Engineering processive DNA polymerases with maximum benefit at minimum cost
Bibliographic record
Abstract
DNA polymerases need to be engineered to achieve optimal performance for biotechnological applications, which often require high fidelity replication when using modified nucleotides and when replicating difficult DNA sequences. These tasks are achieved for the bacteriophage T4 DNA polymerase by replacing leucine with methionine in the highly conserved Motif A sequence (L412M). The costs are minimal. Although base substitution errors increase moderately, accuracy is maintained for templates with mono- and dinucleotide repeats while replication efficiency is enhanced. The L412M substitution increases intrinsic processivity and addition of phage T4 clamp and single-stranded DNA binding proteins further enhance the ability of the phage T4 L412M-DNA polymerase to replicate all types of difficult DNA sequences. Increased pyrophosphorolysis is a drawback of increased processivity, but pyrophosphorolysis is curbed by adding an inorganic pyrophosphatase or divalent metal cations, Mn(2+) or Ca(2+). In the absence of pyrophosphorolysis inhibitors, the T4 L412M-DNA polymerase catalyzed sequence-dependent pyrophosphorolysis under DNA sequencing conditions. The sequence specificity of the pyrophosphorolysis reaction provides insights into how the T4 DNA polymerase switches between nucleotide incorporation, pyrophosphorolysis and proofreading pathways. The L-to-M substitution was also tested in the yeast DNA polymerases delta and alpha. Because the mutant DNA polymerases displayed similar characteristics, we propose that amino acid substitutions in Motif A have the potential to increase processivity and to enhance performance in biotechnological applications. An underlying theme in this chapter is the use of genetic methods to identify mutant DNA polymerases with potential for use in current and future biotechnological applications.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".