disease Control and Prevention (CDC) targeting viral ORF1ab or N gene, which showed that ddPCR could largely minimize the false negatives reports resulted by qRT-PCR [Suo T, Liu X, Feng J, et al. ddPCR: a more sensitive and accurate tool for SARS-CoV-2 detection in low viral load specimens. medRxiv [Internet]. 2020;2020.02.29.20029439. Available from: https://medrxiv.org/content/early/2020/03/06/2020.02.29.20029439.abstract]. Here, we further stringently compared the performance of qRT-PCR and ddPCR for 8 primer/probe sets with the same clinical samples and conditions. Results showed that none of 8 primer/probe sets used in qRT-PCR could significantly distinguish true negatives and positives with low viral load (10-4 dilution). Moreover, false positive reports of qRT-PCR with UCDC-N1, N2 and CCDC-N primers/probes sets were observed. In contrast, ddPCR showed significantly better performance in general for low viral load samples compared to qRT-PCR. Remarkably, the background readouts of ddPCR are relatively lower, which could efficiently reduce the production of false positive reports.

ddPCR: a more accurate tool for SARS-CoV-2 detection in low viral load specimens.

Quantitative real time PCR (RT-PCR) is widely used as the gold standard for clinical detection of SARS-CoV-2. However, due to the low viral load specimens and the limitations of RT-PCR, significant numbers of false negative reports are inevitable, which results in failure to timely diagnose, cut off transmission, and assess discharge criteria. To improve this situation, an optimized droplet digital PCR (ddPCR) was used for detection of SARS-CoV-2, which showed that the limit of detection of ddPCR is significantly lower than that of RT-PCR. We further explored the feasibility of ddPCR to detect SARS-CoV-2 RNA from 77 patients, and compared with RT-PCR in terms of the diagnostic accuracy based on the results of follow-up survey. 26 patients of COVID-19 with negative RT-PCR reports were reported as positive by ddPCR. The sensitivity, specificity, PPV, NPV, negative likelihood ratio (NLR) and accuracy were improved from 40% (95% CI: 27-55%), 100% (95% CI: 54-100%), 100%, 16% (95% CI: 13-19%), 0.6 (95% CI: 0.48-0.75) and 47% (95% CI: 33-60%) for RT-PCR to 94% (95% CI: 83-99%), 100% (95% CI: 48-100%), 100%, 63% (95% CI: 36-83%), 0.06 (95% CI: 0.02-0.18), and 95% (95% CI: 84-99%) for ddPCR, respectively. Moreover, 6/14 (42.9%) convalescents were detected as positive by ddPCR at 5-12 days post discharge. Overall, ddPCR shows superiority for clinical diagnosis of SARS-CoV-2 to reduce the false negative reports, which could be a powerful complement to the RT-PCR.