A sensitive assay for dNTPs based on long synthetic oligonucleotides, EvaGreen dye and inhibitor-resistant high-fidelity DNA polymerase
Bibliographic record
Abstract
Deoxyribonucleoside triphosphates (dNTPs) are vital for the biosynthesis and repair of DNA. Their cellular concentration peaks during the S phase of the cell cycle. In non-proliferating cells, dNTP concentrations are low, making their reliable quantification from tissue samples of heterogeneous cellular composition challenging. Partly because of this, the current knowledge related to the regulation of and disturbances in cellular dNTP concentrations derive mostly from cell culture experiments with little corroboration at the tissue or organismal level. Here, we fill the methodological gap by presenting a simple non-radioactive microplate assay for the quantification of dNTPs with a minimum requirement of 4-12 mg of biopsy material. In contrast to published assays, this assay is based on long synthetic single-stranded DNA templates (50-200 nucleotides), an inhibitor-resistant high-fidelity DNA polymerase, and the double-stranded-DNA-binding EvaGreen dye. The assay quantified reliably less than 50 fmol of each of the four dNTPs and discriminated well against ribonucleotides. Additionally, thermostable RNAse HII-mediated nicking of the reaction products and a subsequent shift in their melting temperature allowed near-complete elimination of the interfering ribonucleotide signal, if present. Importantly, the assay allowed measurement of minute dNTP concentrations in mouse liver, heart and skeletal muscle.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.005 |
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".