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Dynamic SARS-CoV-2 emergence algorithm for rationally-designed logical next-generation vaccines.

ABSTRACT: SARS-CoV-2 worldwide spread and evolution has resulted in variants containing mutations resulting in immune evasive epitopes that decrease vaccine efficacy. We acquired SARS-CoV-2 positive clinical samples and compared the worldwide emerged spike mutations from Variants of Concern/Interest, and developed an algorithm for monitoring the evolution of SARS-CoV-2 in the context of vaccines and monoclonal antibodies. The algorithm partitions logarithmic-transformed prevalence data monthly and Pearson's correlation determines exponential emergence of amino acid substitutions (AAS) and lineages. The SARS-CoV-2 genome evaluation indicated 49 mutations, with 44 resulting in AAS. Nine of the ten most worldwide prevalent (>70%) spike protein changes have Pearson's coefficient r > 0.9. The tenth, D614G, has a prevalence >99% and r-value of 0.67. The resulting algorithm is based on the patterns these ten substitutions elucidated. The strong positive correlation of the emerged spike protein changes and algorithmic predictive value can be harnessed in designing vaccines with relevant immunogenic epitopes. Monitoring, next-generation vaccine design, and mAb clinical efficacy must keep up with SARS-CoV-2 evolution, as the virus is predicted to remain endemic.

SUBMITTER: Maison DP

PROVIDER: S-EPMC9550860 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature

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Dynamic SARS-CoV-2 emergence algorithm for rationally-designed logical next-generation vaccines.

Maison David P DP Ching Lauren L LL Cleveland Sean B SB Tseng Alanna C AC Nakano Eileen E Shikuma Cecilia M CM Nerurkar Vivek R VR

Communications biology 20221010 1

SARS-CoV-2 worldwide spread and evolution has resulted in variants containing mutations resulting in immune evasive epitopes that decrease vaccine efficacy. We acquired SARS-CoV-2 positive clinical samples and compared the worldwide emerged spike mutations from Variants of Concern/Interest, and developed an algorithm for monitoring the evolution of SARS-CoV-2 in the context of vaccines and monoclonal antibodies. The algorithm partitions logarithmic-transformed prevalence data monthly and Pearson ...[more]

PMID: 36217024

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Project description:Influenza virus vaccine production is currently limited by the ability to grow circulating human strains in chicken eggs or in cell culture. To facilitate cost-effective growth, vaccine strains are serially passaged under production conditions, which frequently results in mutations of the major antigenic protein, the viral hemagglutinin (HA). Human vaccination with an antigenically drifted strain is known to contribute to poor vaccine efficacy. To address this problem, we developed a replication-competent influenza A virus (IAV) with an artificial genomic organization that allowed the incorporation of two independent and functional HA proteins with different growth requirements onto the same virion. Vaccination with these viruses induced protective immunity against both strains from which the HA proteins were derived, and the magnitude of the response was as high as or higher than vaccination with either of the monovalent parental strains alone. Dual-HA viruses also displayed remarkable antigenic stability; even when using an HA protein known to be highly unstable during growth in eggs, we observed high-titer virus amplification without a single adaptive mutation. Thus, the viral genomic design described in this work can be used to grow influenza virus vaccines to high titers without introducing antigenic mutations.IMPORTANCE Influenza A virus (IAV) is a major public health threat, and vaccination is currently the best available strategy to prevent infection. While there have been many advances in influenza vaccine production, the fact that we cannot predict the growth characteristics of a given strain under vaccine production conditions a priori introduces fundamental uncertainty into the process. Clinically relevant IAV strains frequently grow poorly under vaccine conditions, and this poor growth can result in the delay of vaccine production or the exchange of the recommended strain for one with favorable growth properties. Even in strains that grow to high titers, adaptive mutations in the antigenic protein hemagglutinin (HA) that make it antigenically dissimilar to the circulating strain are common. The genomic restructuring of the influenza virus described in this work offers a solution to the problem of uncertain or unstable growth of IAV during vaccine production.

Project description:SARS-CoV-2 has caused the COVID-19 pandemic, with over 673 million infections and 6.85 million deaths globally. Novel mRNA and viral-vectored vaccines were developed and licensed for global immunizations under emergency approval. They have demonstrated good safety and high protective efficacy against the SARS-CoV-2 Wuhan strain. However, the emergence of highly infectious and transmissible variants of concern (VOCs) such as Omicron was associated with considerable reductions in the protective efficacy of the current vaccines. The development of next-generation vaccines that could confer broad protection against both the SARS-CoV-2 Wuhan strain and VOCs is urgently needed. A bivalent mRNA vaccine encoding the Spike proteins of both the SARS-CoV-2 Wuhan strain and the Omicron variant has been constructed and approved by the US FDA. However, mRNA vaccines are associated with instability and require an extremely low temperature (-80 °C) for storage and transportation. They also require complex synthesis and multiple chromatographic purifications. Peptide-based next-generation vaccines could be developed by relying on in silico predictions to identify peptides specifying highly conserved B, CD4+ and CD8+ T cell epitopes to elicit broad and long-lasting immune protection. These epitopes were validated in animal models and in early phase clinical trials to demonstrate immunogenicity and safety. Next-generation peptide vaccine formulations could be developed to incorporate only naked peptides, but they are costly to synthesize and production would generate extensive chemical waste. Continual production of recombinant peptides specifying immunogenic B and T cell epitopes could be achieved in hosts such as E. coli or yeast. However, recombinant protein/peptide vaccines require purification before administration. The DNA vaccine might serve as the most effective next-generation vaccine for low-income countries, since it does not require an extremely low temperature for storage or need extensive chromatographic purification. The construction of recombinant plasmids carrying genes specifying highly conserved B and T cell epitopes meant that vaccine candidates representing highly conserved antigenic regions could be rapidly developed. Poor immunogenicity of DNA vaccines could be overcome by the incorporation of chemical or molecular adjuvants and the development of nanoparticles for effective delivery.

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Dynamic SARS-CoV-2 emergence algorithm for rationally-designed logical next-generation vaccines.

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Dynamic SARS-CoV-2 emergence algorithm for rationally-designed logical next-generation vaccines.

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