Characterization of residual microRNAs in AAV vector batches produced in HEK293 mammalian cells and Sf9 insect cells
Bibliographic record
Abstract
. One critical quality attribute analyzed in AAV batches is the presence of residual DNA, as it could pose genotoxic risks or induce immune responses. Surprisingly, the presence of small cell-derived RNAs, such as microRNAs (miRNAs), has not been investigated previously. In this study, we examined the presence of miRNAs in purified AAV batches produced in mammalian or in insect cells. Our findings revealed that miRNAs were present in all batches, regardless of the production cell line or capsid serotype (2 and 8). Quantitative assays indicated that miRNAs were co-purified with the recombinant AAV particles in a proportion correlated with their abundance in the production cells. The level of residual miRNAs was reduced via an immunoaffinity chromatography purification process including a tangential flow filtration step or by RNase treatment, suggesting that most miRNA contaminants are likely non-encapsidated. In summary, we demonstrate, for the first time, that miRNAs are co-purified with AAV particles. Further investigations are required to determine whether these miRNAs could interfere with the safety or efficacy of AAV-mediated gene therapy.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".