Physician perspectives of Helicobacter pylori diagnostic and treatment practices in Canada: results of a Canadian survey.

BACKGROUND: Helicobacter pylori infection is prevalent worldwide and can lead to peptic ulcer disease (PUD) and gastric cancer. Effective diagnosis and treatment of H. pylori infection by gastroenterologists and family physicians is crucial. However, there are differing views on optimal diagnosis and treatment. The objective of this study is to understand the impressions of Canadian physicians regarding H. pylori diagnosis and treatment and whether impressions differ between gastroenterologists and family physicians. A second objective is to understand physician perspectives on rising antibiotic resistance and how that guides empiric management. METHODS: A survey facilitated via REDCap was administered to Canadian gastroenterologists and family physicians. A total of 105 participants completed the survey, including 43 gastroenterologists and 62 family physicians. Gastroenterologists were recruited from across the country and family physicians were recruited from Manitoba. RESULTS: For diagnosis of H. pylori, 67% of gastroenterologists reported endoscopic biopsies for histology assessment as most common and 73% of family physicians reported serology as their main diagnostic test. While nearly all gastroenterologists believed antibiotic resistance to be a problem, nearly one quarter of family physicians did not believe it was a problem. CONCLUSIONS: There is variability in practices among both gastroenterologists and family physicians regarding diagnosis of H. pylori infection. There was consensus that local antibiotic resistance patterns should guide management. If known, the degree and patterns of antibiotic resistance could bring a more uniform consensus to H. pylori management. Greater education of physicians, especially family physicians regarding management of H pylori is needed.

Use of a taxon-specific reference database for accurate metagenomics-based pathogen detection of Listeria monocytogenes in turkey deli meat and spinach.

BACKGROUND: The reliability of culture-independent pathogen detection in foods using metagenomics is contingent on the quality and composition of the reference database. The inclusion of microbial sequences from a diverse representation of taxonomies in universal reference databases is recommended to maximize classification precision for pathogen detection. However, these sizable databases have high memory requirements that may be out of reach for some users. In this study, we aimed to assess the performance of a foodborne pathogen (FBP)-specific reference database (taxon-specific) relative to a universal reference database (taxon-agnostic). We tested our FBP-specific reference database's performance for detecting Listeria monocytogenes in two complex food matrices-ready-to-eat (RTE) turkey deli meat and prepackaged spinach-using three popular read-based DNA-to-DNA metagenomic classifiers: Centrifuge, Kraken 2 and KrakenUniq. RESULTS: In silico host sequence removal led to substantially fewer false positive (FP) classifications and higher classification precision in RTE turkey deli meat datasets using the FBP-specific reference database. No considerable improvement in classification precision was observed following host filtering for prepackaged spinach datasets and was likely a consequence of a higher microbe-to-host sequence ratio. All datasets classified with Centrifuge using the FBP-specific reference database had the lowest classification precision compared to Kraken 2 or KrakenUniq. When a confidence-scoring threshold was applied, a nearly equivalent precision to the universal reference database was achieved for Kraken 2 and KrakenUniq. Recall was high for both reference databases across all datasets and classifiers. Substantially fewer computational resources were required for metagenomics-based detection of L. monocytogenes using the FBP-specific reference database, especially when combined with Kraken 2. CONCLUSIONS: A universal (taxon-agnostic) reference database is not essential for accurate and reliable metagenomics-based pathogen detection of L. monocytogenes in complex food matrices. Equivalent classification performance can be achieved using a taxon-specific reference database when the appropriate quality control measures, classification software, and analysis parameters are applied. This approach is less computationally demanding and more attainable for the broader scientific and food safety communities.

Clinical Metagenomics Is Increasingly Accurate and Affordable to Detect Enteric Bacterial Pathogens in Stool.

