Strain-specific recovery of S. sonnei from artificially contaminated baby carrots: Enhancing food-safety investigations with a customized Shigella detection method based on genomically-predicted antibiotic resistance traits.

Shigella spp. are Gram-negative gastrointestinal bacterial pathogens that cause bacillary dysentery or shigellosis in humans. Isolation of Shigella from outbreak-associated foods is often problematic due to the lack of selectivity of cultural enrichment broths. To facilitate Shigella recovery from foods, we have developed strain-specific enrichment media based on the genomically-predicted antimicrobial resistance (AMR) features of an outbreak-associated Shigella sonnei strain harbouring resistance genes for streptomycin (STR) and trimethoprim (TMP). To assess performance of the method, baby carrots were artificially contaminated with the S. sonnei strain at low (2.4 CFU), medium (23.5 CFU) and high levels (235 CFU) along with 10-fold higher levels of a Shigella-inhibiting Escherichia coli strain. The target S. sonnei strain was successfully recovered from artificially-contaminated baby carrots when enriched in modified Tryptone Soya Broth (mTSB) supplemented with TMP, whereas Shigella was not recovered from Shigella broth (SB) or SB supplemented with STR. Quantitative PCR analysis of the enrichment culture indicated that supplementation of the enrichment cultures with TMP or STR increased the relative proportion of S. sonnei in enrichment cultures, except at the lowest inoculation level for STR. Microbiome profiling of the baby carrot enrichment cultures conducted by 16S rRNA gene sequencing indicated that both SB-STR and mTSB-TMP repressed the growth of competing Enterobacteriaceae in the enrichment cultures, relative to SB without supplementation. Overall, improved Shigella recovery was achieved with the addition of the appropriate custom selective agent during cultural enrichments demonstrating that genomically-informed custom selective enrichment of Shigella could be a valuable tool for supporting future foodborne shigellosis outbreak investigations.

Analysis of Antimicrobial Resistance in Bacterial Pathogens Recovered from Food and Human Sources: Insights from 639,087 Bacterial Whole-Genome Sequences in the NCBI Pathogen Detection Database.

Understanding the role of foods in the emergence and spread of antimicrobial resistance necessitates the initial documentation of antibiotic resistance genes within bacterial species found in foods. Here, the NCBI Pathogen Detection database was used to query antimicrobial resistance gene prevalence in foodborne and human clinical bacterial isolates. Of the 1,843,630 sequence entries, 639,087 (34.7%) were assigned to foodborne or human clinical sources with 147,788 (23.14%) from food and 427,614 (76.88%) from humans. The majority of foodborne isolates were either Salmonella (47.88%), Campylobacter (23.03%), Escherichia (11.79%), or Listeria (11.3%), and the remaining 6% belonged to 20 other genera. Most foodborne isolates were from meat/poultry (95,251 or 64.45%), followed by multi-product mixed food sources (29,892 or 20.23%) and fish/seafood (6503 or 4.4%); however, the most prominent isolation source varied depending on the genus/species. Resistance gene carriage also varied depending on isolation source and genus/species. Of note, Klebsiella pneumoniae and Enterobacter spp. carried larger proportions of the quinolone resistance gene qnrS and some clinically relevant beta-lactam resistance genes in comparison to Salmonella and Escherichia coli. The prevalence of mec in S. aureus did not significantly differ between meat/poultry and multi-product sources relative to clinical sources, whereas this resistance was rare in isolates from dairy sources. The proportion of biocide resistance in Bacillus and Escherichia was significantly higher in clinical isolates compared to many foodborne sources but significantly lower in clinical Listeria compared to foodborne Listeria. This work exposes the gaps in current publicly available sequence data repositories, which are largely composed of clinical isolates and are biased towards specific highly abundant pathogenic species. We also highlight the importance of requiring and curating metadata on sequence submission to not only ensure correct information and data interpretation but also foster efficient analysis, sharing, and collaboration. To effectively monitor resistance carriage in food production, additional work on sequencing and characterizing AMR carriage in common commensal foodborne bacteria is critical.

Modeling the limits of detection for antimicrobial resistance genes in agri-food samples: a comparative analysis of bioinformatics tools.

