Multidrug Adaptive Resistance of Pseudomonas aeruginosa Swarming Cells

Abstract

Swarming surface motility is a complex adaptation leading to multidrug antibiotic resistance and virulence factor production in Pseudomonas aeruginosa Here, we expanded previous studies to demonstrate that under swarming conditions, P. aeruginosa PA14 is more resistant to multiple antibiotics, including aminoglycosides, β-lactams, chloramphenicol, ciprofloxacin, tetracycline, trimethoprim, and macrolides, than swimming cells, but is not more resistant to polymyxin B. We investigated the mechanism(s) of swarming-mediated antibiotic resistance by examining the transcriptomes of swarming cells and swarming cells treated with tobramycin by transcriptomics (RNA-Seq) and reverse transcriptase quantitative PCR (qRT-PCR). RNA-Seq of swarming cells (versus swimming) revealed 1,581 dysregulated genes, including 104 transcriptional regulators, two-component systems, and sigma factors, numerous upregulated virulence and iron acquisition factors, and downregulated ribosomal genes. Strain PA14 mutants in resistome genes that were dysregulated under swarming conditions were tested for their ability to swarm in the presence of tobramycin. In total, 41 mutants in genes dysregulated under swarming conditions were shown to be more resistant to tobramycin under swarming conditions, indicating that swarming-mediated tobramycin resistance was multideterminant. Focusing on two genes downregulated under swarming conditions, both prtN and wbpW mutants were more resistant to tobramycin, while the prtN mutant was additionally resistant to trimethoprim under swarming conditions; complementation of these mutants restored susceptibility. RNA-Seq of swarming cells treated with subinhibitory concentrations of tobramycin revealed the upregulation of the multidrug efflux pump MexXY and downregulation of virulence factors.

Keywords: Pseudomonas aeruginosa; RNA-Seq; antibiotic resistance; swarming motility; tobramycin.

FIG 1

Swarming bacteria exhibited heightened resistance to most antibiotic classes. (Top) P. aeruginosa PA14 grown to mid-log phase was used to inoculate BM2 agar plates (0.3% agar for swimming, 0.4% for swarming, and 1.5% for spread plates) with antibiotic discs. After overnight incubation, the distances between the antibiotic discs and nearest visible growth were measured as the zones of inhibition. Averages ± standard errors are depicted. Statistically significant differences were determined by analysis of variance (ANOVA) using GraphPad Prism; n ≥ 3. (Bottom) Zone of inhibition assay for PA14 WT using tobramycin discs. *, P ≤ 0.05; **, P ≤ 0.01; ***, P ≤ 0.001; ****, P ≤ 0.0001; ns, not significant.

FIG 2

Tobramycin kill curve showing that swarming cells survived better than swimming cells in the presence of tobramycin. Averages ± standard errors are depicted; n = 3.

FIG 3

Antibiotic susceptibility of PA14 mutants under swarming conditions using the disc diffusion method and 0.5% agar. Means ± standard errors are depicted. Statistically significant differences were determined by paired t tests using GraphPad Prism; n ≥ 4. *, P ≤ 0.05; **, P ≤ 0.01.

FIG 4

Agar dilution method for determining the swarming inhibitory concentration (IC) of PA14 mutants on 0.5% agar. (A) tobramycin swarming IC = 1 μg/ml; (B) trimethoprim IC = 10 μg/ml; (C) tobramycin IC = 1 μg/ml; n ≥ 3.

FIG 5

Complementation of swarming antibiotic susceptibility phenotypes for prtN (A) and wbpW (B) mutants. All strains were transformed with either the respective empty vector (WT and mutants) or a vector with insert (complemented “+” strains); n ≥ 3.

FIG 6

A wbpW mutant had reduced membrane permeabilization. Swarm cells were harvested and treated where indicated with NPN (a) and tobramycin (b); n = 3.