Intranasal CD40-targeted recombinant MERS-CoV S1 protein is superior to intramuscular immunization in eliciting systemic and mucosal immune responses in mice
Bibliographic record
Abstract
The Middle East respiratory syndrome coronavirus (MERS-CoV) is a global One Health challenge with a potential pandemic threat, with no approved vaccines or antiviral drugs available to date. Thus, there is an urgent need for a safe and effective vaccine. Herein, we developed a recombinant subunit self-adjuvanted fusion protein vaccine targeting the MERS-CoV S1 subunit to CD40-expessing APCs (S1-F/CD40L). We found that intramuscular injection of S1-F/CD40L in conjunction with Alum and CpG was superior to Alum or CpG alone in terms of systemic Ag-specific humoral and cellular responses and Th1-dominant phenotype. Furthermore, the immunogenicity of co-adjuvanted S1-F/CD40L was compared to that of S1 alone via both intramuscular and intranasal immunization. Two intramuscular and intranasal doses of S1-F/CD40L and S1 were immunogenic in eliciting systemic and mucosal humoral and cellular immunity, including IgG, IgA, neutralizing antibodies (nAbs), and T cell responses in mice, with a greater response in the CD40-targeted S1 group. Intranasal vaccination with S1-F/CD40L induced systemic humoral and cellular immune responses comparable to those induced by intramuscular vaccination, including binding and nAbs and T cell responses. Importantly, intranasal vaccine was able to elicit significantly higher local mucosal humoral and cellular immune responses in mouse lungs and markedly elevated circulating IgA levels compared to intramuscular vaccination. Collectively, our results suggest that the S1-F/CD40L vaccine co-adjuvanted with Alum and CpG can be used as an effective and safe mucosal candidate vaccine against MERS-CoV. Furthermore, these data demonstrate that the incorporation of CD40L as APCs targeting ligand and molecular adjuvant enhances immunogenicity, thus offering a promising platform that could be explored further to respond to future emerging pathogens and possible outbreaks.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".