Stool culture is the gold standard method to diagnose enteric bacterial infections; however, many clinical laboratories are transitioning to syndromic multiplex PCR panels. PCR is rapid, accurate, and affordable, yet does not yield subtyping information critical for foodborne disease surveillance. A metagenomics-based stool testing approach could simultaneously provide diagnostic and public health information. Here, we evaluated shotgun metagenomics to assess the detection of common enteric bacterial pathogens in stool. We sequenced 304 stool specimens from 285 patients alongside routine diagnostic testing for Salmonella spp., Campylobacter spp., Shigella spp., and shiga-toxin producing Escherichia coli. Five analytical approaches were assessed for pathogen detection: microbiome profiling, Kraken2, MetaPhlAn, SRST2, and KAT-SECT. Among analysis tools and databases compared, KAT-SECT analysis provided the best sensitivity and specificity for all pathogens tested compared to culture (91.2% and 96.2%, respectively). Where metagenomics detected a pathogen in culture-negative specimens, standard PCR was positive 85% of the time. The cost of metagenomics is approaching the current combined cost of PCR, reflex culture, and whole genome sequencing for pathogen detection and subtyping. As cost, speed, and analytics for single-approach metagenomics improve, it may be more routinely applied in clinical and public health laboratories.

Economic evaluation of whole genome sequencing for pathogen identification and surveillance - results of case studies in Europe and the Americas 2016 to 2019.

BackgroundWhole genome sequencing (WGS) is increasingly used for pathogen identification and surveillance.AimWe evaluated costs and benefits of routine WGS through case studies at eight reference laboratories in Europe and the Americas which conduct pathogen surveillance for avian influenza (two laboratories), human influenza (one laboratory) and food-borne pathogens (five laboratories).MethodsThe evaluation focused on the institutional perspective, i.e. the 'investment case' for implementing WGS compared with conventional methods, based on costs and benefits during a defined reference period, mostly covering at least part of 2017. A break-even analysis estimated the number of cases of illness (for the example of Salmonella surveillance) that would need to be avoided through WGS in order to 'break even' on costs.ResultsOn a per-sample basis, WGS was between 1.2 and 4.3 times more expensive than routine conventional methods. However, WGS brought major benefits for pathogen identification and surveillance, substantially changing laboratory workflows, analytical processes and outbreaks detection and control. Between 0.2% and 1.1% (on average 0.7%) of reported salmonellosis cases would need to be prevented to break even with respect to the additional costs of WGS.ConclusionsEven at cost levels documented here, WGS provides a level of additional information that more than balances the additional costs if used effectively. The substantial cost differences for WGS between reference laboratories were due to economies of scale, degree of automation, sequencing technology used and institutional discounts for equipment and consumables, as well as the extent to which sequencers are used at full capacity.

Shared genome analyses of notable listeriosis outbreaks, highlighting the critical importance of epidemiological evidence, input datasets and interpretation criteria.

The persuasiveness of genomic evidence has pressured scientific agencies to supplement or replace well-established methodologies to inform public health and food safety decision-making. This study of 52 epidemiologically defined Listeria monocytogenes isolates, collected between 1981 and 2011, including nine outbreaks, was undertaken (1) to characterize their phylogenetic relationship at finished genome-level resolution, (2) to elucidate the underlying genetic diversity within an endemic subtype, CC8, and (3) to re-evaluate the genetic relationship and epidemiology of a CC8-delimited outbreak in Canada in 2008. Genomes representing Canadian Listeria outbreaks between 1981 and 2010 were closed and manually annotated. Single nucleotide variants (SNVs) and horizontally acquired traits were used to generate phylogenomic models. Phylogenomic relationships were congruent with classical subtyping and epidemiology, except for CC8 outbreaks, wherein the distribution of SNV and prophages revealed multiple co-evolving lineages. Chronophyletic reconstruction of CC8 evolution indicates that prophage-related genetic changes among CC8 strains manifest as PFGE subtype reversions, obscuring the relationship between CC8 isolates, and complicating the public health interpretation of subtyping data, even at maximum genome resolution. The size of the shared genome interrogated did not change the genetic relationship measured between highly related isolates near the tips of the phylogenetic tree, illustrating the robustness of these approaches for routine public health applications where the focus is recent ancestry. The possibility exists for temporally and epidemiologically distinct events to appear related even at maximum genome resolution, highlighting the continued importance of epidemiological evidence.

