Phylotyper: in silico predictor of gene subtypes.

SUMMARY: Whole genome sequencing (WGS) is being adopted in public health for improved surveillance and outbreak analysis. In public health, subtyping has been used to infer phenotypes and distinguish bacterial strain groups. In silico tools that predict subtypes from sequences data are needed to transition historical data to WGS-based protocols. Phylotyper is a novel solution for in silico subtype prediction from gene sequences. Designed for incorporation into WGS pipelines, it is a general prediction tool that can be applied to different subtype schemes. Phylotyper uses phylogeny to model the evolution of the subtype and infer subtypes for unannotated sequences. The phylogenic framework in Phylotyper improves accuracy over approaches based solely on sequence similarity and provides useful contextual feedback. AVAILABILITY AND IMPLEMENTATION: Phylotyper is a python and R package. It is available from: https://github.com/superphy/insilico-subtyping. CONTACT: matthew.whiteside@phac-aspc.gc.ca. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

SuperPhy: predictive genomics for the bacterial pathogen Escherichia coli.

BACKGROUND: Predictive genomics is the translation of raw genome sequence data into a phenotypic assessment of the organism. For bacterial pathogens, these phenotypes can range from environmental survivability, to the severity of human disease. Significant progress has been made in the development of generic tools for genomic analyses that are broadly applicable to all microorganisms; however, a fundamental missing component is the ability to analyze genomic data in the context of organism-specific phenotypic knowledge, which has been accumulated from decades of research and can provide a meaningful interpretation of genome sequence data. RESULTS: In this study, we present SuperPhy, an online predictive genomics platform ( http://lfz.corefacility.ca/superphy/ ) for Escherichia coli. The platform integrates the analytical tools and genome sequence data for all publicly available E. coli genomes and facilitates the upload of new genome sequences from users under public or private settings. SuperPhy provides real-time analyses of thousands of genome sequences with results that are understandable and useful to a wide community, including those in the fields of clinical medicine, epidemiology, ecology, and evolution. SuperPhy includes identification of: 1) virulence and antimicrobial resistance determinants 2) statistical associations between genotypes, biomarkers, geospatial distribution, host, source, and phylogenetic clade; 3) the identification of biomarkers for groups of genomes on the based presence/absence of specific genomic regions and single-nucleotide polymorphisms and 4) in silico Shiga-toxin subtype. CONCLUSIONS: SuperPhy is a predictive genomics platform that attempts to provide an essential link between the vast amounts of genome information currently being generated and phenotypic knowledge in an organism-specific context.

Commensal Escherichia coli Strains of Bovine Origin Competitively Mitigated Escherichia coli O157:H7 in a Gnotobiotic Murine Intestinal Colonization Model with or without Physiological Stress.

Cattle are a primary reservoir of enterohemorrhagic Escherichia coli (EHEC) O157:H7. Currently, there are no effective methods of eliminating this important zoonotic pathogen from cattle, and colonization resistance in relation to EHEC O157:H7 in cattle is poorly understood. We developed a gnotobiotic EHEC O157:H7 murine model to examine aspects of the cattle pathogen-microbiota interaction, and to investigate competitive suppression of EHEC O157:H7 by 18 phylogenetically distinct commensal E. coli strains of bovine origin. As stress has been suggested to influence enteric colonization by EHEC O157:H7 in cattle, corticosterone administration (±) to incite a physiological stress response was included as an experimental variable. Colonization of the intestinal tract (IT) of mice by the bovine EHEC O157:H7 strain, FRIK-2001, mimicked characteristics of bovine IT colonization. In this regard, FRIK-2001 successfully colonized the IT and temporally incited minimal impacts on the host relative to other EHEC O157:H7 strains, including on the renal metabolome. The presence of the commensal E. coli strains decreased EHEC O157:H7 densities in the cecum, proximal colon, and distal colon. Moreover, histopathologic changes and inflammation markers were reduced in the distal colon of mice inoculated with commensal E. coli strains (both propagated separately and communally). Although stress induction affected the behavior of mice, it did not influence EHEC O157:H7 densities or disease. These findings support the use of a gnotobiotic murine model of enteric bovine EHEC O157:H7 colonization to better understand pathogen-host-microbiota interactions toward the development of effective on-farm mitigations for EHEC O157:H7 in cattle, including the identification of bacteria capable of competitively colonizing the IT.

