ABSTRACT
Antimicrobial resistance is a significant threat to the treatment of infectious disease. Multiple mechanisms of resistance to different classes of antibiotics have been identified and well-studied. However, these mechanisms are studied with bacteria in isolation, whereas often, infections have a polymicrobial basis. Using a biofilm slide chamber model, we visualized the formation and development of clinical Pseudomonas aeruginosa biofilms in the presence of secreted Staphylococcus aureus exoproducts, two bacteria that commonly co-infect pediatric patients with cystic fibrosis. We showed that, over time, certain isolates of P. aeruginosa can form different biofilm architecture in the presence of S. aureus exoproducts. We further determined that this interaction was dependent on Psl produced by P. aeruginosa and staphylococcal protein A from S. aureus. Importantly, we identified a mechanism of antibiotic resistance to tobramycin that is dependent on the polymicrobial interactions between these two bacteria. This interaction occurred in isolates of P. aeruginosa recovered from children with cystic fibrosis who failed to clear P. aeruginosa following inhaled tobramycin treatment.
ABSTRACT
The aim of this study was to compare two traditional pattern matching techniques, pulsed-field gel electrophoresis (PFGE) and random amplified polymorphic DNA (RAPD), with the more reproducible technique of multilocus sequence typing (MLST) to genotype a blinded sample of Pseudomonas aeruginosa isolates from cystic fibrosis (CF) patients. A blinded sample of 48 well-characterized CF P. aeruginosa isolates was genotyped by PFGE, RAPD, and MLST, each performed in a different laboratory. The discriminatory power and congruence between the methods were compared using the Simpson's index, Rand index, and Wallace coefficient. PFGE and MLST had the greatest congruence with the highest Rand index (0.697). The discriminatory power of PFGE, RAPD, and MLST were comparable, with high Simpson's indices (range 0.973-0.980). MLST identified the most clonal relationships. When clonality was defined as agreement between two or more methods, MLST had the greatest predictive value (100 %) in labeling strains as unique, while PFGE had the greatest predictive value (96 %) in labeling strains as clonal. This study demonstrated the highest level of agreement between PFGE and MLST in genotyping P. aeruginosa isolates from CF patients. MLST had the greatest predictive value in identifying strains as unique and, thus, has the potential to be a cost-efficient, high-throughput, first-pass typing method.
