Genome sequence of <i>Aspergillus flavus</i> A7, a marine-derived fungus with antibacterial activity
Bibliographic record
Abstract
Due to the specific properties of the marine environment, marine microorganisms have exclusive physicochemical characteristics that are different from those of terrestrial microorganisms, which can produce various secondary metabolites (SMs) with considerable structural diversity and biological activity. In this study, three strains of coepiphytic Aspergillus with potential antibacterial activities, A7 (Aspergillus flavus), B27 (Aspergillus flavipes), and R12 (Aspergillus sydowii), were isolated from the South China Sea. Via the Illumina MiSeq sequencing platform, the genomes of the three strains were sequenced, and genome comparison showed the highest diversity of the biosynthetic gene clusters (BGCs) in A7. In addition, a comparison of physiological and genomic characteristics between A7 and other A. flavus strains demonstrated the superior environmental adaptability of A7, which is apparently consistent with the genetic richness of BGCs. By assigning reads to known BGCs, putative BGCs were allocated in A7 that corresponded to various SMs, including naphthopyrone, pyranonigrin E, and cyclopiazonic acids. Based on gene homology analysis, we surmise that a region is involved in the biosynthesis of ustiloxin-like RiPPs, a less thoroughly studied SM in fungi. Our results provide genetic information for the investigation of marine Aspergillus spp., which may help to elucidate their chemical diversity and adaptive strategies.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".