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.

ECTyper: in silico Escherichia coli serotype and species prediction from raw and assembled whole-genome sequence data.

Escherichia coli is a priority foodborne pathogen of public health concern and phenotypic serotyping provides critical information for surveillance and outbreak detection activities. Public health and food safety laboratories are increasingly adopting whole-genome sequencing (WGS) for characterizing pathogens, but it is imperative to maintain serotype designations in order to minimize disruptions to existing public health workflows. Multiple in silico tools have been developed for predicting serotypes from WGS data, including SRST2, SerotypeFinder and EToKi EBEis, but these tools were not designed with the specific requirements of diagnostic laboratories, which include: speciation, input data flexibility (fasta/fastq), quality control information and easily interpretable results. To address these specific requirements, we developed ECTyper (https://github.com/phac-nml/ecoli_serotyping) for performing both speciation within Escherichia and Shigella, and in silico serotype prediction. We compared the serotype prediction performance of each tool on a newly sequenced panel of 185 isolates with confirmed phenotypic serotype information. We found that all tools were highly concordant, with 92-97 % for O-antigens and 98-100 % for H-antigens, and ECTyper having the highest rate of concordance. We extended the benchmarking to a large panel of 6954 publicly available E. coli genomes to assess the performance of the tools on a more diverse dataset. On the public data, there was a considerable drop in concordance, with 75-91 % for O-antigens and 62-90 % for H-antigens, and ECTyper and SerotypeFinder being the most concordant. This study highlights that in silico predictions show high concordance with phenotypic serotyping results, but there are notable differences in tool performance. ECTyper provides highly accurate and sensitive in silico serotype predictions, in addition to speciation, and is designed to be easily incorporated into bioinformatic workflows.

Distribution of heavy metal resistance elements in Canadian Salmonella 4,[5],12:i:- populations and association with the monophasic genotypes and phenotype.

Salmonella 4,[5],12:i:- are monophasic S. Typhimurium variants incapable of producing the second-phase flagellar antigen. They have emerged since the mid-1990s to become one of the most prevalent Salmonella serotypes causing human disease world-wide. Multiple genetic events associated with different genetic elements can result in the monophasic phenotype. Several jurisdictions have reported the emergence of a Salmonella 4,[5],12:i:- clone with SGI-4 and a genetic element (MREL) encoding a mercury resistance operon and antibiotic resistance loci that disrupts the second phase antigen region near the iroB locus in the Salmonella genome. We have sequenced 810 human and animal Canadian Salmonella 4,[5],12:i:- isolates and determined that isolates with SGI-4 and the mercury resistance element (MREL; also known as RR1&RR2) constitute several global clades containing various proportions of Canadian, US, and European isolates. Detailed analysis of the data provides a clearer picture of how these heavy metal elements interact with bacteria within the Salmonella population to produce the monophasic phenotype. Insertion of the MREL near iroB is associated with several deletions and rearrangements of the adjacent flaAB hin region, which may be useful for defining human case clusters that could represent outbreaks. Plasmids carrying genes encoding silver, copper, mercury, and antimicrobial resistance appear to be derived from IS26 mediated acquisition of these genes from genomes carrying SGI-4 and the MREL. Animal isolates with the mercury and As/Cu/Ag resistance elements are strongly associated with porcine sources in Canada as has been shown previously for other jurisdictions. The data acquired in these investigations, as well as from the extensive literature on the subject, may aid source attribution in outbreaks of the organism and interventions to decrease the prevalence of this clone and reduce its impact on human disease.

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.

"These Aren't the Strains You're Looking for": Recovery Bias of Common Campylobacter jejuni Subtypes in Mixed Cultures.

Microbiological surveillance of the food chain plays a critical role in improving our understanding of the distribution and circulation of food-borne pathogens along the farm to fork continuum toward the development of interventions to reduce the burden of illness. The application of molecular subtyping to bacterial isolates collected through surveillance has led to the identification of strains posing the greatest risk to public health. Past evidence suggests that enrichment methods for Campylobacter jejuni, a leading bacterial foodborne pathogen worldwide, may lead to the differential recovery of subtypes, obscuring our ability to infer the composition of a mixed-strain sample and potentially biasing prevalence estimates in surveillance data. To assess the extent of potential selection bias resulting from enrichment-based isolation methods, we compared enrichment and non-enrichment isolation of mixed subtype cultures of C. jejuni, followed by subtype-specific enumeration using both colony plate-counts and digital droplet PCR. Results differed from the null hypothesis that similar proportions of C. jejuni subtypes are recovered from both methods. Our results also indicated a significant effect of subtype prevalence on isolation frequency post-recovery, with the recovery of more common subtypes being consistently favored. This bias was exacerbated when an enrichment step was included in the isolation procedure. Taken together, our results emphasize the importance of selecting multiple colonies per sample, and where possible, the use of both enrichment and non-enrichment isolation procedures to maximize the likelihood of recovering multiple subtypes present in a sample. Moreover, the effects of subtype-specific recovery bias should be considered in the interpretation of strain prevalence data toward improved risk assessment from microbiological surveillance data.