Evaluation of whole-genome sequencing for outbreak detection of Verotoxigenic Escherichia coli O157:H7 from the Canadian perspective.

BACKGROUND: Rapid and accurate identification of Verotoxigenic Escherichia coli (VTEC) O157:H7 is dependent on well-established, standardized and highly discriminatory typing methods. Currently, conventional subtyping tests for foodborne bacterial pathogen surveillance are rapidly being replaced with whole-genome sequencing (WGS) in public health laboratories. The capacity of WGS to revolutionize global foodborne disease surveillance has positioned this tool to become the new gold standard; however, to ensure evidence standards for public health decision making can still be achieved, the performance of WGS must be thoroughly validated against current gold standard methods prior to implementation. Here we aim to verify the performance of WGS in comparison to pulsed-field gel electrophoresis (PFGE) and multiple-locus variable-number tandem repeat analysis (MLVA) for eight retrospective outbreaks of VTEC O157:H7 from the Canadian perspective. Since real-time implementation and routine use of WGS in public health laboratories is highly reliant on standardized data analysis tools, we also provide a comparative analysis of two popular methodologies for WGS analyses; an in-house developed single nucleotide variant phylogenomics (SNVPhyl) pipeline and the BioNumerics whole genome multilocus sequence typing (wgMLST) tool. To provide a useful and consistent starting point for examining laboratory-based surveillance data for VTEC O157:H7 in Canada, we also aim to describe the number of genetic differences observed among outbreak-associated isolates. RESULTS: WGS provided enhanced resolution over traditional subtyping methods, and accurately distinguished outbreak-related isolates from non-outbreak related isolates with high epidemiological concordance. WGS also illuminated potential linkages between sporadic cases of illness and contaminated food, and isolates spanning multiple years. The topologies generated by SNVPhyl and wgMLST were highly congruent with strong statistical support. Few genetic differences were observed among outbreak-related isolates (≤5 SNVs/ < 10 wgMLST alleles) unless the outbreak was suspected to be multi-strain. CONCLUSIONS: This study validates the superiority of WGS and indicates the BioNumerics wgMLST schema is suitable for surveillance and cluster detection of VTEC O157:H7. These findings will provide a useful and consistent starting point for examining WGS data for prospective laboratory-based surveillance of VTEC O157:H7, but however, the data will continue to be interpreted according to context and in combination with epidemiological and food safety evidence to inform public-health decision making in Canada.

Highlighting Clinical Metagenomics for Enhanced Diagnostic Decision-making: A Step Towards Wider Implementation.

Clinical metagenomics (CMg) is the discipline that refers to the sequencing of all nucleic acid material present within a clinical specimen with the intent to recover clinically relevant microbial information. From a diagnostic perspective, next-generation sequencing (NGS) offers the ability to rapidly identify putative pathogens and predict their antimicrobial resistance profiles to optimize targeted treatment regimens. Since the introduction of metagenomics nearly a decade ago, numerous reports have described successful applications in an increasing variety of biological specimens, such as respiratory secretions, cerebrospinal fluid, stool, blood and tissue. Considerable advancements in sequencing and computational technologies in recent years have made CMg a promising tool in clinical microbiology laboratories. Moreover, costs per sample and turnaround time from specimen receipt to clinical management continue to decrease, making the prospect of CMg more feasible. Many difficulties, however, are associated with CMg and warrant further improvements such as the informatics infrastructure and analytical pipelines. Thus, the current review focuses on comprehensively assessing applications of CMg for diagnostic and subtyping purposes.

Neptune: a bioinformatics tool for rapid discovery of genomic variation in bacterial populations.

