Targeted Metabolite Fingerprints of Thirteen Gambierdiscus, Five Coolia and Two Fukuyoa Species
Bibliographic record
Abstract
The genus Gambierdiscus produces an array of bioactive hydrophilic and lipophilic secondary metabolites that range in mode of action and toxicity. In this study, the metabolite fingerprint was mapped for thirteen Gambierdiscus, five Coolia and two Fukuyoa species (34 isolates) by assessing the production of 56 characterised secondary metabolites. Gambierdiscus polynesiensis was the only species to produce Pacific-ciguatoxin-3B (P-CTX3B), P-CTX3C, iso-P-CTX3B/C, P-CTX4A, P-CTX4B and iso-P-CTX4A/B. G. australes produced maitotoxin-1 (MTX-1) and MTX-5, G. cheloniae produced MTX-6 and G. honu produced MTX-7. Ubiquitous production of 44-methylgambierone was observed amongst all the Gambierdiscus isolates, with nine species also producing gambierone. Additional gambierone analogues, including anhydrogambierone (tentatively described herein), were also detected in all Gambierdiscus species, two Coolia and two Fukuyoa species. Gambieroxide was detected in G. lewisii and G. pacificus and gambieric acid A was detected in ten Gambierdiscus species, with G. australes (CAWD381) being the only isolate to produce gambieric acids A–D. This study has demonstrated that the isolates tested to date produce the known CTXs or MTXs, but not both, and highlighted several species that produced ‘unknown’ compounds displaying characteristics of cyclic polyethers, which will be the focus of future compound discovery efforts.
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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 | 0.001 | 0.001 |
| 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".