Dual role of TRBP in HIV replication and RNA interference: viral diversion of a cellular pathway or evasion from antiviral immunity?
Bibliographic record
Abstract
Increasing evidence indicates that RNA interference (RNAi) may be used to provide antiviral immunity in mammalian cells. Human micro (mi)RNAs can inhibit the replication of a primate virus, whereas a virally-encoded miRNA from HIV inhibits its own replication. Indirect proof comes from RNAi suppressors encoded by mammalian viruses. Influenza NS1 and Vaccinia E3L proteins can inhibit RNAi in plants, insects and worms. HIV-1 Tat protein and Adenovirus VA RNAs act as RNAi suppressors in mammalian cells. Surprisingly, many RNAi suppressors are also inhibitors of the interferon (IFN)-induced protein kinase R (PKR) but the potential overlap between the RNAi and the IFN pathways remains to be determined. The link between RNAi as an immune response and the IFN pathway may be formed by a cellular protein, TRBP, which has a dual role in HIV replication and RNAi. TRBP has been isolated as an HIV-1 TAR RNA binding protein that increases HIV expression and replication by inhibiting PKR and by increasing translation of structured RNAs. A recent report published in the Journal of Virology shows that the poor replication of HIV in astrocytes is mainly due to a heightened PKR response that can be overcome by supplying TRBP exogenously. In two recent papers published in Nature and EMBO Reports, TRBP is now shown to interact with Dicer and to be required for RNAi mediated by small interfering (si) and micro (mi)RNAs. The apparent discrepancy between TRBP requirement in RNAi and in HIV replication opens the hypotheses that RNAi may be beneficial for HIV-1 replication or that HIV-1 may evade the RNAi restriction by diverting TRBP from Dicer and use it for its own benefit.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".