The ready availability of vast amounts of genomic sequence data has created the need to rethink comparative genomics algorithms using 'big data' approaches. Neptune is an efficient system for rapidly locating differentially abundant genomic content in bacterial populations using an exact k-mer matching strategy, while accommodating k-mer mismatches. Neptune's loci discovery process identifies sequences that are sufficiently common to a group of target sequences and sufficiently absent from non-targets using probabilistic models. Neptune uses parallel computing to efficiently identify and extract these loci from draft genome assemblies without requiring multiple sequence alignments or other computationally expensive comparative sequence analyses. Tests on simulated and real datasets showed that Neptune rapidly identifies regions that are both sensitive and specific. We demonstrate that this system can identify trait-specific loci from different bacterial lineages. Neptune is broadly applicable for comparative bacterial analyses, yet will particularly benefit pathogenomic applications, owing to efficient and sensitive discovery of differentially abundant genomic loci. The software is available for download at: http://github.com/phac-nml/neptune.

SNVPhyl: a single nucleotide variant phylogenomics pipeline for microbial genomic epidemiology.

The recent widespread application of whole-genome sequencing (WGS) for microbial disease investigations has spurred the development of new bioinformatics tools, including a notable proliferation of phylogenomics pipelines designed for infectious disease surveillance and outbreak investigation. Transitioning the use of WGS data out of the research laboratory and into the front lines of surveillance and outbreak response requires user-friendly, reproducible and scalable pipelines that have been well validated. Single Nucleotide Variant Phylogenomics (SNVPhyl) is a bioinformatics pipeline for identifying high-quality single-nucleotide variants (SNVs) and constructing a whole-genome phylogeny from a collection of WGS reads and a reference genome. Individual pipeline components are integrated into the Galaxy bioinformatics framework, enabling data analysis in a user-friendly, reproducible and scalable environment. We show that SNVPhyl can detect SNVs with high sensitivity and specificity, and identify and remove regions of high SNV density (indicative of recombination). SNVPhyl is able to correctly distinguish outbreak from non-outbreak isolates across a range of variant-calling settings, sequencing-coverage thresholds or in the presence of contamination. SNVPhyl is available as a Galaxy workflow, Docker and virtual machine images, and a Unix-based command-line application. SNVPhyl is released under the Apache 2.0 license and available at http://snvphyl.readthedocs.io/ or at https://github.com/phac-nml/snvphyl-galaxy.

Multi-provincial Salmonellosis Outbreak Related to Newly Hatched Chicks and Poults: A Genomics Perspective.

BACKGROUND: A multi-provincial outbreak of Salmonella enterica serovar Enteritidis was linked to newly hatched chicks and poults from a single hatchery during the spring of 2015. In total, there were 61 human cases that were epidemiologically confirmed to be linked to the chicks and poults and the outbreak was deemed to have ended in the summer of 2015. METHODS: PulseNet Canada, in coordination with the affected provinces, used genome sequencing of human and agricultural Salmonella Enteritidis isolates to aid in the epidemiological investigation, while also using traditional typing methods such as phagetyping and pulsed-field gel electrophoresis (PFGE). RESULTS: All human outbreak cases, except one, were Phage Type (PT) 13a. Single nucleotide variant analysis (SNV) was able to provide a level of resolution commensurate with the results of the epidemiological investigation. SNV analysis was also able to separate PT13a outbreak-related isolates from isolates not linked to chicks or poults, while clustering some non-PT13a agricultural strains with the outbreak cluster. CONCLUSIONS: Based on conventional typing methods (phagetyping or PFGE), clinical and agricultural PT13a SE isolates would have been considered as part of a related cluster. In contrast, phagetyping would have led to the exclusion of several non- PT13a strains that clustered with the outbreak isolates using the genome sequence data. This study demonstrates the improved resolution of genome sequence analysis for coordinated surveillance and source attribution of both human and agricultural SE isolates.

Metagenomics: The Next Culture-Independent Game Changer.

