Sustaining <i>S</i>‐adenosyl‐<scp>l</scp>‐methionine‐dependent methyltransferase activity in plant cells
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Many biochemical reactions in plants involve the transfer of a methyl group from S ‐adenosyl‐ l ‐methionine (SAM). The transfer of the methyl group from SAM generates S ‐adenosyl‐ l ‐homocysteine (SAH), a potent inhibitor of SAM‐dependent methyltransferases (MTs). To mitigate the toxic effects of SAH on MT activity, SAH is removed by SAH hydrolase (SAHH, EC 3.3.1.1) in a reaction generating homocysteine and adenosine (Ado). However, SAHH catalyzes a reversible reaction that is favored to move in the direction of SAH hydrolysis only by removal of these products. Removal of Ado is reported to exert a greater influence on promoting SAH hydrolysis. Whereas animals appear to rely upon Ado deaminase (EC 3.5.4.4) to catabolize Ado, plants appear to use adenosine kinase (EC 2.7.1.20) for this important role. Compounds undergoing methylation represent a broad spectrum of chemically diverse substrates ranging from nucleic acids, lipids and cell wall components to comparatively simpler amines, alcohols and metal halides. Given the diverse nature of methyl acceptor compounds, it is very likely that the demand for SAM synthesis and SAH removal changes both temporally and spatially during the course of plant growth and development. Plants also use SAM as a precursor for the synthesis of ethylene, polyamines, biotin and nicotianamine. These uses are also expected to undergo changes reflective of the metabolic activities of different plants, plant organs, or cells. This review examines the various uses of SAM in plants and addresses how they allocate this resource to satisfy potentially competing needs.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it