Spatial and temporal drivers of zoonotic pathogen contamination of an agricultural watershed.

In regions where animal agriculture is prominent, such as southern Alberta, higher rates of gastrointestinal illness have been reported when compared with nonagricultural regions. This difference in the rate of illness is thought to be a result of increased zoonotic pathogen exposure through environmental sources such as water. In this study, temporal and spatial factors associated with bacterial pathogen contamination of the Oldman River, which transverses this region, were analyzed using classification and regression tree analysis. Significantly higher levels of fecal indicators; more frequent isolations of Campylobacter spp., Escherichia coli O157:H7, and Salmonella enterica spp.; and higher rates of detection of pig-specific Bacteroides markers occurred at downstream sites than at upstream sites, suggesting additive stream inputs. Fecal indicator densities were also significantly higher when any one of these three bacterial pathogens was present and where there were higher total animal manure units; however, occasionally pathogens were present when fecal indicator levels were low or undetectable. Overall, Salmonella spp., Campylobacter spp., and E. coli O157:H7 presence was associated with season, animal manure units, and total rainfall on the day of sampling and 3 d in advance of sampling. Several of the environmental variables analyzed in this study appear to influence pathogen prevalence and therefore may be useful in predicting water quality and safety and in the improvement of watershed management practices in this and other agricultural regions.

Rapid and accurate SNP genotyping of clonal bacterial pathogens with BioHansel.

Hierarchical genotyping approaches can provide insights into the source, geography and temporal distribution of bacterial pathogens. Multiple hierarchical SNP genotyping schemes have previously been developed so that new isolates can rapidly be placed within pre-computed population structures, without the need to rebuild phylogenetic trees for the entire dataset. This classification approach has, however, seen limited uptake in routine public health settings due to analytical complexity and the lack of standardized tools that provide clear and easy ways to interpret results. The BioHansel tool was developed to provide an organism-agnostic tool for hierarchical SNP-based genotyping. The tool identifies split k-mers that distinguish predefined lineages in whole genome sequencing (WGS) data using SNP-based genotyping schemes. BioHansel uses the Aho-Corasick algorithm to type isolates from assembled genomes or raw read sequence data in a matter of seconds, with limited computational resources. This makes BioHansel ideal for use by public health agencies that rely on WGS methods for surveillance of bacterial pathogens. Genotyping results are evaluated using a quality assurance module which identifies problematic samples, such as low-quality or contaminated datasets. Using existing hierarchical SNP schemes for Mycobacterium tuberculosis and Salmonella Typhi, we compare the genotyping results obtained with the k-mer-based tools BioHansel and SKA, with those of the organism-specific tools TBProfiler and genotyphi, which use gold-standard reference-mapping approaches. We show that the genotyping results are fully concordant across these different methods, and that the k-mer-based tools are significantly faster. We also test the ability of the BioHansel quality assurance module to detect intra-lineage contamination and demonstrate that it is effective, even in populations with low genetic diversity. We demonstrate the scalability of the tool using a dataset of ~8100 S. Typhi public genomes and provide the aggregated results of geographical distributions as part of the tool's output. BioHansel is an open source Python 3 application available on PyPI and Conda repositories and as a Galaxy tool from the public Galaxy Toolshed. In a public health context, BioHansel enables rapid and high-resolution classification of bacterial pathogens with low genetic diversity.

Assessing the genomic relatedness and evolutionary rates of persistent verotoxigenic Escherichia coli serotypes within a closed beef herd in Canada.

