Characterization of Systemic and Mucosal Humoral Immune Responses to an Adjuvanted Intranasal SARS-CoV-2 Protein Subunit Vaccine Candidate in Mice
Bibliographic record
Abstract
Continuous viral evolution of SARS-CoV-2 has resulted in variants capable of immune evasion, vaccine breakthrough infections and increased transmissibility. New vaccines that invoke mucosal immunity may provide a solution to reducing virus transmission. Here, we evaluated the immunogenicity of intranasally administered subunit protein vaccines composed of a stabilized SARS-CoV-2 spike trimer or the receptor binding domain (RBD) adjuvanted with either cholera toxin (CT) or an archaeal lipid mucosal adjuvant (AMVAD). We show robust induction of immunoglobulin (Ig) G and IgA responses in plasma, nasal wash and bronchoalveolar lavage in mice only when adjuvant is used in the vaccine formulation. While the AMVAD adjuvant was more effective at inducing systemic antibodies against the RBD antigen than CT, CT was generally more effective at inducing overall higher IgA and IgG titers against the spike antigen in both systemic and mucosal compartments. Furthermore, vaccination with adjuvanted spike led to superior mucosal IgA responses than with the RBD antigen and produced broadly targeting neutralizing plasma antibodies against ancestral, Delta and Omicron variants in vitro; whereas adjuvanted RBD elicited a narrower antibody response with neutralizing activity only against ancestral and Delta variants. Our study demonstrates that intranasal administration of an adjuvanted protein subunit vaccine in immunologically naïve mice induced both systemic and mucosal neutralizing antibody responses that were most effective at neutralizing SARS-CoV-2 variants when the trimeric spike was used as an antigen compared to RBD.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".