Literature DB >> 22406296

High resolution melt analysis to track infections due to ribotype 027 Clostridium difficile.

Danilla Grando1, Mohamed M Said, Barrie C Mayall, Volker Gurtler.   

Abstract

The increased prevalence of hypervirulent ribotype 027 Clostridium difficile requires rapid identification of isolates in order to implement timely infection control strategies. High resolution melt (HRM) analysis of PCR products can identify strain variation amongst genera of bacteria. The intergenic (16S-23S rDNA) spacer region contains sequence regions conserved within genera and other sequence region variables between species within genera. We wished to investigate whether HRM analysis of PCR ribotyping products could identify ribotype 027 C. difficile. Ribotyping was performed on 93 clinical isolates and five control strains and band patterns were analysed using GelCompar II (Applied Maths, USA). Real-time PCR using ribotyping primers was performed and normalised melt curves were generated. The HRM data was then imported into ScreenClust software (QIAGEN) to generate principal component analysis graphs depicting clustered relationships of strains. Ribotyping produced clear PCR bands for 88/98 isolates tested. Dendrograms generated by GelCompar showed a diversity of ribotype patterns amongst these 88 isolates with 18 groups identified with 70% homology. One clinical isolate showed 100% homology with the control 027 strains. ScreenClust analysis of the same 88 HRM results showed clustering of isolates, with 027 strains identifiable as a unique cluster. HRM analysis correctly identified the control 027 stains and the clinical isolate shown to be 027. HRM combined with ScreenClust analysis of real-time PCR products of the 16S-23S rDNA spacer region successfully identified ribotype 027 strains. For infection control purposes this was achieved within 2-3 h of colony isolation. Crown
Copyright © 2012. Published by Elsevier B.V. All rights reserved.

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Year:  2012        PMID: 22406296     DOI: 10.1016/j.mimet.2012.02.011

Source DB:  PubMed          Journal:  J Microbiol Methods        ISSN: 0167-7012            Impact factor:   2.363


  4 in total

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  4 in total

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