Abstract

IntroductionPseudomonas aeruginosa is one of the important causes of nosocomial infections. Analyzing the diversity of these isolates is important to control the diseases caused by them. Studies of molecular epidemiology depend on the application of typing methods.PurposeThis study aims to assess the performance of PCR- based typing techniques (RAPD, ribotyping, tDNA, and ERIC) in determining the genetic diversity of 44 P. aeruginosa urinary isolates.MethodsPerformance parameters were analyzed for each of the tested methods. The banding pattern was assessed by calculating polymorphism, genotypic gene diversity and the effective multiplex ratio. Moreover, strain diversity, typeability, and discriminatory power were used to measure the efficiency of typing methods. The congruence among typing methods was calculated by Rand’s and Wallace coefficients.ResultsP-640 among RAPD primers and Ribo-2 among ribotyping primers were more informative as they gave high strain diversity, the highest number of clusters, and highest discriminatory power (ISD=70.45%, 29 clusters at 70% cutoff, DI=0.97 and ISD=75%, 25 clusters at 70% cutoff DI=0.969, respectively). Comparison of typing methods showed that RAPD-PCR gave the highest mean percent polymorphism per assay (76.85%) followed by ERIC-PCR. ERIC-PCR outperformed in most marker parameters; highest mean number of alleles, number of monomorphic bands per assay unit, mean genotypic gene diversity, effective multiplex ratio, and assay efficiency index. Calculated congruence revealed that individual methods demonstrate moderate to poor predictive power. Interestingly, this power increased by combining data obtained from another method.ConclusionRAPD primer (P-640) had more discrimination power followed by ribo-2 and ERIC. The performance and predictive power of typing methods can be improved by combining data obtained from different methods as ERIC+OPA-02 and ERIC+P-640 combinations gave complete typeability and discrimination of isolates. ERIC, ERIC+OPA-02, and ERIC+P-640 combinations can provide finer discrimination and classification of P. aeruginosa strains than the other tested methods.

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