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Acinetobacter baumannii is an important opportunistic pathogen responsible for nosocomial outbreaks, mostly occurring in intensive care units. Due to the multiplicity of infection sources, reliable molecular fingerprinting techniques are needed to establish epidemiological correlations among A. baumannii isolates. Multiple-locus variable-number tandem-repeat analysis (MLVA) has proven to be a fast, reliable, and cost-effective typing method for several bacterial species. In this study, an MLVA assay compatible with simple PCR- and agarose gel-based electrophoresis steps as well as with high-throughput automated methods was developed for A. baumannii typing. Preliminarily, 10 potential polymorphic variable-number tandem repeats (VNTRs) were identified upon bioinformatic screening of six annotated genome sequences of A. baumannii. A collection of 7 reference strains plus 18 well-characterized isolates, including unique types and representatives of the three international A. baumannii lineages, was then evaluated in a two-center study aimed at validating the MLVA assay and comparing it with other genotyping assays, namely, macrorestriction analysis with pulsed-field gel electrophoresis (PFGE) and PCR-based sequence group (SG) profiling. The results showed that MLVA can discriminate between isolates with identical PFGE types and SG profiles. A panel of eight VNTR markers was selected, all showing the ability to be amplified and good amounts of polymorphism in the majority of strains. Independently generated MLVA profiles, composed of an ordered string of allele numbers corresponding to the number of repeats at each VNTR locus, were concordant between centers. Typeability, reproducibility, stability, discriminatory power, and epidemiological concordance were excellent. A database containing information and MLVA profiles for several A. baumannii strains is available from http://mlva.u-psud.fr/.

journal of clinical microbiology

Identification of Variable-Number Tandem-Repeat (VNTR) Sequences in Acinetobacter baumannii and Interlaboratory Validation of an Optimized Multiple-Locus VNTR Analysis Typing Scheme