BACKGROUND: Although the spread of antimicrobial resistance (AMR) through food and its production poses a significant concern, there is limited research on the prevalence of AMR bacteria in various agri-food products. Sequencing technologies are increasingly being used to track the spread of AMR genes (ARGs) in bacteria, and metagenomics has the potential to bypass some of the limitations of single isolate characterization by allowing simultaneous analysis of the agri-food product microbiome and associated resistome. However, metagenomics may still be hindered by methodological biases, presence of eukaryotic DNA, and difficulties in detecting low abundance targets within an attainable sequence coverage. The goal of this study was to assess whether limits of detection of ARGs in agri-food metagenomes were influenced by sample type and bioinformatic approaches. RESULTS: We simulated metagenomes containing different proportions of AMR pathogens and analysed them for taxonomic composition and ARGs using several common bioinformatic tools. Kraken2/Bracken estimates of species abundance were closest to expected values. However, analysis by both Kraken2/Bracken indicated presence of organisms not included in the synthetic metagenomes. Metaphlan3/Metaphlan4 analysis of community composition was more specific but with lower sensitivity than the Kraken2/Bracken analysis. Accurate detection of ARGs dropped drastically below 5X isolate genome coverage. However, it was sometimes possible to detect ARGs and closely related alleles at lower coverage levels if using a lower ARG-target coverage cutoff (< 80%). While KMA and CARD-RGI only predicted presence of expected ARG-targets or closely related gene-alleles, SRST2 (which allows read to map to multiple targets) falsely reported presence of distantly related ARGs at all isolate genome coverage levels. The presence of background microbiota in metagenomes influenced the accuracy of ARG detection by KMA, resulting in mcr-1 detection at 0.1X isolate coverage in the lettuce but not in the beef metagenome. CONCLUSIONS: This study demonstrates accurate detection of ARGs in synthetic metagenomes using various bioinformatic methods, provided that reads from the ARG-encoding organism exceed approximately 5X isolate coverage (i.e. 0.4% of a 40 million read metagenome). While lowering thresholds for target gene detection improved sensitivity, this led to the identification of alternative ARG-alleles, potentially confounding the identification of critical ARGs in the resistome. Further advancements in sequencing technologies providing increased coverage depth or extended read lengths may improve ARG detection in agri-food metagenomic samples, enabling use of this approach for tracking clinically important ARGs in agri-food samples.

Artificial intelligence and real-world data for drug and food safety - A regulatory science perspective.

In 2013, the Global Coalition for Regulatory Science Research (GCRSR) was established with members from over ten countries (www.gcrsr.net). One of the main objectives of GCRSR is to facilitate communication among global regulators on the rise of new technologies with regulatory applications through the annual conference Global Summit on Regulatory Science (GSRS). The 11th annual GSRS conference (GSRS21) focused on "Regulatory Sciences for Food/Drug Safety with Real-World Data (RWD) and Artificial Intelligence (AI)." The conference discussed current advancements in both AI and RWD approaches with a specific emphasis on how they impact regulatory sciences and how regulatory agencies across the globe are pursuing the adaptation and oversight of these technologies. There were presentations from Brazil, Canada, India, Italy, Japan, Germany, Switzerland, Singapore, the United Kingdom, and the United States. These presentations highlighted how various agencies are moving forward with these technologies by either improving the agencies' operation and/or preparing regulatory mechanisms to approve the products containing these innovations. To increase the content and discussion, the GSRS21 hosted two debate sessions on the question of "Is Regulatory Science Ready for AI?" and a workshop to showcase the analytical data tools that global regulatory agencies have been using and/or plan to apply to regulatory science. Several key topics were highlighted and discussed during the conference, such as the capabilities of AI and RWD to assist regulatory science policies for drug and food safety, the readiness of AI and data science to provide solutions for regulatory science. Discussions highlighted the need for a constant effort to evaluate emerging technologies for fit-for-purpose regulatory applications. The annual GSRS conferences offer a unique platform to facilitate discussion and collaboration across regulatory agencies, modernizing regulatory approaches, and harmonizing efforts.

Exploiting a targeted resistome sequencing approach in assessing antimicrobial resistance in retail foods.

