SNVPhyl: A Single Nucleotide Variant Phylogenomics pipeline for microbial genomic epidemiology

Petkau, A.; Mabon, Philip; Sieffert, Cameron; Knox, Natalie; Cabral, Jennifer; Iskander, Mariam; Iskander, Mark; Weedmark, Kelly; Zaheer, Rahat; Katz, Lee S.; Nadon, Céline; Reimer, Aleisha; Taboada, Eduardo; Beiko, Robert G.; Hsiao, William W. L.; Brinkman, Fiona S. L.; Graham, Morag; Domselaar, Gary Van

doi:10.1101/092940

Cited by 30 publications

(44 citation statements)

References 42 publications

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“…“1” indicates the feature is present; “0” indicates that the feature is absent. A comparison of software-level features, e.g., command-line vs. web interface, has already been performed in Petkau et al (2016) .…”

Section: Methodsmentioning

confidence: 99%

“…The initial version of SET was used for the Haiti cholera outbreak of 2010 (Katz et al, 2013). The common code base of SET has since been forked, with the NML branch rebranded as SNVPhyl (Petkau et al, 2016) and the CDC version as Lyve-SET, named after the organisms with which it was first used: Listeria, Yersinia, Vibrio , and Enterobacteriaceae. Since 2013, the Centers of Disease Control and Prevention (CDC) has participated in an interagency collaboration to routinely sequence and analyze all clinical and food-related Listeria monocytogenes isolates in the US with the eventual goal to replace PFGE (Carleton and Gerner-Smidt, 2016).…”

Section: Introductionmentioning

confidence: 99%

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A Comparative Analysis of the Lyve-SET Phylogenomics Pipeline for Genomic Epidemiology of Foodborne Pathogens

et al. 2017

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Modern epidemiology of foodborne bacterial pathogens in industrialized countries relies increasingly on whole genome sequencing (WGS) techniques. As opposed to profiling techniques such as pulsed-field gel electrophoresis, WGS requires a variety of computational methods. Since 2013, United States agencies responsible for food safety including the CDC, FDA, and USDA, have been performing whole-genome sequencing (WGS) on all Listeria monocytogenes found in clinical, food, and environmental samples. Each year, more genomes of other foodborne pathogens such as Escherichia coli, Campylobacter jejuni, and Salmonella enterica are being sequenced. Comparing thousands of genomes across an entire species requires a fast method with coarse resolution; however, capturing the fine details of highly related isolates requires a computationally heavy and sophisticated algorithm. Most L. monocytogenes investigations employing WGS depend on being able to identify an outbreak clade whose inter-genomic distances are less than an empirically determined threshold. When the difference between a few single nucleotide polymorphisms (SNPs) can help distinguish between genomes that are likely outbreak-associated and those that are less likely to be associated, we require a fine-resolution method. To achieve this level of resolution, we have developed Lyve-SET, a high-quality SNP pipeline. We evaluated Lyve-SET by retrospectively investigating 12 outbreak data sets along with four other SNP pipelines that have been used in outbreak investigation or similar scenarios. To compare these pipelines, several distance and phylogeny-based comparison methods were applied, which collectively showed that multiple pipelines were able to identify most outbreak clusters and strains. Currently in the US PulseNet system, whole genome multi-locus sequence typing (wgMLST) is the preferred primary method for foodborne WGS cluster detection and outbreak investigation due to its ability to name standardized genomic profiles, its central database, and its ability to be run in a graphical user interface. However, creating a functional wgMLST scheme requires extended up-front development and subject-matter expertise. When a scheme does not exist or when the highest resolution is needed, SNP analysis is used. Using three Listeria outbreak data sets, we demonstrated the concordance between Lyve-SET SNP typing and wgMLST.Availability: Lyve-SET can be found at https://github.com/lskatz/Lyve-SET.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Comparative Analysis of the Lyve-SET Phylogenomics Pipeline for Genomic Epidemiology of Foodborne Pathogens

et al. 2017

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“…To infer the genetic distance for the Calgary 2012 isolates compared to other ST222 strains, a phylogeny based on core SNVs was generated [25] (Fig. 6).…”

