Involvement of the IκB Kinase (IKK)-Related Kinases Tank-Binding Kinase 1/IKKi and Cullin-Based Ubiquitin Ligases in IFN Regulatory Factor-3 Degradation
Bibliographic record
Abstract
Activation of the innate arm of the immune system following pathogen infection relies on the recruitment of latent transcription factors involved in the induction of a subset of genes responsible for viral clearance. One of these transcription factors, IFN regulatory factor 3 (IRF-3), is targeted for proteosomal degradation following virus infection. However, the molecular mechanisms involved in this process are still unknown. In this study, we show that polyubiquitination of IRF-3 increases in response to Sendai virus infection. Using an E1 temperature-sensitive cell line, we demonstrate that polyubiquitination is required for the observed degradation of IRF-3. Inactivation of NEDD8-activating E1 enzyme also results in stabilization of IRF-3 suggesting the NEDDylation also plays a role in IRF-3 degradation following Sendai virus infection. In agreement with this observation, IRF-3 is recruited to Cullin1 following virus infection and overexpression of a dominant-negative mutant of Cullin1 significantly inhibits the degradation of IRF-3 observed in infected cells. We also asked whether the C-terminal cluster of phosphoacceptor sites of IRF-3 could serve as a destabilization signal and we therefore measured the half-life of C-terminal phosphomimetic IRF-3 mutants. Interestingly, we found them to be short-lived in contrast to wild-type IRF-3. In addition, no degradation of IRF-3 was observed in TBK1(-/-) mouse embryonic fibroblasts. All together, these data demonstrate that virus infection stimulates a host cell signaling pathway that modulates the expression level of IRF-3 through its C-terminal phosphorylation by the IkappaB kinase-related kinases followed by its polyubiquitination, which is mediated in part by a Cullin-based ubiquitin ligase.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".