A comparison of two informative SNP-based strategies for typing Pseudomonas aeruginosa isolates from patients with cystic fibrosis

Syrmis, Melanie W., Kidd, Timothy J., Moser, Ralf J., Ramsay, Kay A., Gibson, Kristen M., Anuj, Snehal, Bell, Scott C., Wainwright, Claire E., Grimwood, Keith, Nissen, Michael, Sloots, Theo P. and Whiley, David M. (2014) A comparison of two informative SNP-based strategies for typing Pseudomonas aeruginosa isolates from patients with cystic fibrosis. BMC Infectious Diseases, 14 1: 307.1-307.8. doi:10.1186/1471-2334-14-307


Author Syrmis, Melanie W.
Kidd, Timothy J.
Moser, Ralf J.
Ramsay, Kay A.
Gibson, Kristen M.
Anuj, Snehal
Bell, Scott C.
Wainwright, Claire E.
Grimwood, Keith
Nissen, Michael
Sloots, Theo P.
Whiley, David M.
Title A comparison of two informative SNP-based strategies for typing Pseudomonas aeruginosa isolates from patients with cystic fibrosis
Journal name BMC Infectious Diseases   Check publisher's open access policy
ISSN 1471-2334
Publication date 2014-05-05
Year available 2014
Sub-type Article (original research)
DOI 10.1186/1471-2334-14-307
Open Access Status DOI
Volume 14
Issue 1
Start page 307.1
End page 307.8
Total pages 8
Place of publication London, United Kingdom
Publisher BioMed Central Ltd.
Collection year 2015
Language eng
Subject 2725 Infectious Diseases
Abstract Background: Molecular typing is integral for identifying Pseudomonas aeruginosa strains that may be shared between patients with cystic fibrosis (CF). We conducted a side-by-side comparison of two P. aeruginosa genotyping methods utilising informative-single nucleotide polymorphism (SNP) methods; one targeting 10 P. aeruginosa SNPs and using real-time polymerase chain reaction technology (HRM10SNP) and the other targeting 20 SNPs and based on the Sequenom MassARRAY platform (iPLEX20SNP). Methods: An in-silico analysis of the 20 SNPs used for the iPLEX20SNP method was initially conducted using sequence type (ST) data on the P. aeruginosa PubMLST website. A total of 506 clinical isolates collected from patients attending 11 CF centres throughout Australia were then tested by both the HRM10SNP and iPLEX20SNP assays. Type-ability and discriminatory power of the methods, as well as their ability to identify commonly shared P. aeruginosa strains, were compared. Results: The in-silico analyses showed that the 1401 STs available on the PubMLST website could be divided into 927 different 20-SNP profiles (D-value = 0.999), and that most STs of national or international importance in CF could be distinguished either individually or as belonging to closely related single- or double-locus variant groups. When applied to the 506 clinical isolates, the iPLEX20SNP provided better discrimination over the HRM10SNP method with 147 different 20-SNP and 92 different 10-SNP profiles observed, respectively. For detecting the three most commonly shared Australian P. aeruginosa strains AUST-01, AUST-02 and AUST-06, the two methods were in agreement for 80/81 (98.8%), 48/49 (97.8%) and 11/12 (91.7%) isolates, respectively. Conclusions: The iPLEX20SNP is a superior new method for broader SNP-based MLST-style investigations of P. aeruginosa. However, because of convenience and availability, the HRM10SNP method remains better suited for clinical microbiology laboratories that only utilise real-time PCR technology and where the main interest is detection of the most highly-prevalent P. aeruginosa CF strains within Australian clinics.
Keyword Cystic fibrosis
Pseudomonas aeruginosa
Typing
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2015 Collection
Queensland Children's Medical Research Institute Publications
School of Medicine Publications
 
Versions
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 4 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 4 times in Scopus Article | Citations
Google Scholar Search Google Scholar
Created: Tue, 24 Jun 2014, 00:44:23 EST by System User on behalf of Child Health Research Centre