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.

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.

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.

Long-term monitoring of waterborne pathogens and microbial source tracking markers in paired agricultural watersheds under controlled and conventional tile drainage management.

Surface waters from paired agricultural watersheds under controlled tile drainage (CTD) and uncontrolled tile drainage (UCTD) were monitored over 7 years in order to determine if there was an effect of CTD (imposed during the growing season) on occurrences and loadings of bacterial and viral pathogens, coliphages, and microbial source tracking markers. There were significantly lower occurrences of human, ruminant, and livestock (ruminant plus pig) Bacteroidales markers in the CTD watershed in relation to the UCTD watershed. As for pathogens, there were significantly lower occurrences of Salmonella spp. and Arcobacter spp. in the CTD watershed. There were no instances where there were significantly higher quantitative loadings of any microbial target in the CTD watershed, except for F-specific DNA (F-DNA) and F-RNA coliphages, perhaps as a result of fecal inputs from a hobby farm independent of the drainage practice treatments. There was lower loading of the ruminant marker in the CTD watershed in relation to the UCTD system, and results were significant at the level P = 0.06. The odds of Salmonella spp. occurring increased when a ruminant marker was present relative to when the ruminant marker was absent, yet for Arcobacter spp., the odds of this pathogen occurring significantly decreased when a ruminant marker was present relative to when the ruminant marker was absent (but increased when a wildlife marker was present relative to when the wildlife marker was absent). Interestingly, the odds of norovirus GII (associated with human and swine) occurring in water increased significantly when a ruminant marker was present relative to when a ruminant marker was absent. Overall, this study suggests that fecal pollution from tile-drained fields to stream could be reduced by CTD utilization.

Identification of a novel prophage regulator in Escherichia coli controlling the expression of type III secretion.

This study has identified horizontally acquired genomic regions of enterohaemorrhagic Escherichia coli O157:H7 that regulate expression of the type III secretion (T3S) system encoded by the locus of enterocyte effacement (LEE). Deletion of O-island 51, a 14.93 kb cryptic prophage (CP-933C), resulted in a reduction in LEE expression and T3S. The deletion also had a reduced capacity to attach to epithelial cells and significantly reduced E. coli O157 excretion levels from sheep. Further characterization of O-island 51 identified a novel positive regulator of the LEE, encoded by ecs1581 in the E. coli O157:H7 strain Sakai genome and present but not annotated in the E. coli strain EDL933 sequence. Functionally important residues of ECs1581 were identified based on phenotypic variants present in sequenced E. coli strains and the regulator was termed RgdR based on a motif demonstrated to be important for stimulation of gene expression. While RgdR activated expression from the LEE1 promoter in the presence or absence of the LEE-encoded regulator (Ler), RgdR stimulation of T3S required ler and Ler autoregulation. RgdR also controlled the expression of other phenotypes, including motility, indicating that this new family of regulators may have a more global role in E. coli gene expression.

Coherence among different microbial source tracking markers in a small agricultural stream with or without livestock exclusion practices.

Over 1,400 water samples were collected biweekly over 6 years from an intermittent stream protected and unprotected from pasturing cattle. The samples were monitored for host-specific Bacteroidales markers, Cryptosporidium species/genotypes, viruses and coliphages associated with humans or animals, and bacterial zoonotic pathogens. Ruminant Bacteroidales markers did not increase within the restricted cattle access reach of the stream, whereas the ruminant Bacteroidales marker increased significantly in the unrestricted cattle access reach. Human Bacteroidales markers significantly increased downstream of homes where septic issues were documented. Wildlife Bacteroidales markers were detected downstream of the cattle exclusion practice where stream and riparian habitat was protected, but detections decreased after the unrestricted pasture, where the stream and riparian zone was unprotected from livestock. Detection of a large number of human viruses was shown to increase downstream of homes, and similar trends were observed for the human Bacteroidales marker. There was considerable interplay among biomarkers with stream flow, season, and the cattle exclusion practices. There were no to very weak associations with Bacteroidales markers and bacterial, viral, and parasitic pathogens. Overall, discrete sample-by-sample coherence among the different microbial source tracking markers that expressed a similar microbial source was minimal, but spatial trends were physically meaningful in terms of land use (e.g., beneficial management practice) effects on sources of fecal pollution.

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.

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.

Development and validation of a comparative genomic fingerprinting method for high-resolution genotyping of Campylobacter jejuni.

Campylobacter spp. are a leading cause of bacterial gastroenteritis worldwide. The need for molecular subtyping methods with enhanced discrimination in the context of surveillance- and outbreak-based epidemiologic investigations of Campylobacter spp. is critical to our understanding of sources and routes of transmission and the development of mitigation strategies to reduce the incidence of campylobacteriosis. We describe the development and validation of a rapid and high-resolution comparative genomic fingerprinting (CGF) method for C. jejuni. A total of 412 isolates from agricultural, environmental, retail, and human clinical sources obtained from the Canadian national integrated enteric pathogen surveillance program (C-EnterNet) were analyzed using a 40-gene assay (CGF40) and multilocus sequence typing (MLST). The significantly higher Simpson's index of diversity (ID) obtained with CGF40 (ID = 0.994) suggests that it has a higher discriminatory power than MLST at both the level of clonal complex (ID = 0.873) and sequence type (ID = 0.935). High Wallace coefficients obtained when CGF40 was used as the primary typing method suggest that CGF and MLST are highly concordant, and we show that isolates with identical MLST profiles are comprised of isolates with distinct but highly similar CGF profiles. The high concordance with MLST coupled with the ability to discriminate between closely related isolates suggests that CFG40 is useful in differentiating highly prevalent sequence types, such as ST21 and ST45. CGF40 is a high-resolution comparative genomics-based method for C. jejuni subtyping with high discriminatory power that is also rapid, low cost, and easily deployable for routine epidemiologic surveillance and outbreak investigations.

