Mycin and peptin lipopeptides are major contributors to the biocontrol of Sclerotinia sclerotiorum by Pseudomonas mediterranea
Bibliographic record
Abstract
The fungal pathogen Sclerotinia sclerotiorum is the causal agent of the white mold disease in several economically important crops. Control methods are currently limited to the use of synthetic fungicides and resistance to these fungicides is increasing. Biological control may prove to be a more sustainable control strategy for this disease, as well as other fungal diseases. In a previous study, our team identified Pseudomonas strains that can reduce white mold symptom severity in lettuce. The exact mechanisms underlying this biocontrol were not explored, but the biocontrol activity of these Pseudomonas strains strongly correlated with the presence of three gene clusters involved in the biosynthesis of the lipopeptides brabantamides, corpeptin, and thanamycin. In this study, to better understand the mechanisms at play and progress towards the development of a Pseudomonas -based biocontrol inoculant against S. sclerotiorum , key genes involved in the biosynthesis of these lipopeptides were knocked out in the genome of P. mediterranea B21-060. The impact that the loss of function had on the ability of P. mediterranea to inhibit the growth or S. sclerotiorum in vitro and control white mold development in planta was evaluated. Production of corpeptin and thanamycin by P. mediterranea was required to repress the growth of S. sclerotiorum and suppress white mold symptom development in lettuce. Furthermore, corpeptin and thanamycin were also identified as key inhibitory molecules against Botrytis cinerea and Rhizoctonia solani , two other important fungal pathogens. This study highlights the potential of corpeptin and thanamycin in Pseudomonas-mediated control of different fungal plant diseases.
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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 | 0.000 |
| 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".