Werner Protein Is a Target of DNA-dependent Protein Kinase in Vivo and in Vitro, and Its Catalytic Activities Are Regulated by Phosphorylation
Bibliographic record
Abstract
Human Werner Syndrome is characterized by early onset of aging, elevated chromosomal instability, and a high incidence of cancer. Werner protein (WRN) is a member of the recQ gene family, but unlike other members of the recQ family, it contains a unique 3'-->5' exonuclease activity. We have reported previously that human Ku heterodimer interacts physically with WRN and functionally stimulates WRN exonuclease activity. Because Ku and DNA-PKcs, the catalytic subunit of DNA-dependent protein kinase (DNA-PK), form a complex at DNA ends, we have now explored the possibility of functional modulation of WRN exonuclease activity by DNA-PK. We find that although DNA-PKcs alone does not affect the WRN exonuclease activity, the additional presence of Ku mediates a marked inhibition of it. The inhibition of WRN exonuclease by DNA-PKcs requires the kinase activity of DNA-PKcs. WRN is a target for DNA-PKcs phosphorylation, and this phosphorylation requires the presence of Ku. We also find that treatment of recombinant WRN with a Ser/Thr phosphatase enhances WRN exonuclease and helicase activities and that WRN catalytic activity can be inhibited by rephosphorylation of WRN with DNA-PK. Thus, the level of phosphorylation of WRN appears to regulate its catalytic activities. WRN forms a complex, both in vitro and in vivo, with DNA-PKC. WRN is phosphorylated in vivo after treatment of cells with DNA-damaging agents in a pathway that requires DNA-PKcs. Thus, WRN protein is a target for DNA-PK phosphorylation in vitro and in vivo, and this phosphorylation may be a way of regulating its different catalytic activities, possibly in the repair of DNA dsb.
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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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".