Covering All Bases: A Computational Method to Design Broad-spectrum T-cell-inducing Vaccines Applied to Betacoronaviruses

Abstract

Antigenically diverse pathogens, such as coronaviruses, pose substantial threats to global health. This highlights the need for effective broad-spectrum vaccines that elicit robust immune responses in a large proportion of the human population against a wide array of pathogen variants. Here, we introduce Spectravax, an AI-enabled computational method to design broad-spectrum vaccines that account for genetic diversity in both the host and pathogen populations. Using Spectravax, we designed a nucleocapsid (N) antigen to elicit cross-reactive immune responses to viruses from the Sarbecovirus and Merbecovirus subgenera of Betacoronaviruses. In silico analyses demonstrated superior predicted host and pathogen coverage for Spectravax compared to wild-type sequences and existing computational designs. Experimental validation in mice supported these predictions: Spectravax N elicited robust immune responses to SARS-CoV, SARS-CoV-2, and MERS-CoV--the three coronaviruses responsible for major outbreaks in humans since 2002--while wild-type and existing computational designs elicited limited responses. Furthermore, we were able to identify the MERS-CoV N epitopes responsible for Spectravaxs cross-reactivity. Thus, we advance the rational design of broad-spectrum vaccines for pandemic preparedness.