Dataset Information

Computationally Optimized SARS-CoV-2 MHC Class I and II Vaccine Formulations Predicted to Target Human Haplotype Distributions.

ABSTRACT: We present a combinatorial machine learning method to evaluate and optimize peptide vaccine formulations for SARS-CoV-2. Our approach optimizes the presentation likelihood of a diverse set of vaccine peptides conditioned on a target human-population HLA haplotype distribution and expected epitope drift. Our proposed SARS-CoV-2 MHC class I vaccine formulations provide 93.21% predicted population coverage with at least five vaccine peptide-HLA average hits per person (? 1 peptide: 99.91%) with all vaccine peptides perfectly conserved across 4,690 geographically sampled SARS-CoV-2 genomes. Our proposed MHC class II vaccine formulations provide 97.21% predicted coverage with at least five vaccine peptide-HLA average hits per person with all peptides having an observed mutation probability of ? 0.001. We provide an open-source implementation of our design methods (OptiVax), vaccine evaluation tool (EvalVax), as well as the data used in our design efforts here: https://github.com/gifford-lab/optivax.

SUBMITTER: Liu G

PROVIDER: S-EPMC7384425 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

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Computationally Optimized SARS-CoV-2 MHC Class I and II Vaccine Formulations Predicted to Target Human Haplotype Distributions.

Liu Ge G Carter Brandon B Bricken Trenton T Jain Siddhartha S Viard Mathias M Carrington Mary M Gifford David K DK

Cell systems 20200727 2

We present a combinatorial machine learning method to evaluate and optimize peptide vaccine formulations for SARS-CoV-2. Our approach optimizes the presentation likelihood of a diverse set of vaccine peptides conditioned on a target human-population HLA haplotype distribution and expected epitope drift. Our proposed SARS-CoV-2 MHC class I vaccine formulations provide 93.21% predicted population coverage with at least five vaccine peptide-HLA average hits per person (≥ 1 peptide: 99.91%) with all ...[more]

PMID: 32721383

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Project description:Among circulating influenza viruses in humans, H3N2 viruses typically evolve faster than other subtypes and have caused disease in millions of people since emerging in 1968. Computationally optimized broadly reactive antigen (COBRA) technology is one strategy to broaden vaccine-elicited antibody responses among influenza subtypes. In this study, we determined the structural integrity of an H3N2 COBRA hemagglutinin (HA), TJ5, and we probed the antigenic profile of several H3N2 COBRA HAs by assessing recognition of these immunogens by human B cells from seasonally vaccinated human subjects. Of three recently described COBRA H3 HA antigens (TJ5, NG2, and J4), we determined that TJ5 and J4 HA proteins recognize pre-existing B cells more effectively than NG2 HA and a wild-type Hong Kong/4801/2014 protein. We also isolated a panel of 12 H3 HA-specific human monoclonal antibodies (MAbs) and identified that most MAbs recognize both wild-type and COBRA HA proteins and have functional activity against a broad panel of H3N2 viruses. Most MAbs target the receptor-binding site, and one MAb targets the HA stem. MAb TJ5-5 recognizes TJ5 and J4 COBRA HA proteins but has poor recognition of NG2 HA, similar to the global B-cell analysis. We determined a 3.4 Å structure via cryo-electron microscopy of Fab TJ5-5 complexed with the H3 COBRA TJ5, which revealed residues important to the differential binding. Overall, these studies determined that COBRA H3 HA proteins have correct antigenic and structural features, and the proteins are recognized by B cells and MAbs isolated from seasonally vaccinated humans. IMPORTANCE Vaccine development for circulating influenza viruses, particularly for the H3N2 subtype, remains challenging due to consistent antigenic drift. Computationally optimized broadly reactive antigen (COBRA) technology has proven effective for broadening influenza hemagglutinin (HA)-elicited antibody responses compared to wild-type immunogens. Here, we determined the structural features and antigenic profiles of H3 COBRA HA proteins. Two H3 COBRA HA proteins, TJ5 and J4, are better recognized by pre-existing B cells and monoclonal antibodies from the 2017 to 2018 vaccine season compared to COBRA NG2 and a wild-type A/Hong Kong/2014 HA protein. We determined a cryo-electron microscopy (cryo-EM) structure of one MAb that poorly recognizes NG2, MAb TJ5-5, in complex with the TJ5 COBRA HA protein and identified residues critical to MAb recognition. As NG2 is more effective than TJ5 for the recent Hong Kong/2019 virus, these data provide insights into the diminished effectiveness of influenza vaccines across vaccine seasons.

Dataset Information

Computationally Optimized SARS-CoV-2 MHC Class I and II Vaccine Formulations Predicted to Target Human Haplotype Distributions.

Publications

Computationally Optimized SARS-CoV-2 MHC Class I and II Vaccine Formulations Predicted to Target Human Haplotype Distributions.

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