Stringent testing identifies highly potent and escape‐proof anti‐HIV short hairpin RNAs
Bibliographic record
Abstract
BACKGROUND: RNA interference (RNAi) is a cellular mechanism that can be induced by small interfering RNAs to mediate sequence-specific gene silencing by cleavage of the targeted mRNA. RNAi can be used as an antiviral approach to silence the human immunodeficiency virus type 1 (HIV-1) through stable expression of short hairpin RNAs (shRNAs). Previously, we used a co-transfection assay in which shRNA constructs were transfected with an HIV-1 molecular clone to identify 20 shRNA inhibitors that target highly conserved HIV-1 sequences. METHODS: In the present study, we selected the most potent shRNAs to formulate a combinatorial shRNA therapy and determine the best and easiest method for antiviral shRNA selection. We performed transient inhibition assays with either a luciferase reporter or HIV-1 molecular clone and also infected shRNA-expressing T cell lines with HIV-1 and monitored virus replication. The latter assay allows detection of viral escape. In addition, we also tested shRNA-expressing T cells upon challenge with increasing dosages of HIV-1, and measured the dose required to result in massive virus-induced syncytia formation in this 2-week assay. RESULTS: Extended culturing selected three highly effective shRNAs that do not allow viral replication for more than 100 days. This difference in potency was not observed in the transient co-transfection assays. The use of increased dosages of HIV-1 selected the same highly potent shRNAs as the laborious and extended escape study. CONCLUSIONS: These highly potent shRNAs could be used for a clinical vector and the comparison of the developed assays might help other researchers in their search for antiviral shRNAs.
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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 | 0.002 | 0.002 |
| 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 | 0.000 | 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".