Direct Identification and Quantification of Recombinant Adeno-Associated Virus in Crude Cell Lysate and Conditioned Medium by Mass Photometry
Bibliographic record
Abstract
Recombinant adeno-associated virus (rAAV) has attracted attention as a gene therapy vector. Monitoring the percentage of full particles (FPs) to the sum of empty particles (EPs) and FPs (F/E ratio) is required to optimize the rAAV production conditions; however, there is a lack of analytical methods to identify FPs and EPs and quantify the F/E ratio of rAAV without purification. Here, we established a direct analysis method for identifying FPs and EPs and quantifying the F/E ratio and genomic titer of unpurified rAAV in crude cell lysate and conditioned medium by mass photometry (MP). MP can detect the events of both molecules that bind to the glass surface and molecules that unbind from the glass surface. Few unbinding molecules were detected in the cell lysate and conditioned medium, but unbinding particles were as prevalent as binding particles in rAAV. By analyzing the unbinding side of the histogram, the F/E ratio of rAAV in the cell lysate was directly quantified with accuracy comparable to that of purified rAAV, which showed there was no interference from impurities. The genomic titer of rAAV in cell lysate was also estimated using particle counts of the unbinding side. This method can successfully determine the F/E ratio and estimate genomic titers of rAAV in crude cell lysate and conditioned medium during the manufacturing process. Direct quantification by MP is a convenient, rapid, and accurate method for quantifying unpurified rAAV and will be useful for improving rAAV production processes, for example, by screening manufacturing conditions.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".