Verotoxigenic Escherichia coli (VTEC) are food- and water-borne pathogens associated with both sporadic illness and outbreaks of enteric disease. While it is known that cattle are reservoirs of VTEC, little is known about the genomic variation of VTEC in cattle, and whether the variation in genomes reported for human outbreak strains is consistent with individual animal or group/herd sources of infection. A previous study of VTEC prevalence identified serotypes carried persistently by three consecutive cohorts of heifers within a closed herd of cattle. This present study aimed to: (i) determine whether the genomic relatedness of bovine isolates is similar to that reported for human strains associated with single source outbreaks, (ii) estimate the rates of genome change among dominant serotypes over time within a cattle herd, and (iii) identify genomic features of serotypes associated with persistence in cattle. Illumina MiSeq genome sequencing and genotyping based on allelic and single nucleotide variations were completed, while genome change over time was measured using Bayesian evolutionary analysis sampling trees. The accessory genome, including the non-protein-encoding intergenic regions (IGRs), virulence factors, antimicrobial-resistance genes and plasmid gene content of representative persistent and sporadic cattle strains were compared using Fisher's exact test corrected for multiple comparisons. Herd strains from serotypes O6:H34 (n=22), O22:H8 (n=30), O108:H8 (n=39), O139:H19 (n=44) and O157:H7 (n=106) were readily distinguishable from epidemiologically unrelated strains of the same serotype using a similarity threshold of 10 or fewer allele differences between adjacent nodes. Temporal-cohort clustering within each serotype was supported by date randomization analysis. Substitutions per site per year were consistent with previously reported values for E. coli; however, there was low branch support for these values. Acquisition of the phage-encoded Shiga toxin 2 gene in serotype O22:H8 was observed. Pan-genome analyses identified accessory regions that were more prevalent in persistent serotypes (P≤0.05) than in sporadic serotypes. These results suggest that VTEC serotypes from a specific cattle population are highly clonal with a similar level of relatedness as human single-source outbreak-associated strains, but changes in the genome occur gradually over time. Additionally, elements in the accessory genomes may provide a selective advantage for persistence of VTEC within cattle herds.

In silico genomic analyses reveal three distinct lineages of Escherichia coli O157:H7, one of which is associated with hyper-virulence.

BACKGROUND: Many approaches have been used to study the evolution, population structure and genetic diversity of Escherichia coli O157:H7; however, observations made with different genotyping systems are not easily relatable to each other. Three genetic lineages of E. coli O157:H7 designated I, II and I/II have been identified using octamer-based genome scanning and microarray comparative genomic hybridization (mCGH). Each lineage contains significant phenotypic differences, with lineage I strains being the most commonly associated with human infections. Similarly, a clade of hyper-virulent O157:H7 strains implicated in the 2006 spinach and lettuce outbreaks has been defined using single-nucleotide polymorphism (SNP) typing. In this study an in silico comparison of six different genotyping approaches was performed on 19 E. coli genome sequences from 17 O157:H7 strains and single O145:NM and K12 MG1655 strains to provide an overall picture of diversity of the E. coli O157:H7 population, and to compare genotyping methods for O157:H7 strains. RESULTS: In silico determination of lineage, Shiga-toxin bacteriophage integration site, comparative genomic fingerprint, mCGH profile, novel region distribution profile, SNP type and multi-locus variable number tandem repeat analysis type was performed and a supernetwork based on the combination of these methods was produced. This supernetwork showed three distinct clusters of strains that were O157:H7 lineage-specific, with the SNP-based hyper-virulent clade 8 synonymous with O157:H7 lineage I/II. Lineage I/II/clade 8 strains clustered closest on the supernetwork to E. coli K12 and E. coli O55:H7, O145:NM and sorbitol-fermenting O157 strains. CONCLUSION: The results of this study highlight the similarities in relationships derived from multi-locus genome sampling methods and suggest a "common genotyping language" may be devised for population genetics and epidemiological studies. Future genotyping methods should provide data that can be stored centrally and accessed locally in an easily transferable, informative and extensible format based on comparative genomic analyses.

Targeting discriminatory SNPs in Salmonella enterica serovar Heidelberg genomes using RNase H2-dependent PCR.

