Kinetic analysis of histone acetylation turnover and Trichostatin A induced hyper- and hypoacetylation in alfalfa
Bibliographic record
Abstract
Dynamic histone acetylation is a characteristic of chromatin transcription. The first estimates for the rate of acetylation turnover of plants are reported, measured in alfalfa cells by pulse, pulse-chase, and steady-state acetylation labeling. Acetylation turnover half-lives of about 0.5 h were observed by all methods used for histones H3, H4, and H2B. This is consistent with the rate at which changes in gene expression occur in plants. Treatment with histone deacetylase inhibitor Trichostatin A (TSA) induced hyperacetylation at a similar rate. Replacement histone variant H3.2, preferentially localized in highly acetylated chromatin, displayed faster acetyl turnover. Histone H2A with a low level of acetylation was not subject to rapid turnover or hyperacetylation. Patterns of acetate labeling revealed fundamental differences between histone H3 versus histones H4 and H2B. In H3, acetylation of all molecules, limited by lysine methylation, had similar rates, independent of the level of lysine acetylation. Acetylation of histones H4 and H2B was seen in only a fraction of all molecules and involved multiacetylation. Acetylation turnover rates increased from mono- to penta- and hexaacetylated forms, respectively. TSA was an effective inhibitor of alfalfa histone deacetylases in vivo and caused a doubling in steady-state acetylation levels by 4-6 h after addition. However, hyperacetylation was transient due to loss of TSA inhibition. TSA-induced overexpression of cellular deacetylase activity produced hypoacetylation by 18 h treatment with enhanced acetate turnover labeling of alfalfa histones. Thus, application of TSA to change gene expression in vivo in plants may have unexpected consequences.
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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 | 0.001 |
| 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".