HIV-1 RRE RNA acts as an RNA silencing suppressor by competing with TRBP-bound siRNAs
Bibliographic record
Abstract
Several proteins and RNAs expressed by mammalian viruses have been reported to interfere with RNA interference (RNAi) activity. We investigated the ability of the HIV-1-encoded RNA elements Trans-Activation Response (TAR) and Rev-Response Element (RRE) to alter RNAi. MicroRNA let7-based assays showed that RRE is a potent suppressor of RNAi activity, while TAR displayed moderate RNAi suppression. We demonstrate that RRE binds to TAR-RNA Binding Protein (TRBP), an essential component of the RNA Induced Silencing Complex (RISC). The binding of TAR and RRE to TRBP displaces small interfering (si)RNAs from binding to TRBP. Several stem-deleted RRE mutants lost their ability to suppress RNAi activity, which correlated with a reduced ability to compete with siRNA-TRBP binding. A lentiviral vector expressing TAR and RRE restricted RNAi, but RNAi was restored when Rev or GagPol were coexpressed. Adenoviruses are restricted by RNAi and encode their own suppressors of RNAi, the Virus-Associated (VA) RNA elements. RRE enhanced the replication of wild-type and VA-deficient adenovirus. Our work describes RRE as a novel suppressor of RNAi that acts by competing with siRNAs rather than by disrupting the RISC. This function is masked in lentiviral vectors co-expressed with viral proteins and thus will not affect their use in gene therapy. The potent RNAi suppressive effects of RRE identified in this study could be used to enhance the expression of RNAi restricted viruses used in oncolysis such as adenoviruses.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".