HLA Peptide Length Preferences Control CD8+ T Cell Responses
Bibliographic record
Abstract
Class I HLAs generally present peptides of 8-10 aa in length, although it is unclear whether peptide length preferences are affected by HLA polymorphism. In this study, we investigated the CD8(+) T cell response to the BZLF1 Ag of EBV, which includes overlapping sequences of different size that nevertheless conform to the binding motif of the large and abundant HLA-B*44 supertype. Whereas HLA-B*18:01(+) individuals responded strongly and exclusively to the octamer peptide (173)SELEIKRY(180), HLA-B*44:03(+) individuals responded to the atypically large dodecamer peptide (169)EECDSELEIKRY(180), which encompasses the octamer peptide. Moreover, the octamer peptide bound more stably to HLA-B*18:01 than did the dodecamer peptide, whereas, conversely, HLA-B*44:03 bound only the longer peptide. Furthermore, crystal structures of these viral peptide-HLA complexes showed that the Ag-binding cleft of HLA-B*18:01 was more ideally suited to bind shorter peptides, whereas HLA-B*44:03 exhibited characteristics that favored the presentation of longer peptides. Mass spectrometric identification of > 1000 naturally presented ligands revealed that HLA-B*18:01 was more biased toward presenting shorter peptides than was HLA-B*44:03. Collectively, these data highlight a mechanism through which polymorphism within an HLA class I supertype can diversify determinant selection and immune responses by varying peptide length preferences.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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; both teacher heads agree on what is shown here.
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".