<i>In vitro</i> biofilm formation only partially predicts beneficial <i>Pseudomonas fluorescens</i> protection against rhizosphere pathogens
Bibliographic record
Abstract
Abstract Plant roots form associations with both beneficial and pathogenic soil microorganisms. While members of the rhizosphere microbiome can protect against pathogens, the mechanisms are poorly understood. We hypothesized that the ability to form a robust biofilm on the root surface is necessary for the exclusion of pathogens; however, it is not known if the same biofilm formation components required in vitro are necessary in vivo. Pseudomonas fluorescens WCS365 is a beneficial strain that is phylogenetically closely related to an opportunistic pathogen P. fluorescens N2C3 and confers robust protection against P. fluorescens N2C3 in the rhizosphere. We used this plant-mutualist-pathogen model to screen collections of P. fluorescens WCS365 increased a ttachment m utants ( iam ) and s urface a ttachment d efective ( sad ) transposon insertion mutants that form increased or decreased levels of biofilm on an abiotic surface, respectively. We found that while the P. fluorescens WCS365 mutants had altered biofilm formation in vitro , only a subset of these mutants, including those involved in large adhesion protein (Lap) biosynthesis, flagellin biosynthesis and O-antigen biosynthesis, lost protection against P. fluorescens N2C3. We found that the inability of P. fluorescens WCS365 mutants to grow in planta , and the inability to suppress pathogen growth, both partially contributed to loss of plant protection. We did not find a correlation between the extent of biofilm formed in vitro and pathogen protection in planta indicating that biofilm formation on abiotic surfaces may not fully predict pathogen exclusion in planta . Collectively, our work provides insights into mechanisms of biofilm formation and host colonization that shape the outcomes of host-microbe-pathogen interactions.
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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 | 0.001 |
| 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".