We report a novel RNase H2-dependent PCR (rhPCR) genotyping assay for a small number of discriminatory single-nucleotide polymorphisms (SNPs) that identify lineages and sub-lineages of the highly clonal pathogen Salmonella Heidelberg (SH). Standard PCR primers targeting numerous SNP locations were initially designed in silico, modified to be RNase H2-compatible, and then optimized by laboratory testing. Optimization often required repeated cycling through variations in primer design, assay conditions, reagent concentrations and selection of alternative SNP targets. The final rhPCR assay uses 28 independent rhPCR reactions to target 14 DNA bases that can distinguish 15 possible lineages and sub-lineages of SH. On evaluation, the assay correctly identified the 12 lineages and sub-lineages represented in a panel of 75 diverse SH strains. Non-specific amplicons were observed in 160 (15.2%) of the 1050 reactions, but due to their low intensity did not compromise assay performance. Furthermore, in silico analysis of 500 closed genomes from 103 Salmonella serovars and laboratory rhPCR testing of five prevalent Salmonella serovars including SH indicated the assay can identify Salmonella isolates as SH, since only SH isolates generated amplicons from all 14 target SNPs. The genotyping results can be fully correlated with whole genome sequencing (WGS) data in silico. This fast and economical assay, which can identify SH isolates and classify them into related or unrelated lineages and sub-lineages, has potential applications in outbreak identification, source attribution and microbial source tracking.

Multi-Year Persistence of Verotoxigenic Escherichia coli (VTEC) in a Closed Canadian Beef Herd: A Cohort Study.

In this study, fecal samples were collected from a closed beef herd in Alberta, Canada from 2012 to 2015. To limit serotype bias, which was observed in enrichment broth cultures, Verotoxigenic Escherichia coli (VTEC) were isolated directly from samples using a hydrophobic grid-membrane filter verotoxin immunoblot assay. Overall VTEC isolation rates were similar for three different cohorts of yearling heifers on both an annual (68.5 to 71.8%) and seasonal basis (67.3 to 76.0%). Across all three cohorts, O139:H19 (37.1% of VTEC-positive samples), O22:H8 (15.8%) and O?(O108):H8 (15.4%) were among the most prevalent serotypes. However, isolation rates for serotypes O139:H19, O130:H38, O6:H34, O91:H21, and O113:H21 differed significantly between cohort-years, as did isolation rates for some serotypes within a single heifer cohort. There was a high level of VTEC serotype diversity with an average of 4.3 serotypes isolated per heifer and 65.8% of the heifers classified as "persistent shedders" of VTEC based on the criteria of >50% of samples positive and ≥4 consecutive samples positive. Only 26.8% (90/336) of the VTEC isolates from yearling heifers belonged to the human disease-associated seropathotypes A (O157:H7), B (O26:H11, O111:NM), and C (O22:H8, O91:H21, O113:H21, O137:H41, O2:H6). Conversely, seropathotypes B (O26:NM, O111:NM) and C (O91:H21, O2:H29) strains were dominant (76.0%, 19/25) among VTEC isolates from month-old calves from this herd. Among VTEC from heifers, carriage rates of vt1, vt2, vt1+vt2, eae, and hlyA were 10.7, 20.8, 68.5, 3.9, and 88.7%, respectively. The adhesin gene saa was present in 82.7% of heifer strains but absent from all of 13 eae+ve strains (from serotypes/intimin types O157:H7/γ1, O26:H11/ß1, O111:NM/θ, O84:H2/ζ, and O182:H25/ζ). Phylogenetic relationships inferred from wgMLST and pan genome-derived core SNP analysis showed that strains clustered by phylotype and serotype. Further, VTEC strains of the same serotype usually shared the same suite of antibiotic resistance and virulence genes, suggesting the circulation of dominant clones within this distinct herd. This study provides insight into the diverse and dynamic nature of VTEC populations within groups of cattle and points to a broad spectrum of human health risks associated with these E. coli strains.

