The Main Role of Human Thymine-DNA Glycosylase Is Removal of Thymine Produced by Deamination of 5-Methylcytosine and Not Removal of Ethenocytosine
Bibliographic record
Abstract
Metabolites of vinyl chloride react with cytosine in DNA to form 3,N(4)-ethenocytosine. Recent studies suggest that ethenocytosine is repaired by the base excision repair pathway with the ethenobase being removed by thymine-DNA glycosylase. Here single turnover kinetics have been used to compare the excision of ethenocytosine by thymine-DNA glycosylase with the excision of thymine. The effect of flanking DNA sequence on the excision of ethenocytosine was also investigated. The 34-bp duplexes studied here fall into three categories. Ethenocytosine base-paired with guanine within a CpG site (i.e. CpG.(epsilon)C-DNA) was by far the best substrate having a specificity constant (k(2)/K(d)) of 25.1 x 10(6) m(-1) s(-1). The next best substrates were DNA duplexes containing TpG.(epsilon)C, GpG.(epsilon)C, and CpG.T. These had specificity constants 45-130 times smaller than CpG.(epsilon)C-DNA. The worst substrates were DNA duplexes containing ApG.(epsilon)C and TpG.T, which had specificity constants, respectively, 1,600 and 7,400 times lower than CpG.(epsilon)C-DNA. DNA containing ethenocytosine was bound much more tightly than DNA containing a G.T mismatch. This is probably because thymine-DNA glycosylase can flip out ethenocytosine from a G.(epsilon)C base pair more easily than it can flip out thymine from a G.T mismatch. Because thymine-DNA glycosylase has a larger specificity constant for the removal of ethenocytosine, it has been suggested its primary purpose is to deal with ethenocytosine. However, these results showing that thymine-DNA glycosylase has a strong sequence preference for CpG sites in the excision of both thymine and ethenocytosine suggest that the main role of thymine-DNA glycosylase in vivo is the removal of thymine produced by deamination of 5-methylcytosine at CpG sites.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".