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.

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.

Pan-genome sequence analysis using Panseq: an online tool for the rapid analysis of core and accessory genomic regions.

BACKGROUND: The pan-genome of a bacterial species consists of a core and an accessory gene pool. The accessory genome is thought to be an important source of genetic variability in bacterial populations and is gained through lateral gene transfer, allowing subpopulations of bacteria to better adapt to specific niches. Low-cost and high-throughput sequencing platforms have created an exponential increase in genome sequence data and an opportunity to study the pan-genomes of many bacterial species. In this study, we describe a new online pan-genome sequence analysis program, Panseq. RESULTS: Panseq was used to identify Escherichia coli O157:H7 and E. coli K-12 genomic islands. Within a population of 60 E. coli O157:H7 strains, the existence of 65 accessory genomic regions identified by Panseq analysis was confirmed by PCR. The accessory genome and binary presence/absence data, and core genome and single nucleotide polymorphisms (SNPs) of six L. monocytogenes strains were extracted with Panseq and hierarchically clustered and visualized. The nucleotide core and binary accessory data were also used to construct maximum parsimony (MP) trees, which were compared to the MP tree generated by multi-locus sequence typing (MLST). The topology of the accessory and core trees was identical but differed from the tree produced using seven MLST loci. The Loci Selector module found the most variable and discriminatory combinations of four loci within a 100 loci set among 10 strains in 1 s, compared to the 449 s required to exhaustively search for all possible combinations; it also found the most discriminatory 20 loci from a 96 loci E. coli O157:H7 SNP dataset. CONCLUSION: Panseq determines the core and accessory regions among a collection of genomic sequences based on user-defined parameters. It readily extracts regions unique to a genome or group of genomes, identifies SNPs within shared core genomic regions, constructs files for use in phylogeny programs based on both the presence/absence of accessory regions and SNPs within core regions and produces a graphical overview of the output. Panseq also includes a loci selector that calculates the most variable and discriminatory loci among sets of accessory loci or core gene SNPs. AVAILABILITY: Panseq is freely available online at http://76.70.11.198/panseq. Panseq is written in Perl.

Lineage and host source are both correlated with levels of Shiga toxin 2 production by Escherichia coli O157:H7 strains.

Escherichia coli O157:H7 strains fall into three major genetic lineages that differ in their distribution among humans and cattle. Several recent studies have reported differences in the expression of virulence factors between E. coli O157:H7 strains from these two host species. In this study, we wished to determine if important virulence-associated "mobile genetic elements" such as Shiga toxin 2 (Stx2)-encoding prophage are lineage restricted or are host source related and acquired independently of the pathogen genotype. DNA sequencing of the stx(2) flanking region from a lineage II (LII) strain, EC970520, revealed that the transcriptional activator gene Q in LI strain EDL933 (upstream of stx(2)) is replaced by a pphA (serine/threonine phosphatase) homologue and an altered Q gene in this and all other LII strains tested. In addition, nearly all LI strains carried stx(2), whereas all LII strains carried variant stx(2c) and 4 of 14 LI/II strains had copies of both stx(2) and variant stx(2c). Real-time PCR (RT-PCR) and enzyme-linked immunosorbent assay (ELISA) demonstrated that LI and LI/II strains produce significantly more stx(2) mRNA and Stx2 than LII strains. However, among LI strains significantly more Stx2 is also produced by strains from humans than from cattle. Therefore, lineage-associated differences among E. coli O157:H7 strains such as prophage content, toxin type, and toxin expression may contribute to host isolation bias. However, the level of Stx2 production alone may also play an important role in the within-lineage association of E. coli O157:H7 strains with human clinical disease.

The occurrence and sources of Campylobacter spp., Salmonella enterica and Escherichia coli O157:H7 in the Salmon River, British Columbia, Canada.

In this study, we wished to assess the prevalence and determine the sources of three zoonotic bacterial pathogens (Salmonella, Campylobacter, and Escherichia coli O157:H7) in the Salmon River watershed in southwestern British Columbia. Surface water, sewage, and animal faecal samples were collected from the watershed. Selective bacterial culture and PCR techniques were used to isolate these three pathogens and indicator bacteria from these samples and characterize them. Campylobacter was the most prevalent pathogen in all samples, followed by Salmonella, and E. coli O157:H7. E. coli O157:H7 and Salmonella isolation rates from water, as well as faecal coliform densities correlated positively with precipitation, while Campylobacter isolation rates correlated negatively with precipitation. Analysis of DNA extracted from water samples for the presence of Bacteroides host-species markers, and comparisons of C. jejuni flaA-RFLP types and Salmonella serovars from faecal and water samples provided evidence that human sewage and specific domestic and wild animal species were sources of these pathogens; however, in most cases the source could not be determined or more than one source was possible. The frequent isolation of these zoonotic pathogens in the Salmon River highlights the risks to human health associated with intentional and unintentional consumption of untreated surface waters.

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.

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.

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.