SUMOylation mediates CtIP’s functions in DNA end resection and replication fork protection
Bibliographic record
Abstract
Double-strand breaks and stalled replication forks are a significant threat to genomic stability that can lead to chromosomal rearrangements or cell death. The protein CtIP promotes DNA end resection, an early step in homologous recombination repair, and has been found to protect perturbed forks from excessive nucleolytic degradation. However, it remains unknown how CtIP's function in fork protection is regulated. Here, we show that CtIP recruitment to sites of DNA damage and replication stress is impaired upon global inhibition of SUMOylation. We demonstrate that CtIP is a target for modification by SUMO-2 and that this occurs constitutively during S phase. The modification is dependent on the activities of cyclin-dependent kinases and the PI-3-kinase-related kinase ATR on CtIP's carboxyl-terminal region, an interaction with the replication factor PCNA, and the E3 SUMO ligase PIAS4. We also identify residue K578 as a key residue that contributes to CtIP SUMOylation. Functionally, a CtIP mutant where K578 is substituted with a non-SUMOylatable arginine residue is defective in promoting DNA end resection, homologous recombination, and in protecting stalled replication forks from excessive nucleolytic degradation. Our results shed further light on the tightly coordinated regulation of CtIP by SUMOylation in the maintenance of genome stability.
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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 | 0.001 |
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".