The Clearance of Human Cytomegalovirus Using CRISPR/Cas9 RNA Lipid Nanoparticles
Bibliographic record
Abstract
Abstract Human cytomegalovirus (HCMV), a DNA virus, poses significant health risks to immunocompromised and immunosuppressed individuals and newborns. Clinical antiviral drugs like ganciclovir inhibit viral replication but have toxicities, are ineffective against drug-resistant strains, and cannot destroy HCMV DNA. CRISPR/Cas9 can cleave DNA, but has not been used therapeutically to target and degrade HCMV DNA in cells post-infection. We developed an all-in-one CRISPR/Cas9 RNA lipid nanoparticle (LNP) that clears established HCMV infections, permits rapid updating to combat resistance and is effective against multiple strains. Bioinformatic analyses identified essential, conserved viral genes as CRISPR/Cas9 targets. A delivery material screen revealed that antiviral activity was dependent on the ionizable lipid and LNP composition. Our lead formulation, βN2-40, inhibited up to 93.5% of HCMV infection with a single treatment. Furthermore, multitargeting βN2-40 LNPs demonstrated antiviral kinetics and a safety profile similar to ganciclovir, making it a compelling alternative to existing small-molecule antiviral drugs.
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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) | 0.000 | 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".