The Leaf Epidermome of<i>Catharanthus roseus</i>Reveals Its Biochemical Specialization
Bibliographic record
Abstract
Catharanthus roseus is the sole commercial source of the monoterpenoid indole alkaloids (MIAs), vindoline and catharanthine, components of the commercially important anticancer dimers, vinblastine and vincristine. Carborundum abrasion technique was used to extract leaf epidermis-enriched mRNA, thus sampling the epidermome, or complement, of proteins expressed in the leaf epidermis. Random sequencing of the derived cDNA library established 3655 unique ESTs, composed of 1142 clusters and 2513 singletons. Virtually all known MIA pathway genes were found in this remarkable set of ESTs, while only four known genes were found in the publicly available Catharanthus EST data set. Several novel MIA pathway candidate genes were identified, as demonstrated by the cloning and functional characterization of loganic acid O-methyltransferase involved in secologanin biosynthesis. The pathways for triterpene biosynthesis were also identified, and metabolite analysis showed that oleanane-type triterpenes were localized exclusively to the cuticular wax layer. The pathways for flavonoid and very-long-chain fatty acid biosynthesis were also located in this cell type. The results illuminate the biochemical specialization of Catharanthus leaf epidermis for the production of multiple classes of metabolites. The value and versatility of this EST data set for biochemical and biological analysis of leaf epidermal cells is also discussed.
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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".