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The Receptor Binding Domain of SARS-CoV-2 Omicron Subvariants Targets Siglec-9 to Decrease the Immunogenicity by Preventing Phagocytosis of Macrophages

ABSTRACT: SARS-CoV-2 Omicron infection results in a milder clinical feature compared to the Delta strain. The development of Omicron specific vaccine has also been hampered due to the low immunogenicity. By reverse-mutating the amino acids in the Omicron receptor binding domain (RBD), we identified that the mutation from Phenylalanine 375 (F375) in the Omicron spike to Serine 375 (S375) in Delta and other early strains significantly enhances the immune response in the manner of vaccines. Interestingly, the new evolution of the 371FAPF375FAF sequence in Omicron exhibited a potent inhibitory effect on macrophage uptake of the RBD nanoparticle or spike-pseudovirus particles. Omicron RBD enhances binding to Siglec-9 on macrophages to reduce the immunogenicity and increase the immune evasion, which could be abrogated by Serine 375 mutation. Based upon these observations, we further developed a bivalent Omicron RBD with S375 mutation and Delta RBD nanoparticle vaccine, which elicited potent and broad neutralizing antibodies in mice, rabbits, and rhesus macaques. Our research suggests that manipulating the Siglec-9 pathway could be a promising approach to enhancing vaccine response. Importantly, our findings suggest that Omicron subvariants have developed a new strategy to evade immune surveillance by impairing the phagocytosis and antigen presentation processes of macrophages.

ORGANISM(S): Mus musculus

PROVIDER: GSE251973 | GEO | 2023/12/28

REPOSITORIES: GEO

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Project description:Next-generation T-cell-directed vaccines for COVID-19 aim to induce durable T-cell immunity against circulating and future hypermutated SARS-CoV-2 variants. Mass Spectrometry (MS)based immunopeptidomics holds promise for guiding vaccine design, but computational challenges impede the precise and unbiased identification of conserved T-cell epitopes crucial for vaccines against rapidly mutating viruses. We introduce a computational framework and analysis platform integrating a novel machine learning algorithm, immunopeptidomics, intra-host data, epitope immunogenicity, and geo-temporal CD8+ T-cell epitope conservation analyses. Central to our approach is MHCvalidator, a novel artificial neural network algorithm enhancing MS-based immunopeptidomics sensitivity by modeling antigen presentation and sequence features. MHCvalidator identified a novel nonconventional SARS-CoV-2 T-cell epitope presented by B7 supertype molecules, originating from a +1-frameshift in a truncated Spike (S) antigen, supported by ribo-seq data. Intra-host analysis of SARS-CoV-2 proteomes from ~100,000 COVID-19 patients revealed a prevalent S antigen truncation in ~51% of cases, exposing a rich source of frameshifted viral antigens. Our framework includes EpiTrack, a new computational pipeline tracking global mutational dynamics of MHCvalidator-identified SARS-CoV-2 CD8+ epitopes from vaccine BNT162b4. While most vaccine-encoded CD8+ epitopes exhibit global conservation from January 2020 to October 2023, a highly immunodominant A*01-associated epitope, especially in hospitalized patients, undergoes substantial mutations in Delta and Omicron variants. Our approach unveils unprecedented SARS-CoV-2 T-cell epitopes, elucidates novel antigenic features, and underscores mutational dynamics of vaccine-relevant epitopes. The analysis platform is applicable to any viruses, and underscores the need for continual vigilance in T-cell vaccine development against the evolving landscape of hypermutating SARS-CoV-2 variants.

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The Receptor Binding Domain of SARS-CoV-2 Omicron Subvariants Targets Siglec-9 to Decrease the Immunogenicity by Preventing Phagocytosis of Macrophages

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