Strong TCR Conservation and Altered T Cell Cross-Reactivity Characterize a B*57-Restricted Immune Response in HIV-1 Infection
Bibliographic record
Abstract
HLA-B*57 is associated with slower disease progression to AIDS, and CD8+ T cell responses to B*57-restricted epitopes are thought to contribute to this protective effect. In this study, we evaluate the B*57-restricted p24 KAFSPEVIPMF (KF11) immune response which is immunodominant during chronic infection. Previously, we observed that the KF11 clade variants KGFNPEVIPMF [A2G,S4N] and KAFNPEIIMPF [S4N,V7I], sharing a position 4 mutation, are differentially recognized by KF11-specific T cells. By combining structural and cellular studies, we now demonstrate that the KF11 and [A2G,S4N] epitopes induce distinct functional responses in [A2G,S4N] and KF11-specific T cells, respectively, despite minimal structural differences between the individual B*57-peptide complexes. Recently, we also elucidated the highly distinct structure of KF11 in complex with B*5703, and have now characterized the CD8+ T cell repertoire recognizing this epitope. We now report striking features of TCR conservation both in terms of TCR Valpha and Vbeta chain usage, and throughout the hypervariable region. Collectively, our findings highlight unusual features of the B*5701/B*5703-KF11-specific immune responses which could influence disease progression and that might be important to consider when designing future vaccine regimens.
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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) | 0.001 | 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".