Vaccination with Span, an antigen guided by SARS-CoV-2 S protein evolution, protects against challenge with viral variants in mice.

SARS-CoV-2 continues to accumulate mutations to evade immunity, leading to breakthrough infections after vaccination. How researchers can anticipate the evolutionary trajectory of the virus in advance in the design of next-generation vaccines requires investigation. Here, we performed a comprehensive study of 11,650,487 SARS-CoV-2 sequences, which revealed that the SARS-CoV-2 spike (S) protein evolved not randomly but into directional paths of either high infectivity plus low immune resistance or low infectivity plus high immune resistance. The viral infectivity and immune resistance of variants are generally incompatible, except for limited variants such as Beta and Kappa. The Omicron variant has the highest immune resistance but showed high infectivity in only one of the tested cell lines. To provide cross-clade immunity against variants that undergo diverse evolutionary pathways, we designed a new pan-vaccine antigen (Span). Span was designed by analyzing the homology of 2675 SARS-CoV-2 S protein sequences from the NCBI database before the Delta variant emerged. The refined Span protein harbors high-frequency residues at given positions that reflect cross-clade generality in sequence evolution. Compared with a prototype wild-type (Swt) vaccine, which, when administered to mice, induced serum with decreased neutralization activity against emerging variants, Span vaccination of mice elicited broad immunity to a wide range of variants, including those that emerged after our design. Moreover, vaccinating mice with a heterologous Span booster conferred complete protection against lethal infection with the Omicron variant. Our results highlight the importance and feasibility of a universal vaccine to fight against SARS-CoV-2 antigenic drift.

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.