Protein Engineering of <i>Taq</i> DNA Polymerase for Ultrafast PCR and Its Application in Molecular Diagnostics of Genetically Modified Crops
Bibliographic record
Abstract
To shorten the turnaround time of molecular diagnostics, an ultrafast polymerase chain reaction (PCR) technique has been developed in recent years, which requires thermostable DNA polymerases with high kinetic properties. In the present study, Thermus aquaticus ( Taq ) DNA polymerase was engineered through two strategies: fusion with CL7, a thermostable nonspecific DNA-binding tag, and rational design in its N-terminal exonuclease domain. The results indicated that the CL7 tag promoted the thermostability of this polymerase dramatically, while triple substitutions, L208I/E209 K/E210R, increased its polymerase activity by approximately 5-fold. Moreover, this engineered enzyme demonstrated a strong resistance to crude plant tissue lysate up to 30% (v/v) in the PCR system. Therefore, an ultrafast qPCR system was established to detect exogenous genes in genetically modified (GM) crops with this variant. The whole detection procedure was shortened to <30 min. Moreover, the limit of detection reached approximately 0.1 copies/μL. This study established a highly simple and accurate system suitable for rapid molecular diagnosis. More importantly, this is the first report about improving the kinetic properties of Taq polymerase through rational design of its exonuclease domain.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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".