BATF controls IFN I production via DC-SCRIPT in plasmacytoid dendritic cells
Bibliographic record
Abstract
Abstract The basic leucine zipper ATF-like transcription factor (BATF) plays a pivotal role in coordinating various aspects of lymphoid cell biology, yet essential functions in dendritic cells (DCs) have not been reported. Here we demonstrate that BATF deficiency leads to increased interferon (IFN) I production in Toll-like receptor 9 (TLR9)-activated plasmacytoid dendritic cells (pDCs), while BATF overexpression has an inhibitory effect. BATF-deficient mice exhibit elevated IFN I serum levels early in lymphocytic choriomeningitis virus (LCMV) infection. Through ATAC-Seq analysis, BATF emerges as a pioneer transcription factor, regulating approximately one third of the known transcription factors in pDCs. Integrated transcriptomics and ChIP-Seq approaches identified the transcriptional regulator DC-SCRIPT as a direct target of BATF that suppresses IFN I promoter activity by interacting with the interferon regulatory factor 7 (IRF7). Genome-wide association study (GWAS) analyses further implicate BATF in pDC-mediated human diseases. Our findings establish a novel negative feedback axis in IFN I regulation in pDCs during anti-viral immune responses orchestrated by BATF and DC-SCRIPT, with broader implications for pDC and IFN I-mediated autoimmunity.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".