A putative de-<i>N</i>-acetylase of the PIG-L superfamily affects fluoroquinolone tolerance in<i>Pseudomonas aeruginosa</i>
Bibliographic record
Abstract
A major cause of treatment failure of infections caused by Pseudomonas aeruginosa is the presence of antibiotic-insensitive persister cells. The mechanism of persister formation in P. aeruginosa is largely unknown, and so far, only few genetic determinants have been linked to P. aeruginosa persistence. Based on a previous high-throughput screening, we here present dnpA (de-N-acetylase involved in persistence; gene locus PA14_66140/PA5002) as a new gene involved in noninherited fluoroquinolone tolerance in P. aeruginosa. Fluoroquinolone tolerance of a dnpA mutant is strongly reduced both in planktonic culture and in a biofilm model, whereas overexpression of dnpA in the wild-type strain increases the persister fraction. In addition, the susceptibility of the dnpA mutant to different classes of antibiotics is not affected. dnpA is part of the conserved LPS core oligosaccharide biosynthesis gene cluster. Based on primary sequence analysis, we predict that DnpA is a de-N-acetylase, acting on an unidentified substrate. Site-directed mutagenesis suggests that this enzymatic activity is essential for DnpA-mediated persistence. A transcriptome analysis indicates that DnpA primarily affects the expression of genes involved in surface-associated processes. We discuss the implications of these findings for future antipersister therapies targeted at chronic P. aeruginosa infections.
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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 | 0.000 | 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) | 0.000 | 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".