Structural basis of T cell receptor specificity and cross-reactivity of two HLA-DQ2.5-restricted gluten epitopes in celiac disease
Bibliographic record
Abstract
Celiac disease is a T cell-mediated chronic inflammatory condition often characterized by human leukocyte antigen (HLA)-DQ2.5 molecules presenting gluten epitopes derived from wheat, barley, and rye. Although some T cells exhibit cross-reactivity toward distinct gluten epitopes, the structural basis underpinning such cross-reactivity is unclear. Here, we investigated the T-cell receptor specificity and cross-reactivity of two immunodominant wheat gluten epitopes, DQ2.5-glia-α1a (PFPQPELPY) and DQ2.5-glia-ω1 (PFPQPEQPF). We show by surface plasmon resonance that a T-cell receptor alpha variable (TRAV) 4 + -T-cell receptor beta variable (TRBV) 29-1 + TCR bound to HLA-DQ2.5-glia-α1a and HLA-DQ2.5-glia-ω1 with similar affinity, whereas a TRAV4 - (TRAV9-2 + ) TCR recognized HLA-DQ2.5-glia-ω1 only. We further determined the crystal structures of the TRAV4 + -TRBV29-1 + TCR bound to HLA-DQ2.5-glia-α1a and HLA-DQ2.5-glia-ω1, as well as the structure of an epitope-specific TRAV9-2 + -TRBV7-3 + TCR-HLA-DQ2.5-glia-ω1 complex. We found that position 7 (p7) of the DQ2.5-glia-α1a and DQ2.5-glia-ω1 epitopes made very limited contacts with the TRAV4 + TCR, thereby explaining the TCR cross-reactivity across these two epitopes. In contrast, within the TRAV9-2 + TCR-HLA-DQ2.5-glia-ω1 ternary complex, the p7-Gln was situated in an electrostatic pocket formed by the hypervariable CDR3β loop of the TCR and Arg70β from HLA-DQ2.5, a polar network which would not be supported by the p7-Leu residue of DQ2.5-glia-α1a. In conclusion, we provide additional insights into the molecular determinants of TCR specificity and cross-reactivity to two closely-related epitopes in celiac disease.
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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".