Constitutive fusion of ubiquitin to PCNA provides DNA damage tolerance independent of translesion polymerase activities
Bibliographic record
Abstract
In response to replication-blocking DNA lesions, proliferating cell nuclear antigen (PCNA) can be conjugated with a single ubiquitin (Ub) or Lys63-linked Ub chains at the Lys164 residue, leading to two modes of DNA damage tolerance (DDT), namely translesion synthesis (TLS) and error-free DDT, respectively. Several reports suggest a model whereby monoubiquitylated PCNA recruits TLS polymerases through an enhanced physical association. We sought to examine this model in Saccharomyces cerevisiae through artificial fusions of Ub to PCNA in vivo. We created N- and C- terminal gene fusions of Ub to PCNA-K164R (collectively called PCNA.Ub) and found that both conferred tolerance to DNA damage. The creation of viable PCNA.Ub strains lacking endogenous PCNA enabled a thorough analysis of roles for PCNA mono-Ub in DDT. As expected, the DNA damage resistance provided by PCNA.Ub is not dependent on RAD18 or UBC13. Surprisingly, inactivation of TLS polymerases did not abolish PCNA.Ub resistance to DNA damage, nor did PCNA.Ub cause elevated spontaneous mutagenesis, which is a defining characteristic of REV3-dependent TLS activity. Taken together, our data suggest that either the monoubiquitylation of PCNA does not promote TLS activity in all cases or PCNA.Ub reveals a currently undiscovered role for monoubiquitylated PCNA in DNA damage tolerance.
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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".