A bivalent ChAd nasal vaccine protects against SARS-CoV-2 BQ.1.1 and XBB.1.5 infection and disease in mice and hamsters.
Baoling YingTamarand L DarlingPritesh DesaiChieh-Yu LiangIgor P DmitrievNadia SoudaniTraci BrickerElena A KashentsevaHouda HarastaniAaron G SchmidtDavid T CurielAdrianus C M BoonMichael S. DiamondPublished in: bioRxiv : the preprint server for biology (2023)
We previously described a nasally delivered monovalent adenoviral-vectored SARS- CoV-2 vaccine (ChAd-SARS-CoV-2-S, targeting Wuhan-1 spike [S]; iNCOVACC®) that is currently used in India as a primary or booster immunization. Here, we updated the mucosal vaccine for Omicron variants by creating ChAd-SARS-CoV-2-BA.5-S, which encodes for a pre- fusion and surface-stabilized S protein of the BA.5 strain, and then tested monovalent and bivalent vaccines for efficacy against circulating variants including BQ.1.1 and XBB.1.5. Whereas monovalent ChAd-vectored vaccines effectively induced systemic and mucosal antibody responses against matched strains, the bivalent ChAd-vectored vaccine elicited greater breadth. However, serum neutralizing antibody responses induced by both monovalent and bivalent vaccines were poor against the antigenically distant XBB.1.5 Omicron strain and did not protect in passive transfer experiments. Nonetheless, nasally delivered bivalent ChAd- vectored vaccines induced robust antibody and spike-specific memory T cell responses in the respiratory mucosa, and conferred protection against WA1/2020 D614G and Omicron variants BQ.1.1 and XBB.1.5 in the upper and lower respiratory tracts of both mice and hamsters. Our data suggest that a nasally delivered bivalent adenoviral-vectored vaccine induces protective mucosal and systemic immunity against historical and emerging SARS-CoV-2 strains without requiring high levels of serum neutralizing antibody.
Keyphrases
- sars cov
- respiratory syndrome coronavirus
- copy number
- escherichia coli
- drug induced
- high glucose
- adipose tissue
- lymph node
- oxidative stress
- diabetic rats
- machine learning
- type diabetes
- big data
- working memory
- electronic health record
- gene expression
- insulin resistance
- endothelial cells
- zika virus
- cancer therapy
- binding protein
- respiratory tract