Adapting Next-Generation Sequencing to in Process CRISPR-Cas9 Genome Editing of Recombinant AcMNPV Vectors: From Shotgun to Tiled-Amplicon Sequencing
Bibliographic record
Abstract
The alphabaculovirus Autographa californica multiple nucleopolyhedrovirus (AcMNPV) is the most commonly used virus in the Baculovirus Expression Vector System (BEVS) and has been utilized for the production of many human and veterinary biologics. AcMNPV has a large dsDNA genome that remains understudied, and relatively unmodified from the wild-type, especially considering how extensively utilized it is as an expression vector. Previously, our group utilized CRISPR-Cas9 genome engineering that revealed phenotypic changes when baculovirus genes are targeted using either co-expressed sgRNA or transfected sgRNA into a stable insect cell line that produced the Cas9 protein. Here, we describe a pipeline to sequence the recombinant AcMNPV expression vectors using shotgun sequencing, provide a set of primers for tiled-amplicon sequencing, show that untargeted baculovirus vector genomes remain relatively unchanged when amplified in Sf9-Cas9 cells, and confirm that AcMNPV gp64 gene disruption can minimize baculovirus contamination in cell cultures. Our findings provide a robust baseline for analyzing in process genome editing of baculoviruses.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 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".