Epstein-Barr Virus BGLF2 commandeers RISC to interfere with cellular miRNA function
Bibliographic record
Abstract
The Epstein-Barr virus (EBV) BGLF2 protein is a tegument protein with multiple effects on the cellular environment, including induction of SUMOylation of cellular proteins. Using affinity-purification coupled to mass-spectrometry, we identified the miRNA-Induced Silencing Complex (RISC), essential for miRNA function, as a top interactor of BGLF2. We confirmed BGLF2 interaction with the Ago2 and TNRC6 components of RISC in multiple cell lines and their co-localization in cytoplasmic bodies that also contain the stress granule marker G3BP1. In addition, BGLF2 expression led to the loss of processing bodies in multiple cell types, suggesting disruption of RISC function in mRNA regulation. Consistent with this observation, BGLF2 disrupted Ago2 association with multiple miRNAs. Using let-7 miRNAs as a model, we tested the hypothesis that BGLF2 interfered with the function of RISC in miRNA-mediated mRNA silencing. Using multiple reporter constructs with 3'UTRs containing let-7a regulated sites, we showed that BGLF2 inhibited let-7a miRNA activity dependent on these 3'UTRs, including those from SUMO transcripts which are known to be regulated by let-7 miRNAs. In keeping with these results, we showed that BGLF2 increased the cellular level of unconjugated SUMO proteins without affecting the level of SUMO transcripts. Such an increase in free SUMO is known to drive SUMOylation and would account for the effect of BGLF2 in inducing SUMOylation. We further showed that BGLF2 expression inhibited the loading of let-7 miRNAs into Ago2 proteins, and conversely, that lytic infection with EBV lacking BGLF2 resulted in increased interaction of let-7a and SUMO transcripts with Ago2, relative to WT EBV infection. Therefore, we have identified a novel role for BGLF2 as a miRNA regulator and shown that one outcome of this activity is the dysregulation of SUMO transcripts that leads to increased levels of free SUMO proteins and SUMOylation.
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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) | 0.001 | 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 | 0.001 | 0.001 |
| 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".