Ten emerging SARS-CoV-2 spike variants exhibit variable infectivity, animal tropism, and antibody neutralization.

Emerging mutations in SARS-CoV-2 cause several waves of COVID-19 pandemic. Here we investigate the infectivity and antigenicity of ten emerging SARS-CoV-2 variants-B.1.1.298, B.1.1.7(Alpha), B.1.351(Beta), P.1(Gamma), P.2(Zeta), B.1.429(Epsilon), B.1.525(Eta), B.1.526-1(Iota), B.1.526-2(Iota), B.1.1.318-and seven corresponding single amino acid mutations in the receptor-binding domain using SARS-CoV-2 pseudovirus. The results indicate that the pseudovirus of most of the SARS-CoV-2 variants (except B.1.1.298) display slightly increased infectivity in human and monkey cell lines, especially B.1.351, B.1.525 and B.1.526 in Calu-3 cells. The K417N/T, N501Y, or E484K-carrying variants exhibit significantly increased abilities to infect mouse ACE2-overexpressing cells. The activities of furin, TMPRSS2, and cathepsin L are increased against most of the variants. RBD amino acid mutations comprising K417T/N, L452R, Y453F, S477N, E484K, and N501Y cause significant immune escape from 11 of 13 monoclonal antibodies. However, the resistance to neutralization by convalescent serum or vaccines elicited serum is mainly caused by the E484K mutation. The convalescent serum from B.1.1.7- and B.1.351-infected patients neutralized the variants themselves better than other SARS-CoV-2 variants. Our study provides insights regarding therapeutic antibodies and vaccines, and highlights the importance of E484K mutation.

Translational adaptation of human viruses to the tissues they infect.

Viruses need to hijack the translational machinery of the host cell for a productive infection to happen. However, given the dynamic landscape of tRNA pools among tissues, it is unclear whether different viruses infecting different tissues have adapted their codon usage toward their tropism. Here, we collect the coding sequences of 502 human-infecting viruses and determine that tropism explains changes in codon usage. Using the tRNA abundances across 23 human tissues from The Cancer Genome Atlas (TCGA), we build an in silico model of translational efficiency that validates the correspondence of the viral codon usage with the translational machinery of their tropism. For instance, we detect that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is specifically adapted to the upper respiratory tract and alveoli. Furthermore, this correspondence is specifically defined in early viral proteins. The observed tissue-specific translational efficiency could be useful for the development of antiviral therapies and vaccines.