Structural basis of NKT cell inhibition using the T-cell receptor-blocking anti-CD1d antibody 1B1
Bibliographic record
Abstract
Natural killer T (NKT) cells are a subset of T lymphocytes that recognize glycolipid antigens presented by the CD1d molecule (CD1d). They rapidly respond to antigen challenge and can activate both innate and adaptive immune cells. To study the role of antigen presentation in NKT cell activation, previous studies have developed several anti-CD1d antibodies that block CD1d binding to T-cell receptors (TCRs). Antibodies that are specific to both CD1d and the presented antigen can only be used to study the function of only a limited number of antigens. In contrast, antibodies that bind CD1d and block TCR binding regardless of the presented antigen can be widely used to assess the role of TCR-mediated NKT cell activation in various disease models. Here, we report the crystal structure of the widely used anti-mouse CD1d antibody 1B1 bound to CD1d at a resolution of 2.45 Å and characterized its binding to CD1d-presented glycolipids. We observed that 1B1 uses a long hydrophobic H3 loop that is inserted deep into the binding groove of CD1d where it makes intimate nonpolar contacts with the lipid backbone of an incorporated spacer lipid. Using an NKT cell agonist that has a modified sphingosine moiety, we further demonstrate that 1B1 in its monovalent form cannot block TCR-mediated NKT cell activation, because 1B1 fails to bind with high affinity to mCD1d. Our results suggest potential limitations of using 1B1 to assess antigen recognition by NKT cells, especially when investigating antigens that do not follow the canonical two alkyl-chain rule.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".