Chromatin Contributes to Structural Integrity of Promyelocytic Leukemia Bodies through a SUMO-1-independent Mechanism
Bibliographic record
Abstract
Promyelocytic leukemia (PML) protein is implicated in transcriptional regulation, apoptosis, DNA repair, and tumor suppression. It is not known, however, whether PML and other components of PML bodies function within the vicinity of the bodies or elsewhere in the nucleoplasm. In this study, we demonstrate that chromatin organization around PML bodies influences their morphology, dynamics, and structural integrity by a SUMO-1-independent mechanism. Following transcriptional inhibition and during early apoptosis, chromatin retracts from the periphery of PML bodies, coinciding with the formation of new PML-containing structures through fission of supramolecular PML-containing microbodies. Both fission and fusion of microbodies with parental PML bodies indicate a loss of structural integrity of the bodies, dependent on the state of the surrounding chromatin. This is supported by the observation that treatment of live cells with DNase I could reproduce the structural instability of PML bodies. In addition, PML bodies, which are normally surrounded by chromatin and are positionally stable, become more dynamic following these treatments, presumably due to the loss of chromatin contacts. Overexpression of SUMO-1, a modification required for PML body formation, did not prevent PML body fission, indicating that chromatin-based integrity of PML body structure occurs through a SUMO-1-independent mechanism.
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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".