Spfy: an integrated graph database for real-time prediction of bacterial phenotypes and downstream comparative analyses.

Public health laboratories are currently moving to whole-genome sequence (WGS)-based analyses, and require the rapid prediction of standard reference laboratory methods based solely on genomic data. Currently, these predictive genomics tasks rely on workflows that chain together multiple programs for the requisite analyses. While useful, these systems do not store the analyses in a genome-centric way, meaning the same analyses are often re-computed for the same genomes. To solve this problem, we created Spfy, a platform that rapidly performs the common reference laboratory tests, uses a graph database to store and retrieve the results from the computational workflows and links data to individual genomes using standardized ontologies. The Spfy platform facilitates rapid phenotype identification, as well as the efficient storage and downstream comparative analysis of tens of thousands of genome sequences. Though generally applicable to bacterial genome sequences, Spfy currently contains 10 243 Escherichia coli genomes, for which in-silico serotype and Shiga-toxin subtype, as well as the presence of known virulence factors and antimicrobial resistance determinants have been computed. Additionally, the presence/absence of the entire E. coli pan-genome was computed and linked to each genome. Owing to its database of diverse pre-computed results, and the ability to easily incorporate user data, Spfy facilitates hypothesis testing in fields ranging from population genomics to epidemiology, while mitigating the re-computation of analyses. The graph approach of Spfy is flexible, and can accommodate new analysis software modules as they are developed, easily linking new results to those already stored. Spfy provides a database and analyses approach for E. coli that is able to match the rapid accumulation of WGS data in public databases.

Pan-genome Analyses of the Species Salmonella enterica, and Identification of Genomic Markers Predictive for Species, Subspecies, and Serovar.

Food safety is a global concern, with upward of 2.2 million deaths due to enteric disease every year. Current whole-genome sequencing platforms allow routine sequencing of enteric pathogens for surveillance, and during outbreaks; however, a remaining challenge is the identification of genomic markers that are predictive of strain groups that pose the most significant health threats to humans, or that can persist in specific environments. We have previously developed the software program Panseq, which identifies the pan-genome among a group of sequences, and the SuperPhy platform, which utilizes this pan-genome information to identify biomarkers that are predictive of groups of bacterial strains. In this study, we examined the pan-genome of 4893 genomes of Salmonella enterica, an enteric pathogen responsible for the loss of more disability adjusted life years than any other enteric pathogen. We identified a pan-genome of 25.3 Mbp, a strict core of 1.5 Mbp present in all genomes, and a conserved core of 3.2 Mbp found in at least 96% of these genomes. We also identified 404 genomic regions of 1000 bp that were specific to the species S. enterica. These species-specific regions were found to encode mostly hypothetical proteins, effectors, and other proteins related to virulence. For each of the six S. enterica subspecies, markers unique to each were identified. No serovar had pan-genome regions that were present in all of its genomes and absent in all other serovars; however, each serovar did have genomic regions that were universally present among all constituent members, and statistically predictive of the serovar. The phylogeny based on SNPs within the conserved core genome was found to be highly concordant to that produced by a phylogeny using the presence/absence of 1000 bp regions of the entire pan-genome. Future studies could use these predictive regions as components of a vaccine to prevent salmonellosis, as well as in simple and rapid diagnostic tests for both in silico and wet-lab applications, with uses ranging from food safety to public health. Lastly, the tools and methods described in this study could be applied as a pan-genomics framework to other population genomic studies seeking to identify markers for other bacterial species and their sub-groups.

Comparative Genomic Analysis of Escherichia coli O157:H7 Isolated from Super-Shedder and Low-Shedder Cattle.