BACKGROUND: With the escalating risk of antimicrobial resistance (AMR), there are limited analytical options available that can comprehensively assess the burden of AMR carried by clinical/environmental samples. Food can be a potential source of AMR bacteria for humans, but its significance in driving the clinical spread of AMR remains unclear, largely due to the lack of holistic-yet-sensitive tools for surveillance and evaluation. Metagenomics is a culture-independent approach well suited for uncovering genetic determinants of defined microbial traits, such as AMR, present within unknown bacterial communities. Despite its popularity, the conventional approach of non-selectively sequencing a sample's metagenome (namely, shotgun-metagenomics) has several technical drawbacks that lead to uncertainty about its effectiveness for AMR assessment; for instance, the low discovery rate of resistance-associated genes due to their naturally small genomic footprint within the vast metagenome. Here, we describe the development of a targeted resistome sequencing method and demonstrate its application in the characterization of the AMR gene profile of bacteria associated with several retail foods. RESULT: A targeted-metagenomic sequencing workflow using a customized bait-capture system targeting over 4,000 referenced AMR genes and 263 plasmid replicon sequences was validated against both mock and sample-derived bacterial community preparations. Compared to shotgun-metagenomics, the targeted method consistently provided for improved recovery of resistance gene targets with a much-improved target detection efficiency (> 300-fold). Targeted resistome analyses conducted on 36 retail-acquired food samples (fresh sprouts, n = 10; ground meat, n = 26) and their corresponding bacterial enrichment cultures (n = 36) reveals in-depth features regarding the identity and diversity of AMR genes, most of which were otherwise undetected by the whole-metagenome shotgun sequencing method. Furthermore, our findings suggest that foodborne Gammaproteobacteria could be the major reservoir of food-associated AMR genetic determinants, and that the resistome structure of the selected high-risk food commodities are, to a large extent, dictated by microbiome composition. CONCLUSIONS: For metagenomic sequencing-based surveillance of AMR, the target-capture method presented herein represents a more sensitive and efficient approach to evaluate the resistome profile of complex food or environmental samples. This study also further implicates retail foods as carriers of diverse resistance-conferring genes indicating a potential impact on the dissemination of AMR.

Genomically Informed Custom Selective Enrichment of Shiga Toxigenic Escherichia coli (STEC) Outbreak Strains in Foods Using Antibiotics.

Shiga toxigenic Escherichia coli (STEC) have been implicated in major foodborne outbreaks worldwide. The STEC family of pathogens is biochemically diverse, and current microbiological methods for detecting STEC are limited by the lack of a universal selective enrichment approach and prone to interference by high levels of background microbiota associated with certain types of foods. A novel approach has been developed for the recovery of foodborne illness outbreak strains during outbreak investigations based on the analysis of whole genome sequence data of implicated clinical isolates to determine antimicrobial resistance (AMR) genes. The presence of certain AMR genes in STEC has been correlated with the ability to grow in the presence of a specific antibiotic, which can be used to supplement enrichment broths to improve the recovery of a target strain. The enhanced recovery of STEC strains with different AMR profiles from various food types (beef, sprouts, leafy greens, and raw milk cheese) containing high levels of background microbiota was demonstrated using AMR predictions for nine different antibiotics. This genomically informed custom selective enrichment approach increases the availability of analytical options and improves the reliability of food microbiological analyses in confirming food vehicles implicated in outbreak events and defining the scope of product contamination to support risk assessment and risk management actions.

Microbial Antagonism in Food-Enrichment Culture: Inhibition of Shiga Toxin-Producing Escherichia coli and Shigella Species.

Bacterial pathogens, such as Shiga toxin-producing Escherichia coli (STEC) and Shigella spp., are important causes of foodborne illness internationally. Recovery of these organisms from foods is critical for food safety investigations to support attribution of illnesses to specific food commodities; however, isolation of bacterial cultures can be challenging. Methods for the isolation of STEC and Shigella spp. from foods typically require enrichment to amplify target organisms to detectable levels. Yet, during enrichment, target organisms can be outcompeted by other bacteria in food matrices due to faster growth rates, or through production of antimicrobial agents such as bacteriocins or bacteriophages. The purpose of this study was to evaluate the occurrence of Shigella and STEC inhibitors produced by food microbiota. The production of antimicrobial compounds in cell-free extracts from 200 bacterial strains and 332 food-enrichment broths was assessed. Cell-free extracts produced by 23 (11.5%) of the strains tested inhibited growth of at least one of the five Shigella and seven STEC indicator strains used in this study. Of the 332 enrichment broths tested, cell-free extracts from 25 (7.5%) samples inhibited growth of at least one of the indicator strains tested. Inhibition was most commonly associated with E. coli recovered from meat products. Most of the inhibiting compounds were determined to be proteinaceous (34 of the 48 positive samples, 71%; including 17 strains, 17 foods) based on inactivation by proteolytic enzymes, indicating presence of bacteriocins. The cell-free extracts from 13 samples (27%, eight strains, five foods) were determined to contain bacteriophages based on the observation of plaques in diluted extracts and/or resistance to proteolytic enzymes. These results indicate that the production of inhibitors by food microbiota may be an important challenge for the recovery of foodborne pathogens, particularly for Shigella sonnei. The performance of enrichment media for recovery of Shigella and STEC could be improved by mitigating the impact of inhibitors produced by food microbiota during the enrichment process.

