A conserved miRNA-183 cluster regulates the innate antiviral response
Bibliographic record
Abstract
Upon immune recognition of viruses, the mammalian innate immune response activates a complex signal transduction network to combat infection. This activation requires phosphorylation of key transcription factors regulating IFN production and signaling, including IFN regulatory factor 3 (IRF3) and STAT1. The mechanisms regulating these STAT1 and IRF3 phosphorylation events remain unclear. Here, using human and mouse cell lines along with gene microarrays, quantitative RT-PCR, viral infection and plaque assays, and reporter gene assays, we demonstrate that a microRNA cluster conserved among bilaterian animals, encoding miR-96, miR-182, and miR-183, regulates IFN signaling. In particular, we observed that the miR-183 cluster promotes IFN production and signaling, mediated by enhancing IRF3 and STAT1 phosphorylation. We also found that the miR-183 cluster activates the IFN pathway and inhibits vesicular stomatitis virus infection by directly targeting several negative regulators of IRF3 and STAT1 activities, including protein phosphatase 2A (PPP2CA) and tripartite motif-containing 27 (TRIM27). Overall, our work reveals an important role of the evolutionarily conserved miR-183 cluster in the regulation of mammalian innate immunity.
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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 | 0.001 |
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".