Zinc controls PML nuclear body formation through regulation of a paralog specific auto-inhibition in SUMO1
Bibliographic record
Abstract
SUMO proteins are important regulators of many key cellular functions in part through their ability to form interactions with other proteins containing SUMO interacting motifs (SIMs). One characteristic feature of all SUMO proteins is the presence of a highly divergent intrinsically disordered region at their N-terminus. In this study, we examine the role of this N-terminal region of SUMO proteins in SUMO-SIM interactions required for the formation of nuclear bodies by the promyelocytic leukemia (PML) protein (PML-NBs). We demonstrate that the N-terminal region of SUMO1 functions in a paralog specific manner as an auto-inhibition domain by blocking its binding to the phosphorylated SIMs of PML and Daxx. Interestingly, we find that this auto-inhibition in SUMO1 is relieved by zinc, and structurally show that zinc stabilizes the complex between SUMO1 and a phospho-mimetic form of the SIM of PML. In addition, we demonstrate that increasing cellular zinc levels enhances PML-NB formation in senescent cells. Taken together, these results provide important insights into a paralog specific function of SUMO1, and suggest that zinc levels could play a crucial role in regulating SUMO1-SIM interactions required for PML-NB formation and function.
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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".