Heartwood‐specific transcriptome and metabolite signatures of tropical sandalwood (<i>Santalum album</i>) reveal the final step of (<i>Z</i>)‐santalol fragrance biosynthesis
Bibliographic record
Abstract
Tropical sandalwood (Santalum album) produces one of the world's most highly prized fragrances, which is extracted from mature heartwood. However, in some places such as southern India, natural populations of this slow-growing tree are threatened by over-exploitation. Sandalwood oil contains four major and fragrance-defining sesquiterpenols: (Z)-α-santalol, (Z)-β-santalol, (Z)-epi-β-santalol and (Z)-α-exo-bergamotol. The first committed step in their biosynthesis is catalyzed by a multi-product santalene/bergamotene synthase. Sandalwood cytochromes P450 of the CYP76F sub-family were recently shown to hydroxylate santalenes and bergamotene; however, these enzymes produced mostly (E)-santalols and (E)-α-exo-bergamotol. We hypothesized that different santalene/bergamotene hydroxylases evolved in S. album to stereo-selectively produce (E)- or (Z)-sesquiterpenols, and that genes encoding (Z)-specific P450s contribute to sandalwood oil formation if co-expressed in the heartwood with upstream genes of sesquiterpene biosynthesis. This hypothesis was validated by the discovery of a heartwood-specific transcriptome signature for sesquiterpenoid biosynthesis, including highly expressed SaCYP736A167 transcripts. We characterized SaCYP736A167 as a multi-substrate P450, which stereo-selectively produces (Z)-α-santalol, (Z)-β-santalol, (Z)-epi-β-santalol and (Z)-α-exo-bergamotol, matching authentic sandalwood oil. This work completes the discovery of the biosynthetic enzymes of key components of sandalwood fragrance, and highlights the evolutionary diversification of stereo-selective P450s in sesquiterpenoid biosynthesis. Bioengineering of microbial systems using SaCYP736A167, combined with santalene/bergamotene synthase, has potential for development of alternative industrial production systems for sandalwood oil fragrances.
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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 | 0.001 |
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".