Targeted Delivery of Mutant Tolerant Anti-Coxsackievirus Artificial MicroRNAs Using Folate Conjugated Bacteriophage Phi29 pRNA
Bibliographic record
Abstract
BACKGROUND: Myocarditis is the major heart disease in infants and young adults. It is very commonly caused by coxsackievirus B3 (CVB3) infection; however, no specific treatment or vaccine is available at present. RNA interference (RNAi)-based anti-viral therapy has shown potential to inhibit viral replication, but this strategy faces two major challenges; viral mutational escape from drug suppression and targeted delivery of the reagents to specific cell populations. METHODOLOGY/PRINCIPAL FINDINGS: In this study, we designed artificial microRNAs (AmiRs) targeting the 3'untranslated region (3'UTR) of CVB3 genome with mismatches to the central region of their targeting sites. Antiviral evaluation showed that AmiR-1 and AmiR-2 reduced CVB3 (Kandolf and CG strains) replication approximately 100-fold in both HeLa cells and HL-1 cardiomyocytes. To achieve specific delivery, we linked AmiRs to the folate-conjugated bacterial phage packaging RNA (pRNA) and delivered the complexes into HeLa cells, a folate receptor positive cancer cells widely used as an in vitro model for CVB3 infection, via folate-mediated specific internalization. We found that our designed pRNA-AmiRs conjugates were tolerable to target mutations and have great potential to suppress viral mutational escape with little effect on triggering interferon induction. CONCLUSION/SIGNIFICANCE: This study provides important clues for designing AmiRs targeting the 3'UTR of viral genome. It also proves the feasibility of specific deliver of AmiRs using conjugated pRNA vehicles. These small AmiRs combined with pRNA-folate conjugates could form a promising system for antiviral drug development.
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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".