The Efflux Inhibitor Phenylalanine-Arginine Beta-Naphthylamide (PAβN) Permeabilizes the Outer Membrane of Gram-Negative Bacteria
Bibliographic record
Abstract
Active efflux of antimicrobial agents is a primary mechanism by which bacterial pathogens can become multidrug resistant. The combined use of efflux pump inhibitors (EPIs) with pump substrates is under exploration to overcome efflux-mediated multidrug resistance. Phenylalanine-arginine β-naphthylamide (PAβN) is a well-studied EPI that is routinely combined with fluoroquinolone antibiotics, but few studies have assessed its utility in combination with β-lactam antibiotics. The initial goal of this study was to assess the efficacy of β-lactams in combination with PAβN against the opportunistic pathogen, Pseudomonas aeruginosa. PAβN reduced the minimal inhibitory concentrations (MICs) of several β-lactam antibiotics against P. aeruginosa; however, the susceptibility changes were not due entirely to efflux inhibition. Upon PAβN treatment, intracellular levels of the chromosomally-encoded AmpC β-lactamase that inactivates β-lactam antibiotics were significantly reduced and AmpC levels in supernatants correspondingly increased, potentially due to permeabilization of the outer membrane. PAβN treatment caused a significant increase in uptake of 8-anilino-1-naphthylenesulfonic acid, a fluorescent hydrophobic probe, and sensitized P. aeruginosa to bulky antibiotics (e.g. vancomycin) that are normally incapable of crossing the outer membrane, as well as to detergent-like bile salts. Supplementation of growth media with magnesium to stabilize the outer membrane increased MICs in the presence of PAβN and restored resistance to vancomycin. Thus, PAβN permeabilizes bacterial membranes in a concentration-dependent manner at levels below those typically used in combination studies, and this additional mode of action should be considered when using PAβN as a control for efflux studies.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".