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.

Genomic Analysis of Shiga Toxin-Producing E. coli O157 Cattle and Clinical Isolates from Alberta, Canada.

Shiga toxin (stx) is the principal virulence factor of the foodborne pathogen, Shiga toxin-producing Escherichia coli (STEC) O157:H7 and is associated with various lambdoid bacterio (phages). A comparative genomic analysis was performed on STEC O157 isolates from cattle (n = 125) and clinical (n = 127) samples to characterize virulence genes, stx-phage insertion sites and antimicrobial resistance genes that may segregate strains circulating in the same geographic region. In silico analyses revealed that O157 isolates harboured the toxin subtypes stx1a and stx2a. Most cattle (76.0%) and clinical (76.4%) isolates carried the virulence gene combination of stx1, stx2, eae and hlyA. Characterization of stx1 and stx2-carrying phages in assembled contigs revealed that they were associated with mlrA and wrbA insertion sites, respectively. In cattle isolates, mlrA and wrbA insertion sites were occupied more often (77% and 79% isolates respectively) than in clinical isolates (38% and 1.6% isolates, respectively). Profiling of antimicrobial resistance genes (ARGs) in the assembled contigs revealed that 8.8% of cattle (11/125) and 8.7% of clinical (11/127) isolates harboured ARGs. Eight antimicrobial resistance genes cassettes (ARCs) were identified in 14 isolates (cattle, n = 8 and clinical, n = 6) with streptomycin (aadA1, aadA2, ant(3'')-Ia and aph(3'')-Ib) being the most prevalent gene in ARCs. The profound disparity between the cattle and clinical strains in occupancy of the wrbA locus suggests that this trait may serve to differentiate cattle from human clinical STEC O157:H7. These findings are important for stx screening and stx-phage insertion site genotyping as well as monitoring ARGs in isolates from cattle and clinical samples.

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.

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.

Antibiotic Resistance in Shiga Toxigenic Escherichia coli Isolates from Surface Waters and Sediments in a Mixed Use Urban Agricultural Landscape.

Antibiotic resistance (AR) phenotypes and acquired resistance determinants (ARDs) detected by in silico analysis of genome sequences were examined in 55 Shiga toxin-producing Escherichia coli (STEC) isolates representing diverse serotypes recovered from surfaces waters and sediments in a mixed use urban/agricultural landscape in British Columbia, Canada. The isolates displayed decreased susceptibility to florfenicol (65.5%), chloramphenicol (7.3%), tetracycline (52.7%), ampicillin (49.1%), streptomycin (34.5%), kanamycin (20.0%), gentamycin (10.9%), amikacin (1.8%), amoxicillin/clavulanic acid (21.8%), ceftiofur (18.2%), ceftriaxone (3.6%), trimethoprim-sulfamethoxazole (12.7%), and cefoxitin (3.6%). All surface water and sediment isolates were susceptible to ciprofloxacin, nalidixic acid, ertapenem, imipenem and meropenem. Eight isolates (14.6%) were multidrug resistant. ARDs conferring resistance to phenicols (floR), trimethoprim (dfrA), sulfonamides (sul1/2), tetracyclines (tetA/B), and aminoglycosides (aadA and aph) were detected. Additionally, narrow-spectrum ß-lactamase blaTEM-1b and extended-spectrum AmpC ß-lactamase (cephalosporinase) blaCMY-2 were detected in the genomes, as were replicons from plasmid incompatibility groups IncFII, IncB/O/K/Z, IncQ1, IncX1, IncY and Col156. A comparison with surveillance data revealed that AR phenotypes and ARDs were comparable to those reported in generic E. coli from food animals. Aquatic environments in the region are potential reservoirs for the maintenance and transmission of antibiotic resistant STEC, associated ARDs and their plasmids.

Decontamination of Bacillus anthracis Spores at Subzero Temperatures by Complete Submersion.

Introduction: Bacillus anthracis, the etiological agent of anthrax, produces long-lived spores, which are resistant to heat, cold, pH, desiccation, and chemical agents. The spores maintain their ability to produce viable bacteria even after decades, and when inhaled can cause fatal disease in over half of the clinical cases. Owing to these characteristics, anthrax has been repeatedly selected for both bioweapon and bioterrorism use. In the event of a bioterrorism attack, surfaces in the vicinity of the attack will be contaminated, and recovering from such an event requires rapid and effective decontamination. Previous decontamination method development has focused mainly on temperatures >0°C, and have shown poor efficacy at subzero temperatures. Methods: In this study, we demonstrate the use of calcium chloride (CaCl2) as a freezing point depression agent for pH-adjusted sodium hypochlorite (NaOCl) for the effective and rapid decontamination of B. anthracis Sterne strain spores at subzero temperatures. Results: We show the complete decontamination of 106 B. anthracis Sterne strain spores at temperatures as low as -20°C within 2.5 min by submersion in solution containing 25% (w/v) CaCl2, 0.50% NaOCl, and 0.40% (v/v) acetic acid. We also demonstrate significant reduction in number of spores at -28°C. Conclusions: The results show promise for rapidly decontaminating equipment and materials used in the response to bioterrorism events using readily available consumer chemicals. Future study should examine the efficacy of these results on complex surfaces.

