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.

Human listeriosis outbreaks in Canada have been predominantly caused by serotype 1/2a isolates with highly similar pulsedfield gel electrophoresis (PFGE) patterns. Multilocus sequence typing (MLST) and multi-virulence-locus sequence typing (MV-LST) 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.

Enterobacter sakazakii has been implicated as the causal organism in a severe form of neonatal meningitis, with reported mortality rates of 40 to 80%. Dried infant formula has been identified as a potential source of the organism in both outbreaks and sporadic cases. In this study, clinical and foodborne isolates of E. sakazakii were evaluated for enterotoxin production by the suckling mouse assay. In addition, suckling mice were challenged both orally and by intraperitoneal injection. Of 18 E. sakazakii strains evaluated, four were found to test positive for enterotoxin production. All strains of E. sakazakii were lethal to suckling mice at 10(8) CFU per mouse by intraperitoneal injection, while two strains caused death by the peroral route. In in vitro assays, CHO, Vero, and Y-1 cells demonstrated both cell lysis and rounding when exposed to E. sakazakii strain LA filtrates. This is the first report describing any putative virulence factors of E. sakazakii.

BackgroundMembers of the genus Cronobacter are causes of rare but severe illness in neonates and preterm infants following the ingestion of contaminated infant formula. Seven species have been described and two of the species genomes were subsequently published. In this study, we performed comparative genomics on eight strains of Cronobacter, including six that we sequenced (representing six of the seven species) and two previously published, closed genomes.ResultsWe identified and characterized the features associated with the core and pan genome of the genus Cronobacter in an attempt to understand the evolution of these bacteria and the genetic content of each species. We identified 84 genomic regions that are present in two or more Cronobacter genomes, along with 45 unique genomic regions. Many potentially horizontally transferred genes, such as lysogenic prophages, were also identified. Most notable among these were several type six secretion system gene clusters, transposons that carried tellurium, copper and/or silver resistance genes, and a novel integrative conjugative element.ConclusionsCronobacter have diverged into two clusters, one consisting of C. dublinensis and C. muytjensii (Cdub-Cmuy) and the other comprised of C. sakazakii, C. malonaticus, C. universalis, and C. turicensis, (Csak-Cmal-Cuni-Ctur) from the most recent common ancestral species. While several genetic determinants for plant-association and human virulence could be found in the core genome of Cronobacter, the four Cdub-Cmuy clade genomes contained several accessory genomic regions important for survival in a plant-associated environmental niche, while the Csak-Cmal-Cuni-Ctur clade genomes harbored numerous virulence-related genetic traits.

The wide availability of whole-genome sequencing (WGS) and an abundance of open-source software have made detection of single-nucleotide polymorphisms (SNPs) in bacterial genomes an increasingly accessible and effective tool for comparative analyses. Thus, ensuring that real nucleotide differences between genomes (i.e., true SNPs) are detected at high rates and that the influences of errors (such as false positive SNPs, ambiguously called sites, and gaps) are mitigated is of utmost importance. The choices researchers make regarding the generation and analysis of WGS data can greatly influence the accuracy of short-read sequence alignments and, therefore, the efficacy of such experiments. We studied the effects of some of these choices, including: i) depth of sequencing coverage, ii) choice of reference-guided short-read sequence assembler, iii) choice of reference genome, and iv) whether to perform read-quality filtering and trimming, on our ability to detect true SNPs and on the frequencies of errors. We performed benchmarking experiments, during which we assembled simulated and real Listeria monocytogenes strain 08-5578 short-read sequence datasets of varying quality with four commonly used assemblers (BWA, MOSAIK, Novoalign, and SMALT), using reference genomes of varying genetic distances, and with or without read pre-processing (i.e., quality filtering and trimming). We found that assemblies of at least 50-fold coverage provided the most accurate results. In addition, MOSAIK yielded the fewest errors when reads were aligned to a nearly identical reference genome, while using SMALT to align reads against a reference sequence that is ∼0.82% distant from 08-5578 at the nucleotide level resulted in the detection of the greatest numbers of true SNPs and the fewest errors. Finally, we show that whether read pre-processing improves SNP detection depends upon the choice of reference sequence and assembler. In total, this study demonstrates that researchers should test a variety of conditions to achieve optimal results.

Canadian cases and outbreaks of illness caused by Listeria monocytogenes between 1995 and 2004 were assessed. Isolates (722 total) were characterized by serotyping, and pulsed-field gel electrophoresis (PFGE) was performed to provide a means of detecting case clusters. Rates of listeriosis remained fairly consistent during the period of study, and patient characteristics were similar to those seen in studies of other populations. Most isolates were obtained from blood and cerebrospinal fluid, although during some outbreak investigations isolates were also obtained from stools. Serotype 1/2a predominated in isolates from patients in Canada, followed by serotypes 4b and 1/2b. Outbreaks caused by L. monocytogenes that occurred during the period of study were caused by isolates with serotypes 1/2a and 4b. A retrospective analysis of PFGE data uncovered several clusters that might have represented undetected outbreaks, suggesting that comprehensive prospective PFGE analysis coupled with prompt epidemiological investigations might lead to improved outbreak detection and control.

Listeria monocytogenes can cause serious illness in humans, and subsequent epidemiological investigation requires molecular characterization to allow the identification of specific isolates. L. monocytogenes is usually characterized by serotyping and is subtyped by using pulsed-field gel electrophoresis (PFGE) or ribotyping. DNA microarrays provide an alternative means to resolve genetic differences among isolates, and unlike PFGE and ribotyping, microarrays can be used to identify specific genes associated with strains of interest. Twenty strains of L. monocytogenes representing six serovars were used to generate a shotgun library, and subsequently a 629-probe microarray was constructed by using features that included only potentially polymorphic gene probe sequences. Fifty-two strains of L. monocytogenes were genotyped by using the condensed array, including strains associated with five major listeriosis epidemics. Cluster analysis of the microarray data grouped strains according to phylogenetic lineage and serotype. Most epidemiologically linked strains were grouped together, and subtyping resolution was the same as that with PFGE (using AscI and ApaI) and better than that with multilocus sequence typing (using six housekeeping genes) and ribotyping. Additionally, a majority of epidemic strains were grouped together within phylogenetic Division I. This epidemic cluster was clearly distinct from the two other Division I clusters, which encompassed primarily sporadic and environmental strains. Discriminant function analysis allowed identification of 22 probes from the mixed-genome array that distinguish serotypes and subtypes, including several potential markers that were distinct for the epidemic cluster. Many of the subtype-specific genes encode proteins that likely confer survival advantages in the environment and/or host.

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