Engineering filamentous phage as carriers that focus antibody responses against a peptide (47.11)
Bibliographic record
Abstract
Abstract Antibody (Ab) responses to a B-cell epitope can be produced by immunization with a peptide bearing the epitope of interest. Such peptides are often poor immunogens, requiring conjugation or fusion to carrier proteins that provide T-cell help. However, carrier proteins may also divert the Ab response away from the targeted peptide via its own B-cell epitopes. Thus, an ideal peptide carrier should provide T-cell help to drive B-cell responses but contain relatively few B-cell epitopes. The Ab response to filamentous phage is restricted to the 12 N-terminal residues of the major coat protein (pVIII) and the external domains of the minor coat protein, pIII. Previously, we reported that the Ab response against a synthetic peptide conjugated to phage was more focused on the peptide compared to ovalbumin as the carrier. In some cases, the anti-peptide Ab titer exceeded the anti-carrier Ab titer by > 20 fold. The reduced complexity of the phage surface compared to ovalbumin’s may be responsible for this. Here, we tested the hypothesis that Ab responses to weakly immunogenic peptides would be improved by removing immunodominant epitopes from the phage surface; immunogenic residues on pVIII were altered, and the external domains of pIII were truncated. The phage were tested alone as immunogens, and as carriers for pVIII-displayed peptides. The results and the implication for vaccine design are discussed. Supported by NIH R01AI-49111
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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) | 0.000 | 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) | 0.000 | 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 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".