The T-cell-directed vaccine BNT162b4 encoding conserved non-spike antigens protects animals from severe SARS-CoV-2 infection

T-cell responses play an important role in protection against beta-coronavirus infections, including SARS-CoV-2, where they associate with decreased COVID-19 disease severity and duration. To enhance T-cell immunity across epitopes infrequently altered in SARS-CoV-2 variants, we designed BNT162b4, an mRNA vaccine component which is intended to be combined with BNT162b2, the spike-protein-encoding vaccine. BNT162b4 encodes variant-conserved, immunogenic segments of the SARS-CoV-2 nucleocapsid, membrane, and ORF1ab proteins, targeting diverse HLA alleles. BNT162b4 elicits polyfunctional CD4+ and CD8+ T-cell responses from diverse epitopes in animal models, alone or when co-administered with BNT162b2 while preserving spike-specific immunity. Importantly, we demonstrate that BNT162b4 protects hamsters from severe disease and reduces viral titers following challenge with viral variants. These data suggest that a combination of BNT162b2 and BNT162b4 could reduce COVID-19 disease severity and duration caused by circulating or future variants. BNT162b4 is currently being clinically evaluated in combination with the BA.4/BA.5 Omicron-updated bivalent BNT162b2 (NCT05541861). Graphical Adding non-spike targeting components to mRNA vaccination elicits promising T cell responses against SARS-CoV-2 variant strains in rodent models of COVID-19

Early computational detection of potential high-risk SARS-CoV-2 variants.

The ongoing COVID-19 pandemic is leading to the discovery of hundreds of novel SARS-CoV-2 variants daily. While most variants do not impact the course of the pandemic, some variants pose an increased risk when the acquired mutations allow better evasion of antibody neutralisation or increased transmissibility. Early detection of such high-risk variants (HRVs) is paramount for the proper management of the pandemic. However, experimental assays to determine immune evasion and transmissibility characteristics of new variants are resource-intensive and time-consuming, potentially leading to delays in appropriate responses by decision makers. Presented herein is a novel in silico approach combining spike (S) protein structure modelling and large protein transformer language models on S protein sequences to accurately rank SARS-CoV-2 variants for immune escape and fitness potential. Both metrics were experimentally validated using in vitro pseudovirus-based neutralisation test and binding assays and were subsequently combined to explore the changing landscape of the pandemic and to create an automated Early Warning System (EWS) capable of evaluating new variants in minutes and risk-monitoring variant lineages in near real-time. The system accurately pinpoints the putatively dangerous variants by selecting on average less than 0.3% of the novel variants each week. The EWS flagged all 16 variants designated by the World Health Organization (WHO) as variants of interest (VOIs) if applicable or variants of concern (VOCs) otherwise with an average lead time of more than one and a half months ahead of their designation as such.

Early computational detection of potential high-risk SARS-CoV-2 variants

The ongoing COVID-19 pandemic is leading to the discovery of hundreds of novel SARS-CoV-2 variants daily. While most variants do not impact the course of the pandemic, some variants pose an increased risk when the acquired mutations allow better evasion of antibody neutralisation or increased transmissibility. Early detection of such high-risk variants (HRVs) is paramount for the proper management of the pandemic. However, experimental assays to determine immune evasion and transmissibility characteristics of new variants are resource-intensive and time-consuming, potentially leading to delays in appropriate responses by decision makers. Presented herein is a novel in silico approach combining spike (S) protein structure modelling and large protein transformer language models on S protein sequences to accurately rank SARS-CoV-2 variants for immune escape and fitness potential. Both metrics were experimentally validated using in vitro pseudovirus-based neutralisation test and binding assays and were subsequently combined to explore the changing landscape of the pandemic and to create an automated Early Warning System (EWS) capable of evaluating new variants in minutes and risk-monitoring variant lineages in near real-time. The system accurately pinpoints the putatively dangerous variants by selecting on average less than 0.3% of the novel variants each week. The EWS flagged all 16 variants designated by the World Health Organisation (WHO) as variants of interest (VOIs) if applicable or variants of concern (VOCs) otherwise with an average lead time of more than one and a half months ahead of their designation as such.

A universal MHCII technology platform to characterize antigen-specific CD4+ T cells.

CD4+ T cells are critical to the immune system and perform multiple functions; therefore, their identification and characterization are crucial to better understanding the immune system in both health and disease states. However, current methods rarely preserve their ex vivo phenotype, thus limiting our understanding of their in vivo functions. Here we introduce a flexible, rapid, and robust platform for ex vivo CD4+ T cell identification. By combining MHCII allele purification, allele-independent peptide loading, and multiplexed flow cytometry technologies, we can enable high-throughput personalized CD4+ T cell identification, immunophenotyping, and sorting. Using this platform in combination with single-cell sorting and multimodal analyses, we identified and characterized antigen-specific CD4+ T cells relevant to COVID-19 and cancer neoantigen immunotherapy. Overall, our platform can be used to detect and characterize CD4+ T cells across multiple diseases, with potential to guide CD4+ T cell epitope design for any disease-specific immunization strategy.

