Back

Enhanced mucosal B- and T-cell responses against SARS-CoV-2 after heterologous intramuscular mRNA prime/intranasal protein boost vaccination with a combination adjuvant.

Laghlali, G.; Wiest, M. J.; Karada, D.; Warang, P.; O'Konek, J. J.; Chang, L. A.; Park, S.; Farazuddin, M.; Landers, J. J.; Janczak, K. W.; Garcia-Sastre, A.; Baker, J. R.; Wong, P. T.; Schotsaert, M.

2024-03-29 immunology
10.1101/2024.03.28.587260 bioRxiv
Show abstract

Current COVID-19 mRNA vaccines delivered intramuscularly (IM) induce effective systemic immunity, but with suboptimal immunity at mucosal sites, limiting their ability to impart sterilizing immunity. There is strong interest in rerouting immune responses induced in the periphery by parenteral vaccination to the portal entry site of respiratory viruses, such as SARS-CoV-2, by mucosal vaccination. We previously demonstrated the combination adjuvant, NE/IVT, consisting of a nanoemulsion (NE) and an RNA-based RIG-I agonist (IVT) induces potent systemic and mucosal immune responses in protein-based SARS-CoV-2 vaccines administered intranasally (IN). Herein, we demonstrate priming IM with mRNA followed by heterologous IN boosting with NE/IVT adjuvanted recombinant antigen induces strong mucosal and systemic antibody responses and enhances antigen-specific T cell responses in mucosa-draining lymph nodes compared to IM/IM and IN/IN prime/boost regimens. While all regimens induced cross-neutralizing antibodies against divergent variants and sterilizing immunity in the lungs of challenged mice, mucosal vaccination, either as homologous prime/boost or heterologous IN boost after IM mRNA prime was required to impart sterilizing immunity in the upper respiratory tract. Our data demonstrate the benefit of hybrid regimens whereby strong immune responses primed via IM vaccination are rerouted by IN vaccination to mucosal sites to provide optimal protection to SARS-CoV-2.

Matching journals

The top 4 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.