AlgW regulates multiple <i>Pseudomonas syringae</i> virulence strategies
Bibliographic record
Abstract
Gram-negative bacterial pathogens have evolved a number of virulence-promoting strategies including the production of extracellular polysaccharides such as alginate and the injection of effector proteins into host cells. The induction of these virulence mechanisms can be associated with concomitant downregulation of the abundance of proteins that trigger the host immune system, such as bacterial flagellin. In Pseudomonas syringae, we observed that bacterial motility and the abundance of flagellin were significantly reduced under conditions that induce the type III secretion system. To identify genes involved in this negative regulation, we conducted a forward genetic screen with P. syringae pv. maculicola ES4326 using motility as a screening phenotype. We identified the periplasmic protease AlgW as a key negative regulator of flagellin abundance that also positively regulates alginate biosynthesis and the type III secretion system. We also demonstrate that AlgW constitutes a major virulence determinant of P. syringae required to dampen plant immune responses. Our findings support the conclusion that P. syringae co-ordinately regulates virulence strategies through AlgW in order to effectively suppress host immunity.
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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 | 0.000 |
| 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".