Dynamic time warping assessment and sensitive high resolution melting analysis for subtyping Salmonella isolates from the Northern Thailand

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1 Department of Material Engineering, School of Science, Mae Fah Luang University, Chiang Rai, Thailand
2 Department of Medical Sciences, WHO National Salmonella and Shigella Center, National Institute of Health, Ministry of Public Health, Bangkok, Thailand
3 Veterinary Research and Development Center (Upper Northern Region), Lampang, Thailand
4 Division of Biology, School of Science, University of Phayao, Phayao, Thailand
5 Division of Biochemistry, School of Medical Sciences, University of Phayao, Phayao, Thailand
DOI
10.7287/peerj.preprints.27664v1
Published
Accepted
Subject Areas
Microbiology, Molecular Biology, Epidemiology
Keywords
Salmonella subtyping, S-HRM analysis, Dynamic time warping assessment, Northern Thailand, Clustering methods, HRM serotyping
Copyright
© 2019 Wisittipanit et al.
Licence
This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Preprints) and either DOI or URL of the article must be cited.
Cite this article
Wisittipanit N, Pulsrikarn C, Wutthiosot S, Pinmongkhonkul S, Poonchareon K. 2019. Dynamic time warping assessment and sensitive high resolution melting analysis for subtyping Salmonella isolates from the Northern Thailand. PeerJ Preprints 7:e27664v1

Abstract

Background: Nontyphoidal Salmonella spp. transmitted through various routes are a major concern of food poisoning due to the consumption of contaminated food.

Objective: To establish a molecular-based protocol for simple and rapid subtyping of Salmonella isolates from various sources.

Materials and methods: Sensitive High-Resolution Melting-curve analysis (S-HRMa) and Dynamic Time Warping assessment (DTW) were applied for serotyping forty Salmonella spp. isolates from various origins and locations in seven provinces in the north of Thailand; the results were compared to those from conventional serotyping and ERIC- PCR.

Results: HRM serotyping of forty Salmonella spp. initially produced fourteen melting-curves with two predominant clusters: C1 (n=18) and C2 (n=9). Applying S-HRMa and serogroups generated twenty-five sensitive clusters. Conventional serotyping revealed that cluster C1 and C2 comprised of six different Salmonella serotypes with S. Weltevradent (n=14) as the predominant one. The S-HRMa also suggested the possible subtyping in some serotypes. In addition, DTW was performed to cluster those forty Salmonella spp. into twenty-eight clusters, assigned into different four clades corresponding to S-HRMa. The two clustering methods indicated that the S. Weltevreden was the predominant subtype (DTW4-S1, n=6). Three ERIC clusters at 92% similarity index also corresponded to the results of those two clustering methods. With important and related epidemiological data, S. Derby and S. Monophasic were suggested to be related to the slaughterhouse and swine. In this study, the ERIC cluster 10 comprising two Salmonella isolates of S. Weltevraden suggested the transmission route was likely to be farm-to-farm in the same province.

Conclusions: The DTW assessment and S-HRMa effectively increased the discrimatory power of clustering to the same level as that of ERIC - PCR and were a simple and rapid protocol to perform Salmonella subtyping for the epidemiological research.

Author Comment

This is a submission to PeerJ for review.

Supplemental Information

Normalized Melt Relative Fluorescent Unit (RFU) data of 40 Salmonella isolates at the Northern Thailand during February 2018 to September 2019

Normalized melt curves generated from HRM were used to construct a dendrogram of hierarchical clustering, using DTW as a distance measure.

DOI: 10.7287/peerj.preprints.27664v1/supp-1