A Novel Triple-Mutant AAV6 Capsid Induces Rapid and Potent Transgene Expression in the Muscle and Respiratory Tract of Mice
Bibliographic record
Abstract
Gene therapy for the treatment of genetic disorders has demonstrated considerable therapeutic success in clinical trials. Among the most effective and commonly used gene delivery vectors are those based on adeno-associated virus (AAV). Despite these advances in clinical gene therapy, further improvements in AAV vector properties such as rapid intracellular processing and transgene expression, targeted transduction of therapeutically relevant cell types, and longevity of transgene expression, will render extension of such successes to many other human diseases. Engineering of AAV capsids continues to evolve the specificity and efficiency of AAV-mediated gene transfer. Here, we describe a triple AAV6 mutant, termed AAV6.2FF, containing F129L, Y445F, and Y731F mutations. AAV6.2FF yielded 10-fold greater transgene expression in lung than AAV6 after 21 days. Additionally, this novel capsid demonstrated 101-fold and 49-fold increased transgene expression in the muscle and lungs, respectively, 24 hr post vector delivery when compared with the parental AAV6. Furthermore, AAV6.2FF retains heparin sulfate binding capacity and displays a 10-fold increase in resistance to pooled immunoglobulin neutralization in vitro . The rapid and potent expression mediated by AAV6.2FF is ideally suited to applications such as vectored immunoprophylaxis, in which rapid transgene expression is vital for use during an outbreak response scenario.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".