A trend towards the abandonment of obtaining pure culture isolates in frontline laboratories is at a crossroads with the ability of public health agencies to perform their basic mandate of foodborne disease surveillance and response. The implementation of culture-independent diagnostic tests (CIDTs) including nucleic acid and antigen-based assays for acute gastroenteritis is leaving public health agencies without laboratory evidence to link clinical cases to each other and to food or environmental substances. This limits the efficacy of public health epidemiology and surveillance as well as outbreak detection and investigation. Foodborne outbreaks have the potential to remain undetected or have insufficient evidence to support source attribution and may inadvertently increase the incidence of foodborne diseases. Next-generation sequencing of pure culture isolates in clinical microbiology laboratories has the potential to revolutionize the fields of food safety and public health. Metagenomics and other 'omics' disciplines could provide the solution to a cultureless future in clinical microbiology, food safety and public health. Data mining of information obtained from metagenomics assays can be particularly useful for the identification of clinical causative agents or foodborne contamination, detection of AMR and/or virulence factors, in addition to providing high-resolution subtyping data. Thus, metagenomics assays may provide a universal test for clinical diagnostics, foodborne pathogen detection, subtyping and investigation. This information has the potential to reform the field of enteric disease diagnostics and surveillance and also infectious diseases as a whole. The aim of this review will be to present the current state of CIDTs in diagnostic and public health laboratories as they relate to foodborne illness and food safety. Moreover, we will also discuss the diagnostic and subtyping utility and concomitant bias limitations of metagenomics and comparable detection techniques in clinical microbiology, food and public health laboratories. Early advances in the discipline of metagenomics, however, have indicated noteworthy challenges. Through forthcoming improvements in sequencing technology and analytical pipelines among others, we anticipate that within the next decade, detection and characterization of pathogens via metagenomics-based workflows will be implemented in routine usage in diagnostic and public health laboratories.

The Validation and Implications of Using Whole Genome Sequencing as a Replacement for Traditional Serotyping for a National Salmonella Reference Laboratory.

Salmonella serotyping remains the gold-standard tool for the classification of Salmonella isolates and forms the basis of Canada's national surveillance program for this priority foodborne pathogen. Public health officials have been increasingly looking toward whole genome sequencing (WGS) to provide a large set of data from which all the relevant information about an isolate can be mined. However, rigorous validation and careful consideration of potential implications in the replacement of traditional surveillance methodologies with WGS data analysis tools is needed. Two in silico tools for Salmonella serotyping have been developed, the Salmonella in silico Typing Resource (SISTR) and SeqSero, while seven gene MLST for serovar prediction can be adapted for in silico analysis. All three analysis methods were assessed and compared to traditional serotyping techniques using a set of 813 verified clinical and laboratory isolates, including 492 Canadian clinical isolates and 321 isolates of human and non-human sources. Successful results were obtained for 94.8, 88.2, and 88.3% of the isolates tested using SISTR, SeqSero, and MLST, respectively, indicating all would be suitable for maintaining historical records, surveillance systems, and communication structures currently in place and the choice of the platform used will ultimately depend on the users need. Results also pointed to the need to reframe serotyping in the genomic era as a test to understand the genes that are carried by an isolate, one which is not necessarily congruent with what is antigenically expressed. The adoption of WGS for serotyping will provide the simultaneous collection of information that can be used by multiple programs within the current surveillance paradigm; however, this does not negate the importance of the various programs or the role of serotyping going forward.

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

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

Genomic insights from whole genome sequencing of four clonal outbreak Campylobacter jejuni assessed within the global C. jejuni population.

