Harnessing the Activation of Toll-Like Receptor 2/6 by Self-Assembled Cross-β Fibrils to Design Adjuvanted Nanovaccines
Bibliographic record
Abstract
Protein fibrils characterized with a cross-β-sheet quaternary structure have gained interest as nanomaterials in biomedicine, including in the design of subunit vaccines. Recent studies have shown that by conjugating an antigenic determinant to a self-assembling β-peptide, the resulting supramolecular assemblies act as an antigen delivery system that potentiates the epitope-specific immune response. In this study, we used a ten-mer self-assembling sequence (I10) derived from an amyloidogenic peptide to biophysically and immunologically characterize a nanofibril-based vaccine against the influenza virus. The highly conserved epitope from the ectodomain of the matrix protein 2 (M2e) was elongated at the N-terminus of I10 by solid phase peptide synthesis. The chimeric M2e-I10 peptide readily self-assembled into unbranched, long, and twisted fibrils with a diameter between five and eight nm. These cross-β nanoassemblies were cytocompatible and activated the heterodimeric Toll-like receptor (TLR) 2/6. Upon mice subcutaneous immunization, M2e-fibrils triggered a robust anti-M2e specific immune response, which was dependent on self-assembly and did not require the use of an adjuvant. Overall, this study describes the efficacy of cross-β fibrils to activate the TLR 2/6 and to stimulate the epitope-specific immune response, supporting usage of these proteinaceous assemblies as a self-adjuvanted delivery system for antigens.
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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 | 0.000 |
| 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".