Surfactin and Spo0A-Dependent Antagonism by Bacillus subtilis Strain UD1022 against Medicago sativa Phytopathogens
Bibliographic record
Abstract
Plant growth-promoting rhizobacteria (PGPR) such as the root colonizers Bacillus spp. may be ideal alternatives to chemical crop treatments. This work sought to extend the application of the broadly active PGPR UD1022 to Medicago sativa (alfalfa). Alfalfa is susceptible to many phytopathogens resulting in losses of crop yield and nutrient value. UD1022 was cocultured with four alfalfa pathogen strains to test antagonism. We found UD1022 to be directly antagonistic toward Collectotrichum trifolii, Ascochyta medicaginicola (formerly Phoma medicaginis), and Phytophthora medicaginis, and not toward Fusarium oxysporum f. sp. medicaginis. Using mutant UD1022 strains lacking genes in the nonribosomal peptide (NRP) and biofilm pathways, we tested antagonism against A. medicaginicola StC 306-5 and P. medicaginis A2A1. The NRP surfactin may have a role in the antagonism toward the ascomycete StC 306-5. Antagonism toward A2A1 may be influenced by B. subtilis biofilm pathway components. The B. subtilis central regulator of both surfactin and biofilm pathways Spo0A was required for the antagonism of both phytopathogens. The results of this study indicate that the PGPR UD1022 would be a good candidate for further investigations into its antagonistic activities against C. trifolii, A. medicaginicola, and P. medicaginis in plant and field studies.
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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".