Innate immunity can distinguish beneficial from pathogenic rhizosphere microbiota
Bibliographic record
Abstract
Abstract For optimal growth and development, hosts depend on their ability to promote healthy symbiotic interactions while restricting pathogen growth. To ask whether hosts can distinguish phylogenetically similar pathogens and beneficial bacteria, we used two closely related plant-associated strains of Pseudomonas fluorescens where one is beneficial and the other exhibits toxin-dependent virulence. We show that while the two strains co-exist in vitro , the beneficial outcompetes that pathogen in planta . Using several readouts for plant innate immunity, we found that the beneficial and pathogenic strains elicit mechanistically distinct immune responses that occur in distinct root compartments. We show that while both the pathogenic and beneficial bacterial have plant recognizable MAMPs, the pathogen uniquely induces MAMP-independent immune responses. We found that the pathogen induces both a toxin-independent and a unique toxin-dependent defense response that remains intact in immune signaling mutants including bak1/bkk1 and npr1/4D . We conclude that hosts can distinguish between phylogenetically similar microbes.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".