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Exploiting Bacterial Whole-Genome Sequencing Data for Evaluation of Diagnostic Assays: Campylobacter Species Identification as a Case Study

The application of whole-genome sequencing (WGS) to problems in clinical microbiology has had a major impact on the field. Clinical laboratories are now using WGS for pathogen identification, antimicrobial susceptibility testing, and epidemiological typing. WGS data also represent a valuable resourc...

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Bibliographic Details
Published in:Journal of clinical microbiology 2016-12, Vol.54 (12), p.2882-2890
Main Authors: Jansen van Rensburg, Melissa J, Swift, Craig, Cody, Alison J, Jenkins, Claire, Maiden, Martin C J
Format: Article
Language:English
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Summary:The application of whole-genome sequencing (WGS) to problems in clinical microbiology has had a major impact on the field. Clinical laboratories are now using WGS for pathogen identification, antimicrobial susceptibility testing, and epidemiological typing. WGS data also represent a valuable resource for the development and evaluation of molecular diagnostic assays, which continue to play an important role in clinical microbiology. To demonstrate this application of WGS, this study used publicly available genomic data to evaluate a duplex real-time PCR (RT-PCR) assay that targets mapA and ceuE for the detection of Campylobacter jejuni and Campylobacter coli, leading global causes of bacterial gastroenteritis. In silico analyses of mapA and ceuE primer and probe sequences from 1,713 genetically diverse C. jejuni and C. coli genomes, supported by RT-PCR testing, indicated that the assay was robust, with 1,707 (99.7%) isolates correctly identified. The high specificity of the mapA-ceuE assay was the result of interspecies diversity and intraspecies conservation of the target genes in C. jejuni and C. coli Rare instances of a lack of specificity among C. coli isolates were due to introgression in mapA or sequence diversity in ceuE The results of this study illustrate how WGS can be exploited to evaluate molecular diagnostic assays by using publicly available data, online databases, and open-source software.
ISSN:0095-1137
1098-660X
DOI:10.1128/JCM.01522-16