Insights into the nature of ichthyotoxins from the Chrysochromulina leadbeateri blooms in Northern Norwegian fjords
Bibliographic record
Abstract
In May–June 2019, the microalga Chrysochromulina leadbeateri caused a massive fish-killing event in several fjords in Northern Norway, resulting in the largest direct impact ever on aquaculture in northern Europe due to toxic algae. Motivated by the fact that no algal toxins have previously been described from C. leadbeateri, we set out to investigate the chemical nature and toxicity of secondary metabolites in extracts of two strains (UIO 393, UIO 394) isolated from the 2019 bloom, as well as one older strain (UIO 035) isolated during a bloom in Northern Norway in 1991. Initial LC–DAD–MS/MS-based molecular networking analysis of the crude MeOH extracts of the cultivated strains showed that their profiles of small organic molecules, including a large number of known lipids, were very similar, suggesting that the same class of toxin(s) were likely the causative agents of the two harmful algal bloom (HAB) events. Next, bioassay-guided fractionation using the RTgill-W1 cell line and metabolomics analysis pointed to a major compound affording [M + H]+ ions at m/z 1399.8333 as a possible toxin, corresponding to a compound with the formula C67H127ClO27. Moreover, our study unveiled a series of minor analogues exhibiting distinct patterns of chlorination and sulfation, together defining a new family of compounds, which we propose to name leadbeaterins. Remarkably, these suspected toxins were detected in situ in samples collected during the 2019 bloom close to Tromsø, thereby consistent with a role in fish kills. The elemental compositions of the putative C. leadbeateri ichthyotoxins strongly indicate them to be long linear polyhydroxylated polyketides, structurally similar to sterolysins reported from a number of dinoflagellates.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".