Cattle are the primary reservoir of the foodborne pathogen Escherichia coli O157:H7, with the concentration and frequency of E. coli O157:H7 shedding varying substantially among individual hosts. The term ''super-shedder" has been applied to cattle that shed ≥10(4) cfu E. coli O157:H7/g of feces. Super-shedders have been reported to be responsible for the majority of E. coli O157:H7 shed into the environment. The objective of this study was to determine if there are phenotypic and/or genotypic differences between E. coli O157:H7 isolates obtained from super-shedder compared to low-shedder cattle. From a total of 784 isolates, four were selected from low-shedder steers and six isolates from super-shedder steers (4.01-8.45 log cfu/g feces) for whole genome sequencing. Isolates were phage and clade typed, screened for substrate utilization, pH sensitivity, virulence gene profiles and Stx bacteriophage insertion (SBI) sites. A range of 89-2473 total single nucleotide polymorphisms (SNPs) were identified when sequenced strains were compared to E. coli O157:H7 strain Sakai. More non-synonymous SNP mutations were observed in low-shedder isolates. Pan-genomic and SNPs comparisons did not identify genetic segregation between super-shedder or low-shedder isolates. All super-shedder isolates and 3 of 4 of low-shedder isolates were typed as phage type 14a, SBI cluster 3 and SNP clade 2. Super-shedder isolates displayed increased utilization of galactitol, thymidine and 3-O-ß-D-galactopyranosyl-D-arabinose when compared to low-shedder isolates, but no differences in SNPs were observed in genes encoding for proteins involved in the metabolism of these substrates. While genetic traits specific to super-shedder isolates were not identified in this study, differences in the level of gene expression or genes of unknown function may still contribute to some strains of E. coli O157:H7 reaching high densities within bovine feces.

The Salmonella In Silico Typing Resource (SISTR): An Open Web-Accessible Tool for Rapidly Typing and Subtyping Draft Salmonella Genome Assemblies.

For nearly 100 years serotyping has been the gold standard for the identification of Salmonella serovars. Despite the increasing adoption of DNA-based subtyping approaches, serotype information remains a cornerstone in food safety and public health activities aimed at reducing the burden of salmonellosis. At the same time, recent advances in whole-genome sequencing (WGS) promise to revolutionize our ability to perform advanced pathogen characterization in support of improved source attribution and outbreak analysis. We present the Salmonella In Silico Typing Resource (SISTR), a bioinformatics platform for rapidly performing simultaneous in silico analyses for several leading subtyping methods on draft Salmonella genome assemblies. In addition to performing serovar prediction by genoserotyping, this resource integrates sequence-based typing analyses for: Multi-Locus Sequence Typing (MLST), ribosomal MLST (rMLST), and core genome MLST (cgMLST). We show how phylogenetic context from cgMLST analysis can supplement the genoserotyping analysis and increase the accuracy of in silico serovar prediction to over 94.6% on a dataset comprised of 4,188 finished genomes and WGS draft assemblies. In addition to allowing analysis of user-uploaded whole-genome assemblies, the SISTR platform incorporates a database comprising over 4,000 publicly available genomes, allowing users to place their isolates in a broader phylogenetic and epidemiological context. The resource incorporates several metadata driven visualizations to examine the phylogenetic, geospatial and temporal distribution of genome-sequenced isolates. As sequencing of Salmonella isolates at public health laboratories around the world becomes increasingly common, rapid in silico analysis of minimally processed draft genome assemblies provides a powerful approach for molecular epidemiology in support of public health investigations. Moreover, this type of integrated analysis using multiple sequence-based methods of sub-typing allows for continuity with historical serotyping data as we transition towards the increasing adoption of genomic analyses in epidemiology. The SISTR platform is freely available on the web at https://lfz.corefacility.ca/sistr-app/.

A new pyrosequencing assay for rapid detection and genotyping of Shiga toxin, intimin and O157-specific rfbE genes of Escherichia coli.

