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Journal article

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

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.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1038/s41467-025-61571-x

Authors

More by this author
Institution:
University of Oxford
Division:
MSD
Department:
Paediatrics
Role:
Author
ORCID:
0000-0002-6902-9886
More by this author
Institution:
University of Oxford
Division:
MSD
Department:
Paediatrics
Role:
Author
ORCID:
0000-0003-1701-1390
More by this author
Role:
Author
ORCID:
0000-0003-1781-0053
More by this author
Institution:
University of Oxford
Division:
MSD
Department:
Paediatrics
Role:
Author
ORCID:
0000-0002-0855-2737
More by this author
Institution:
University of Oxford
Division:
MSD
Department:
Paediatrics
Role:
Author


More from this funder
Funder identifier:
https://ror.org/019af4n30
Grant:
115861


Publisher:
Springer Nature
Journal:
Nature Communications More from this journal
Volume:
16
Issue:
1
Article number:
6331
Publication date:
2025-07-09
Acceptance date:
2025-06-25
DOI:
EISSN:
2041-1723


Language:
English
Pubs id:
2243068
Local pid:
pubs:2243068
Deposit date:
2025-07-14
ARK identifier:

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