Functions of Lipopeptides Bacillomycin D and Fengycin in Antagonism of <i>Bacillus amyloliquefaciens</i> C06 towards <i>Monilinia fructicola</i>
Bibliographic record
Abstract
In previous studies, Bacillus amyloliquefaciens C06 has been proven to be effective in controlling brown rot of stone fruit caused by Monilinia fructicola. When tested in vitro, cell-free filtrate of B. amyloliquefaciens C06 significantly inhibited mycelial growth and conidial germination of the fungal pathogen. This study aimed to determine the role of the antifungal compound(s) in the cell-free filtrate of B. amyloliquefaciens C06 by an approach combining a DNA-based suppression subtractive hybridization (SSH) method with MALDI-TOF-MS analysis. It was demonstrated that B. amyloliquefaciens C06 harbored two genes, bmyC and fenD, involved in biosynthesis of bacillomycin D and fengycin, two lipopeptides belonging to the iturin and fengycin family, respectively. To determine the roles of bacillomycin D and fengycin of B. amyloliquefaciens C06 in suppressing M. fructicola, the mutants of B. amyloliquefaciens C06 deficient in producing bacillomy- cin D, fengycin or both were constructed, and evaluated in vitro together with the wild-type B. amyloliquefaciens C06. The results indicated that bacillomycin D and fengycin jointly contributed to the inhibition of conidial germination of M. fructicola, and fengycin played a major role in suppressing mycelial growth of the fungal pathogen.
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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) | 0.001 | 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".