Shiga toxin (stx)-producing Escherichia coli (STEC) contamination in food and water is one of the most recognized concerns and a major financial burden in human hygiene control worldwide. Rapid and highly reliable methods of detecting and identifying STEC causing gastroenteric illnesses are crucial to prevent foodborne outbreaks. A number of tests have been developed and commercialized to detect STEC using molecular microbiology techniques. Most of these are designed to identify virulence factors such as Shiga toxin and intimin as well as E. coli O and H antigen serotype specific genes. In order to screen pathogenic STEC without relying on O:H serotyping, we developed a rapid detection and genotyping assay for STEC virulence genes using a PCR-pyrosequencing application. We adapted the PyroMark Q24 Pyrosequencing platform for subtyping 4 major virulence genes, Shiga toxin 1 and 2 (stx1 and stx2), intimin (eae) and O157-antigen gene cluster target rfbE, using Single Nucleotide Polymorphism (SNP) analysis. A total of 224 E. coli strains including isolates from Canadian environment, food and clinical cases were examined. Based on the multiple alignment analysis of 30-80 base nucleotide pyrogram reads, three alleles of the Shiga toxin 1a gene (stx1a) (stx1a-I, stx1a-II, stx1a-III) were identified. Results of the stx1, stx2, eae and rfbE genotyping revealed that each group of O:H serotype shares distinctive characteristics that could be associated with the virulence of each genotype. O157:H7/NM carries stx1a-II (94%), stx2a (82%), λ/γ1-eae (100%) and rfbE type-H7/NM (100%). Whereas isolates of the "Top-6" serotypes (O26, O45, O103, O111, O121, O145) had a high incidence of stx1a-I (90%) and stx2a (100%). stx1a-III (60%) was only observed in non Top-7 (Top-6 plus O157) STEC and Shigella spp. The entire assay, from extracting DNA from colonies on a plate to the generation of sequence information, can be completed in 5h. The method of profiling these 4 STEC pathogenic genotypes as demonstrated in this paper is rapid, easily performed, informative and cost-effective, and thus has a potential to be deployed in the food industry for the routine screening of potentially pathogenic STEC isolates.

Exploiting the explosion of information associated with whole genome sequencing to tackle Shiga toxin-producing Escherichia coli (STEC) in global food production systems.

The rates of foodborne disease caused by gastrointestinal pathogens continue to be a concern in both the developed and developing worlds. The growing world population, the increasing complexity of agri-food networks and the wide range of foods now associated with STEC are potential drivers for increased risk of human disease. It is vital that new developments in technology, such as whole genome sequencing (WGS), are effectively utilized to help address the issues associated with these pathogenic microorganisms. This position paper, arising from an OECD funded workshop, provides a brief overview of next generation sequencing technologies and software. It then uses the agent-host-environment paradigm as a basis to investigate the potential benefits and pitfalls of WGS in the examination of (1) the evolution and virulence of STEC, (2) epidemiology from bedside diagnostics to investigations of outbreaks and sporadic cases and (3) food protection from routine analysis of foodstuffs to global food networks. A number of key recommendations are made that include: validation and standardization of acquisition, processing and storage of sequence data including the development of an open access "WGSNET"; building up of sequence databases from both prospective and retrospective isolates; development of a suite of open-access software specific for STEC accessible to non-bioinformaticians that promotes understanding of both the computational and biological aspects of the problems at hand; prioritization of research funding to both produce and integrate genotypic and phenotypic information suitable for risk assessment; training to develop a supply of individuals working in bioinformatics/software development; training for clinicians, epidemiologists, the food industry and other stakeholders to ensure uptake of the technology and finally review of progress of implementation of WGS. Currently the benefits of WGS are being slowly teased out by academic, government, and industry or private sector researchers around the world. The next phase will require a coordinated international approach to ensure that it's potential to contribute to the challenge of STEC disease can be realized in a cost effective and timely manner.

Characteristics of clinical Shiga toxin-producing Escherichia coli isolated from British Columbia.

