Detection of Uracil-Excising DNA Glycosylases in Cancer Cell Samples Using a Three-Dimensional DNAzyme Walker
Bibliographic record
Abstract
DNA glycosylase dysregulation is implicated in carcinogenesis and therapeutic resistance of cancers. Thus, various DNA-based detection platforms have been developed by leveraging the base excision activity of DNA glycosylases. However, the efficacy of DNA-based methods is hampered due to nonspecific degradation by nucleases commonly present in cancer cells and during preparations of cell lysates. In this report, we describe a fluorescence-based assay using a specific and nuclease-resistant three-dimensional DNAzyme walker to investigate the activity of DNA glycosylases from cancer cell lysates. We focus on DNA glycosylases that excise uracil from deoxyuridine (dU) lesions, namely, uracil DNA glycosylase (UDG) and single-stranded monofunctional uracil DNA glycosylase (SMUG1). The limits of detection for detecting UDG and SMUG1 in the buffer were 3.2 and 3.0 pM, respectively. The DNAzyme walker detected uracil excision activity in diluted cancer cell lysate from as few as 48 A549 cells. The results of the UDG inhibitor experiments demonstrate that UDG is the predominant uracil-excising glycosylase in A549 cells. Approximately 500 nM of UDG is present in each A549 cell on average. No fluorescence was generated in the samples lacking DNAzyme activation, indicating that there was no nonspecific nuclease interference. The ability of the DNAzyme walker to respond to glycosylase activity illustrates the potential use of DNAzyme walker technology to monitor and study biochemical processes involving glycosylases.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".