Adenosine Kinase Contributes to Cytokinin Interconversion in Arabidopsis
Bibliographic record
Abstract
Purine salvage enzymes have been implicated, but not proven, to be involved in the interconversion of cytokinin (CK) bases, ribosides, and nucleotides. Here, we use Arabidopsis (Arabidopsis thaliana) lines silenced in adenosine kinase (ADK) expression to understand the contributions of this enzyme activity to in vivo CK metabolism. Both small interfering RNA- and artificial microRNA-mediated silencing of ADK led to impaired root growth, small, crinkled rosette leaves, and reduced apical dominance. Further examination of ADK-deficient roots and leaves revealed their irregular cell division. Root tips had uneven arrangements of root cap cells, reduced meristem sizes, and enlarged cells in the elongation zone; rosette leaves exhibited decreased cell size but increased cell abundance. Expression patterns of the cyclinB1;1::β-glucuronidase and Arabidopsis Response Regulator5::β-glucuronidase reporters in the ADK-deficient background were consistent with altered cell division and an increase in CK activity, respectively. In vivo feeding of ADK-deficient leaves with radiolabeled CK ribosides of isopentenyladenosine and zeatin showed a decreased flux into the corresponding CK nucleotides. Comprehensive high-performance liquid chromatography-tandem mass spectrometry analysis detected significantly higher levels of active CK ribosides in both sense ADK and artificial microADK. Taken together, these metabolic and phenotypic analyses of ADK-deficient lines indicate that ADK contributes to CK homeostasis in vivo.
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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".