The T Cell Receptor β-Chain Second Complementarity Determining Region Loop (CDR2β) Governs T Cell Activation and Vβ Specificity by Bacterial Superantigens
Bibliographic record
Abstract
Superantigens (SAgs) are microbial toxins defined by their ability to activate T lymphocytes in a T cell receptor (TCR) β-chain variable domain (Vβ)-specific manner. Although existing structural information indicates that diverse bacterial SAgs all uniformly engage the Vβ second complementarity determining region (CDR2β) loop, the molecular rules that dictate SAg-mediated T cell activation and Vβ specificity are not fully understood. Herein we report the crystal structure of human Vβ2.1 (hVβ2.1) in complex with the toxic shock syndrome toxin-1 (TSST-1) SAg, and mutagenesis of hVβ2.1 indicates that the non-canonical length of CDR2β is a critical determinant for recognition by TSST-1 as well as the distantly related SAg streptococcal pyrogenic exotoxin C. Frame work (FR) region 3 is uniquely critical for TSST-1 function explaining the fine Vβ-specificity exhibited by this SAg. Furthermore, domain swapping experiments with SAgs, which use distinct domains to engage both CDR2β and FR3/4β revealed that the CDR2β contacts dictate T lymphocyte Vβ-specificity. These findings demonstrate that the TCR CDR2β loop is the critical determinant for functional recognition and Vβ-specificity by diverse bacterial SAgs.
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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".