Cold atmospheric pressure plasma-antibiotic synergy in Pseudomonas aeruginosa biofilms is mediated via oxidative stress response

Abstract

Cold atmospheric-pressure plasma (CAP) has emerged as a potential alternative or adjuvant to conventional antibiotics for the treatment of bacterial infections, including those caused by antibiotic-resistant pathogens. The potential of sub-lethal CAP exposures to synergise conventional antimicrobials for the eradication of Pseudomonas aeruginosa biofilms is investigated in this study. The efficacy of antimicrobials following or in the absence of sub-lethal CAP pre-treatment in P. aeruginosa biofilms was assessed. CAP pre-treatment resulted in an increase in both planktonic and biofilm antimicrobial sensitivity for all three strains tested (PAO1, PA14, and PA10548), with both minimum inhibitory concentrations (MICs) and minimum biofilm eradication concentrations (MBECs) of individual antimicrobials, being significantly reduced following CAP pre-treatment of the biofilm (512-fold reduction with ciprofloxacin/gentamicin; and a 256-fold reduction with tobramycin). At all concentrations of antimicrobial used, the combination of sub-lethal CAP exposure and antimicrobials was effective at increasing time-to-peak metabolism, as measured by isothermal microcalorimetry, again indicating enhanced susceptibility. CAP is known to damage bacterial cell membranes and DNA by causing oxidative stress through the in situ generation of reactive oxygen and nitrogen species (RONS). While the exact mechanism is not clear, oxidative stress on outer membrane proteins is thought to damage/perturb cell membranes, confirmed by ATP and LDH leakage, allowing antimicrobials to penetrate the bacterial cell more effectively, thus increasing bacterial susceptibility. Transcriptomic analysis, reveals that cold-plasma mediated oxidative stress caused upregulation of P. aeruginosa superoxide dismutase, cbb3 oxidases, catalases, and peroxidases, and upregulation in denitrification genes, suggesting that P. aeruginosa uses these enzymes to degrade RONS and mitigate the effects of cold plasma mediated oxidative stress. CAP treatment also led to an increased production of the signalling molecule ppGpp in P. aeruginosa, indicative of a stringent response being established. Although we did not directly measure persister cell formation, this stringent response may potentially be associated with the formation of persister cells in biofilm cultures. The production of ppGpp and polyphosphate may be associated with protein synthesis inhibition and increase efflux pump activity, factors which can result in antimicrobial tolerance. The transcriptomic analysis also showed that by 6 h post-treatment, there was downregulation in ribosome modulation factor, which is involved in the formation of persister cells, suggesting that the cells had begun to resuscitate/recover. In addition, CAP treatment at 4 h post-exposure caused downregulation of the virulence factors pyoverdine and pyocyanin; by 6 h post-exposure, virulence factor production was increasing. Transcriptomic analysis provides valuable insights into the mechanisms by which P. aeruginosa biofilms exhibits enhanced susceptibility to antimicrobials. Overall, these findings suggest, for the first time, that short CAP sub-lethal pre-treatment can be an effective strategy for enhancing the susceptibility of P. aeruginosa biofilms to antimicrobials and provides important mechanistic insights into cold plasma-antimicrobial synergy. Transcriptomic analysis of the response to, and recovery from, sub-lethal cold plasma exposures in P. aeruginosa biofilms improves our current understanding of cold plasma biofilm interactions.

Keywords: Antimicrobial synergy; Biofilm; Cold plasma; Persister cells; Plasma Medicine; Pseudomonas aeruginosa; Transcriptomics; ppGpp.

Fig. 1

Diagram of the cold plasma jet configuration depicting the electrodes, plasma plume, and the electrode geometry used for the treatment of a P. aeruginosa biofilm grown on a CBD peg.

Fig. 2

Reductions (log₁₀ CFU/mL) in P. aeruginosa culturability over time (s) (A) planktonic (B) biofilm (strains PAO1, PA14, and PA10548) after CAP treatment assessed by colony count assay. Error bars indicate the mean ± standard deviation determined from biological replicates (n = 3). The significance levels were the same for each strain and therefore only one set is displayed. Asterisks denote significant differences between the relevant exposure times compared to baseline (t = 0).

Fig. 3

MIC and MBC determinations (μg/mL) of tobramycin (A), gentamicin (B), ciprofloxacin (C), and chlorhexidine (D) against P. aeruginosa strains PAO1, PA14, and PA10548. Strains were either untreated (UT) or CAP treated for 45 s, immediately followed by the addition of one of the antimicrobial compounds for 16 h. These results are based on endpoint visual assessment (no error bars) based on three biological replicates (n = 3).

Fig. 4

MIC, MBC, and MBEC determinations (μg/mL) of tobramycin (A), gentamicin (B), ciprofloxacin (C), and chlorhexidine (D) for biofilms of P. aeruginosa strains PAO1, PA14, and PA10548. Strains were either untreated (UT) or CAP treated for 90 s followed by the addition of the antimicrobial for 16 h. Results are based on endpoint visual assessment (no error bars) based on three biological replicates (n = 3).

Fig. 5

Time to peak metabolism (h) of the three P. aeruginosa biofilms - PAO1 (A), PA14 (B), and PA10548 (C) against tobramycin [1], gentamicin [2], ciprofloxacin [3], and chlorhexidine [4]. Biofilms were either untreated or CAP treated for 90 s followed by the addition of antimicrobial. Error bars indicate the mean ± standard deviation determined from biological replicates, asterisks indicate significant differences between the untreated and CAP-treated groups (p < 0.05, p < 0.01, p < 0.001, and p < 0.0001) using one-way ANOVA and Dunnett's post-test analysis (n = 3).

Fig. 6

Differential gene expression in P. aeruginosa (PA01) biofilms after sub-lethal CAP exposure at different time points post-treatment. (A) 4 h post-exposure, (B) 6 h post-exposure, (C) 24 h post-exposure.

Fig. 7

Changes in the transcription (log₂FC) of four genes related to the arginine deaminase system at 4 h, 6 h, and 24 h post-exposure to CAP. The error bars indicate the mean ± standard deviation determined from biological replicates (n = 3).

Fig. 8

Log₂FC in the transcription of 11 genes related to CAP generated reactive oxygen and reactive nitrogen species defence at 4 h, 6 h, and 24 h post-exposure. The error bars indicate the mean ± standard deviation determined from biological replicates (n = 3).

Fig. 9

Log₂FC in the transcription of 7 genes related to iron storage at 4 h, 6 h, and 24 h post-exposure. The error bars indicate the mean ± standard deviation determined from biological replicates (n = 3).

Fig. 10

Absorbance of (p)ppGpp measured at 414 nm from PAO1 cells following different CAP exposure times (s). Error bars indicate the mean ± standard deviation determined from biological replicates (n = 3). Asterisks denote significant differences between the relevant exposure times compared to baseline (t = 0).

Fig. 11

Measurement of time-dependant (A) extracellular ATP and (B) LDH leakage following CAP treatment of PAO1 cells. Error bars indicate the mean ± standard deviation determined from biological replicates (n = 3). Asterisks denote significant differences between the relevant exposure times compared to baseline (t = 0).

Fig. 12

Pyoverdine and pyocyanin production by PAO1 at 4 h, 6 h, and 24 h post CAP treatment. Heatmap depicting changes in the transcript expression with genes related to (A) pyocyanin expression (B) and pyoverdine expression. To confirm these phenotypes, pyocyanin and pyoverdine concentrations were measured using absorbance and fluorescence for (C) pyocyanin (D) and pyoverdine. The error bars indicate the mean ± standard deviation determined from biological replicates (n = 3).