Characterization of Atypical Shiga Toxin Gene Sequences and Description of Stx2j, a New Subtype.

Shiga toxin (Stx) is the definitive virulence factor of Shiga toxin-producing Escherichia coli (STEC). Stx variants are currently organized into a taxonomic system of three Stx1 (a, c, and d) and seven Stx2 (a, b, c, d, e, f, and g) subtypes. In this study, seven STEC isolates from food and clinical samples possessing stx2 sequences that do not fit current Shiga toxin taxonomy were identified. Genome assemblies of the STEC strains were created from Oxford Nanopore and Illumina sequence data. The presence of atypical stx2 sequences was confirmed by Sanger sequencing, as were Stx2 expression and cytotoxicity. A strain of O157:H7 was found to possess stx1a and a truncated stx2a, which were originally misidentified as an atypical stx2. Two strains possessed unreported variants of Stx2a (O8:H28) and Stx2b (O146:H21). In four of the strains, we found three Stx subtypes that are not included in the current taxonomy. Stx2h (O170:H18) was identified in a Canadian sprout isolate; this subtype has only previously been reported in STEC from Tibetan Marmots. Stx2o (O85:H1) was identified in a clinical isolate. Finally, Stx2j (O158:H23 and O33:H14) was found in lettuce and clinical isolates. The results of this study expand the number of known Stx subtypes, the range of STEC serotypes, and isolation sources in which they may be found. The presence of the Stx2j and Stx2o in clinical isolates of STEC indicates that strains carrying these variants are potential human pathogens.

Systematic Evaluation of Whole-Genome Sequencing Based Prediction of Antimicrobial Resistance in Campylobacter jejuni and C. coli.

The increasing prevalence of antimicrobial resistance (AMR) in Campylobacter spp. is a global concern. This study evaluated the use of whole-genome sequencing (WGS) to predict AMR in Campylobacter jejuni and C. coli. A panel of 271 isolates recovered from Canadian poultry was used to compare AMR genotype to antimicrobial susceptibility testing (AST) results (azithromycin, ciprofloxacin, erythromycin, gentamicin, tetracycline, florfenicol, nalidixic acid, telithromycin, and clindamycin). The presence of antibiotic resistance genes (ARGs) was determined for each isolate using five computational approaches to evaluate the effect of: ARG screening software, input data (i.e., raw reads, draft genome assemblies), genome coverage and genome assembly software. Overall, concordance between the genotype and phenotype was influenced by the computational pipelines, level of genome coverage and the type of ARG but not by input data. For example, three of the pipelines showed a 99% agreement between detection of a tet(O) gene and tetracycline resistance, whereas agreement between the detection of tet(O) and TET resistance was 98 and 93% for two pipelines. Overall, higher levels of genome coverage were needed to reliably detect some ARGs; for example, at 15X coverage a tet(O) gene was detected in >70% of the genomes, compared to <60% of the genomes for bla(OXA). No genes associated with florfenicol or gentamicin resistance were found in the set of strains included in this study, consistent with AST results. Macrolide and fluoroquinolone resistance was associated 100% with mutations in the 23S rRNA (A2075G) and gyrA (T86I) genes, respectively. A lower association between a A2075G 23S rRNA gene mutation and resistance to clindamycin and telithromycin (92.8 and 78.6%, respectively) was found. While WGS is an effective approach to predicting AMR in Campylobacter, this study demonstrated the impact that computational pipelines, genome coverage and the genes can have on the reliable identification of an AMR genotype.

