Healthcare-associated infections are a major burden for public health world-wide. Hospital surveillance is one of the most effective strategies to control pathogen spreading in hospital settings. Multi Locus Sequence Typing (MLST) and Whole Genome Sequencing (WGS) are common methods for pathogens typing in hospitals. These methods are expensive and/or time consuming and/or require specialized skills. This has limited their application in hospital real time surveillance programs. High Resolution Melting (HRM) is a PCR based method to discriminate amplicons on the basis of their melting temperatures. Thus, an HRM protocol designed on hypervariable genes of a pathogen can be used to discriminate clones: this approach is called HRM Typing or HRMT. Designing primers on hypervariable genes is challenging, therefore we developed EasyPrimer: a web tool able to identify the most suitable regions for HRM primer design. The melting temperatures obtained from HRMT characterization of hospital isolates can be used to identify clones and to perform transmission analysis. To facilitate this step, we developed MeltingPlot: a user-friendly web tool specifically designed for HRMT application in hospital settings. We validated this HRMT approach on Klebsiella pneumoniae. We developed a HRMT protocol using EasyPrimer and we performed a surveillance analysis in an italian hospital using HRMT, MLST and WGS. The three methods identified highly similar K. pneumoniae clusters. Considering that HRMT is faster (~5 hours) and less expensive (~5 euros per isolate) than MLST and WGS, this result clearly shows that HRMT is suitable for real time surveillance programs in hospital settings.

High Resolution Melting Typing (HRMT) is suitable for real time hospital surveillance / M. Perini. ((Intervento presentato al convegno International Conference on Biomedical, Biopharma and Clinical Research tenutosi a Online nel 2020.

High Resolution Melting Typing (HRMT) is suitable for real time hospital surveillance

M. Perini
2020

Abstract

Healthcare-associated infections are a major burden for public health world-wide. Hospital surveillance is one of the most effective strategies to control pathogen spreading in hospital settings. Multi Locus Sequence Typing (MLST) and Whole Genome Sequencing (WGS) are common methods for pathogens typing in hospitals. These methods are expensive and/or time consuming and/or require specialized skills. This has limited their application in hospital real time surveillance programs. High Resolution Melting (HRM) is a PCR based method to discriminate amplicons on the basis of their melting temperatures. Thus, an HRM protocol designed on hypervariable genes of a pathogen can be used to discriminate clones: this approach is called HRM Typing or HRMT. Designing primers on hypervariable genes is challenging, therefore we developed EasyPrimer: a web tool able to identify the most suitable regions for HRM primer design. The melting temperatures obtained from HRMT characterization of hospital isolates can be used to identify clones and to perform transmission analysis. To facilitate this step, we developed MeltingPlot: a user-friendly web tool specifically designed for HRMT application in hospital settings. We validated this HRMT approach on Klebsiella pneumoniae. We developed a HRMT protocol using EasyPrimer and we performed a surveillance analysis in an italian hospital using HRMT, MLST and WGS. The three methods identified highly similar K. pneumoniae clusters. Considering that HRMT is faster (~5 hours) and less expensive (~5 euros per isolate) than MLST and WGS, this result clearly shows that HRMT is suitable for real time surveillance programs in hospital settings.
3-dic-2020
Settore MED/07 - Microbiologia e Microbiologia Clinica
High Resolution Melting Typing (HRMT) is suitable for real time hospital surveillance / M. Perini. ((Intervento presentato al convegno International Conference on Biomedical, Biopharma and Clinical Research tenutosi a Online nel 2020.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/861404
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