Epidemiological investigation of ' Pseudomonas aeruginosa ' isolates from a six-year-long hospital outbreak using high-throughput whole genome sequencing

Snyder, L.A., Loman, N.J., Faraj, L.J., Levi, K., Weinstock, J., Boswell, T.C., Pallen, M.J. and Ala’Aldeen, D.A. (2013) Epidemiological investigation of ' Pseudomonas aeruginosa ' isolates from a six-year-long hospital outbreak using high-throughput whole genome sequencing. Eurosurveillance, 18(42), ISSN (print) 1025-496X

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Abstract

Although previous bacterial typing methods have been informative about potential relatedness of isolates collected during outbreaks, next-generation sequencing has emerged as a powerful tool to not only look at similarity between isolates, but also put differences into biological context. In this study, we have investigated the whole genome sequence of five Pseudomonas aeruginosa isolates collected during a persistent six-year outbreak at Nottingham University Hospitals National Health Service (NHS) Trust – City Campus, United Kingdom. Sequencing, using both Roche 454 and Illumina, reveals that most of these isolates are closely related. Some regions of difference are noted between this cluster of isolates and previously published genome sequences. These include regions containing prophages and prophage remnants such as the serotype-converting bacteriophage D3 and the cytotoxin-converting phage phi CTX. Additionally, single nucleotide polymorphisms (SNPs) between the genomic sequence data reveal key single base differences that have accumulated during the course of this outbreak, giving insight into the evolution of the outbreak strain. Differentiating SNPs were found within a wide variety of genes, including lasR, nrdG, tadZ, and algB. These have been generated at a rate estimated to be one SNP every four to five months. In conclusion, we demonstrate that the single base resolution of whole genome sequencing is a powerful tool in analysis of outbreak isolates that can not only show strain similarity, but also evolution over time and potential adaptation through gene sequence changes.

Item Type: Article
Research Area: Allied health professions and studies
Biological sciences
Epidemiology and public health
Faculty, School or Research Centre: Faculty of Science, Engineering and Computing
Faculty of Science, Engineering and Computing > School of Life Sciences
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Depositing User: Sue Snelling
Date Deposited: 06 Nov 2013 15:40
Last Modified: 12 Jul 2016 11:38
URI: http://eprints.kingston.ac.uk/id/eprint/26779

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