Isolation and Characterization of <i>Bacillus velezensis</i> EB14, an Endophytic Bacterial Strain Antagonistic to Poplar Stem Canker Pathogen <i>Sphaerulina musiva</i> and Its Interactions with the Endophytic Fungal Microbiome in Poplar
Bibliographic record
Abstract
Species of the genus Populus (commonly known as poplar) are one of the most widely used groups of forest trees in North America and Europe, and play a significant ecological role as a pioneer species in boreal forests and as a dominant species in the riparian forests that serve as wildlife habitats and watersheds. Natural and artificial hybrids of poplar are being extensively used in commercial plantations. However, many hybrid poplar trees are susceptible to Sphaerulina musiva, the pathogenic fungus that causes leaf spots and stem cankers and limits the utility of hybrid poplar as a plantation tree. We isolated an endophytic bacterial strain, Bacillus velezensis EB14, from a Populus hybrid which showed a strong antifungal activity against S. musiva. Through mass spectrometric analyses of cocultured B. velezensis EB14 and S. musiva, we identified five cyclic lipopeptides produced by B. velezensis EB14: iturin A1, iturin A2, iturin A9, subtulene A, and fengycin. In addition, B. velezensis EB14 produced four major unidentified compounds in cocultivation with S. musiva. The cyclopeptide production by B. velezensis EB14 was more pronounced (20- to 1,000-fold) in the cocultured plates due to elicitation by S. musiva. We also discovered that the native endophytic B. velezensis EB14 strain exhibited different levels of interactions against the endophytic fungal microbiomes of Populus sp. Overall, our results indicate that B. velezensis EB14 strain as a promising biocontrol agent that could be used against stem canker and leaf spot diseases caused by S. musiva in poplar plantations. [Formula: see text] Copyright © 2021 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license .
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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 | 0.000 |
| 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 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".