DNA damage-induced phosphorylation of the human telomere-associated protein TRF2
Bibliographic record
Abstract
Several protein kinases from diverse eukaryotes known to perform important roles in DNA repair have also been shown to play critical roles in telomere maintenance. Here, we report that the human telomere-associated protein TRF2 is rapidly phosphorylated in response to DNA damage. We find that the phosphorylated form of TRF2 is not bound to telomeric DNA, as is the ground form of TRF2, and is rapidly localized to damage sites. Our results suggest that the ataxia-telangiectasia-mutated (ATM) protein kinase signal-transduction pathway is primarily responsible for the DNA damage-induced phosphorylation of TRF2. Unlike DNA damage-induced phosphorylation of other ATM targets, the phosphorylated form of TRF2 is transient, being detected rapidly at DNA damage sites postirradiation, but largely dissipated by 2 hours. In addition, we report that the phosphorylated form of TRF2 is present at telomeres in cell types undergoing telomere-based crisis and a recombination-driven, telomerase-independent, alternative lengthening of telomeres (ALT) pathway, likely as a consequence of a telomere-based DNA damage response. Our results link the induction of TRF2 phosphorylation to the DNA damage-response system, providing an example of direct cross-talk via a signaling pathway between these two major cellular processes essential for genomic stability, telomere maintenance, and DNA repair.
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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) | 0.002 | 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".