Shiga toxin-producing Escherichia coli (STEC) are significant public health threats. Although STEC O157 are recognized foodborne pathogens, non-O157 STEC are also important causes of human disease. We characterized 10 O157:H7 and 15 non-O157 clinical STEC derived from British Columbia (BC). Eae, hlyA, and stx were more frequently observed in STEC O157, and 80 and 100% of isolates possessed stx1 and stx2, respectively. In contrast, stx1 and stx2 occurred in 80 and 40% of non-O157 STEC, respectively. Comparative genomic fingerprinting (CGF) revealed three distinct clusters (C). STEC O157 was identified as lineage I (LI; LSPA-6 111111) and clustered as a single group (C1). The cdi gene previously observed only in LII was seen in two LI O157 isolates. CGF C2 strains consisted of diverse non-O157 STEC while C3 included only O103:H25, O118, and O165 serogroup isolates. With the exception of O121 and O165 isolates which were similar in virulence gene complement to STEC O157, C1 O157 STEC produced more Stx2 than non-O157 STEC. Antimicrobial resistance (AMR) screening revealed resistance or reduced sensitivity in all strains, with higher levels occurring in non-O157 STEC. One STEC O157 isolate possessed a mobile bla(CMY-2) gene transferrable across genre via conjugation.

A comparison of Shiga-toxin 2 bacteriophage from classical enterohemorrhagic Escherichia coli serotypes and the German E. coli O104:H4 outbreak strain.

Escherichia coli O104:H4 was associated with a severe foodborne disease outbreak originating in Germany in May 2011. More than 4000 illnesses and 50 deaths were reported. The outbreak strain was a typical enteroaggregative E. coli (EAEC) that acquired an antibiotic resistance plasmid and a Shiga-toxin 2 (Stx2)-encoding bacteriophage. Based on whole-genome phylogenies, the O104:H4 strain was most closely related to other EAEC strains; however, Stx2-bacteriophage are mobile, and do not necessarily share an evolutionary history with their bacterial host. In this study, we analyzed Stx2-bacteriophage from the E. coli O104:H4 outbreak isolates and compared them to all available Stx2-bacteriophage sequences. We also compared Stx2 production by an E. coli O104:H4 outbreak-associated isolate (ON-2011) to that of E. coli O157:H7 strains EDL933 and Sakai. Among the E. coli Stx2-phage sequences studied, that from O111:H- strain JB1-95 was most closely related phylogenetically to the Stx2-phage from the O104:H4 outbreak isolates. The phylogeny of most other Stx2-phage was largely concordant with their bacterial host genomes. Finally, O104:H4 strain ON-2011 produced less Stx2 than E. coli O157:H7 strains EDL933 and Sakai in culture; however, when mitomycin C was added, ON-2011 produced significantly more toxin than the E. coli O157:H7 strains. The Stx2-phage from the E. coli O104:H4 outbreak strain and the Stx2-phage from O111:H- strain JB1-95 likely share a common ancestor. Incongruence between the phylogenies of the Stx2-phage and their host genomes suggest the recent Stx2-phage acquisition by E. coli O104:H4. The increase in Stx2-production by ON-2011 following mitomycin C treatment may or may not be related to the high rates of hemolytic uremic syndrome associated with the German outbreak strain. Further studies are required to determine whether the elevated Stx2-production levels are due to bacteriophage or E. coli O104:H4 host related factors.

Everything at once: comparative analysis of the genomes of bacterial pathogens.

The sum of unique genes in all genomes of a bacterial species is referred to as the pan-genome and is comprised of variably absent or present accessory genes and universally present core genes. The accessory genome is an important source of genetic variability in bacterial populations, allowing sub-populations of bacteria to better adapt to specific niches. Such subgroups may themselves have a relatively stable core genome that may influence host preference, virulence, or an association with specific disease syndromes. The core genome provides a useful means of phylogenetic reconstruction as well as contributing to phenotypic heterogeneity. Variation within the pan-genome forms the basis of comparative genotyping techniques, which have evolved alongside technology. Current high-throughput sequencing platforms have created an unprecedented opportunity for comparisons among multiple, closely related genomes. The computer algorithms and software for such comparisons continue to evolve and promise exciting advances in the world of bacterial comparative genomics. We review genotyping techniques based upon phenotypic traits, both core and accessory genomes, and look at some of the software programs currently available to perform whole-genome comparative analyses.