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Comparative Study
. 2010 Mar;76(5):1533-44.
doi: 10.1128/AEM.02215-09. Epub 2009 Dec 18.

Comparison of PCR binary typing (P-BIT), a new approach to epidemiological subtyping of Campylobacter jejuni, with serotyping, pulsed-field gel electrophoresis, and multilocus sequence typing methods

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Comparative Study

Comparison of PCR binary typing (P-BIT), a new approach to epidemiological subtyping of Campylobacter jejuni, with serotyping, pulsed-field gel electrophoresis, and multilocus sequence typing methods

Angela J Cornelius et al. Appl Environ Microbiol. 2010 Mar.

Abstract

To overcome some of the deficiencies with current molecular typing schema for Campylobacter spp., we developed a prototype PCR binary typing (P-BIT) approach. We investigated the distribution of 68 gene targets in 58 Campylobacter jejuni strains, one Campylobacter lari strain, and two Campylobacter coli strains for this purpose. Gene targets were selected on the basis of distribution in multiple genomes or plasmids, and known or putative status as an epidemicity factor. Strains were examined with Penner serotyping, pulsed-field gel electrophoresis (PFGE; using SmaI and KpnI enzymes), and multilocus sequence typing (MLST) approaches for comparison. P-BIT provided 100% typeability for strains and gave a diversity index of 98.5%, compared with 97.0% for SmaI PFGE, 99.4% for KpnI PFGE, 96.1% for MLST, and 92.8% for serotyping. Numerical analysis of the P-BIT data clearly distinguished strains of the three Campylobacter species examined and correlated somewhat with MLST clonal complex assignations and with previous classifications of "high" and "low" risk. We identified 18 gene targets that conferred the same level of discrimination as the 68 initially examined. We conclude that P-BIT is a useful approach for subtyping, offering advantages of speed, cost, and potential for strain risk ranking unavailable from current molecular typing schema for Campylobacter spp.

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Figures

FIG. 1.
FIG. 1.
Cluster analysis of P-BIT data based on 68 gene targets using the simple matching coefficient and Ward's clustering.
FIG. 2.
FIG. 2.
Cluster analysis of P-BIT data based on the suggested minimal set of 18 gene targets using the simple matching coefficient and Ward's clustering. “68 p-bit” refers to the clusters illustrated in Fig. 1.
FIG. 3.
FIG. 3.
Minimum spanning tree based on 18 P-BIT targets. The tree was created using BioNumerics 5.1 software, using the binary coefficient. The MST is presented with logarithmic branch lengths; complexes are shaded based on a maximum neighbor distance of 2 changes and minimum of 2 types. Thick lines between nodes indicate one change, thinner lines two changes, dark dotted lines three to four changes, and gray dotted lines five or more changes. Mix 1 contains ST 3580 and 3581, and mix 2 contains ST 21 and 43. nv, nonviable; lari, C. lari isolate.

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