The AP-1 transcription factor JunD activates the leukocyte immunoglobulin-like receptor 1 distal promoter
Bibliographic record
Abstract
Leukocyte immunoglobulin-like receptor 1 (LILRB1) is an inhibitory receptor that binds classical and non-classical MHC-I as well as UL18, a viral MHC-I homolog. LILRB1 is encoded within the leukocyte receptor complex and is widely expressed on immune cells. Two distinct promoters used differentially by lymphoid and myeloid cells were previously identified, but little is known regarding molecular regulation of each promoter or cell-type-specific usage. Here, we have investigated the transcriptional regulation of human LILRB1 focusing on elements that drive expression in NK cells. We found that while both the distal and proximal promoter regions are active in reporter plasmids in lymphoid and myeloid cells, the proximal promoter is used minimally to transcribe LILRB1 in NK cells compared with monocytes. We defined a 120-bp core region of transcriptional activity in the distal promoter that can bind several factors in NK cell nuclear extracts. Within this region, we investigated overlapping putative AP-1 sites. An inhibitor of JNK decreased LILRB1 transcript in a LILRB1⁺ NK cell line. Upon examining binding of specific AP-1 factors, we found JunD associated with the LILRB1 distal promoter. Finally, depletion of JunD led to a decrease in distal promoter transcript, indicating an activating role for JunD in regulation of LILRB1 transcription. This study presents the first description of regions/factors required for activity of the LILRB1 distal promoter, the first description of a role for JunD in NK cells and suggests a potential mechanism for dynamic regulation of LILRB1 by cytokines.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".