Key mutations in the spike protein of SARS-CoV-2 affecting neutralization resistance and viral internalization.

To control the ongoing COVID-19 pandemic, a variety of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccines have been developed. However, the rapid mutations of SARS-CoV-2 spike (S) protein may reduce the protective efficacy of the existing vaccines which is mainly determined by the level of neutralizing antibodies targeting S. In this study, we screened prevalent S mutations and constructed 124 pseudotyped lentiviral particles carrying these mutants. We challenged these pseudoviruses with sera vaccinated by Sinovac CoronaVac and ZF2001 vaccines, two popular vaccines designed for the initial strain of SARS-CoV-2, and then systematically assessed the susceptivity of these SARS-CoV-2 variants to the immune sera of vaccines. As a result, 14 S mutants (H146Y, V320I + S477N, V382L, K444R, L455F + S477N, L452M + F486L, F486L, Y508H, P521R, A626S, S477N + S698L, A701V, S477N + T778I, E1144Q) were found to be significantly resistant to neutralization, indicating reduced protective efficacy of the vaccines against these SARS-CoV-2 variants. In addition, F486L and Y508H significantly enhanced the utilization of human angiotensin-converting enzyme 2, suggesting a potentially elevated infectivity of these two mutants. In conclusion, our results show that some prevalent S mutations of SARS-CoV-2 reduced the protective efficacy of current vaccines and enhance the infectivity of the virus, indicating the necessity of vaccine renewal and providing direction for the development of new vaccines.

VirusRecom: an information-theory-based method for recombination detection of viral lineages and its application on SARS-CoV-2.

Genomic recombination is an important driving force for viral evolution, and recombination events have been reported for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) during the Coronavirus Disease 2019 pandemic, which significantly alter viral infectivity and transmissibility. However, it is difficult to identify viral recombination, especially for low-divergence viruses such as SARS-CoV-2, since it is hard to distinguish recombination from in situ mutation. Herein, we applied information theory to viral recombination analysis and developed VirusRecom, a program for efficiently screening recombination events on viral genome. In principle, we considered a recombination event as a transmission process of ``information'' and introduced weighted information content (WIC) to quantify the contribution of recombination to a certain region on viral genome; then, we identified the recombination regions by comparing WICs of different regions. In the benchmark using simulated data, VirusRecom showed a good balance between precision and recall compared to two competing tools, RDP5 and 3SEQ. In the detection of SARS-CoV-2 XE, XD and XF recombinants, VirusRecom providing more accurate positions of recombination regions than RDP5 and 3SEQ. In addition, we encapsulated the VirusRecom program into a command-line-interface software for convenient operation by users. In summary, we developed a novel approach based on information theory to identify viral recombination within highly similar sequences, providing a useful tool for monitoring viral evolution and epidemic control.