Role of poly(ADP-ribose) polymerase-1 in the removal of UV-induced DNA lesions by nucleotide excision repair
Bibliographic record
Abstract
Among the earliest responses of mammalian cells to DNA damage is catalytic activation of a nuclear enzyme poly(ADP-ribose) polymerase-1 (PARP-1). Activated PARP-1 forms the polymers of ADP-ribose (pADPr or PAR) that posttranslationally modify its target proteins, such as PARP-1 and DNA repair-related proteins. Although this metabolism is known to be implicated in other repair pathways, here we show its role in the versatile nucleotide excision repair pathway (NER) that removes a variety of DNA damages including those induced by UV. We show that PARP inhibition or specific depletion of PARP-1 decreases the efficiency of removal of UV-induced DNA damage from human skin fibroblasts or mouse epidermis. Using NER-proficient and -deficient cells and in vitro PARP-1 assays, we show that damaged DNA-binding protein 2 (DDB2), a key lesion recognition protein of the global genomic subpathway of NER (GG-NER), associates with PARP-1 in the vicinity of UV-damaged chromatin, stimulates its catalytic activity, and is modified by pADPr. PARP inhibition abolishes UV-induced interaction of DDB2 with PARP-1 or xeroderma pigmentosum group C (XPC) and also decreases localization of XPC to UV-damaged DNA, which is a key step that leads to downstream events in GG-NER. Thus, PARP-1 collaborates with DDB2 to increase the efficiency of the lesion recognition step of GG-NER.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".