Background 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 and it has the potential to be used for pathogen typing. Despite this, HRM application in hospital settings is limited because it is challenging to develop novel discriminatory typing protocols and to interpret data. Here we present Multi-Locus Melting Clustering (MLMC), a novel approach to easily develop highly discriminatory HRM protocols and to perform repeatable and portable pathogen typing for epidemiological investigations using HRM data. Methods The MLMC approach includes two main steps: i) the development of an HRM protocol on hypervariable genes; ii) the use of melting temperatures to cluster/type isolates and to perform epidemiological investigations. We developed a highly discriminatory HRM protocol for Klebsiella pneumoniae typing, using the software EasyPrimer. Then, we developed and used the software MeltingPlot to type all the K. pneumoniae isolates (n=80) collected in 2017 in a large hospital in Milan (Italy) by MLMC, in silico MLST and WGS, and we compared the results. Results As shown in figure 1 and figure 2, Multi-Locus Melting Clustering is able to provide an accurate description of the epidemiological scenario with a definition that is comparable to MLST and WGS. Even if MLMC is less precise than WGS, it is able to correctly identify the two most prevalent clones (highlighted by the gray rectangles in the figures). Conclusions Considering that Multi-Locus Melting Clustering (MLMC) is faster (~5 hours) and less expensive (~5 euros per isolate) than MLST and WGS (~50 and ~100 euro per isolate, see figure 3), this result clearly shows that MLMC is suitable for real time surveillance programs in hospital settings.

Multi-Locus Melting Clustering (MLMC): a novel, fast and inexpensive approach to pathogen typing. Application in a year-long real time nosocomial surveillance program / M. Perini, A. Piazza, S. Papaleo, A. Alvaro, F. Vailati, S. Gaiarsa, F. Saluzzo, F. Gona, C. Farina, P. Marone, D. Maria Cirillo, A. Cavallero, C. Bandi, G.V. Zuccotti, F. Comandatore. ((Intervento presentato al 31. convegno ECCMID - European Congress of Clinical Microbiology & Infectious Diseases tenutosi a Online nel 2021.

Multi-Locus Melting Clustering (MLMC): a novel, fast and inexpensive approach to pathogen typing. Application in a year-long real time nosocomial surveillance program

M. Perini
Primo
;
S. Papaleo;A. Alvaro;C. Bandi;G.V. Zuccotti;F. Comandatore
Ultimo
2021-07-10

Abstract

Background 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 and it has the potential to be used for pathogen typing. Despite this, HRM application in hospital settings is limited because it is challenging to develop novel discriminatory typing protocols and to interpret data. Here we present Multi-Locus Melting Clustering (MLMC), a novel approach to easily develop highly discriminatory HRM protocols and to perform repeatable and portable pathogen typing for epidemiological investigations using HRM data. Methods The MLMC approach includes two main steps: i) the development of an HRM protocol on hypervariable genes; ii) the use of melting temperatures to cluster/type isolates and to perform epidemiological investigations. We developed a highly discriminatory HRM protocol for Klebsiella pneumoniae typing, using the software EasyPrimer. Then, we developed and used the software MeltingPlot to type all the K. pneumoniae isolates (n=80) collected in 2017 in a large hospital in Milan (Italy) by MLMC, in silico MLST and WGS, and we compared the results. Results As shown in figure 1 and figure 2, Multi-Locus Melting Clustering is able to provide an accurate description of the epidemiological scenario with a definition that is comparable to MLST and WGS. Even if MLMC is less precise than WGS, it is able to correctly identify the two most prevalent clones (highlighted by the gray rectangles in the figures). Conclusions Considering that Multi-Locus Melting Clustering (MLMC) is faster (~5 hours) and less expensive (~5 euros per isolate) than MLST and WGS (~50 and ~100 euro per isolate, see figure 3), this result clearly shows that MLMC is suitable for real time surveillance programs in hospital settings.
Settore MED/07 - Microbiologia e Microbiologia Clinica
ESCMID - European Society of Clinical Microbiology and Infectious Diseases
Multi-Locus Melting Clustering (MLMC): a novel, fast and inexpensive approach to pathogen typing. Application in a year-long real time nosocomial surveillance program / M. Perini, A. Piazza, S. Papaleo, A. Alvaro, F. Vailati, S. Gaiarsa, F. Saluzzo, F. Gona, C. Farina, P. Marone, D. Maria Cirillo, A. Cavallero, C. Bandi, G.V. Zuccotti, F. Comandatore. ((Intervento presentato al 31. convegno ECCMID - European Congress of Clinical Microbiology & Infectious Diseases tenutosi a Online nel 2021.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/2434/861402
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