The CRISPR/Cas9 system inactivates latent HIV-1 proviral DNA
Bibliographic record
Abstract
BACKGROUND: Highly active antiretroviral therapy (HAART) has transformed HIV-1 infection from a deadly disease to a manageable chronic illness, albeit does not provide a cure. The recently developed genome editing system called CRISPR/Cas9 offers a new tool to inactivate the integrated latent HIV-1 DNA and may serve as a new avenue toward cure. FINDINGS: We tested 10 sites in HIV-1 DNA that can be targeted by CRISPR/Cas9. The engineered CRISPR/Cas9 system was introduced into the JLat10.6 cells that are latently infected by HIV-1. The sequencing results showed that each target site in HIV-1 DNA was efficiently mutated by CRISPR/Cas9 with the target site in the second exon of Rev (called T10) exhibiting the highest degree of mutation. As a result, HIV-1 gene expression and virus production were significantly diminished with T10 causing a 20-fold reduction. CONCLUSIONS: The CRISPR/Cas9 complex efficiently mutates and deactivates HIV-1 proviral DNA in latently infected Jurkat cells. Our results also revealed a highly efficient Cas9 target site within the second exon of Rev that represents a promising target to be further explored in the CRISPR/Cas9-based cure strategy.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".