Concerted SUMO-targeted ubiquitin ligase activities of TOPORS and RNF4 are essential for stress management and cell proliferation
Bibliographic record
Abstract
Protein SUMOylation provides a principal driving force for cellular stress responses, including DNA-protein crosslink (DPC) repair and arsenic-induced PML body degradation. In this study, using genome-scale screens, we identified the human E3 ligase TOPORS as a key effector of SUMO-dependent DPC resolution. We demonstrate that TOPORS promotes DPC repair by functioning as a SUMO-targeted ubiquitin ligase (STUbL), combining ubiquitin ligase activity through its RING domain with poly-SUMO binding via SUMO-interacting motifs, analogous to the STUbL RNF4. Mechanistically, TOPORS is a SUMO1-selective STUbL that complements RNF4 in generating complex ubiquitin landscapes on SUMOylated targets, including DPCs and PML, stimulating efficient p97/VCP unfoldase recruitment and proteasomal degradation. Combined loss of TOPORS and RNF4 is synthetic lethal even in unstressed cells, involving defective clearance of SUMOylated proteins from chromatin accompanied by cell cycle arrest and apoptosis. Our findings establish TOPORS as a STUbL whose parallel action with RNF4 defines a general mechanistic principle in crucial cellular processes governed by direct SUMO-ubiquitin crosstalk.
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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 | 0.000 | 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".