Predicting Antibiotic-Associated Virulence of Pseudomonas aeruginosa Using an ex vivo Lung Biofilm Model

• Main Authors: Marwa M. Hassan, Niamh E. Harrington, Esther Sweeney, Freya Harrison
• Format: Article
• Language: English
• Published: Frontiers Media S.A. 2020-09-01
• Series: Frontiers in Microbiology
• Subjects: antibiotic susceptibility testing; antimicrobial resistance; bacterial biofilm; cystic fibrosis; antibiotic tolerance
• Online Access: https://www.frontiersin.org/article/10.3389/fmicb.2020.568510/full

BackgroundBacterial biofilms are known to have high antibiotic tolerance which directly affects clearance of bacterial infections in people with cystic fibrosis (CF). Current antibiotic susceptibility testing methods are either based on planktonic cells or do not reflect the complexity of biofilms in vivo. Consequently, inaccurate diagnostics affect treatment choice, preventing bacterial clearance and potentially selecting for antibiotic resistance. This leads to prolonged, ineffective treatment.MethodsIn this study, we use an ex vivo lung biofilm model to study antibiotic tolerance and virulence of Pseudomonas aeruginosa. Sections of pig bronchiole were dissected, prepared and infected with clinical isolates of P. aeruginosa and incubated in artificial sputum media to form biofilms, as previously described. Then, lung-associated biofilms were challenged with antibiotics, at therapeutically relevant concentrations, before their bacterial load and virulence were quantified and detected, respectively.ResultsThe results demonstrated minimal effect on the bacterial load with therapeutically relevant concentrations of ciprofloxacin and meropenem, with the latter causing an increased production of proteases and pyocyanin. A combination of meropenem and tobramycin did not show any additional decrease in bacterial load but demonstrated a slight decrease in total proteases and pyocyanin production.ConclusionIn this initial study of six clinical isolates of P. aeruginosa showed high levels of antibiotic tolerance, with minimal effect on bacterial load and increased proteases production, which could negatively affect lung function. Thus, the ex vivo lung model has the potential to be effectively used in larger studies of antibiotic tolerance in in vivo-like biofilms, and show how sub optimal antibiotic treatment of biofilms may potentially contribute to exacerbations and eventual lung failure. We demonstrate a realistic model for understanding antibiotic resistance and tolerance in biofilms clinically and for molecules screening in anti-biofilm drug development.