BACKGROUND: Whole genome sequencing (WGS) is useful for determining clusters of human cases, investigating outbreaks, and defining the population genetics of bacteria. It also provides information about other aspects of bacterial biology, including classical typing results, virulence, and adaptive strategies of the organism. Cell culture invasion and protein expression patterns of four related multilocus sequence type 21 (ST21) C. jejuni isolates from a significant Canadian water-borne outbreak were previously associated with the presence of a CJIE1 prophage. Whole genome sequencing was used to examine the genetic diversity among these isolates and confirm that previous observations could be attributed to differential prophage carriage. Moreover, we sought to determine the presence of genome sequences that could be used as surrogate markers to delineate outbreak-associated isolates. RESULTS: Differential carriage of the CJIE1 prophage was identified as the major genetic difference among the four outbreak isolates. High quality single-nucleotide variant (hqSNV) and core genome multilocus sequence typing (cgMLST) clustered these isolates within expanded datasets consisting of additional C. jejuni strains. The number and location of homopolymeric tract regions was identical in all four outbreak isolates but differed from all other C. jejuni examined. Comparative genomics and PCR amplification enabled the identification of large chromosomal inversions of approximately 93 kb and 388 kb within the outbreak isolates associated with transducer-like proteins containing long nucleotide repeat sequences. The 93-kb inversion was characteristic of the outbreak-associated isolates, and the gene content of this inverted region displayed high synteny with the reference strain. CONCLUSIONS: The four outbreak isolates were clonally derived and differed mainly in the presence of the CJIE1 prophage, validating earlier findings linking the prophage to phenotypic differences in virulence assays and protein expression. The identification of large, genetically syntenous chromosomal inversions in the genomes of outbreak-associated isolates provided a unique method for discriminating outbreak isolates from the background population. Transducer-like proteins appear to be associated with the chromosomal inversions. CgMLST and hqSNV analysis also effectively delineated the outbreak isolates within the larger C. jejuni population structure.

Whole genome-based population biology and epidemiological surveillance of Listeria monocytogenes.

Listeria monocytogenes (Lm) is a major human foodborne pathogen. Numerous Lm outbreaks have been reported worldwide and associated with a high case fatality rate, reinforcing the need for strongly coordinated surveillance and outbreak control. We developed a universally applicable genome-wide strain genotyping approach and investigated the population diversity of Lm using 1,696 isolates from diverse sources and geographical locations. We define, with unprecedented precision, the population structure of Lm, demonstrate the occurrence of international circulation of strains and reveal the extent of heterogeneity in virulence and stress resistance genomic features among clinical and food isolates. Using historical isolates, we show that the evolutionary rate of Lm from lineage I and lineage II is low (∼2.5 × 10-7 substitutions per site per year, as inferred from the core genome) and that major sublineages (corresponding to so-called 'epidemic clones') are estimated to be at least 50-150 years old. This work demonstrates the urgent need to monitor Lm strains at the global level and provides the unified approach needed for global harmonization of Lm genome-based typing and population biology.

Phenotypic H-Antigen Typing by Mass Spectrometry Combined with Genetic Typing of H Antigens, O Antigens, and Toxins by Whole-Genome Sequencing Enhances Identification of Escherichia coli Isolates.

Mass spectrometry-based phenotypic H-antigen typing (MS-H) combined with whole-genome-sequencing-based genetic identification of H antigens, O antigens, and toxins (WGS-HOT) was used to type 60 clinical Escherichia coli isolates, 43 of which were previously identified as nonmotile, H type undetermined, or O rough by serotyping or having shown discordant MS-H and serotyping results. Whole-genome sequencing confirmed that MS-H was able to provide more accurate data regarding H antigen expression than serotyping. Further, enhanced and more confident O antigen identification resulted from gene cluster based typing in combination with conventional typing based on the gene pair comprising wzx and wzy and that comprising wzm and wzt The O antigen was identified in 94.6% of the isolates when the two genetic O typing approaches (gene pair and gene cluster) were used in conjunction, in comparison to 78.6% when the gene pair database was used alone. In addition, 98.2% of the isolates showed the existence of genes for various toxins and/or virulence factors, among which verotoxins (Shiga toxin 1 and/or Shiga toxin 2) were 100% concordant with conventional PCR based testing results. With more applications of mass spectrometry and whole-genome sequencing in clinical microbiology laboratories, this combined phenotypic and genetic typing platform (MS-H plus WGS-HOT) should be ideal for pathogenic E. coli typing.

Mass Spectrometry-Based Escherichia coli H Antigen/Flagella Typing: Validation and Comparison with Traditional Serotyping.

