Pseudomonas entomophila 23S Produces a Novel Antagonistic Compound against Clavibacter michiganensis subsp. michiganensis, a Pathogen of Tomato Bacterial Canker
Bibliographic record
Abstract
Biopesticides, which consist of antagonistic microorganisms, or the bioactive compounds they produce offer attractive alternatives to synthetic agrochemicals as a means of reducing plant diseases in crop production systems. In our previous study, a strain of Pseudomonas entomophila 23S was reported to have a strong antagonistic activity toward Clavibacter michiganensis subsp. michiganensis (Cmm), a pathogen of tomato bacterial canker disease, which causes serious damage to the tomato production industry. This study focused on purification and characterization of the anti-Cmm compound(s) produced by P. entomophila 23S. The cell-free supernatant was first subjected to butanol extraction, fractioned by solid-phase extraction (SPE), and purified by high-performance liquid-chromatography (HPLC). The semi-preparative purified compounds retained anti-Cmm activity. These compounds were then characterized by liquid chromatography coupled with high-resolution tandem mass spectrometry (LC-HRMS/MS) and nuclear magnetic resonance (NMR). Two anti-Cmm compounds, C15H16N2O and C16H18N2O, were isolated by this procedure. From the LC/MS spectra, the compounds were predicted to have an isoquinoline ring, the presence of which was confirmed by NMR. The compounds differed with respect to the presence of a methyl group in a side chain. In addition, P. entomophila 23S grown in different culture media produced the greatest amounts of these anti-Cmm compounds when in Nutrient Broth (NB), where bacterial growth was the slowest. NB composition is more favorable in stimulating P. entomophila 23S to produce higher amounts of these anti-Cmm compounds.
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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".