Neutralization of SARS-CoV-2 Omicron by BNT162b2 mRNA vaccine-elicited human sera.

The globally circulating severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variant of concern Omicron (B.1.1.529) has a large number of mutations, especially in the spike protein, indicating that recognition by neutralizing antibodies may be compromised. We tested Wuhan (Wuhan-Hu-1 reference strain), Beta (B.1.351), Delta (B.1.617.2), or Omicron pseudoviruses with sera of 51 participants who received two or three doses of the messenger RNA (mRNA)-based COVID-19 vaccine BNT162b2. After two doses, Omicron-neutralizing titers were reduced >22-fold compared with Wuhan-neutralizing titers. One month after the third vaccine dose, Omicron-neutralizing titers were increased 23-fold relative to their levels after two doses and were similar to levels of Wuhan-neutralizing titers after two doses. The requirement of a third vaccine dose to effectively neutralize Omicron was confirmed with sera from a subset of participants using live SARS-CoV-2. These data suggest that three doses of the mRNA vaccine BNT162b2 may protect against Omicron-mediated COVID-19.

BNT162b2 vaccine induces neutralizing antibodies and poly-specific T cells in humans.

BNT162b2, a nucleoside-modified mRNA formulated in lipid nanoparticles that encodes the SARS-CoV-2 spike glycoprotein (S) stabilized in its prefusion conformation, has demonstrated 95% efficacy in preventing COVID-191. Here we extend a previous phase-I/II trial report2 by presenting data on the immune response induced by BNT162b2 prime-boost vaccination from an additional phase-I/II trial in healthy adults (18-55 years old). BNT162b2 elicited strong antibody responses: at one week after the boost, SARS-CoV-2 serum geometric mean 50% neutralizing titres were up to 3.3-fold above those observed in samples from individuals who had recovered from COVID-19. Sera elicited by BNT162b2 neutralized 22 pseudoviruses bearing the S of different SARS-CoV-2 variants. Most participants had a strong response of IFNγ+ or IL-2+ CD8+ and CD4+ T helper type 1 cells, which was detectable throughout the full observation period of nine weeks following the boost. Using peptide-MHC multimer technology, we identified several BNT162b2-induced epitopes that were presented by frequent MHC alleles and conserved in mutant strains. One week after the boost, epitope-specific CD8+ T cells of the early-differentiated effector-memory phenotype comprised 0.02-2.92% of total circulating CD8+ T cells and were detectable (0.01-0.28%) eight weeks later. In summary, BNT162b2 elicits an adaptive humoral and poly-specific cellular immune response against epitopes that are conserved in a broad range of variants, at well-tolerated doses.

Sequence-based prediction of SARS-CoV-2 vaccine targets using a mass spectrometry-based bioinformatics predictor identifies immunogenic T cell epitopes.

BACKGROUND: The ongoing COVID-19 pandemic has created an urgency to identify novel vaccine targets for protective immunity against SARS-CoV-2. Early reports identify protective roles for both humoral and cell-mediated immunity for SARS-CoV-2. METHODS: We leveraged our bioinformatics binding prediction tools for human leukocyte antigen (HLA)-I and HLA-II alleles that were developed using mass spectrometry-based profiling of individual HLA-I and HLA-II alleles to predict peptide binding to diverse allele sets. We applied these binding predictors to viral genomes from the Coronaviridae family and specifically focused on T cell epitopes from SARS-CoV-2 proteins. We assayed a subset of these epitopes in a T cell induction assay for their ability to elicit CD8+ T cell responses. RESULTS: We first validated HLA-I and HLA-II predictions on Coronaviridae family epitopes deposited in the Virus Pathogen Database and Analysis Resource (ViPR) database. We then utilized our HLA-I and HLA-II predictors to identify 11,897 HLA-I and 8046 HLA-II candidate peptides which were highly ranked for binding across 13 open reading frames (ORFs) of SARS-CoV-2. These peptides are predicted to provide over 99% allele coverage for the US, European, and Asian populations. From our SARS-CoV-2-predicted peptide-HLA-I allele pairs, 374 pairs identically matched what was previously reported in the ViPR database, originating from other coronaviruses with identical sequences. Of these pairs, 333 (89%) had a positive HLA binding assay result, reinforcing the validity of our predictions. We then demonstrated that a subset of these highly predicted epitopes were immunogenic based on their recognition by specific CD8+ T cells in healthy human donor peripheral blood mononuclear cells (PBMCs). Finally, we characterized the expression of SARS-CoV-2 proteins in virally infected cells to prioritize those which could be potential targets for T cell immunity. CONCLUSIONS: Using our bioinformatics platform, we identify multiple putative epitopes that are potential targets for CD4+ and CD8+ T cells, whose HLA binding properties cover nearly the entire population. We also confirm that our binding predictors can predict epitopes eliciting CD8+ T cell responses from multiple SARS-CoV-2 proteins. Protein expression and population HLA allele coverage, combined with the ability to identify T cell epitopes, should be considered in SARS-CoV-2 vaccine design strategies and immune monitoring.