Efficacy and Site-Specificity of Adenoviral Vector Integration Mediated by the Phage φC31 Integrase
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Bibliographic record
Abstract
Adenoviral vectors deleted of all their viral genes (helper-dependent [HD]) are efficient gene-transfer vehicles. Because transgene expression is rapidly lost in actively dividing cells, we investigated the feasibility of using phage φC31 integrase (φC31-Int) to integrate an HD carrying an attB site and the puromycin resistance gene into human cells (HeLa) and murine myoblasts (C2C12) by co-infection with a second HD-expressing φC31-Int. Because the HD genome is linear, we also investigated whether its circularization, through expression of Cre using a third HD, affects integration. Efficacy and specificity were determined by scoring the number of puromycin-resistant colonies and by sequencing integration sites. Unexpectedly, circularization of HD was unnecessary and it even reduced the integration efficacy. The maximum integration efficacy achieved was 0.5% in HeLa cells and 0.1% in C2C12 myoblasts. Up to 76% of the integration events occurred at pseudo attP sites and previously characterized hotspots were found. A small (two- to three-fold) increase in the number of γ-H2AX positive foci, accompanied by no noticeable change in γ-H2AX expression, indicated the low genotoxicity of φC31-Int. In conclusion, integration of HD mediated by φC31-Int is an attractive alternative to engineer cells, because it permits site-specific integration of large DNA fragments with low genotoxicity. Robert and colleagues investigate the feasibility of using phage φC31 integrase to integrate a helper-dependent (HD) adenoviral vector into mammalian cells. Using this approach, the authors are able to achieve an integration efficacy of 0.5% and 0.12% in HeLa cells and C2C12 myoblasts, respectively. Moreover, they report that up to 76% of the integration events occur at pseudo attP sites and previously characterized hot spots.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 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) | 0.000 | 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 it