Activation of the ILT7 receptor and plasmacytoid dendritic cell responses are governed by structurally-distinct BST2 determinants
Bibliographic record
Abstract
Type I interferons (IFN-I) are key innate immune effectors predominantly produced by activated plasmacytoid dendritic cells (pDCs). By modulating immune responses at their foundation, IFNs can widely reshape immunity to control infectious diseases and malignancies. Nevertheless, their biological activities can also be detrimental to surrounding healthy cells, as prolonged IFN-I signaling is associated with excessive inflammation and immune dysfunction. The interaction of the human pDC receptor immunoglobulin-like transcript 7 (ILT7) with its IFN-I-regulated ligand, bone marrow stromal cell antigen 2 (BST2) plays a key role in controlling the IFN-I amounts produced by pDCs in response to Toll-like receptor (TLR) activation. However, the structural determinants and molecular features of BST2 that govern ILT7 engagement and activation are largely undefined. Using two functional assays to measure BST2-stimulated ILT7 activation as well as biophysical studies, here we identified two structurally-distinct regions of the BST2 ectodomain that play divergent roles during ILT7 activation. We found that although the coiled-coil region contains a newly defined ILT7-binding surface, the N-terminal region appears to suppress ILT7 activation. We further show that a stable BST2 homodimer binds to ILT7, but post-binding events associated with the unique BST2 coiled-coil plasticity are required to trigger receptor signaling. Hence, BST2 with an unstable or a rigid coiled-coil fails to activate ILT7, whereas substitutions in its N-terminal region enhance activation. Importantly, the biological relevance of these newly defined domains of BST2 is underscored by the identification of substitutions having opposing potentials to activate ILT7 in pathological malignant conditions.
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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 | 0.001 |
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".