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Repeatability and reproducibility of the wzi high resolution melting-based clustering analysis for Klebsiella pneumoniae typing

ABSTRACT: High resolution melting (HRM) is a fast closed-tube method for nucleotide variant scanning applicable for bacterial species identification or molecular typing. Recently a novel HRM-based method for Klebsiella pneumoniae typing has been proposed: it consists of an HRM protocol designed on the capsular wzi gene and an HRM-based algorithm of strains clustering. In this study, we evaluated the repeatability and reproducibility of this method by performing the HRM typing of a set of K. pneumoniae strains, on three different instruments and by two different operators. The results showed that operators do not affect melting temperatures while different instruments can. Despite this, we found that strain clustering analysis, performed using MeltingPlot separately on the data from the three instruments, remains almost perfectly consistent. The HRM method under study resulted highly repeatable and thus reliable for large studies, even when several operators are involved. Furthermore, the HRM clusters obtained from the three different instruments were highly conserved, suggesting that this method could be applied in multicenter studies, even if different instruments are used.

SUBMITTER: Pasala A

PROVIDER: S-EPMC7736600 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature

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Project description:Pathogen typing is pivotal to detecting the emergence of high-risk clones in hospital settings and to limit their spread. Unfortunately, the most commonly used typing methods (i.e., pulsed-field gel electrophoresis [PFGE], multilocus sequence typing [MLST], and whole-genome sequencing [WGS]) are expensive or time-consuming, limiting their application to real-time surveillance. High-resolution melting (HRM) can be applied to perform cost-effective and fast pathogen typing, but developing highly discriminatory protocols is challenging. Here, we present hypervariable-locus melting typing (HLMT), a novel approach to HRM-based typing that enables the development of more effective and portable typing protocols. HLMT types the strains by assigning them to melting types (MTs) on the basis of a reference data set (HLMT-assignment) and/or by clustering them using melting temperatures (HLMT-clustering). We applied the HLMT protocol developed on the capsular gene wzi for Klebsiella pneumoniae on 134 strains collected during surveillance programs in four hospitals. Then, we compared the HLMT results to those obtained using wzi, MLST, WGS, and PFGE typing. HLMT distinguished most of the K. pneumoniae high-risk clones with a sensitivity comparable to that of PFGE and MLST+wzi. It also drew surveillance epidemiological curves comparable to those obtained using MLST+wzi, PFGE, and WGS typing. Furthermore, the results obtained using HLMT-assignment were consistent with those of wzi typing for 95% of the typed strains, with a Jaccard index value of 0.9. HLMT is a fast and scalable approach for pathogen typing, suitable for real-time hospital microbiological surveillance. HLMT is also inexpensive, and thus, it is applicable for infection control programs in low- and middle-income countries. IMPORTANCE In this work, we describe hypervariable-locus melting typing (HLMT), a novel fast approach to pathogen typing using the high-resolution melting (HRM) assay. The method includes a novel approach for gene target selection, primer design, and HRM data analysis. We successfully applied this method to distinguish the high-risk clones of Klebsiella pneumoniae, one of the most important nosocomial pathogens worldwide. We also compared HLMT to typing using WGS, the capsular gene wzi, MLST, and PFGE. Our results show that HLMT is a typing method suitable for real-time epidemiological investigation. The application of HLMT to hospital microbiology surveillance can help to rapidly detect outbreak emergence, improving the effectiveness of infection control strategies.

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Repeatability and reproducibility of the wzi high resolution melting-based clustering analysis for Klebsiella pneumoniae typing

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