The tumor suppressor SirT2 regulates cell cycle progression and genome stability by modulating the mitotic deposition of H4K20 methylation
Bibliographic record
Abstract
The establishment of the epigenetic mark H4K20me1 (monomethylation of H4K20) by PR-Set7 during G2/M directly impacts S-phase progression and genome stability. However, the mechanisms involved in the regulation of this event are not well understood. Here we show that SirT2 regulates H4K20me1 deposition through the deacetylation of H4K16Ac (acetylation of H4K16) and determines the levels of H4K20me2/3 throughout the cell cycle. SirT2 binds and deacetylates PR-Set7 at K90, modulating its chromatin localization. Consistently, SirT2 depletion significantly reduces PR-Set7 chromatin levels, alters the size and number of PR-Set7 foci, and decreases the overall mitotic deposition of H4K20me1. Upon stress, the interaction between SirT2 and PR-Set7 increases along with the H4K20me1 levels, suggesting a novel mitotic checkpoint mechanism. SirT2 loss in mice induces significant defects associated with defective H4K20me1-3 levels. Accordingly, SirT2-deficient animals exhibit genomic instability and chromosomal aberrations and are prone to tumorigenesis. Our studies suggest that the dynamic cross-talk between the environment and the genome during mitosis determines the fate of the subsequent cell cycle.
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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 | 0.000 |
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".