Campylobacter jejuni Strain Dynamics in a Raccoon (Procyon lotor) Population in Southern Ontario, Canada: High Prevalence and Rapid Subtype Turnover.

Free-ranging wildlife are increasingly recognized as potential reservoirs of disease-causing Campylobacter species such as C. jejuni and C. coli. Raccoons (Procyon lotor), which live at the interface of rural, urban, and more natural environments, are ideal subjects for exploring the potential role that wildlife play in the epidemiology of campylobacteriosis. We studied the prevalence and genetic diversity of Campylobacter from live-captured raccoons on five swine farms and five conservation areas in southwest Ontario. From 2011 to 2013, we collected fecal swabs (n = 1,096) from raccoons, and (n = 50) manure pit samples from the swine farm environment. We subtyped the resulting Campylobacter isolates (n = 581) using Comparative Genomic Fingerprinting (CGF) and 114 distinct subtypes were observed, including 96 and 18 subtypes among raccoon and manure pit isolates, respectively. Campylobacter prevalence in raccoons was 46.3%, with 98.7% of isolates recovered identified as C. jejuni. Novel raccoon-specific CGF subtypes (n = 40/96) accounted for 24.6% (n = 143/581) of Campylobacter isolates collected in this study. Our results also show that C. jejuni is readily acquired and lost in this wild raccoon population and that a high Campylobacter prevalence is observed despite transient carriage typically lasting 30 days or fewer. Moreover, although raccoons appeared to be colonized by species-adapted subtypes, they also harbored agriculture-associated genotypes that accounted for the majority of isolates observed (66.4%) and that are strongly associated with human infections. This suggests that raccoons may act as vectors in the transmission of clinically-relevant C. jejuni subtypes at the interface of rural, urban, and more natural environments.

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.

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.

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.

A Genome-Wide Association Study to Identify Diagnostic Markers for Human Pathogenic Campylobacter jejuni Strains.

Campylobacter jejuni is a leading human enteric pathogen worldwide and despite an improved understanding of its biology, ecology, and epidemiology, limited tools exist for identifying strains that are likely to cause disease. In the current study, we used subtyping data in a database representing over 24,000 isolates collected through various surveillance projects in Canada to identify 166 representative genomes from prevalent C. jejuni subtypes for whole genome sequencing. The sequence data was used in a genome-wide association study (GWAS) aimed at identifying accessory gene markers associated with clinically related C. jejuni subtypes. Prospective markers (n = 28) were then validated against a large number (n = 3,902) of clinically associated and non-clinically associated genomes from a variety of sources. A total of 25 genes, including six sets of genetically linked genes, were identified as robust putative diagnostic markers for clinically related C. jejuni subtypes. Although some of the genes identified in this study have been previously shown to play a role in important processes such as iron acquisition and vitamin B5 biosynthesis, others have unknown function or are unique to the current study and warrant further investigation. As few as four of these markers could be used in combination to detect up to 90% of clinically associated isolates in the validation dataset, and such markers could form the basis for a screening assay to rapidly identify strains that pose an increased risk to public health. The results of the current study are consistent with the notion that specific groups of C. jejuni strains of interest are defined by the presence of specific accessory genes.

The EpiQuant Framework for Computing Epidemiological Concordance of Microbial Subtyping Data.

