Prediction and characterisation of the human B cell response to a heterologous two-dose Ebola vaccine

Daniel O’Connor (), Elizabeth A. Clutterbuck, Malick M. Gibani, Sagida Bibi, Katherine A. Sanders, Rebecca Makinson, Dominic F. Kelly and Andrew J. Pollard
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Daniel O’Connor: University of Oxford
Elizabeth A. Clutterbuck: University of Oxford
Malick M. Gibani: St Mary’s Campus
Sagida Bibi: University of Oxford
Katherine A. Sanders: University of Oxford
Rebecca Makinson: NIHR Oxford Biomedical Research Centre
Dominic F. Kelly: University of Oxford
Andrew J. Pollard: University of Oxford

Nature Communications, 2025, vol. 16, issue 1, 1-15

Abstract: Abstract Ebola virus disease (EVD) outbreaks are increasing, posing significant threats to affected communities. Effective outbreak management depends on protecting frontline health workers, a key focus of EVD vaccination strategies. IgG specific to the viral glycoprotein serves as the correlate of protection for recent vaccine licensures. Using advanced cellular and transcriptomic analyses, we examined B cell responses to the Ad26.ZEBOV, MVA-BN-Filo EVD vaccine. Our findings reveal robust plasma cell and lasting B cell memory responses post-vaccination. Machine-learning models trained on blood gene expression predicted antibody response magnitude. Notably, we identified a unique B cell receptor CDRH3 sequence post-vaccination resembling known Orthoebolavirus zairense (EBOV) glycoprotein-binding antibodies. Single-cell analyses further detailed changes in plasma cell frequency, subclass usage, and CDRH3 properties. These results highlight the predictive power of early immune responses, captured through systems immunology, in shaping vaccine-induced B cell immunity.

Date: 2025
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DOI: 10.1038/s41467-025-61571-x

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