Ultra-efficient Integration of Gene Libraries onto Yeast Cytosolic Plasmids
Bibliographic record
Abstract
diversification of GOIs encoded on a cytosolic plasmid (p1), has been successfully used to drive numerous protein engineering campaigns. However, OrthoRep-based GOI evolution has almost always started from single GOI sequences, limiting the number of locations on a fitness landscape from where evolutionary search begins. Here, we present a simple approach for the high-efficiency integration of GOI libraries onto OrthoRep. By leveraging integrases, we demonstrate recombination of donor DNA onto the cytosolic p1 plasmid at exceptionally high transformation efficiencies, even surpassing the transformation efficiency of standard circular plasmids and linearized plasmid fragments into yeast. We demonstrate our method's utility through the straightforward construction of mock nanobody libraries encoded on OrthoRep, from which rare binders were reliably enriched. Overall, integrase-assisted manipulation of yeast cytosolic plasmids should enhance the versatility of OrthoRep in continuous evolution experiments and support the routine construction of large GOI libraries in yeast, in general.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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".