A fundamental assumption in the use and interpretation of microbial subtyping results for public health investigations is that isolates that appear to be related based on molecular subtyping data are expected to share commonalities with respect to their origin, history, and distribution. Critically, there is currently no approach for systematically assessing the underlying epidemiology of subtyping results. Our aim was to develop a method for directly quantifying the similarity between bacterial isolates using basic sampling metadata and to develop a framework for computing the epidemiological concordance of microbial typing results. We have developed an analytical model that summarizes the similarity of bacterial isolates using basic parameters typically provided in sampling records, using a novel framework (EpiQuant) developed in the R environment for statistical computing. We have applied the EpiQuant framework to a data set comprising 654 isolates of the enteric pathogen Campylobacter jejuni from Canadian surveillance data in order to examine the epidemiological concordance of clusters obtained by using two leading C. jejuni subtyping methods. The EpiQuant framework can be used to directly quantify the similarity of bacterial isolates based on basic sample metadata. These results can then be used to assess the concordance between microbial epidemiological and molecular data, facilitating the objective assessment of subtyping method performance and paving the way for the improved application of molecular subtyping data in investigations of infectious disease.

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.

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.

Quantitative multi-year elucidation of fecal sources of waterborne pathogen contamination in the South Nation River basin using bacteroidales microbial source tracking markers.

Over a seven-year period (2004-2010) 1095 water samples were obtained from the South Nation River basin at multiple watershed monitoring sites (Ontario, Canada). Real-time PCR using Bacteroidales specific markers was used to identify the origin (human (10% prevalence), ruminant (22%), pig (~2%), Canada goose (4%) and muskrat (7%)) of fecal pollution. In parallel, the distribution of fecal indicator bacteria and waterborne pathogens (Cryptosporidium oocysts, Giardia cysts, Escherichia coli O157:H7, Salmonella enterica and Campylobacter spp.) was evaluated. Associations between the detection of specific Bacteroidales markers and the presence of fecal indicator bacteria, pathogens, and distinct land use or environmental variables were evaluated. Linear correlations between Bacteroidales markers and fecal indicator bacteria were weak. However, mean marker densities, and the presence and absence of markers could be discriminated on the basis of threshold fecal indicator densities. The ruminant-specific Bacteroidales marker was the most frequently detected marker in water, consistent with the large number of dairy farms in the study area. Detection of the human or the ruminant markers were associated with a slightly higher risk of detecting S. enterica. Detection of the muskrat marker was related to more frequent Campylobacter spp. detections. Important positive associations between markers and pathogens were found among: i) total Bacteroidales and Cryptosporidium and Giardia, ii) ruminant marker and S. enterica, and iii) muskrat and Campylobacter spp.

Spatiotemporal analysis of Cryptosporidium species/genotypes and relationships with other zoonotic pathogens in surface water from mixed-use watersheds.

Nearly 690 raw surface water samples were collected during a 6-year period from multiple watersheds in the South Nation River basin, Ontario, Canada. Cryptosporidium oocysts in water samples were enumerated, sequenced, and genotyped by detailed phylogenetic analysis. The resulting species and genotypes were assigned to broad, known host and human infection risk classes. Wildlife/unknown, livestock, avian, and human host classes occurred in 21, 13, 3, and <1% of sampled surface waters, respectively. Cryptosporidium andersoni was the most commonly detected livestock species, while muskrat I and II genotypes were the most dominant wildlife genotypes. The presence of Giardia spp., Salmonella spp., Campylobacter spp., and Escherichia coli O157:H7 was evaluated in all water samples. The greatest significant odds ratios (odds of pathogen presence when host class is present/odds of pathogen presence when host class is absent) for Giardia spp., Campylobacter spp., and Salmonella spp. in water were associated, respectively, with livestock (odds ratio of 3.1), avian (4.3), and livestock (9.3) host classes. Classification and regression tree analyses (CART) were used to group generalized host and human infection risk classes on the basis of a broad range of environmental and land use variables while tracking cooccurrence of zoonotic pathogens in these groupings. The occurrence of livestock-associated Cryptosporidium was most strongly related to agricultural water pollution in the fall (conditions also associated with elevated odds ratios of other zoonotic pathogens occurring in water in relation to all sampling conditions), whereas wildlife/unknown sources of Cryptosporidium were geospatially associated with smaller watercourses where urban/rural development was relatively lower. Conditions that support wildlife may not necessarily increase overall human infection risks associated with Cryptosporidium since most Cryptosporidium genotypes classed as wildlife in this study (e.g., muskrat I and II genotype) do not pose significant infection risks to humans. Consequently, from a human health perspective, land use practices in agricultural watersheds that create opportunities for wildlife to flourish should not be rejected solely on the basis of their potential to increase relative proportions of wildlife fecal contamination in surface water. The present study suggests that mitigating livestock fecal pollution in surface water in this region would likely reduce human infection risks associated with Cryptosporidium and other zoonotic pathogens.