Untargeted and targeted metabolomics to understand plant growth regulation and evolution in Wollemi pine (<i>Wollemia nobilis</i>)
Bibliographic record
Abstract
Wollemi pine ( Wollemia nobilis (Jones, Hill, Allen)) is a living fossil, known only through fossil records until its 1994 discovery in Australia. Wollemi Pine is closely related to Norfolk Island pine ( Araucaria heterophylla (Salisb.) Franco), making it an interesting system to study metabolic evolution. We employed untargeted liquid chromatography mass spectrometry-based (LC-MS) metabolomics, with chemometrics, pathway analysis, and our novel plant growth regulator (PGR) putative identification tool (HormonomicsDB), to explore the metabolomes of both species. We identified PGR conjugates and found cytokinin, zeatin, and brassinosteroid pathways to be overrepresented in Wollemi pine tissues, suggesting these PGRs play an important role in its survival. Melatonin, a proposed ancient and stress-related PGR, was not identified in untargeted analysis of either species. Based on our untargeted results, we employed targeted LC-MS to quantify brassinolide and confirm the absence or presence of melatonin in Wollemi and Norfolk Island pine. Both species had similar concentrations of brassinolide, while Wollemi pine had significantly higher melatonin levels than Norfolk Island pine. High levels of melatonin and brassinolide in Wollemi pine supports the hypothesis that these are ancient PGRs that conferred an evolutionary advantage in Wollemi, allowing it to persist.
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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".