Genomic Markers for Quaternary Ammonium Compound Resistance as a Persistence Indicator for Listeria monocytogenes Contamination in Food Manufacturing Environments.

ABSTRACT: Persistent contamination of food manufacturing environments by Listeria monocytogenes is an important public health risk, because such contamination events defy standard sanitization protocols, for example, the application of quaternary ammonium compounds such as benzalkonium chloride (BC), providing a source for prolonged dissemination of the bacteria in food products. We performed whole genome sequencing analyses of 1,279 well-characterized L. monocytogenes isolates from various foods and food manufacturing environments and identified the bcrABC gene cassette associated with BC resistance in 531 (41.5%) isolates. The bcrABC cassette was significantly associated with L. monocytogenes isolates belonging to clonal complex (CC) 321, CC155, CC204, and CC199, which are among the 10 most prevalent genotypes recovered from foods and food production environments. All but 1 of the 177 CC321 isolates harbored the bcrABC cassette. In addition, 384 (38.6%) of the 994 isolates recovered from foods representing 67 different CCs and 119 (59.2%) of isolates from food manufacturing environmental samples representing 26 different CCs were found to harbor the intact bcrABC cassette. A representative set of 69 isolates with and without bcrABC was assayed for the ability to grow in the presence of BC, and 34 of 35 isolates harboring the bcrABC cassette exhibited MICs of ≥10 µg/mL BC. Determination of bcrABC in isolates could be achieved using both PCR and whole genome sequencing techniques, providing food testing laboratories with options for the characterization of isolates. The ability to determine markers of quaternary ammonium compound resistance such as bcrABC and epidemiologic lineage may provide risk managers with a tool to assess the potential for persistent contamination of the food manufacturing environment and the need for more targeted surveillance to ensure the efficacy of mitigation actions.

Centrifugal microfluidic lab-on-a-chip system with automated sample lysis, DNA amplification and microarray hybridization for identification of enterohemorrhagic Escherichia coli culture isolates.

The development of technology for the rapid, automated identification of bacterial culture isolates can help regulatory agencies to shorten response times in food safety surveillance, compliance, and enforcement as well as outbreak investigations. While molecular methods such as polymerase chain reaction (PCR) enable the identification of microbial organisms with high sensitivity and specificity, they generally rely on sophisticated instrumentation and elaborate workflows for sample preparation with an undesirably high level of hands-on engagement. Herein, we describe the design, operation and performance of a lab-on-a-chip system integrating thermal lysis, PCR amplification and microarray hybridization on the same cartridge. The assay is performed on a centrifugal microfluidic platform that allows for pneumatic actuation of liquids during rotation, making it possible to perform all fluidic operations in a fully-automated fashion without the need for integrating active control elements on the microfluidic cartridge. The cartridge, which is fabricated from hard and soft thermoplastic polymers, is compatible with high-volume manufacturing (e.g., injection molding). Chip design and thermal interface were both optimized to ensure efficient heat transfer and allow for fast thermal cycling during the PCR process. The integrated workflow comprises 14 steps and takes less than 2 h to complete. The only manual steps are related to loading of the sample and reagents on the cartridge as well as fluorescence imaging of the microarray. On-chip lysis and PCR amplification both provided results comparable to those obtained by bench-top instrumentation. The microarray, incorporating a panel of oligonucleotide probes for multiplexed detection of seven enterohemorrhagic E. coli priority serotypes, was implemented on a cyclic olefin copolymer substrate using a novel activation scheme that involves the conversion of hydroxyl groups (derived from oxygen plasma treatment) into reactive cyanate ester using cyanogen bromide. On-chip hybridization was demonstrated in a non-quantitative fashion using fluorescently-labelled gene markers for E. coli O157:H7 (rfbO157, eae, vt1, and vt2) obtained through a multiplexed PCR amplification step.

Systematic Evaluation of Whole Genome Sequence-Based Predictions of Salmonella Serotype and Antimicrobial Resistance.

