Original Article
Bacteriology
Preliminary validation of a novel high-resolution melt-based typing method based on the multilocus sequence typing scheme of Streptococcus pyogenes

https://doi.org/10.1111/j.1469-0691.2010.03433.xGet rights and content
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Abstract

The major limitation of current typing methods for Streptococcus pyogenes, such as emm sequence typing and T typing, is that these are based on regions subject to considerable selective pressure. Multilocus sequence typing (MLST) is a better indicator of the genetic backbone of a strain but is not widely used due to high costs. The objective of this study was to develop a robust and cost-effective alternative to S. pyogenes MLST. A 10-member single nucleotide polymorphism (SNP) set that provides a Simpson's Index of Diversity (D) of 0.99 with respect to the S. pyogenes MLST database was derived. A typing format involving high-resolution melting (HRM) analysis of small fragments nucleated by each of the resolution-optimized SNPs was developed. The fragments were 59–119 bp in size and, based on differences in G+C content, were predicted to generate three to six resolvable HRM curves. The combination of curves across each of the 10 fragments can be used to generate a melt type (MelT) for each sequence type (ST). The 525 STs currently in the S. pyogenes MLST database are predicted to resolve into 298 distinct MelTs and the method is calculated to provide a D of 0.996 against the MLST database. The MelTs are concordant with the S. pyogenes population structure. To validate the method we examined clinical isolates of S. pyogenes of 70 STs. Curves were generated as predicted by G+C content discriminating the 70 STs into 65 distinct MelTs.

Keywords

High-resolution melting
multilocus sequence typing
Simpsons index of diversity
single nucleotide polymorphism
Streptococcus pyogenes
typing

Cited by (0)

Editor: P. Tassios

Article published online: 22 November 2010

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Equal contributions made by these two authors.

Present address: Faculty of Health and Human Sciences, Thames Valley University, UK.