Section: Resultsmentioning

confidence: 99%

“…Phylogenies based on single nucleotide variants (SNVs) were generated using the SNVPhyl pipeline [25]. Briefly, paired-end reads were mapped to the Toronto-2005 outbreak reference genome (Genbank accession no.…”

Section: Methodsmentioning

confidence: 99%

Unusual Legionnaires' outbreak in cool, dry Western Canada: an investigation using genomic epidemiology

et al. 2016

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SUMMARYAn outbreak of Legionnaires' disease occurred in an inner city district in Calgary, Canada. This outbreak spanned a 3-week period in November–December 2012, and a total of eight cases were identified. Four of these cases were critically ill requiring intensive care admission but there was no associated mortality. All cases tested positive for Legionella pneumophila serogroup 1 (LP1) by urinary antigen testing. Five of the eight patients were culture positive for LP1 from respiratory specimens. These isolates were further identified as Knoxville monoclonal subtype and sequence subtype ST222. Whole-genome sequencing revealed that the isolates differed by no more than a single vertically acquired single nucleotide variant, supporting a single point-source outbreak. Hypothesis-based environmental investigation and sampling was conducted; however, a definitive source was not identified. Geomapping of case movements within the affected urban sector revealed a 1·0 km common area of potential exposure, which coincided with multiple active construction sites that used water spray to minimize transient dust. This community point-source Legionnaires' disease outbreak is unique due to its ST222 subtype and occurrence in a relatively dry and cold weather setting in Western Canada. This report suggests community outbreaks of Legionella should not be overlooked as a possibility during late autumn and winter months in the Northern Hemisphere.

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“…In the context of outbreak investigation, the genomic data will be used to assess high-quality SNPs and core/whole genome MLST for their usefulness in genetic discrimination in addition to other emerging methods such as CRISPR and prophage sequence typing. As for outbreak investigation software, the National Microbiology Laboratory-Public Health Agency of Canada group has implemented the Integrated Rapid Infectious Disease Analysis project (IRIDA) 5 and developed the SNVPhyl phylogenomics pipeline that is in use by PulseNet Canada for microbial genomic epidemiology (Petkau et al, 2016). A complementary system called the Metagenomics Computation and Analytics Workbench (MCAW) is being implemented as a computing service for food safety (Edlund et al, 2016; Weimer et al, 2016).…”

Section: Sequencing 4500 Salmonella Genomes: Objectives and Strategymentioning

confidence: 99%

A Syst-OMICS Approach to Ensuring Food Safety and Reducing the Economic Burden of Salmonellosis

et al. 2017

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The Salmonella Syst-OMICS consortium is sequencing 4,500 Salmonella genomes and building an analysis pipeline for the study of Salmonella genome evolution, antibiotic resistance and virulence genes. Metadata, including phenotypic as well as genomic data, for isolates of the collection are provided through the Salmonella Foodborne Syst-OMICS database (SalFoS), at https://salfos.ibis.ulaval.ca/. Here, we present our strategy and the analysis of the first 3,377 genomes. Our data will be used to draw potential links between strains found in fresh produce, humans, animals and the environment. The ultimate goals are to understand how Salmonella evolves over time, improve the accuracy of diagnostic methods, develop control methods in the field, and identify prognostic markers for evidence-based decisions in epidemiology and surveillance.

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SNVPhyl: A Single Nucleotide Variant Phylogenomics pipeline for microbial genomic epidemiology

Abstract: 22Motivation: The recent widespread application of whole-genome sequencing (WGS) for microbial 23

Cited by 30 publications

References 42 publications

A Comparative Analysis of the Lyve-SET Phylogenomics Pipeline for Genomic Epidemiology of Foodborne Pathogens

A Comparative Analysis of the Lyve-SET Phylogenomics Pipeline for Genomic Epidemiology of Foodborne Pathogens

Unusual Legionnaires' outbreak in cool, dry Western Canada: an investigation using genomic epidemiology

A Syst-OMICS Approach to Ensuring Food Safety and Reducing the Economic Burden of Salmonellosis

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