Discovery of Fusadapamides, Accessory Chromosome-Associated Metabolites Incorporating <scp>l</scp> -2,3-Diaminopropionic Acid in <i>Fusarium poae</i>
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide Genome mining of fungal plant pathogens has uncovered biosynthetic gene clusters encoded on lineage-specific accessory chromosomes, revealing untapped potential for novel natural product discovery by metabolomic assessment of fungal populations. In Fusarium poae, a species contributing to Fusarium head blight on cereals, whole-genome sequencing and comparative metabolomics identified an accessory chromosome-associated biosynthetic gene cluster responsible for the production of a novel family of secondary metabolites, the fusadapamides. These linear tripeptides contain l -2,3-diaminopropionic acid ( l -Dap), a rare nonproteinogenic amino acid not previously reported in fungi. Biochemical and genetic analyses revealed that F. poae synthesizes l -Dap via an accessory chromosome-encoded two-gene module that uniquely utilizes l -alanine as a substrate, diverging from known bacterial and plant l -Dap biosynthesis pathways. While fusadapamide production appears limited within Fusarium, homologous l -Dap biosynthetic modules were identified across diverse ascomycetes, suggesting a broader role in fungal secondary metabolism. This study highlights the power of using untargeted metabolomics at population-scale to uncover accessory chromosome-linked biosynthetic innovations and expands our understanding of fungal natural product biosynthesis.
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 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".