Harnessing the genomic diversity of Pseudomonas strains against lettuce bacterial pathogens
Bibliographic record
Abstract
Lettuce is a major vegetable crop worldwide that is affected by numerous bacterial pathogens, including Xanthomonas hortorum pv. vitians, Pseudomonas cichorii, and Pectobacterium carotovorum. Control methods are scarce and not always effective. To develop new and sustainable approaches to contain these pathogens, we screened more than 1,200 plant-associated Pseudomonas strains retrieved from agricultural soils for their in vitro antagonistic capabilities against the three bacterial pathogens under study. Thirty-five Pseudomonas strains significantly inhibited some or all three pathogens. Their genomes were fully sequenced and annotated. These strains belong to the P. fluorescens and P. putida phylogenomic groups and are distributed in at least 27 species, including 15 validly described species. They harbor numerous genes and clusters of genes known to be involved in plant-bacteria interactions, microbial competition, and biocontrol. Strains in the P. putida group displayed on average better inhibition abilities than strains in the P. fluorescens group. They carry genes and biosynthetic clusters mostly absent in the latter strains that are involved in the production of secondary metabolites such as 7-hydroxytropolone, putisolvins, pyochelin, and xantholysin-like and pseudomonine-like compounds. The presence of genes involved in the biosynthesis of type VI secretion systems, tailocins, and hydrogen cyanide also positively correlated with the strains’ overall inhibition abilities observed against the three pathogens. These results show promise for the development of biocontrol products against lettuce bacterial pathogens, provide insights on some of the potential biocontrol mechanisms involved, and contribute to public Pseudomonas genome databases, including quality genome sequences on some poorly represented species.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".