Functional genomics uncovers three glucosyltransferases involved in the synthesis of the major sweet glucosides of <i>Stevia rebaudiana</i>
Bibliographic record
Abstract
Stevia rebaudiana leaves accumulate a mixture of at least eight different steviol glycosides. The pattern of glycosylation heavily influences the taste perception of these intensely sweet compounds. The majority of the glycosides are formed by four glucosylation reactions that start with steviol and end with rebaudioside A. The steps involve the addition of glucose to the C-13 hydroxyl of steviol, the transfer of glucose to the C-2' and C-3' of the 13-O-glucose and the addition of glucose to the hydroxyl of the C-4 carboxyl group. We used our collection of ESTs, an UDP-glucosyltransferase (UGT)-specific electronic probe and key word searches to identify candidate genes resident in our collection. Fifty-four expressed sequence tags (ESTs) belonging to 17 clusters were found using this procedure. We isolated full length cDNAs for 12 of the UGTs, cloned them into an expression vector, and produced recombinant enzymes in Escherichia coli. An in vitro glucosyltransferase activity enzyme assay was conducted using quercetin, kaempferol, steviol, steviolmonoside, steviolbioside, and stevioside as sugar acceptors, and (14)C-UDP-glucose as the donor. Thin layer chromatography was used to separate the products and three of the recombinant enzymes produced labelled products that co-migrated with known standards. HPLC and LC-ES/MS were then used to further define those reaction products. We determined that steviol UGTs behave in a regioselective manner and propose a modified pathway for the synthesis of rebaudioside A from steviol.
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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 | 0.001 |
| 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".