Molybdate transporter ModABC is important for Pseudomonas aeruginosa chronic lung infection
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Mechanisms underlying the success of Pseudomonas aeruginosa in chronic lung infection among cystic fibrosis (CF) patients are poorly defined. The modA gene was previously linked to in vivo competitiveness of P. aeruginosa by a genetic screening in the rat lung. This gene encodes a subunit of transporter ModABC, which is responsible for extracellular uptake of molybdate. This compound is essential for molybdoenzymes, including nitrate reductases. Since anaerobic growth conditions are known to occur during CF chronic lung infection, inactivation of a molybdate transporter could inhibit proliferation through the inactivation of denitrification enzymes. Hence, we performed phenotypic characterization of a modA mutant strain obtained by signature-tagged mutagenesis (STM_modA) and assessed its virulence in vivo with two host models. RESULTS: The STM_modA mutant was in fact defective for anaerobic growth and unable to use nitrates in the growth medium for anaerobic respiration. Bacterial growth and nitrate usage were restored when the medium was supplemented with molybdate. Most significantly, the mutant strain showed reduced virulence compared to wild-type strain PAO1 according to a competitive index in the rat model of chronic lung infection and a predation assay with Dictyostelium discoideum amoebae. As the latter took place in aerobic conditions, the in vivo impact of the mutation in modA appears to extend beyond its effect on anaerobic growth. CONCLUSIONS: These results support the modABC-encoded transporter as important for the pathogenesis of P. aeruginosa, and suggest that enzymatic machinery implicated in anaerobic growth during chronic lung infection in CF merits further investigation as a potential target for therapeutic intervention.
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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 | 0.000 |
| 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) | 0.000 | 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 it