WGS shows ‘promise’ as typing method
The researchers evaluated WGS for typing of Salmonella Typhimurium and four different approaches for analyzing and comparing the data.
Different bioinformatics tools were applied on the data; including pan-genome tree, k-mer tree, nucleotide difference tree and SNP tree.
The pan-genome tree clustered 65% of S. Typhimurium isolates according to pre-defined epidemiology, the k-mer tree 88%, the nucleotide difference tree 100% and the SNP tree 100% of the strains.
The 100% means all outbreak-related strains from a particular outbreak clustered together and separated from any background isolates.
WGS alone is insufficient to see if strains are related or unrelated to outbreaks. This still requires combination of epidemiological data and WGS results, said the researchers.
PFGE method
Pulsed-field gel electrophoresis (PFGE) has been the gold standard for epidemiological investigations for Salmonella but it is unable to separate very closely related strains.
Serotyping, phage typing, PFGE and multilocus variable number of tandem repeat analysis (MLVA) have also been used.
The researchers said the cost of WGS has decreased and the technology is becoming increasingly available as well as the potential of the sequencing speed decreasing from days or weeks to hours for a bacterial genome.
A collection of 34 S. Typhimurium isolates was sequenced, 18 isolates from six outbreaks and 16 epidemiologically unrelated background strains. Eight S. Enteritidis and five S. Derby were also sequenced for comparison.
Bioinformatics used
Pan-genome tree was constructed from the pan-genome matrix that composed of genes and genomes as rows and columns respectively.
K-mer tree is constructed from the contiguous sequences of k bases called k-mers.
The nucleotide difference tree (ND tree) based on nucleotide difference between a pair of read mapped reference genomes.
SNP tree was computed from concatenated qualified SNPs identified from mapping raw reads to core genes of the reference genome.
“In conclusion, this study suggests that WGS and analysis using SNP and/or nucleotide difference approaches are superior methodologies for epidemiological typing of S. Typhimurium isolates and might be very successfully applied for outbreak detection,” said the researchers.
“For the very fast but rough result, k-mer tree might meet this requirement with constructing the tree in high speed and giving high accuracy in clade level.”
Source: PloS ONE
Online ahead of print, DOI: 10.1371/journal.pone.0087991
“Evaluation of Whole Genome Sequencing for Outbreak Detection of Salmonella enterica”
Authors: Pimlapas Leekitcharoenphon, Eva M. Nielsen, Rolf S. Kaas, Ole Lund, Frank M. Aarestrup
