UPLC-QTOF-MS-Based Untargeted Study of Metabolites Secreted by Sclerotinia Sclerotiorum Pathogen Under Axenic Condition
Bibliographic record
Abstract
Abstract The stem rot disease has emerged globally as a major disease threat to the productivity and seed quality of oilseed Brassica. The generalist causal pathogen Sclerotinia sclerotiorum (Lib.) de Bary shows large variability in their aggressiveness and pathogenicity. Revealing the metabolic profile and signaling components of the pathogen in host-pathogen interaction are fundamental in understanding host resistance to the disease. In this study, the metabolites released by the pathogenic strains of S. sclerotiorum under the axenic culture have been identified using the untargeted high-resolution UPLC-QTOF-ESI-MS/MS. The analysis of the ethyl acetate extracts of the S. sclerotiorum culture revealed ten major secondary metabolites namely, sclerin, sclerotinin-B, sclerone, melanin, bostrycoidin, botcinin-D, botcinin-A, gliovirin, scleramide, and botcinic acid. The later six metabolites are being reported for the first time in the culture extract of the S. sclerotiorum pathogen. The phylogenetic analysis based on the overlapping and unique informative peaks in the chromatograms, the six S. sclerotiorum strains were grouped into three major clads. The clustering based on metabolic profiles does not substantiate the diversity based on morphology or virulence differences on the host. The findings of the study signified the metabolites secreted under the axenic conditions are varies based on their growth and developmental stages and may not necessarily be the determining factors for their differential aggressiveness and virulence over the host.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".