Dissecting specialized metabolism in space: A MALDI-MSI atlas of Amaryllidaceae alkaloids in <i>Hippeastrum papilio</i> (Ravenna) Van Scheepen
Bibliographic record
Abstract
Abstract Amaryllidoideae produce specific specialized metabolites known as Amaryllidaceae alkaloids (AAs), extensively studied for their significant pharmacological potential. AAs’ spatial distribution and biosynthesis within plant tissues remain poorly understood. This study investigates organ- and tissue-specific localization in Hippeastrum papilio , from precursors to galanthamine and haemanthamine, using matrix-assisted laser desorption/ionization mass spectrometry imaging. Consistent accumulation of AAs was observed in epidermal and vascular tissues, with leaves exhibiting a uniform distribution across all ages and positions. Bulbs exhibited higher concentrations in the outer-scales and basal-plates, while roots displayed compartmentalized patterns, with galanthamine being uniquely abundant in the vascular bundles. Haemanthamine and galanthamine were detected in high quantities in the leaves’ and bulbs’ mucilage, while precursors were scarce. Multivariate analyses revealed that precursors clustered separately from end-products and were specifically enriched in the middle-scales and apical-leaves of the bulbs. Nonetheless, biosynthetic intermediates were observed in all tissues, indicating widespread AA biosynthesis across all organs. These findings suggest a coordinated metabolic network in H . papilio , which challenges existing hypotheses on organ-specific AA biosynthesis and hints at the transport of end-products. This study refines current models of alkaloid biosynthesis and underscore the value of H. papilio as a promising resource for sustainable production of therapeutic AAs. Highlights MALDI-MSI reveals widespread, tissue-specific alkaloid distribution in Hippeastrum papilio, challenging organ-specific biosynthesis and implicating epidermal and vascular tissues in Amaryllidaceae alkaloid production.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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 teacher head, 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".