Whole-genome sequencing (WGS) is used increasingly in public-health laboratories for typing and characterizing foodborne pathogens. To evaluate the performance of existing bioinformatic tools for in silico prediction of antimicrobial resistance (AMR) and serotypes of Salmonella enterica, WGS-based genotype predictions were compared with the results of traditional phenotyping assays. A total of 111 S. enterica isolates recovered from a Canadian baseline study on broiler chicken conducted in 2012-2013 were selected based on phenotypic resistance to 15 different antibiotics and isolates were subjected to WGS. Both SeqSero2 and SISTR accurately determined S. enterica serotypes, with full matches to laboratory results for 87.4 and 89.2% of isolates, respectively, and partial matches for the remaining isolates. Antimicrobial resistance genes (ARGs) were identified using several bioinformatics tools including the Comprehensive Antibiotic Resistance Database - Resistance Gene Identifier (CARD-RGI), Center for Genomic Epidemiology (CGE) ResFinder web tool, Short Read Sequence Typing for Bacterial Pathogens (SRST2 v 0.2.0), and k-mer alignment method (KMA v 1.17). All ARG identification tools had ≥ 99% accuracy for predicting resistance to all antibiotics tested except streptomycin (accuracy 94.6%). Evaluation of ARG detection in assembled versus raw-read WGS data found minimal observable differences that were gene- and coverage- dependent. Where initial phenotypic results indicated isolates were sensitive, yet ARGs were detected, repeat AMR testing corrected discrepancies. All tools failed to find resistance-determining genes for one gentamicin- and two streptomycin-resistant isolates. Further investigation found a single nucleotide polymorphism (SNP) in the nuoF coding region of one of the isolates which may be responsible for the observed streptomycin-resistant phenotype. Overall, WGS-based predictions of AMR and serotype were highly concordant with phenotype determination regardless of computational approach used.

Polymer Micropillar Arrays for Colorimetric DNA Detection.

We describe the use of periodic micropillar arrays, produced from cyclic olefin copolymer using high-fidelity microfabrication, as templates for colorimetric DNA detection. The assay involves PCR-amplified gene markers for E. coli O157:H7 (rfbO157, eae, vt1, and vt2) incorporating a detectable digoxigenin label, which is revealed through an immunoenzymatic process following hybridization with target-specific oligonucleotide capture probes. The capacity of micropillar arrays to induce wicking is used to distribute and confine capture probes with spatial control, making it possible to achieve a uniform signal while allowing multiple, independent probes to be arranged in close proximity on the same substrate. The kinetic profile of color pigment formation on the surface was followed using absorbance measurements, showing maximum signal increase between 20 and 60 min of reaction time. The relationship between microstructure and colorimetric signal was investigated through variation of geometric parameters, such as pitch (10-50 µm), pillar diameter (5-40 µm), and height (16-48 µm). Our findings suggest that signal intensity is largely influenced by the edges of the pillars and less by their height such that it deviates from a linear relationship when both aspect ratio and pillar density become very high. A theoretical model used to simulate the changes in surface composition at the molecular level suggests that differences in the temporal and spatial accumulation of assay components account for this observation.

ConFindr: rapid detection of intraspecies and cross-species contamination in bacterial whole-genome sequence data.

Whole-genome sequencing (WGS) of bacterial pathogens is currently widely used to support public-health investigations. The ability to assess WGS data quality is critical to underpin the reliability of downstream analyses. Sequence contamination is a quality issue that could potentially impact WGS-based findings; however, existing tools do not readily identify contamination from closely-related organisms. To address this gap, we have developed a computational pipeline, ConFindr, for detection of intraspecies contamination. ConFindr determines the presence of contaminating sequences based on the identification of multiple alleles of core, single-copy, ribosomal-protein genes in raw sequencing reads. The performance of this tool was assessed using simulated and lab-generated Illumina short-read WGS data with varying levels of contamination (0-20% of reads) and varying genetic distance between the designated target and contaminant strains. Intraspecies and cross-species contamination was reliably detected in datasets containing 5% or more reads from a second, unrelated strain. ConFindr detected intraspecies contamination with higher sensitivity than existing tools, while also being able to automatically detect cross-species contamination with similar sensitivity. The implementation of ConFindr in quality-control pipelines will help to improve the reliability of WGS databases as well as the accuracy of downstream analyses. ConFindr is written in Python, and is freely available under the MIT License at github.com/OLC-Bioinformatics/ConFindr.

Selection of Multidrug-Resistant Bacteria in Medicated Animal Feeds.

