Rapid Screening of Endonuclease Target Site Preference Using a Modified Bacterial Two-Plasmid Selection
Bibliographic record
Abstract
Homing endonucleases and other site-specific endonucleases have potential applications in genome editing, yet efficient targeting requires a thorough understanding of DNA-sequence specificity. Here, we describe a modified two-plasmid genetic selection in Escherichia coli that allows rapid profiling of nucleotide substitutions within a target site of given endonucleases. The selection utilizes a toxic plasmid (pTox) that encodes a DNA gyrase toxin in addition to the endonuclease target site. Cleavage of the toxic plasmid by an endonuclease expressed from a second plasmid (pEndo) facilitates growth under selective conditions. The modified protocol utilizes competent cells harboring the endonuclease expression plasmid into which target site plasmids are transformed. Replica plating on nonselective and selective media plates identifies cleavable and non-cleavable targets. Thus, a library of randomized target sites, or many individual target sites, can be analyzed using a single transformation. Both cleavable and non-cleavable targets can be analyzed by DNA sequencing to gain information about nucleotide preference in the endonuclease's target site.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".