Evolutionarily smart vaccine strain selection for proactive vaccinology

For viruses, such as SARS-CoV-2, that can change over time to escape immunity, keeping a vaccine up to date, and effective against current variants is a substantial challenge. Circulating viruses are constantly changing and are thus a moving target, that is easy for the variants in the vaccine to fall behind. Before SARS-CoV-2, the only vaccine for which the variants in the vaccine are routinely updated to track the evolution of the virus is the influenza virus vaccine.

For influenza, decades of research and practice have resulted in a WHO assessment and strain recommendation system that functions well, but can still be substantially improved. The equivalent system to influenza vaccine strain selection for SARS-CoV-2 is still in its infancy. Our consortium will build directly on the partners' expertise in both influenza and SARS-CoV-2 to optimize the SARS-CoV-2 vaccine strain selection process to best protect the UK population that is at risk and will continue to be vaccinated against COVID. This project builds on the vaccination strategy outlined in our advisory paper to the UK Government SAGE committee titled 'Setting up medium-and long-term vaccine strain selection and immunity management for SARS-CoV-2'.

To achieve our goals it is necessary to be able to accurately determine 'antigenic' differences among SARS-CoV-2 variants. Antigenic differences are the changes in the virus that result in escape from immunity raised by earlier vaccination or infection. We will test SARS-CoV-2 variants from the UK and around the world to generate, and keep current throughout the project, 'antigenic maps' to determine, at high resolution, the antigenic relationships among SARS-CoV-2 variants. Further, we will horizon-scan and proactively explore how the virus might further evolve using a combination of three methods. 1. Surveillance of UK and global variation in collaboration with the UK Health Security Agency project partner and colleagues world-wide involved in surveillance including the US Centers for Disease Control and US National Institutes of Health. 2. Identifying genetic changes in the virus that reveal early signs of being advantageous by analyzing patterns of parallel evolution in the global sequence surveillance data. 3. Generating in the laboratory variants of the spike protein of the virus (not live virus) with which we experimentally test the antigenic and characteristics of amino acid substitutions ahead of the current evolution.

In combination with this virological surveillance we will also do 'serological surveillance' in which we track the antibody immunity in a cohort of 800 individuals for which we have highly reliable vaccination and infection history from the start of the pandemic and will continue to track during this project. This serological surveillance will allow us to both measure the selection pressure on the virus to escape immunity, and to estimate the population immunity to new variants that might evolve, and thus determine which variants the current population has least immunity to, and thus to which it is most at-risk.

We will then test alternate vaccine strain selection choices to find those that best build immunity in the part of antigenic space that most needs it. There is substantial optimization that can be done here because such vaccination is being done in the context of prior immunity to earlier variants. We will thus select and test vaccine strains using a combination computational models, animal models, and in final stages experimental medicine in humans. This work will be tightly integrated with, and contribute substantially to, the related european, US, and WHO global vaccine strain selection processes.

We will generate, and keep current throughout the project, high resolution antigenic maps to determine the antigenic relationships among SARS-CoV-2 variants. Further, we will horizon-scan and proactively explore antigenic space ahead of the current evolution using a combination of three methods. 1. Surveillance of UK and global variation in collaboration with our UKHSA project partner and colleagues world-wide involved in surveillance including the US CDC and US NIH SAVE consortium. 2. Identifying substitutions showing early signs of selective advantage by analyzing patterns of parallel evolution in the global sequence surveillance data. 3. Deep mutational scanning in which we experimentally test antigenic and other phenotypes of amino acid substitutions ahead of the current evolution. In combination with this virological surveillance we will also do 'serological surveillance' in which we track the antibody landscapes in a cohort of 800 individuals for which we have highly reliable vaccination and infection history from the start of the pandemic and will continue to track during this project. This serological surveillance will allow us to both measure the selection pressure on the virus to escape immunity, and to estimate the population immunity to variants evolving into different parts of antigenic space. We will then test alternate vaccine strain selection choices to find those that best build immunity in the part of antigenic space that most needs it. There is substantial optimization that can be done here because such vaccination is being done in the context of prior immunity to earlier variants. We will thus select and test vaccine strains using a combination computational models, animal models, and in final stages experimental medicine in humans. This work will be tightly integrated with, and contribute substantially to, the related european, US, and WHO global vaccine strain selection processes.