A simple alfalfa seedling infection model for <i>Pseudomonas aeruginosa</i> strains associated with cystic fibrosis shows AlgT (sigma-22) and RhlR contribute to pathogenesis
Bibliographic record
Abstract
A sensitive plant infection model was developed to identify virulence factors in nontypeable, alginate overproducing (mucoid) Pseudomonas aeruginosa strains isolated from cystic fibrosis (CF) patients with chronic pulmonary disease. Nontypeable strains with defects in lipopolysaccharide O-side chains are common to CF and often exhibit low virulence in animal models of infection. However, 1,000 such bacteria were enough to show disease symptoms in the alfalfa infection. A typical mucoid CF isolate, FRD1, and its isogenic mutants were tested for alfalfa seedling infection. Although defects in the global regulators Vfr, RpoS, PvdS, or LasR had no discernable effect on virulence, a defect in RhlR reduced the infection frequency by >50%. A defect in alginate biosynthesis resulted in plant disease with >3-fold more bacteria per plant, suggesting that alginate overproduction attenuated bacterial growth in planta. FRD1 derivatives lacking AlgT, a sigma factor required for alginate production, were reduced >50% in the frequency of infection. Thus, AlgT apparently regulates factors in FRD1, besides alginate, important for pathogenesis. In contrast, in a non-CF strain, PAO1, an algT mutation did not affect its virulence on alfalfa. Conversely, PAO1 virulence was reduced in a mucA mutant that overproduced alginate. These observations suggested that mucoid conversion in CF may be driven by a selection for organisms with attenuated virulence or growth in the lung, which promotes a chronic infection. These studies also demonstrated that the wounded alfalfa seedling infection model is a useful tool to identify factors contributing to the persistence of P. aeruginosa in CF.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".