DNA-damage tolerance mediated by PCNA•Ub fusions in human cells is dependent on Rev1 but not Polη
Bibliographic record
Abstract
In response to replication-blocking lesions, proliferating cell nuclear antigen (PCNA) can be sequentially ubiquitinated at the K164 residue, leading to two modes of DNA-damage tolerance, namely, translesion DNA synthesis (TLS) and error-free lesion bypass. Although the majority of reported data support a model whereby monoubiquitinated PCNA enhances its affinity for TLS polymerases and hence recruits them to the damage sites, this model has also been challenged by several observations. In this study, we expressed the PCNA-164R and ubiquitin (UB) fusion genes in an inducible manner in an attempt to mimic PCNA monoubiquitination in cultured human cells. It was found that expression of both N- and C-terminal PCNA•Ub fusions conferred significant tolerance to ultraviolet (UV)-induced DNA damage. Surprisingly, depletion of Polη, a TLS polymerase dedicated to bypassing UV-induced pyrimidine dimers, did not alter tolerance conferred by PCNA•Ub. In contrast, depletion of Rev1, another TLS polymerase serving as a scaffold for the assembly of the TLS complex, completely abolished PCNA•Ub-mediated damage tolerance. Similar genetic interactions were confirmed when UV-induced monoubiquitination of endogenous PCNA is abolished by RAD18 deletion. Hence, PCNA•Ub fusions bypass the requirement for PCNA monoubiquitination, and UV damage tolerance conferred by these fusions is dependent on Rev1 but independent of Polη.
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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".