DEAF1 Is a Pellino1-interacting Protein Required for Interferon Production by Sendai Virus and Double-stranded RNA*
Bibliographic record
Abstract
Double-stranded (ds) RNA of viral origin, a ligand for Melanoma Differentiation-associated gene 5 (MDA5) and Toll-Like Receptor 3 (TLR3), induces the TANK-Binding Kinase 1 (TBK1)-dependent phosphorylation and activation of Interferon Regulatory Factor 3 (IRF3) and the E3 ubiquitin ligase Pellino1, which are required for interferon β (IFNβ) gene transcription. Here, we report that Pellino1 interacts with the transcription factor Deformed Epidermal Autoregulatory Factor 1 (DEAF1). The interaction is independent of the E3 ligase activity of Pellino1, but weakened by the phosphorylation of Pellino1. We show that DEAF1 binds to the IFNβ promoter and to IRF3 and IRF7, that it is required for the transcription of the IFNβ gene and IFNβ secretion in MEFs infected with Sendai virus or transfected with poly(I:C). DEAF1 is also needed for TLR3-dependent IFNβ production. Taken together, our results identify DEAF1 as a novel component of the signal transduction network by which dsRNA of viral origin stimulates IFNβ production. Background: The E3 ligase Pellino1 is required for interferon (IFN) β production following infection with Sendai virus or poly(I:C). Results: The transcription factor DEAF1 interacts with Pellino1 and, like Pellino1, is needed for transcription of the IFNβ gene. Conclusion: DEAF1 is required for the production of IFNβ . Significance: DEAF1 is a new signaling component required for IFNβ production.
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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 | 0.000 |
| 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) | 0.002 | 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".