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J Clin Microbiol. 2017 Jun;55(6):1946-1953. doi: 10.1128/JCM.00029-17. Epub 2017 Apr 12.

Comparison of Whole-Genome Sequencing Methods for Analysis of Three Methicillin-Resistant Staphylococcus aureus Outbreaks.

Author information

1
Division of Clinical Microbiology, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota, USA.
2
Department of Surgery, Mayo Clinic, Rochester, Minnesota, USA.
3
Advanced Analytics and Information Support, Information Technology, Mayo Clinic, Rochester, Minnesota, USA.
4
Bioinformatics Systems, Information Technology, Mayo Clinic, Rochester, Minnesota, USA.
5
Minnesota Department of Health, Saint Paul, Minnesota, USA.
6
Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, USA.
7
Division of Clinical Microbiology, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota, USA patel.robin@mayo.edu.
8
Division of Infectious Diseases, Department of Medicine, Mayo Clinic, Rochester, Minnesota, USA.

Abstract

Whole-genome sequencing (WGS) can provide excellent resolution in global and local epidemiological investigations of Staphylococcus aureus outbreaks. A variety of sequencing approaches and analytical tools have been used; it is not clear which is ideal. We compared two WGS strategies and two analytical approaches to the standard method of SmaI restriction digestion pulsed-field gel electrophoresis (PFGE) for typing S. aureus Forty-two S. aureus isolates from three outbreaks and 12 reference isolates were studied. Near-complete genomes, assembled de novo with paired-end and long-mate-pair (8 kb) libraries were first assembled and analyzed utilizing an in-house assembly and analytical informatics pipeline. In addition, paired-end data were assembled and analyzed using a commercial software package. Single nucleotide variant (SNP) analysis was performed using the in-house pipeline. Two assembly strategies were used to generate core genome multilocus sequence typing (cgMLST) data. First, the near-complete genome data generated with the in-house pipeline were imported into the commercial software and used to perform cgMLST analysis. Second, the commercial software was used to assemble paired-end data, and resolved assemblies were used to perform cgMLST. Similar isolate clustering was observed using SNP calling and cgMLST, regardless of data assembly strategy. All methods provided more discrimination between outbreaks than did PFGE. Overall, all of the evaluated WGS strategies yielded statistically similar results for S. aureus typing.

KEYWORDS:

MRSA; PFGE; Staphylococcus aureus; molecular typing; whole-genome sequencing

PMID:
28404677
PMCID:
PMC5442552
DOI:
10.1128/JCM.00029-17
[Indexed for MEDLINE]
Free PMC Article

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