Application of artificial intelligence to the in silico assessment of antimicrobial resistance and risks to human and animal health presented by priority enteric bacterial pathogens.

Each year, approximately one in eight Canadians are affected by foodborne illness, either through outbreaks or sporadic illness, with animals being the major reservoir for the pathogens. Whole genome sequence analyses are now routinely implemented by public and animal health laboratories to define epidemiological disease clusters and to identify potential sources of infection. Similarly, a number of bioinformatics tools can be used to identify virulence and antimicrobial resistance (AMR) determinants in the genomes of pathogenic strains. Many important clinical and phenotypic characteristics of these pathogens can now be predicted using machine learning algorithms applied to whole genome sequence data. In this overview, we compare the ability of support vector machines, gradient-boosted decision trees and artificial neural networks to predict the levels of AMR within Salmonella enterica and extended-spectrum ß-lactamase (ESBL) producing Escherichia coli. We show that minimum inhibitory concentrations (MIC) for each of 13 antimicrobials for S. enterica strains can be accurately determined, and that ESBL-producing E. coli strains can be accurately classified as susceptible, intermediate or resistant for each of seven antimicrobials. In addition to AMR and bacterial populations of greatest risk to human health, artificial intelligence algorithms hold promise as tools to predict other clinically and epidemiologically important phenotypes of enteric pathogens.

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.

Eleven High-Quality Reference Genome Sequences and 360 Draft Assemblies of Shiga Toxin-Producing Escherichia coli Isolates from Human, Food, Animal, and Environmental Sources in Canada.

We report high-quality closed reference genomes for 1 bovine strain and 10 human Shiga toxin (Stx)-producing Escherichia coli (STEC) strains from serogroups O26, O45, O91, O103, O104, O111, O113, O121, O145, and O157. We also report draft assemblies, with standardized metadata, for 360 STEC strains isolated from watersheds, animals, farms, food, and human infections.

Phylogeographic Analysis Reveals Multiple International transmission Events Have Driven the Global Emergence of Escherichia coli O157:H7.

BACKGROUND: Shiga toxin-producing Escherchia coli (STEC) O157:H7 is a zoonotic pathogen that causes numerous food and waterborne disease outbreaks. It is globally distributed, but its origin and the temporal sequence of its geographical spread are unknown. METHODS: We analyzed whole-genome sequencing data of 757 isolates from 4 continents, and performed a pan-genome analysis to identify the core genome and, from this, extracted single-nucleotide polymorphisms. A timed phylogeographic analysis was performed on a subset of the isolates to investigate its worldwide spread. RESULTS: The common ancestor of this set of isolates occurred around 1890 (1845-1925) and originated from the Netherlands. Phylogeographic analysis identified 34 major transmission events. The earliest were predominantly intercontinental, moving from Europe to Australia around 1937 (1909-1958), to the United States in 1941 (1921-1962), to Canada in 1960 (1943-1979), and from Australia to New Zealand in 1966 (1943-1982). This pre-dates the first reported human case of E. coli O157:H7, which was in 1975 from the United States. CONCLUSIONS: Inter- and intra-continental transmission events have resulted in the current international distribution of E. coli O157:H7, and it is likely that these events were facilitated by animal movements (eg, Holstein Friesian cattle). These findings will inform policy on action that is crucial to reduce the further spread of E. coli O157:H7 and other (emerging) STEC strains globally.

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.

Genomic Analysis of Third Generation Cephalosporin Resistant Escherichia coli from Dairy Cow Manure.

