CD8+ T cells cross-restricted by HLA-B*57 and HLA-E*01 recognize HIV Gag with different functional profiles
Bibliographic record
Abstract
Few HIV-specific epitopes restricted by non-classical HLA-E have been described, and even less is known about the functional profile of responding CD8+ T cells (CD8s). This study evaluates the functional characteristics of CD8s targeting the Gag epitope KF11 (KAFSPEVIPMF) restricted by either HLA-E (E-CD8s) or HLA-B57 (B57-CD8s). CD8s from 8 people with HIV (PWH) were cocultured with KF11 peptide presented by cell lines expressing HLA-B*57:01, HLA-E*01:01, or HLA-E*01:03. CD8 responses were analyzed using single-cell RNA and TCR sequencing. Supernatants were also assessed for soluble protein profiling. HLA-I multimers were developed to identify CD8s restricted by HLA-B57 and/or HLA-E ex vivo. B57-CD8s secreted higher levels of cytotoxic cytokines such as IFN-γ, whereas E-CD8s produced more chemotactic cytokines, including RANTES, CXCL10 (IP-10), and IL-27, findings that were corroborated through single-cell RNA sequencing. TCR clonotypes stimulated by KF11 were cross-restricted by HLA-B*57 and HLA-E*01:03 as demonstrated by in vitro T cell reporter assays and ex vivo multimer screening. Ex vivo CD8s were singly restricted by HLA-B57 and HLA-E, with dual restriction only observed in PWH with lower viral load. These findings demonstrate that certain HIV-specific CD8s in PWH exhibit dual restriction by HLA-B*57 and HLA-E*01:03, leading to functionally distinct immune responses depending on the restricting allele(s).
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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) | 0.003 | 0.001 |
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".