A Conifer UDP-Sugar Dependent Glycosyltransferase Contributes to Acetophenone Metabolism and Defense against Insects
Bibliographic record
Abstract
Acetophenones are phenolic compounds involved in the resistance of white spruce (Picea glauca) against spruce budworm (Choristoneura fumiferiana), a major forest pest in North America. The acetophenones pungenol and piceol commonly accumulate in spruce foliage in the form of the corresponding glycosides, pungenin and picein. These glycosides appear to be inactive against the insect but can be cleaved by a spruce β-glucosidase, PgβGLU-1, which releases the active aglycons. The reverse glycosylation reaction was hypothesized to involve a family 1 UDP-sugar dependent glycosyltransferase (UGT) to facilitate acetophenone accumulation in the plant. Metabolite and transcriptome profiling over a developmental time course of white spruce bud burst and shoot growth revealed two UGTs, PgUGT5 and PgUGT5b, that glycosylate pungenol. Recombinant PgUGT5b enzyme produced mostly pungenin, while PgUGT5 produced mostly isopungenin. Both UGTs also were active in vitro on select flavonoids. However, the context of transcript and metabolite accumulation did not support a biological role in flavonoid metabolism but correlated with the formation of pungenin in growing shoots. Transcript levels of PgUGT5b were higher than those of PgUGT5 in needles across different genotypes of white spruce. These results support a role of PgUGT5b in the biosynthesis of the glycosylated acetophenone pungenin in white spruce.
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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) | 0.001 | 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".