Genome Sequencing and analyses of Two Marine Fungi from the North Sea Unraveled a Plethora of Novel Biosynthetic Gene Clusters
Bibliographic record
Abstract
Marine Fungi are potent secondary metabolite producers. However, limited genetic information are available their biosynthetic gene clusters (BGCs) and their biotechnological applications. To overcome this lack of information, herein, we used next-generation sequencing methods for genome sequencing of two marine fungi, isolated from the German Wadden Sea, namely Calcarisporium sp. KF525 and Pestalotiopsis sp. KF079. The assembled genome size of the marine isolate Calcarisporium sp. KF525 is about 36.8 Mb with 60 BGCs, while Pestalotiopsis sp. KF079 has a genome size of 47.5 Mb harboring 67 BGCs. Of all BGCs, 98% and 97% are novel clusters of Calcarisporium sp. and Pestalotiopsis sp., respectively. Only few of the BGCs were found to be expressed under laboratory conditions by RNA-seq analysis. The vast majority of all BGCs were found to be novel and unique for these two marine fungi. Along with a description of the identified gene clusters, we furthermore present important genomic features and life-style properties of these two fungi. The two novel fungal genomes provide a plethora of new BGCs, which may have biotechnological applications in the future, for example as novel drugs. The genomic characterizations will provide assistance in future genetics and genomic analyses of marine fungi.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".