Efficient Site‐Directed Mutagenesis Mediated by Primer Pairs with 3’‐Overhangs
Bibliographic record
Abstract
Site-directed mutagenesis is an essential tool in molecular biology, protein engineering, plasmid engineering and synthetic biology. While the QuickChange method has been one of the most employed methods for site-directed mutagenesis, it is hindered by low efficiency and frequent introduction of unwanted mutations at the primer sites, raising the urgent need for new, more efficient, and reliable methods. Here, we present an optimized site-directed mutagenesis protocol that leverages partially complementary primer pairs with 3'-overhangs to improve mutagenesis efficiency and reduce error rates. Our method significantly enhances success rates, achieving an average efficiency of ∼50% with some instances approaching the ideal threshold of 100%, while also minimizing the time required for mutant generation. Typically, only 3 colonies need to be analyzed per mutagenesis reaction, and a skillful trainee can engineer 1 to 2 dozen mutant plasmids within a week. In addition, with an in-house protocol for preparing highly competent bacterial cells, we have further increased the reliability and cost-effectiveness of the method. Notably, such competent cells have been kept in a liquid nitrogen tank for >12 years with minimal loss of competency. Thus, this refined method offers a robust, efficient, and scalable solution for high-precision gene modification in vitro, with broad applications in protein and plasmid engineering. © 2025 The Author(s). Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: In vitro site-directed mutagenesis using an optimized primer design strategy Basic Protocol 2: Preparation of high-efficiency chemocompetent DH5α cells for transformation of mutagenized plasmid products Basic Protocol 3: Transformation of chemocompetent DH5α cells and obtaining bacterial colonies with correctly mutagenized plasmid products Alternate Protocol: Transformation if glycerol stocks are unavailable.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.003 | 0.004 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.016 | 0.023 |
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".