tetano
Editor, Senior Moderator
Cell Rep Methods
. 2026 Jun 29:101508.
doi: 10.1016/j.crmeth.2026.101508. Online ahead of print.
A computational method to design broad-spectrum T cell-inducing vaccines applied to Betacoronaviruses
Phil Palmer[SUP] 1 [/SUP], Sofiya Fedosyuk[SUP] 2 [/SUP], Srivatsan Parthasarathy[SUP] 2 [/SUP], Jonathan Holbrook[SUP] 2 [/SUP], Charlotte George[SUP] 1 [/SUP], Laura O'Reilly[SUP] 1 [/SUP], Lara Wiegand[SUP] 3 [/SUP], George William Carnell[SUP] 4 [/SUP], Jonathan Luke Heeney[SUP] 5 [/SUP], Sneha Vishwanath[SUP] 6 [/SUP]
Affiliations
Antigenically diverse pathogens such as coronaviruses pose substantial global health threats, highlighting the need for broad-spectrum vaccines. Here, we introduce Spectravax, a computational method that designs broad-spectrum vaccines accounting for genetic diversity in both 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 identified the MERS-CoV N epitopes responsible for Spectravax's cross-reactivity, advancing the rational design of broad-spectrum vaccines for pandemic preparedness.
Keywords: Betacoronaviruses; CP: computational biology; CP: immunology; HLA diversity; MERS-CoV; SARS-CoV-2; T cell vaccines; antigen design; artificial intelligence; broad-spectrum vaccines; computational vaccine design; cross-reactive immunity; epitope prediction; immunoinformatics; nucleocapsid protein; pandemic preparedness; population coverage.
. 2026 Jun 29:101508.
doi: 10.1016/j.crmeth.2026.101508. Online ahead of print.
A computational method to design broad-spectrum T cell-inducing vaccines applied to Betacoronaviruses
Phil Palmer[SUP] 1 [/SUP], Sofiya Fedosyuk[SUP] 2 [/SUP], Srivatsan Parthasarathy[SUP] 2 [/SUP], Jonathan Holbrook[SUP] 2 [/SUP], Charlotte George[SUP] 1 [/SUP], Laura O'Reilly[SUP] 1 [/SUP], Lara Wiegand[SUP] 3 [/SUP], George William Carnell[SUP] 4 [/SUP], Jonathan Luke Heeney[SUP] 5 [/SUP], Sneha Vishwanath[SUP] 6 [/SUP]
Affiliations
- PMID: 42372721
- DOI: 10.1016/j.crmeth.2026.101508
Antigenically diverse pathogens such as coronaviruses pose substantial global health threats, highlighting the need for broad-spectrum vaccines. Here, we introduce Spectravax, a computational method that designs broad-spectrum vaccines accounting for genetic diversity in both 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 identified the MERS-CoV N epitopes responsible for Spectravax's cross-reactivity, advancing the rational design of broad-spectrum vaccines for pandemic preparedness.
Keywords: Betacoronaviruses; CP: computational biology; CP: immunology; HLA diversity; MERS-CoV; SARS-CoV-2; T cell vaccines; antigen design; artificial intelligence; broad-spectrum vaccines; computational vaccine design; cross-reactive immunity; epitope prediction; immunoinformatics; nucleocapsid protein; pandemic preparedness; population coverage.