Genome-wide RNAi screen reveals a novel role of WNT/CTNNB1 signaling pathway in regulation of innate antiviral responses (67.7)
Bibliographic record
Abstract
Abstract To identify new regulators of innate antiviral immunity, we completed the first genome-wide gene silencing screen assessing the transcriptional response at the interferon-β gene (IFNB1) promoter following Sendai virus (SeV) infection. We identified 237 potential modulator genes for which negative or positive actions of gene products were mapped to the different steps of the antiviral responses from virus sensing, signal propagation/amplification up to the feedback regulation. In the present study, we will report on specific proteins that promote IFNB1 expression and innate antiviral response. The functional genomics screen uncovers a novel link between WNT family members and innate antiviral immunity. We show that virus-induced secretion of WNT2B and WNT9B down regulates IFNB1 and ISG56 expression in a β-catenin (CTNNB1)-dependent mechanism. The antiviral response is drastically reduced by GSK3 inhibitors but completely restored in CTNNB1 knockdown cells. The findings confirm a novel regulation of the innate antiviral response by a canonical WNT/GSK3/CTNNB1 pathway in a negative feedback mechanism. The study identifies novel avenues for therapeutically regulating innate immunity for effective treatment of viral infection and prevention of excessive response in autoimmune diseases.
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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) | 0.002 | 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".