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High-Resolution Melting Genotyping of Enterococcus faecium Based on Multilocus Sequence Typing Derived Single Nucleotide Polymorphisms

Overview of attention for article published in PLOS ONE, December 2011
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Title
High-Resolution Melting Genotyping of Enterococcus faecium Based on Multilocus Sequence Typing Derived Single Nucleotide Polymorphisms
Published in
PLOS ONE, December 2011
DOI 10.1371/journal.pone.0029189
Pubmed ID
Authors

Steven Y. C. Tong, Shirley Xie, Leisha J. Richardson, Susan A. Ballard, Farshid Dakh, Elizabeth A. Grabsch, M. Lindsay Grayson, Benjamin P. Howden, Paul D. R. Johnson, Philip M. Giffard

Abstract

We have developed a single nucleotide polymorphism (SNP) nucleated high-resolution melting (HRM) technique to genotype Enterococcus faecium. Eight SNPs were derived from the E. faecium multilocus sequence typing (MLST) database and amplified fragments containing these SNPs were interrogated by HRM. We tested the HRM genotyping scheme on 85 E. faecium bloodstream isolates and compared the results with MLST, pulsed-field gel electrophoresis (PFGE) and an allele specific real-time PCR (AS kinetic PCR) SNP typing method. In silico analysis based on predicted HRM curves according to the G+C content of each fragment for all 567 sequence types (STs) in the MLST database together with empiric data from the 85 isolates demonstrated that HRM analysis resolves E. faecium into 231 "melting types" (MelTs) and provides a Simpson's Index of Diversity (D) of 0.991 with respect to MLST. This is a significant improvement on the AS kinetic PCR SNP typing scheme that resolves 61 SNP types with D of 0.95. The MelTs were concordant with the known ST of the isolates. For the 85 isolates, there were 13 PFGE patterns, 17 STs, 14 MelTs and eight SNP types. There was excellent concordance between PFGE, MLST and MelTs with Adjusted Rand Indices of PFGE to MelT 0.936 and ST to MelT 0.973. In conclusion, this HRM based method appears rapid and reproducible. The results are concordant with MLST and the MLST based population structure.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 34 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Mexico 1 3%
Spain 1 3%
Brazil 1 3%
Unknown 31 91%

Demographic breakdown

Readers by professional status Count As %
Student > Master 9 26%
Researcher 6 18%
Professor 3 9%
Student > Doctoral Student 2 6%
Lecturer 2 6%
Other 8 24%
Unknown 4 12%
Readers by discipline Count As %
Agricultural and Biological Sciences 19 56%
Biochemistry, Genetics and Molecular Biology 4 12%
Medicine and Dentistry 3 9%
Immunology and Microbiology 2 6%
Pharmacology, Toxicology and Pharmaceutical Science 1 3%
Other 0 0%
Unknown 5 15%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 19 December 2011.
All research outputs
#18,301,870
of 22,659,164 outputs
Outputs from PLOS ONE
#153,700
of 193,435 outputs
Outputs of similar age
#195,305
of 241,496 outputs
Outputs of similar age from PLOS ONE
#2,232
of 2,973 outputs
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