Nucleosome stability measured in situ by automated quantitative imaging
Bibliographic record
Abstract
Current approaches have limitations in providing insight into the functional properties of particular nucleosomes in their native molecular environment. Here we describe a simple and powerful method involving elution of histones using intercalators or salt, to assess stability features dependent on DNA superhelicity and relying mainly on electrostatic interactions, respectively, and measurement of the fraction of histones remaining chromatin-bound in the individual nuclei using histone type- or posttranslational modification- (PTM-) specific antibodies and automated, quantitative imaging. The method has been validated in H3K4me3 ChIP-seq experiments, by the quantitative assessment of chromatin loop relaxation required for nucleosomal destabilization, and by comparative analyses of the intercalator and salt induced release from the nucleosomes of different histones. The accuracy of the assay allowed us to observe examples of strict association between nucleosome stability and PTMs across cell types, differentiation state and throughout the cell-cycle in close to native chromatin context, and resolve ambiguities regarding the destabilizing effect of H2A.X phosphorylation. The advantages of the in situ measuring scenario are demonstrated via the marked effect of DNA nicking on histone eviction that underscores the powerful potential of topological relaxation in the epigenetic regulation of DNA accessibility.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".