Design and Characterization of a Multistage Peptide-Based Vaccine Platform to Target <i>Mycobacterium tuberculosis</i> Infection
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide The complex immunopathology of Mycobacterium tuberculosis ( Mtb ) is one of the main challenges in developing a novel vaccine against this pathogen, particularly regarding eliciting protection against both active and latent stages. Multistage vaccines, which contain antigens expressed in both phases, represent a promising strategy for addressing this issue, as testified by the tuberculosis vaccine clinical pipeline. Given this approach, we designed and characterized a multistage peptide-based vaccine platform containing CD4+ and CD8+ T cell epitopes previously validated for inducing a relevant T cell response against Mtb . After preliminary screening, CFP10 (32–39), GlfT2 (4–12), HBHA (185–194), and PPE15 (1–15) were selected as promising candidates, and we proved that the PM1 pool of these peptides triggered a T cell response in Mtb -sensitized human peripheral blood mononuclear cells (PBMCs). Taking advantage of the use of thiol-maleimide chemoselective ligation, we synthesized a multiepitope conjugate ( Ac-CGHP ). Our results showed a structure–activity relationship between the conjugation and a higher tendency to fold and assume an ordered secondary structure. Moreover, the palmitoylated conjugate ( Pal-CGHP ) comprising the same peptide antigens was associated with an enhanced cellular uptake in human and murine antigen-presenting cells and a better immunogenicity profile. Immunization study, conducted in BALB/c mice, showed that Pal-CGHP induced a significantly higher T cell proliferation and production of IFNγ and TNFα over PM1 formulated in the Sigma Adjuvant System.
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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) | 0.000 | 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".