Comparison of a SARS-CoV-2 mRNA booster immunization containing additional antigens to a spike-based mRNA vaccine against Omicron BA.5 infection in hACE2 mice
Bibliographic record
Abstract
The emergence of SARS-CoV-2 variants presents challenges to vaccine effectiveness, underlining the necessity for next-generation vaccines with multiple antigens beyond the spike protein. Here, we investigated a multiantigenic booster containing spike and a chimeric construct composed of nucleoprotein (N) and membrane (M) proteins, comparing its efficacy to a spike-only booster against Omicron BA.5 in K18-hACE2 mice. Initially, mice were primed and boosted with Beta (B.1.351) spike-only mRNA, showing strong spike-specific T cell responses and neutralizing antibodies, albeit with limited cross-neutralization to Omicron variants. Subsequently, a spike-NM multiantigenic vaccine was then examined as a second booster dose for protection in hACE2-transgenic mice. Mice receiving either homologous spike-only or heterologous spike-NM booster had nearly complete inhibition of infectious virus shedding in oral swabs and reduced viral burdens in both lung and nasal tissues following BA.5 challenge. Examination of lung pathology further revealed that both spike-only and spike-NM boosters provided comparable protection against inflammatory infiltrates and fibrosis. Moreover, the spike-NM booster demonstrated neutralization efficacy in a pseudovirus assay against Wuhan-Hu-1, Beta, and Omicron variants akin to the spike-only booster. These findings indicate that supplementing spike with additional SARS-CoV-2 targets in a booster immunization confers equivalent immunity and protection against Omicron BA.5. This work highlights a promising strategy for individuals previously vaccinated with spike-only vaccines, potentially offering enhanced protection against emerging coronaviruses.
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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".