Identification and characterization of isoflavonoid specific glycosyltransferase and malonyltransferase from soybean seeds
Bibliographic record
Abstract
Isoflavonoids are a diverse group of biologically active natural products that accumulate in soybean seeds during development. The majority of isoflavonoids are accumulated in the form of their glyco- and malonyl-conjugates in soybean seeds. The conjugation step confers stability and solubility to isoflavone aglycones enabling their compartmentalization to vacuoles or transport to the site of accumulation. A functional genomic approach was used to identify isoflavonoid specific glycosyltransferase (UGT) and malonyltransferase (MT) from soybean (Glycine max) seeds. An expressed sequence tag database for soybean was searched by key words to make a list of candidate genes. The full-length cDNAs for candidate UGTs and MTs were obtained and cloned into an expression vector for the production of recombinant enzymes. The in vitro enzymatic activity assays were conducted for recombinant UGTs and MTs using uridine diphosphate glucose and malonyl CoA, respectively, as donors with isoflavone substrates. Among several recombinant enzymes, UGT73F2 showed glycosylation activity towards all three soybean isoflavone aglycones and GmMT7 exhibited malonylation activity towards isoflavone glycosides. The subcellular localization study revealed both UGT73F2 and GmMT7 to be in the cytoplasm. The transcripts and protein accumulation patterns for UGT73F2 and GmMT7 genes have provided further support for their in planta function.
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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) | 0.000 | 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 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".