Unlocking genetic potential: harnessing phage for targeted mutagenesis in phage-assisted evolution.
Bibliographic record
Abstract
A critical challenge in DNA library genesis for evolution systems is avoiding off-target mutations, which can introduce undesirable changes elsewhere in the plasmid or even the host's genome: such mutations can allow cells or phages to propagate regardless of selective pressure. To construct a diverse pool of genes with mutations restricted to the gene-of-interest (GOI), we merged the strengths of phage-assisted evolution with the MutaT7 system for targeted mutagenesis. Hence, phage infection transfers genetic material to host cells where the MutaT7 system initiates targeted gene alteration. Our viral eMPAE system (enhanced mutation phage-assisted evolution) has three significant advantages over current state-of-the-art. (i) Up to 9 mutations in the GOI at a mutation rate of 5.6 mutations kb-1 day-1; in comparison, two of the most active mutagenesis plasmids, eMutaT7 and MP6, showed just one or no mutations in the GOI under phage-assisted conditions. (ii) No off-target mutations in the entire 6600 base-pair plasmid carrying the GOI; in contrast, MP6 mutations are completely untargeted. (iii) Our system allows easy substitution of GOI and DNA-modifying enzymes through unique restriction sites. Our proof-of-concept evolution experiment validates that protein variants obtained from eMPAE can withstand selective pressure and outperform the parent protein in binding assays. With its superior targeted mutagenesis ability, eMPAE is a transformative tool for constructing a diverse library of mutants. It is especially valuable for directed evolution, as its off-target mutation rate of <6.2 × 10-3 mutations kb-1 day-1 in the target plasmid minimizes the risk of creating cheater phages that circumvent selection.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".