Pentamers Not Found in the Universal Proteome Can Enhance Antigen Specific Immune Responses and Adjuvant Vaccines
Bibliographic record
Abstract
Certain short peptides do not occur in humans and are rare or non-existent in the universal proteome. Antigens that contain rare amino acid sequences are in general highly immunogenic and may activate different arms of the immune system. We first generated a list of rare, semi-common, and common 5-mer peptides using bioinformatics tools to analyze the UniProtKB database. Experimental observations indicated that rare and semi-common 5-mers generated stronger cellular responses in comparison with common-occurring sequences. We hypothesized that the biological process responsible for this enhanced immunogenicity could be used to positively modulate immune responses with potential application for vaccine development. Initially, twelve rare 5-mers, 9-mers, and 13-mers were incorporated in frame at the end of an H5N1 hemagglutinin (HA) antigen and expressed from a DNA vaccine. The presence of some 5-mer peptides induced improved immune responses. Adding one 5-mer peptide exogenously also offered improved clinical outcome and/or survival against a lethal H5N1 or H1N1 influenza virus challenge in BALB/c mice and ferrets, respectively. Interestingly, enhanced anti-HBsAg antibody production by up to 25-fold in combination with a commercial Hepatitis B vaccine (Engerix-B, GSK) was also observed in BALB/c mice. Mechanistically, NK cell activation and dependency was observed with enhancing peptides ex vivo and in NK-depleted mice. Overall, the data suggest that rare or non-existent oligopeptides can be developed as immunomodulators and supports the further evaluation of some 5-mer peptides as potential vaccine adjuvants.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 | 0.000 |
| 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 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".