Modular determinants of cleavage preference in GIY-YIG nucleases revealed by block-based DNA shuffling and directed evolution
Bibliographic record
Abstract
GIY-YIG homing endonucleases are mobile genetic elements found in phage, bacterial, and organellar genomes. Their modular architecture and sequence-tolerant DNA cleavage properties likely represent evolutionary adaptations to tolerate genetic drift at target sites and enable target-site switching. To investigate modular determinants of GIY-YIG nuclease cleavage preference, we constructed 128 chimeric nucleases by shuffling structural blocks between the prototypical GIY-YIG homing endonuclease I-TevI (CNNNG motif preference) and its isoschizomer I-BmoI (NNNNG preference). Chimeras containing a swapped $\alpha$-helix1 and adjacent loop exhibited altered motif preferences, highlighting this region as a modular determinant, whereas swaps in other regions disrupted activity without altering cleavage preference. Directed evolution of nonconserved residues within this region identified a cluster (R30, K33, E36, C39) where substitutions enabled cleavage of targets poorly recognized by wild-type I-TevI, including variants with reprogrammed preference toward TNNNG and GNNNG motifs. Our findings define a modular and structural basis for DNA cleavage preference in the GIY-YIG nuclease domain and suggest that recombination of structural subunits could accelerate adaptation to new target sites over evolutionary time scales. These findings further support a strategy for engineering GIY-YIG nuclease domains with expanded cleavage motif selectivity.
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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 | 0.000 | 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 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".