Mutations in Replicative Stress Response Pathways Are Associated with S Phase-specific Defects in Nucleotide Excision Repair
Bibliographic record
Abstract
Nucleotide excision repair (NER) is a highly conserved pathway that removes helix-distorting DNA lesions induced by a plethora of mutagens, including UV light. Our laboratory previously demonstrated that human cells deficient in either ATM and Rad3-related (ATR) kinase or translesion DNA polymerase η (i.e. key proteins that promote the completion of DNA replication in response to UV-induced replicative stress) are characterized by profound inhibition of NER exclusively during S phase. Toward elucidating the mechanistic basis of this phenomenon, we developed a novel assay to quantify NER kinetics as a function of cell cycle in the model organism Saccharomyces cerevisiae. Using this assay, we demonstrate that in yeast, deficiency of the ATR homologue Mec1 or of any among several other proteins involved in the cellular response to replicative stress significantly abrogates NER uniquely during S phase. Moreover, initiation of DNA replication is required for manifestation of this defect, and S phase NER proficiency is correlated with the capacity of individual mutants to respond to replicative stress. Importantly, we demonstrate that partial depletion of Rfa1 recapitulates defective S phase-specific NER in wild type yeast; moreover, ectopic RPA1-3 overexpression rescues such deficiency in either ATR- or polymerase η-deficient human cells. Our results strongly suggest that reduction of NER capacity during periods of enhanced replicative stress, ostensibly caused by inordinate sequestration of RPA at stalled DNA replication forks, represents a conserved feature of the multifaceted eukaryotic DNA damage response.
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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 | 0.001 | 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) | 0.002 | 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".