Identification of antibodies induced by immunization with the syphilis vaccine candidate Tp0751
Bibliographic record
Abstract
The continued and increasing prevalence of syphilis worldwide highlights the need for an effective syphilis vaccine to complement public health measures. Previous work demonstrated that immunization of the rabbit animal model with vaccine candidates derived from the T. pallidum endothelial cell adhesin Tp0751 could reduce dissemination of T. pallidum to lymph nodes. In those studies, a proportion of animals exhibited complete inhibition of treponemal dissemination and others exhibited partial or no inhibition of treponemal dissemination, consistent with results expected from an outbred animal model. In the current study we further characterized the Tp0751-specific antibody response in immunized animals that showed inhibition of T. pallidum dissemination. To do this, we generated Tp0751 tetramers to identify Tp0751-specific B cells before and after immunization. Using this approach, we found a robust expansion of Tp0751-specific B cells in the blood and spleens of immunized animals compared to unimmunized control animals. Ten antibodies from Tp0751-immunized rabbits were cloned and binding to specific structural regions of the Tp0751 protein was assessed using epitope mapping assays and structural modeling. Importantly, nine out of the ten antibodies cloned from Tp0751 tetramer-binding B cells were able to significantly inhibit T. pallidum attachment to human endothelial cells in vitro, including antibodies exhibiting weaker binding to Tp0751. Combined, our results provide a proof-of-principle that Tp0751-based subunit vaccines can stimulate strong B cell responses resulting in the production of antibodies able to inhibit T. pallidum attachment to endothelial cells.
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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 | 0.001 | 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".