A genome-wide screen identifies genes in rhizosphere-associated <i>Pseudomonas</i> required to evade plant defenses
Bibliographic record
Abstract
Abstract Pseudomonas fluorescens and related plant root- (“rhizosphere”) associated species contribute to plant health by modulating defenses and facilitating nutrient uptake. To identify bacterial fitness determinants in the rhizosphere of the model plant Arabidopsis thaliana , we performed a Tn-Seq screen using the biocontrol and growth-promoting strain Pseudomonas sp. WCS365. The screen, which was performed in parallel on wild-type and an immunocompromised Arabidopsis , identified 231 genes that positively affect fitness in the rhizosphere of wild-type plants. A subset of these genes negatively affect fitness in the rhizosphere of immunocompromised plants. We postulated that these genes might be involved in avoiding plant defenses and verified 7 Pseudomonas sp. WCS365 candidate genes by generating clean deletions. We found that two of these deletion strains, Δ morA (encodes a putative diguanylate cyclase/phosphodiesterase) and Δ spuC (encodes a putrescine aminotransferase) formed enhanced biofilms and inhibited plant growth. Inhibition of plant growth by Δ spuC and Δ morA was the result of pattern triggered immunity (PTI) as measured by induction of an Arabidopsis PTI reporter and FLS2/BAK1 -dependent inhibition of plant growth. We found that MorA acts as a phosphodiesterase to inhibit biofilm formation suggesting a possible role in biofilm dispersal. We found that both putrescine and its precursor arginine promote biofilm formation that is enhanced in the Δ spuC mutant, which cannot break down putrescine suggesting that putrescine might serve as a signaling molecule in the rhizosphere. Collectively, this work identified novel bacterial factors required to evade plant defenses in the rhizosphere. Importance While rhizosphere bacteria hold the potential to improve plant health and fitness, little is known about the bacterial genes required to evade host immunity. Using a model system consisting of Arabidopsis and a beneficial Pseudomonas sp. isolate, we identified bacterial genes required for both rhizosphere fitness and for evading host immune responses. This work advances our understanding of how evasion of host defenses contributes to survival in the rhizosphere.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".