MegaTevs: single-chain dual nucleases for efficient gene disruption
Bibliographic record
Abstract
Targeting gene disruptions in complex genomes relies on imprecise repair by the non-homologous end-joining DNA pathway, creating mutagenic insertions or deletions (indels) at the break point. DNA end-processing enzymes are often co-expressed with genome-editing nucleases to enhance the frequency of indels, as the compatible cohesive ends generated by the nucleases can be precisely repaired, leading to a cycle of cleavage and non-mutagenic repair. Here, we present an alternative strategy to bias repair toward gene disruption by fusing two different nuclease active sites from I-TevI (a GIY-YIG enzyme) and I-OnuI E2 (an engineered meganuclease) into a single polypeptide chain. In vitro, the MegaTev enzyme generates two double-strand breaks to excise an intervening 30-bp fragment. In HEK 293 cells, we observe a high frequency of gene disruption without co-expression of DNA end-processing enzymes. Deep sequencing of disrupted target sites revealed minimal processing, consistent with the MegaTev sequestering the double-strand breaks from the DNA repair machinery. Off-target profiling revealed no detectable cleavage at sites where the I-TevI CNNNG cleavage motif is not appropriately spaced from the I-OnuI binding site. The MegaTev enzyme represents a small, programmable nuclease platform for extremely specific genome-engineering applications.
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How this classification was reachedexpand
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 | 0.001 | 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 | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".