Key Residues at Third CDR3β Position Impact Structure and Antigen Recognition of Human Invariant NK TCRs
Bibliographic record
Abstract
The human invariant NK (iNK) TCR is largely composed of the invariant TCR Vα24-Jα18 chain and semivariant TCR Vβ11 chains with variable CDR3β sequences. The direct role of CDR3β in Ag recognition has been studied extensively. Although it was noted that CDR3β can interact with CDR3α, how this interaction might indirectly influence Ag recognition is not fully elucidated. We observed that the third position of Vβ11 CDR3 can encode an Arg or Ser residue as a result of somatic rearrangement. Clonotypic analysis of the two iNK TCR types with a single amino acid substitution revealed that the staining intensity by anti-Vα24 Abs depends on whether Ser or Arg is encoded. When stained with an anti-Vα24-Jα18 Ab, human primary invariant NKT cells could be divided into Vα24 low- and high-intensity subsets, and Arg-encoding TCR Vβ11 chains were more frequently isolated from the Vα24 low-intensity subpopulation compared with the Vα24 high-intensity subpopulation. The Arg/Ser substitution also influenced Ag recognition as determined by CD1d multimer staining and CD1d-restricted functional responses. Importantly, in silico modeling validated that this Ser-to-Arg mutation could alter the structure of the CDR3β loop, as well as the CDR3α loop. Collectively, these results indicate that the Arg/Ser encoded at the third CDR3β residue can effectively modulate the overall structure of, and Ag recognition by, human iNK TCRs.
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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".