Diversity of phytobeneficial traits revealed by whole‐genome analysis of worldwide‐isolated phenazine‐producing <i>Pseudomonas</i> spp.
Bibliographic record
Abstract
Plant-beneficial Pseudomonas spp. competitively colonize the rhizosphere and display plant-growth promotion and/or disease-suppression activities. Some strains within the P. fluorescens species complex produce phenazine derivatives, such as phenazine-1-carboxylic acid. These antimicrobial compounds are broadly inhibitory to numerous soil-dwelling plant pathogens and play a role in the ecological competence of phenazine-producing Pseudomonas spp. We assembled a collection encompassing 63 strains representative of the worldwide diversity of plant-beneficial phenazine-producing Pseudomonas spp. In this study, we report the sequencing of 58 complete genomes using PacBio RS II sequencing technology. Distributed among four subgroups within the P. fluorescens species complex, the diversity of our collection is reflected by the large pangenome which accounts for 25 413 protein-coding genes. We identified genes and clusters encoding for numerous phytobeneficial traits, including antibiotics, siderophores and cyclic lipopeptides biosynthesis, some of which were previously unknown in these microorganisms. Finally, we gained insight into the evolutionary history of the phenazine biosynthetic operon. Given its diverse genomic context, it is likely that this operon was relocated several times during Pseudomonas evolution. Our findings acknowledge the tremendous diversity of plant-beneficial phenazine-producing Pseudomonas spp., paving the way for comparative analyses to identify new genetic determinants involved in biocontrol, plant-growth promotion and rhizosphere competence.
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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 | 0.001 |
| 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 | 0.000 |
| 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".