Genome macrorestriction analysis of diversity and variability of Pseudomonas aeruginosa strains infecting cystic fibrosis patients

Abstract

Genome macrorestriction fingerprinting with XbaI and Dral was used to analyze the relatedness of 166 Pseudomonas aeruginosa isolates collected from 31 cystic fibrosis patients over a 1-to 20-month period and to correlate their genotype with patterns of resistance to 14 antimicrobial agents. Quantitative comparison of intraand interpatient similarities ofP. aeruginosa macrorestriction patterns disclosed two discrete ranges that clearly discriminated subclonal variation (>80%o relatedness) and clonal diversity (10 to 70%o relatedness). Cloning-derived mutants exhibited up to 20%o divergence of genomic macrorestriction patterns during the course of chronic colonization of individual patients. Change of susceptibility to multiple antimicrobial agents developed in 50%o of sequential pairs of isolates from individual patients. Only 19% of these susceptibility changes were attributable to strain substitution, while the majority (56%) of resistance changes were associated with minor genomic variations of a persistent strain. Sixty-six percent of patients harbored one strain, and 33% carried two strains. Three common strains colonized 5 (28%) of 18 patients attending a cystic fibrosis clinic, and another two strains colonized two patient pairs (31%) of 13 patients staying at a rehabilitation center, suggesting potential cross-infection in these settings. By indexing regional polymorphisms throughout the chromosome structure, macrorestriction analysis can monitor subclonal evolution ofP. aeruginosa and identify isogenic resistance mutants. Quantitative macrorestriction fingerprinting enables discrimination between clonal variants and clones of distinct origins and should therefore provide a reliable tool for investigating the mode of acquisition of P. aeruginosa in cystic fibrosis patients.

Differences in Genomic Macrorestriction Patterns of Arabinose‐Positive (Burkholderia thailandensis) and Arabinose‐Negative Burkholderia pseudomallei

“…The present study demonstrates the reliability of PFGE as a useful tool to discriminate between virulent B. pseudomallei and the previously proposed non-virulent B. thailandensis (2). It confirms previous findings that macrorestriction fingerprinting of genomic DNA is applicable in delineating strains of pathogenic organisms (8,9,11,12,15). Moreover, the method has gained wide acceptance in possessing greater differentiating capacity than those of ribotyping and other probe-based restriction fragment length polymorphism methods (16).…”

Serotypes A1 and A2 ofMannheimia haemolyticaare susceptible to genotypic, capsular and phenotypic variations in contrast to T3 and T4 serotypes ofBibersteinia (Pasteurella) trehalosi

“…Some genuses show a very high degree of plasticity (i.e. Pseudomonas, Burkholderia, Staphylococcus) (Struelens et al, 1993;Tenover et al, 1995) compared with Brucella, for example, which has proven to be remarkably stable by various molecular tools (Gandara et al, 2001;Brower et al, 2007). Applying Tenovers' guidelines to type isolates belonging to the Brucella genus would certainly lead to some errors in interpreting their PFGE patterns.…”

Guidelines for the validation and application of typing methods for use in bacterial epidemiology

“…Computer-assisted cluster analysis is inevitable for the comparison of large numbers of profiles generated at different moments and-in the case of inter-laboratory networks-at different locations. A certain 'similarity threshold' has to be chosen to define types in this situation [67]. An inter-laboratory study with a rigorously standardised protocol investigating outbreak and non-outbreak strains of A. baumannii showed that strains regarded as being the same type clustered at 95-100% if processed in the same laboratory.…”