BACKGROUND: Escherichia coli H antigen typing with antisera, a useful method for flagella clinical identification and classification, is a time-consuming process because of the need to induce flagella growth and the occurrence of undetermined strains. We developed an alternative rapid and analytically sensitive mass spectrometry (MS) method, termed MS-based H antigen typing (MS-H), and applied it at the protein sequence level for H antigen typing. We also performed a comparison with traditional serotyping on reference strains and clinical isolates. METHODS: On the basis of international guidelines, the analytical selectivity and sensitivity, imprecision, correlation, repeatability, and reproducibility of the MS-H platform was evaluated using reference strains. Comparison of MS-H typing and serotyping was performed using 302 clinical isolates from 5 Canadian provinces, and discrepant results between the 2 platforms were resolved through whole genome sequencing. RESULTS: Repeated tests on reference strain EDL933 demonstrated a lower limit of the measuring interval at the subsingle colony (16.97 µg or 1.465 × 10(7) cells) level and close correlation (r(2) > 0.99) between cell culture biomass and sequence coverage. The CV was <10.0% among multiple repeats with 4 reference strains. Intra- and interlaboratory tests demonstrated that the MS-H method was robust and reproducible under various sample preparation and instrumentation conditions. Using discrepancy analysis via whole genome sequencing, performed on isolates with discrepant results, MS-H accurately identified 12.3% more isolates than conventional serotyping. CONCLUSIONS: MS-H typing of E. coli is useful for fast and accurate flagella typing and could be very useful during E. coli outbreaks.

Tolerance of Listeria monocytogenes to Quaternary Ammonium Sanitizers Is Mediated by a Novel Efflux Pump Encoded by emrE.

A novel genomic island (LGI1) was discovered in Listeria monocytogenes isolates responsible for the deadliest listeriosis outbreak in Canada, in 2008. To investigate the functional role of LGI1, the outbreak strain 08-5578 was exposed to food chain-relevant stresses, and the expression of 16 LGI1 genes was measured. LGI1 genes with putative efflux (L. monocytogenes emrE [emrELm]), regulatory (lmo1851), and adhesion (sel1) functions were deleted, and the mutants were exposed to acid (HCl), cold (4°C), salt (10 to 20% NaCl), and quaternary ammonium-based sanitizers (QACs). Deletion of lmo1851 had no effect on the L. monocytogenes stress response, and deletion of sel1 did not influence Caco-2 and HeLa cell adherence/invasion, whereas deletion of emrE resulted in increased susceptibility to QACs (P < 0.05) but had no effect on the MICs of gentamicin, chloramphenicol, ciprofloxacin, erythromycin, tetracycline, acriflavine, and triclosan. In the presence of the QAC benzalkonium chloride (BAC; 5 µg/ml), 14/16 LGI1 genes were induced, and lmo1861 (putative repressor gene) was constitutively expressed at 4 °C, 37 °C, and 52 °C and in the presence of UV exposure (0 to 30 min). Following 1 h of exposure to BAC (10 µg/ml), upregulation of emrE (49.6-fold), lmo1851 (2.3-fold), lmo1861 (82.4-fold), and sigB (4.1-fold) occurred. Reserpine visibly suppressed the growth of the ΔemrELm strain, indicating that QAC tolerance is due at least partially to efflux activity. These data suggest that a minimal function of LGI1 is to increase the tolerance of L. monocytogenes to QACs via emrELm. Since QACs are commonly used in the food industry, there is a concern that L. monocytogenes strains possessing emrE will have an increased ability to survive this stress and thus to persist in food processing environments.

Sequence typing confirms that a predominant Listeria monocytogenes clone caused human listeriosis cases and outbreaks in Canada from 1988 to 2010.

Human listeriosis outbreaks in Canada have been predominantly caused by serotype 1/2a isolates with highly similar pulsed-field gel electrophoresis (PFGE) patterns. Multilocus sequence typing (MLST) and multi-virulence-locus sequence typing (MVLST) each identified a diverse population of Listeria monocytogenes isolates, and within that, both methods had congruent subtypes that substantiated a predominant clone (clonal complex 8; virulence type 59; proposed epidemic clone 5 [ECV]) that has been causing human illness across Canada for more than 2 decades.