Determination of Clonality and Relatedness of Vibrio Cholerae Isolates by Genomic Fingerprinting, Using Long-Range Repetitive Element Sequence-Based PCR

TitleDetermination of Clonality and Relatedness of Vibrio Cholerae Isolates by Genomic Fingerprinting, Using Long-Range Repetitive Element Sequence-Based PCR
Publication TypeJournal Articles
Year of Publication2008
AuthorsChokesajjawatee N, Zo Y-G, Colwell RR
JournalApplied and Environmental MicrobiologyAppl. Environ. Microbiol.Applied and Environmental MicrobiologyAppl. Environ. Microbiol.
Volume74
Type of Article10.1128/AEM.00151-08
ISBN Number0099-2240, 1098-5336
Abstract

A high-throughput method which is applicable for rapid screening, identification, and delineation of isolates of Vibrio cholerae, sensitive to genome variation, and capable of providing phylogenetic inferences enhances environmental monitoring of this bacterium. We have developed and optimized a method for genomic fingerprinting of V. cholerae based on long-range PCR. The method uses a primer set directed to enterobacterial repetitive intergenic consensus sequences, a high-fidelity DNA polymerase, and analysis via conventional agarose gel electrophoresis. Long (∼10 kb), highly reproducible amplicons were generated from V. cholerae isolates, including those from different geographical locations and historical strains isolated during the period 1931-2000. The amplicons yielded reduced variability in their densitometric band patterns to ≤10% and clonal distinction at <90% similarity. Rapid band-matching analysis was accomplished for fingerprints with ≥90% similarity, discriminating O serotypes and biotypes (classical versus El Tor) as well as pathogenic and nonpathogenic strains. Compared to genome similarity measured by DNA-DNA hybridization, the results showed good correlation (r = 0.7; P < 0.001), with five times less measurement error and without bias. The method permits both phylogenetic inference and clonal differentiation of individual V. cholerae strains, enables robust, high-throughput analysis, and does not require specialized equipment to perform. With access to a curated public database furnished with appropriate analytical software applications, the method should prove useful in large-scale multilaboratory surveys, especially those designed to detect specific pathogens in the natural environment.