Beta Spike-Presenting SARS-CoV-2 Virus-like Particle Vaccine Confers Broad Protection against Other VOCs in Mice
Bibliographic record
Abstract
Virus-like particles (VLPs) are non-infectious and serve as promising vaccine platforms because they mimic the membrane-embedded conformations of fusion glycoproteins on native viruses. Here, we employed SARS-CoV-2 VLPs (SMEN) presenting ancestral, Beta, or Omicron spikes to identify the variant spike that elicits potent and cross-protective immune responses in the highly sensitive K18-hACE2 challenge mouse model. A combined intranasal and intramuscular SMEN vaccine regimen generated the most effective immune responses to significantly reduce disease burden. Protection was primarily mediated by antibodies, with minor but distinct contributions from T cells in reducing virus spread and inflammation. Immunization with SMEN carrying ancestral spike resulted in 100, 75, or 0% protection against ancestral, Delta, or Beta variant-induced mortality, respectively. However, SMEN with an Omicron spike provided only limited protection against ancestral (50%), Delta (0%), and Beta (25%) challenges. By contrast, SMEN with Beta spikes offered 100% protection against the variants used in this study. Thus, the Beta variant not only overcame the immunity produced by other variants, but the Beta spike also elicited diverse and effective humoral immune responses. Our findings suggest that leveraging the Beta variant spike protein can enhance SARS-CoV-2 immunity, potentially leading to a more comprehensive vaccine against emerging variants.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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".