In situ cell-surface conformation of the TCR-CD3 signaling complex
Bibliographic record
Abstract
The extracellular molecular organization of the individual CD3 subunits around the αβ T cell receptor (TCR) is critical for initiating T cell signaling. In this study, we incorporate photo-crosslinkers at specific sites within the TCRα, TCRβ, CD3δ, and CD3γ subunits. Through crosslinking and docking, we identify a CD3ε'-CD3γ-CD3ε-CD3δ arrangement situated around the αβTCR in situ within the cell surface environment. We demonstrate the importance of cholesterol in maintaining the stability of the complex and that the 'in situ' complex structure mirrors the structure from 'detergent-purified' complexes. In addition, mutations aimed at stabilizing extracellular TCR-CD3 interfaces lead to poor signaling, suggesting that subunit fluidity is indispensable for signaling. Finally, employing photo-crosslinking and CD3 tetramer assays, we show that the TCR-CD3 complex undergoes minimal subunit movements or reorientations upon interaction with activating antibodies and pMHC tetramers. This suggests an absence of 'inactive-active' conformational states in the TCR constant regions and the extracellular CD3 subunits, unlike the transmembrane regions of the complex. This study contributes a nuanced understanding of TCR signaling, which may inform the development of therapeutics for immune-related disorders.
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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".