Untargeted metabolomics screening reveals unique secondary metabolite production from Alternaria section Alternaria
Bibliographic record
Abstract
Alternaria section Alternaria is comprised of many species that infect a broad diversity of important crop plants and cause post-harvest spoilage. Alternaria section Alternaria species, such as A. alternata and A. arborescens, are prolific producers of secondary metabolites that act as virulence factors of disease and are mycotoxins that accumulate in infected tissues—metabolites that can vary in their spectrum of production between individuals from the same fungal species. Untargeted metabolomics profiling of secondary metabolite production using mass spectrometry is an effective means to detect phenotypic anomalies in secondary metabolism within a species. Secondary metabolite phenotypes from 36 Alternaria section Alternaria isolates were constructed to observe frequency of production patterns. A clear and unique mass feature pattern was observed for three of the strains that were linked with the production of the dehydrocurvularin family of toxins and associated detoxification products. Examination of corresponding genomes revealed the presence of the dehydrocurvularin biosynthesis gene cluster associated with a sub-telomeric accessory region. A comparison of sequence similarity and occurrences of the dehydrocurvularin biosynthetic gene cluster within Pleosporalean fungi is presented and 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) | 0.000 | 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".