Rational design of a booster vaccine against COVID-19 based on antigenic distance

Abstract

Current COVID-19 vaccines are highly effective against symptomatic disease, but repeated booster doses using vaccines based on the ancestral strain offer limited additional protection against SARS-CoV-2 variants of concern (VOCs). To address this, we used antigenic distance to in silico select optimized booster vaccine seed strains effective against both current and future VOCs. Our model suggests that a SARS-CoV-1-based booster vaccine has the potential to cover a broader range of VOCs. Candidate vaccines including the spike protein from ancestral SARS-CoV-2, Delta, Omicron (BA.1), SARS-CoV-1, or MERS-CoV were experimentally evaluated in mice following two doses of the BNT162b2 vaccine. The SARS-CoV-1-based booster vaccine outperformed other candidates in terms of neutralizing antibody breadth and duration, as well as protective activity against Omicron (BA.2) challenge. This study suggests a unique strategy for selecting booster vaccines based on antigenic distance, which may be useful in designing future booster vaccines as new SARS-CoV-2 variants emerge.

Keywords: COVID-19; Omicron; SARS-CoV-1; SARS-CoV-2 variants; antigenic cartography; antigenic distance; antigenic field; booster vaccine; immune imprinting; vaccine seed strain selection.