Exposure to antimicrobial resistant (AMR) bacteria is a major public health issue which may, in part, have roots in food production practices that are conducive to the selection of AMR bacteria ultimately impacting the human microbiome through food consumption. Of particular concern is the prophylactic use of antibiotics in animal husbandry, such as the medication of feeds with sulfonamides and other antibiotics not considered clinically relevant, but which may nonetheless co-select for multi-drug resistant (MDR) bacteria harboring resistance to medically important antibiotics. Using a MDR Klebsiella pneumoniae strain exhibiting resistance to sulfonamides and beta-lactams (including carbapenem) as a model, we examined the ability of non-medicated and commercially medicated (sulfonamide) animal feeds to select for the model strain when inoculated at low levels by measuring its recovery along with key AMR markers, sul1(sulfonamide) and blaKPC-3 (meropenem), under different incubation conditions. When non-medicated feeds were supplemented with defined amounts of sulfadiazine the model strain was significantly enriched after incubation in Mueller Hinton Broth at 37°C overnight, or in same at room temperature for a week, with consistent detection of both the sul1 and blaKPC-3 markers as determined by polymerase chain reaction (PCR) techniques to screen colony isolates recovered on plating media. Significant recoveries of the inoculated strain and the sul1 and blaKPC-3 markers were observed with one of three commercially medicated (sulfamethazine) feeds tested under various incubation conditions. These results demonstrate that under certain conditions the prophylactic use of so-called non-priority antibiotics in feeds can potentially lead to co-selection of environmental AMR bacteria with resistance to medically important antibiotics, which may have far-reaching implications for human health.

Genomically Informed Strain-Specific Recovery of Shiga Toxin-Producing Escherichia coli during Foodborne Illness Outbreak Investigations.

Next-generation sequencing plays an important role in the characterization of clinical bacterial isolates for source attribution purposes during investigations of foodborne illness outbreaks. Once an illness cluster and a suspect food vehicle have been identified, food testing is initiated for confirmation and to determine the scope of a contamination event so that the implicated lots may be removed from the marketplace. For biochemically diverse families of pathogens such as Shiga toxin-producing Escherichia coli (STEC), the ability to detect specific strains may be hampered by the lack of a universal selective enrichment approach for their recovery against high levels of background microbiota. The availability of whole genome sequence data for a given outbreak STEC strain prior to commencement of food testing may provide food microbiologists an opportunity to customize selective enrichment techniques favoring the recovery of the outbreak strain. Here we demonstrate the advantages of using the publicly available ResFinder tool in the analysis of STEC model strains belonging to serotypes O111 and O157 to determine antimicrobial resistance traits that can be used in formulating strain-specific enrichment media to enhance recovery of these strains from microbiologically complex food samples. The improved recovery from ground beef of model STEC strains with various antimicrobial resistance profiles was demonstrated using three classes of antibiotics as selective agents, suggesting the universal applicability of this new approach in supporting foodborne illness investigations.

Genomic characterization of Listeria monocytogenes isolates reveals that their persistence in a pig slaughterhouse is linked to the presence of benzalkonium chloride resistance genes.

BACKGROUND: The aim of this study was to characterize the genomes of 30 Listeria monocytogenes isolates collected at a pig slaughterhouse to determine the molecular basis for their persistence. RESULTS: Comparison of the 30 L. monocytogenes genomes showed that successive isolates (i.e., persistent types) recovered from thew sampling site could be linked on the basis of single nucleotide variants confined to prophage regions. In addition, our study revealed the presence among these strains of the bcrABC cassette which is known to produce efflux pump-mediated benzalkonium chloride resistance, and which may account for the persistence of these isolates in the slaughterhouse environment. The presence of the bcrABC cassette was confirmed by WGS and PCR and the resistance phenotype was determined by measuring minimum inhibitory concentrations. Furthermore, the BC-resistant strains were found to produce lower amounts of biofilm in the presence of sublethal concentrations of BC. CONCLUSIONS: High resolution SNP-based typing and determination of the bcrABC cassette may provide a means of distinguishing between resident and sporadic L. monocytogenes isolates, and this in turn will support better management of this pathogen in the food industry.

The challenges of designing a benchmark strategy for bioinformatics pipelines in the identification of antimicrobial resistance determinants using next generation sequencing technologies.

