Characterization of Bacillus velezensis 32a metabolites and their synergistic bioactivity against crown gall disease
Bibliographic record
Abstract
Crown gall disease caused by Agrobacterium tumefaciens is considered to be the main bacterial threat of stone fruit plants in Mediterranean countries. In a previous study, Bacillus velezensis strain 32a was isolated from Tunisian rhizosphere soil and revealed high antagonistic potential against A. tumefaciens strains. In order to better characterize the antagonistic activity of this strain against this important plant pathogen, the production of secondary metabolites was analyzed using liquid chromatography coupled with mass spectrometry. The results revealed the production of different compounds identified as surfactins, fengycins, iturins and bacillibactin belonging to the lipopeptide group, three polyketides (macrolactins, oxydifficidin and bacillaenes), bacilysin and its chlorinated derivative; chlorotetaine. The involvement of lipopeptides in this antagonistic activity was ruled out by performing agar and broth dilution tests with pure molecules. Thus, the construction of B. velezensis 32a mutants defective in polyketides and bacilysin biosynthesis and their antagonistic activity was performed and compared to a set of derivative mutants of a comparable strain, B. velezensis GA1. The defective difficidin mutants (△dfnA and △dfnD) were unable to inhibit the growth of A. tumefaciens, indicating the high-level contribution of difficidin in the antagonism process. While the macrolactin deficient mutant (∆mlnA) slightly decreased the activity, suggesting a synergetic effect with difficidin. Remarkably, the mutant △dhbC only deficient in bacillibactin production showed significant reduction in its capacity to inhibit the growth of Agrobacterium.Taken collectively, our results showed the strong synergetic effect of difficidin and macrolactins and the significant implication of siderophore to manage crown gall disease.
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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".