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. 2013 Aug;51(8):2526-34.
doi: 10.1128/JCM.00066-13. Epub 2013 May 22.

Real-time genomic epidemiological evaluation of human Campylobacter isolates by use of whole-genome multilocus sequence typing

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Real-time genomic epidemiological evaluation of human Campylobacter isolates by use of whole-genome multilocus sequence typing

Alison J Cody et al. J Clin Microbiol. 2013 Aug.

Abstract

Sequence-based typing is essential for understanding the epidemiology of Campylobacter infections, a major worldwide cause of bacterial gastroenteritis. We demonstrate the practical and rapid exploitation of whole-genome sequencing to provide routine definitive characterization of Campylobacter jejuni and Campylobacter coli for clinical and public health purposes. Short-read data from 384 Campylobacter clinical isolates collected over 4 months in Oxford, United Kingdom, were assembled de novo. Contigs were deposited at the pubMLST.org/campylobacter website and automatically annotated for 1,667 loci. Typing and phylogenetic information was extracted and comparative analyses were performed for various subsets of loci, up to the level of the whole genome, using the Genome Comparator and Neighbor-net algorithms. The assembled sequences (for 379 isolates) were diverse and resembled collections from previous studies of human campylobacteriosis. Small subsets of very closely related isolates originated mainly from repeated sampling from the same patients and, in one case, likely laboratory contamination. Much of the within-patient variation occurred in phase-variable genes. Clinically and epidemiologically informative data can be extracted from whole-genome sequence data in real time with straightforward, publicly available tools. These analyses are highly scalable, are transparent, do not require closely related genome reference sequences, and provide improved resolution (i) among Campylobacter clonal complexes and (ii) between very closely related isolates. Additionally, these analyses rapidly differentiated unrelated isolates, allowing the detection of single-strain clusters. The approach is widely applicable to analyses of human bacterial pathogens in real time in clinical laboratories, with little specialist training required.

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Figures

Fig 1
Fig 1
Rank abundance distributions of clonal complexes in genome sequence data from Oxfordshire in 2011 (dark blue) and MLST-typed samples from Oxfordshire from 2003 to 2009 (light blue) (15), Scotland from July 2005 to September 2006 (red) (22), and northwest England from April 2003 to April 2004 (yellow) (23).
Fig 2
Fig 2
Neighbor-net phylogenies generated for alleles of rMLST loci for 376 Campylobacter isolates labeled by clonal complex (A), rMLST loci for 89 ST-21 complex isolates representing 34 rMLST types labeled by ST (B), 1,595 loci for 10 isolates belonging to ST-21 complex rMLST strain 3 (C), and 1,605 loci for a subset of five strain 3 isolates, two of which (OXC6266 and OXC6292) were isolated from the same patient on the same day (D). Numerals in blue type indicate the distances (numbers of allelic differences) between isolates.
Fig 3
Fig 3
Distribution of the numbers of locus differences among pairwise comparisons of 379 Campylobacter isolates at 1,026 shared loci.
Fig 4
Fig 4
Neighbor-net phylogeny of a cluster of 13 isolates identified by pairwise comparisons of 1,026 shared loci. Blue circles, subclusters within the cluster, representing potential outbreaks.

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