Next-Generation Sequencing (NGS) technologies are expected to play a crucial role in the surveillance of infectious diseases, with their unprecedented capabilities for the characterisation of genetic information underlying the virulence and antimicrobial resistance (AMR) properties of microorganisms.  In the implementation of any novel technology for regulatory purposes, important considerations such as harmonisation, validation and quality assurance need to be addressed.  NGS technologies pose unique challenges in these regards, in part due to their reliance on bioinformatics for the processing and proper interpretation of the data produced.  Well-designed benchmark resources are thus needed to evaluate, validate and ensure continued quality control over the bioinformatics component of the process.  This concept was explored as part of a workshop on "Next-generation sequencing technologies and antimicrobial resistance" held October 4-5 2017.   Challenges involved in the development of such a benchmark resource, with a specific focus on identifying the molecular determinants of AMR, were identified. For each of the challenges, sets of unsolved questions that will need to be tackled for them to be properly addressed were compiled. These take into consideration the requirement for monitoring of AMR bacteria in humans, animals, food and the environment, which is aligned with the principles of a "One Health" approach.

Rapid detection and serovar identification of common Salmonella enterica serovars in Canada using a new pyrosequencing assay.

Serotyping of Salmonella enterica subsp. enterica is a critical step for foodborne salmonellosis investigation. To identify Salmonella enterica subsp. enterica serovars, we have developed a new assay based on a triplex polymerase chain reaction (PCR) with pyrosequencing for amplicon confirmation and phylogenetic discrimination of strains. The top 54 most prevalent serovars of S. enterica in Canada were examined with a total of 23 single-nucleotide polymorphisms (SNPs) and (or) single-nucleotide variations (SNVs) located on 3 genes (fliD, sopE2, and spaO). Seven of the most common serovars, Newport, Typhi, Javiana, Infantis, Thompson, Heidelberg, and Enteritidis, were successfully distinguished from the other serovars based on their unique SNP-SNV combinations. The remaining serovars, including Typhimurium, ssp I:4,[5],12:i:-, and Saintpaul, were further divided into 47 subgroups that demonstrate the relatedness to phylogenetic classifications of each serovar. This pyrosequencing assay is not only cost-effective, rapid, and user-friendly, but also provides phylogenetic information by analyzing 23 selected SNPs. With the added layer of confidence in the PCR results and the accuracy and speed of pyrosequencing, this novel method would benefit the food industry and provides a tool for rapid outbreak investigation through quick detection and identification of common S. enterica serovars in Canada.

Multiplexed Single Intact Cell Droplet Digital PCR (MuSIC ddPCR) Method for Specific Detection of Enterohemorrhagic E. coli (EHEC) in Food Enrichment Cultures.

Foodborne illness attributed to enterohemorrhagic E. coli (EHEC), a highly pathogenic subset of Shiga toxin-producing E. coli (STEC), is increasingly recognized as a significant public health issue. Current microbiological methods for identification of EHEC in foods often use PCR-based approaches to screen enrichment broth cultures for characteristic gene markers [i.e., Shiga toxin (stx) and intimin (eae)]. However, false positives arise when complex food matrices, such as beef, contain mixtures of eae-negative STEC and eae-positive E. coli, but no EHEC with both markers in a single cell. To reduce false-positive detection of EHEC in food enrichment samples, a Multiplexed, Single Intact Cell droplet digital PCR (MuSIC ddPCR) assay capable of detecting the co-occurrence of the stx and eae genes in a single bacterial cell was developed. This method requires: (1) dispersal of intact bacteria into droplets; (2) release of genomic DNA (gDNA) by heat lysis; and (3) amplification and detection of genetic targets (stx and eae) using standard TaqMan chemistries with ddPCR. Performance of the method was tested with panels of EHEC and non-target E. coli. By determining the linkage (i.e., the proportion of droplets in which stx and eae targets were both amplified), samples containing EHEC (typically greater than 20% linkage) could be distinguished from samples containing mixtures of eae-negative STEC and eae-positive E. coli (0-2% linkage). The use of intact cells was necessary as this linkage was not observed with gDNA extracts. EHEC could be accurately identified in enrichment broth cultures containing excess amounts of background E. coli and in enrichment cultures derived from ground beef/pork and leafy-green produce samples. To our knowledge, this is the first report of dual-target detection in single bacterial cells using ddPCR. The application of MuSIC ddPCR to enrichment-culture screening would reduce false-positives, thereby improving the cost, speed, and accuracy of current methods for EHEC detection in foods.