The ubiquitin E3 ligase Huwe1 facilitates viral and self RNA sensing by RIG-I-like receptors
Bibliographic record
Abstract
Abstract RIG-I-like receptors (RLRs) are cytoplasmic RNA sensors that promote type I and type III interferon (IFN) production in response to RNA ligands of viral or endogenous origin. The RLR pathway is tightly regulated by dynamic post-translational modifications, including ubiquitination. Huwe1 is a HECT domain-containing giant ubiquitin E3 ligase that has not been implicated in the RLR or IFN pathway. Here, we investigated whether Huwe1 is required for type I IFN induction downstream of RLRs. We demonstrate that loss of Huwe1 severely attenuates the expression of IFN-β, IFN-λ1 and IFN-stimulated genes (ISGs) in ADAR1-deficient human cells and primary murine bone-marrow derived macrophages, in which unedited self RNAs that serve as RLR ligands accumulate. In addition, depletion of Huwe1 reduces the induction of type I and III IFNs upon transfection with synthetic viral RNA mimetics or infection with a picornavirus. Using proteomics, we identified several putative Huwe1 substrates, which include key components of the RLR pathway (MAVS, TRAFs). We demonstrate that these substrates interact with Huwe1 and that Huwe1 is essential for the activity of TRAF5 in type I IFN induction. Collectively, our results put Huwe1 on the map as an important ubiquitin E3 ligase in the RLR pathway and provide new insights into ubiquitin-dependent regulation of cell-intrinsic antiviral immune pathways.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".