Identification of the Minimal Phosphoacceptor Site Required for in Vivo Activation of Interferon Regulatory Factor 3 in Response to Virus and Double-stranded RNA
Bibliographic record
Abstract
The ubiquitously expressed latent interferon regulatory factor (IRF) 3 transcription factor is activated in response to virus infection by phosphorylation events that target a cluster of Ser/Thr residues, (382)GGASSLENTVDLHISNSHPLSLTSDQY(408) at the C-terminal end of the protein. To delineate the minimal phosphoacceptor sites required for IRF-3 activation, several point mutations were generated and tested for transactivation potential and cAMP-response element-binding protein-binding protein/p300 coactivator association. Expression of the IRF-3 S396D mutant alone was sufficient to induce type I IFN beta, IFNalpha1, RANTES, and the interferon-stimulated gene 561 promoters. Using SDS-PAGE and immunoblotting with a novel phosphospecific antibody, we show for the first time that, in vivo, IRF-3 is phosphorylated on Ser(396) following Sendai virus infection, expression of viral nucleocapsid, and double-stranded RNA treatment. These results demonstrate that Ser(396) within the C-terminal Ser/Thr cluster is targeted in vivo for phosphorylation following virus infection and plays an essential role in IRF-3 activation. The inability of the phosphospecific antibody to detect Ser(396) phosphorylation in lipopolysaccharide-treated cells suggests that other major pathways may be involved in IRF-3 activation following Toll-like receptor 4 stimulation.
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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".