Monoterpenoid Volatile Biosynthesis in Rose-Scented Geranium (Pelargonium graveolens)
Bibliographic record
Abstract
Rose-scented geraniums (Pelargonium graveolens) are rich in monoterpene containing essential oil that is stored in glandular trichomes. This essential oil has substantial variation in its composition with its value directly correlated to the ratio of geraniol to p-menthane monoterpenes. Based on whole plant 13CO2 labeling experiments, at least two biosynthetic pathways contribute to the monoterpenes that are stored in glandular trichomes. Distinct chemotypic groups favor either the accumulation of cyclic p-menthanes such as isomenthone or acyclic monoterpene alcohols such as geraniol and citronellol. This metabolic split between ‘mint-like’ p-menthanes and ‘rose-like’ acyclic monoterpene alcohols reflects the relative contributions of two compartmentally separated monoterpenoid biosynthetic pathways, a scenario which departs from the classical view of plastids as the sole source of monoterpenoid backbones. In this species, p-menthane skeletons are produced in the plastid from geranyl diphosphate (GDP) derived from the 2C-methyl-D-erythritol-4-phosphate (MEP) pathway in a pathway resembling monoterpene biosynthesis in most plant species. However, the acyclic monoterpene alcohols in P. graveolens are produced in the cytosol without the participation of a conventional monoterpene synthase. Instead, a cytosolic Nudix hydrolase acting on an atypical cytosolic pool of GDP forms geranyl monophosphate as a substrate for a phosphatase to produce geraniol directly in the cytosol. Biochemical characterization showed that a cytosolic, farnesyl diphosphate synthase-like cDNA encodes a multi-product enzyme that produces GDP which supplies substrate to this cytosolic geraniol pathway. The identification of distinct monoterpene pathways in the cytosol and plastid of these geraniums offers insight into essential oil biosynthesis in glandular trichome bearing plants.
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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".