The production of extended-spectrum ß-lactamases (ESBLs) conferring resistance to new derivatives of ß-lactams is a major public health threat if present in pathogenic Gram-negative bacteria. The objective of this study was to characterize ceftiofur (TIO)- or cefotaxime (FOX)-resistant Escherichia coli isolated from dairy cow manure. Twenty-four manure samples were collected from four farms and incubated under anaerobic conditions for 20 weeks at 4 °C or at 25 °C. A total of 37 TIO- or FOX-resistant E. coli were isolated from two of the four farms to determine their susceptibility to 14 antibiotics. Among the 37 resistant E. coli, 10 different serotypes were identified, with O8:H1 being the predominant serotype (n = 17). Five isolates belonged to each of serotypes O9:NM and O153:H42, respectively. All 37 cephalosporin resistant isolates were multi-resistant with the most prevalent resistance spectrum being amoxicillin-clavulanic acid-ampicillin-cefoxitin-ceftiofur-ceftriaxone-chloramphenicol-streptomycin-sulfisoxazole-tetracycline-trimethoprim-sulfamethoxazole. The genomes of 18 selected isolates were then sequenced and compared to 14 selected human pathogenic E. coli reference genomes obtained from public repositories using different bioinformatics approaches. As expected, all 18 sequenced isolates carried at least one ß-lactamase bla gene: TEM-1, TEM-81, CTX-M115, CTX-M15, OXA-1, or CMY-2. Several other antibiotic resistance genes (ARGs) and virulence determinants were detected in the sequenced isolates and all of them harbored antimicrobial resistance plasmids belonging to classic Inc groups. Our results confirm the presence of diverse ESBL producing E. coli isolates in dairy cow manure stored for a short period of time. Such manure might constitute a reservoir of resistance and virulence genes for other bacteria that share the same environment.

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.

Genotypes Associated with Listeria monocytogenes Isolates Displaying Impaired or Enhanced Tolerances to Cold, Salt, Acid, or Desiccation Stress.

The human pathogen Listeria monocytogenes is a large concern in the food industry where its continuous detection in food products has caused a string of recalls in North America and Europe. Most recognized for its ability to grow in foods during refrigerated storage, L. monocytogenes can also tolerate several other food-related stresses with some strains possessing higher levels of tolerances than others. The objective of this study was to use a combination of phenotypic analyses and whole genome sequencing to elucidate potential relationships between L. monocytogenes genotypes and food-related stress tolerance phenotypes. To accomplish this, 166 L. monocytogenes isolates were sequenced and evaluated for their ability to grow in cold (4°C), salt (6% NaCl, 25°C), and acid (pH 5, 25°C) stress conditions as well as survive desiccation (33% RH, 20°C). The results revealed that the stress tolerance of L. monocytogenes is associated with serotype, clonal complex (CC), full length inlA profiles, and the presence of a plasmid which was identified in 55% of isolates. Isolates with full length inlA exhibited significantly (p < 0.001) enhanced cold tolerance relative to those harboring a premature stop codon (PMSC) in this gene. Similarly, isolates possessing a plasmid demonstrated significantly (p = 0.013) enhanced acid tolerance. We also identified nine new L. monocytogenes sequence types, a new inlA PMSC, and several connections between CCs and the presence/absence or variations of specific genetic elements. A whole genome single-nucleotide-variants phylogeny revealed sporadic distribution of tolerant isolates and closely related sensitive and tolerant isolates, highlighting that minor genetic differences can influence the stress tolerance of L. monocytogenes. Specifically, a number of cold and desiccation sensitive isolates contained PMSCs in σB regulator genes (rsbS, rsbU, rsbV). Collectively, the results suggest that knowing the sequence type of an isolate in addition to screening for the presence of full-length inlA and a plasmid, could help food processors and food agency investigators determine why certain isolates might be persisting in a food processing environment. Additionally, increased sequencing of L. monocytogenes isolates in combination with stress tolerance profiling, will enhance the ability to identify genetic elements associated with higher risk strains.

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.

Phenotypic and Genotypic Characteristics of Shiga Toxin-Producing Escherichia coli Isolated from Surface Waters and Sediments in a Canadian Urban-Agricultural Landscape.

A hydrophobic grid membrane filtration-Shiga toxin immunoblot method was used to examine the prevalence of Shiga toxin-producing Escherichia coli (STEC) in four watersheds located in the Lower Mainland of British Columbia, Canada, a region characterized by rapid urbanization and intensive agricultural activity. STEC were recovered from 21.6, 23.2, 19.5, and 9.2% of surface water samples collected monthly from five sites in each watershed over a period of 1 year. Overall prevalence was subject to seasonal variation however, ranging between 13.3% during fall months and 34.3% during winter months. STEC were also recovered from 23.8% of sediment samples collected in one randomly selected site. One hundred distinct STEC isolates distributed among 29 definitive and 4 ambiguous or indeterminate serotypes were recovered from water and sediments, including isolates from Canadian "priority" serogroups O157 (3), O26 (4), O103 (5), and O111 (7). Forty seven isolates were further characterized by analysis of whole genome sequences to detect Shiga toxin gene (stx 1 and stx 2), intimin gene (eaeA) allelic variants and acquired virulence factors. These analyses collectively showed that surface waters from the region support highly diverse STEC populations that include strains with virulence factors commonly associated with human pathotypes. The present work served to characterize the microbiological hazard implied by STEC to support future assessments of risks to public health arising from non-agricultural and agricultural uses of surface water resources in the region.