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Background Processing and analyzing whole genome sequencing (WGS) is computationally intense: a single Illumina MiSeq WGS run produces ~ 1 million 250-base-pair reads for each of 24 samples. This poses significant obstacles for smaller laboratories, or laboratories not affiliated with larger projects, which may not have dedicated bioinformatics staff or computing power to effectively use genomic data to protect public health. Building on the success of the cloud-based Galaxy bioinformatics platform ( http://galaxyproject.org ), already known for its user-friendliness and powerful WGS analytical tools, the Center for Food Safety and Applied Nutrition (CFSAN) at the U.S. Food and Drug Administration (FDA) created a customized ‘instance’ of the Galaxy environment, called GalaxyTrakr ( https://www.galaxytrakr.org ), for use by laboratory scientists performing food-safety regulatory research. The goal was to enable laboratories outside of the FDA internal network to (1) perform quality assessments of sequence data, (2) identify links between clinical isolates and positive food/environmental samples, including those at the National Center for Biotechnology Information sequence read archive ( https://www.ncbi.nlm.nih.gov/sra/ ), and (3) explore new methodologies such as metagenomics. GalaxyTrakr hosts a variety of free and adaptable tools and provides the data storage and computing power to run the tools. These tools support coordinated analytic methods and consistent interpretation of results across laboratories. Users can create and share tools for their specific needs and use sequence data generated locally and elsewhere. Results In its first full year (2018), GalaxyTrakr processed over 85,000 jobs and went from 25 to 250 users, representing 53 different public and state health laboratories, academic institutions, international health laboratories, and federal organizations. By mid-2020, it has grown to 600 registered users and processed over 450,000 analytical jobs. To illustrate how laboratories are making use of this resource, we describe how six institutions use GalaxyTrakr to quickly analyze and review their data. Instructions for participating in GalaxyTrakr are provided. Conclusions GalaxyTrakr advances food safety by providing reliable and harmonized WGS analyses for public health laboratories and promoting collaboration across laboratories with differing resources. Anticipated enhancements to this resource will include workflows for additional foodborne pathogens, viruses, and parasites, as well as new tools and services.

Invasive foodborne infection causes gastroenteritis, septicemia, meningitis, and chorioamnionitis, and is associated with high case-fatality rates in the elderly. It is unclear how aging alters gut microbiota, increases risk of listeriosis, and causes dysbiosis post-infection. We used a geriatric murine model of listeriosis as human surrogate of listeriosis for aging individuals to study the effect of aging and infection. Aging and listeriosis-induced perturbation of gut microbiota and disease severity were compared between young-adult and old mice. Young-adult and old mice were dosed intragastrically with . Fecal pellets were collected pre- and post-infection for microbiome analysis. Infected old mice had higher colonization in liver, spleen, and feces. Metagenomics analyses of fecal DNA-sequences showed increase in α-diversity as mice aged, and infection reduced its diversity. The relative abundance of major bacterial phylum like, and remained stable over aging or infection, while the phylum was significantly reduced only in infected old mice. Old mice showed a marked reduction in and bacteria even before infection when compared to uninfected young-adult mice.  infection increased the abundance of and in young-adult mice, while members of the and family were significantly increased in old mice. The abundance of the genera and were significantly reduced post-infection in young-adult and in old mice as compared to their uninfected counterparts. Butyrate producing, immune-modulating bacterial species, like and were significantly increased only in old infected mice, correlating with increased intestinal inflammatory mRNA up-regulation from old mice tissue. Histologic analyses of gastric tissues showed extensive lesions in the -infected old mice, more so in the non-glandular region and fundus than in the pylorus. Commensal species like , , and were only abundant in infected young-adult mice but their abundance diminished in the infected old mice. Listeriosis in old mice enhances the abundance of butyrate-producing inflammatory members of the / bacteria while reducing/eliminating beneficial commensals in the gut. Results of this study indicate that, aging may affect the composition of gut microbiota and increase the risk of invasive infection.

More than 470 serotypes of Shiga toxin-producing Escherichia coli (STEC) have been identified, but not all cause severe illness in humans. Most STEC that cause severe diseases can adhere to epithelial cells, produce specific stx subtypes, and belong to certain serotypes; therefore, these traits appear to be critical STEC risk factors. However, testing for these traits is labor intensive, and serotyping is inadequate because of extensive variations among E. coli O and H antigen types. In the present study, the E. coli identification microarray, which tests for over 40,000 E. coli gene targets, was examined for its potential to quickly characterize STEC strains. Analysis of 47 E. coli isolates, including 31 STEC isolates, recovered from 39 foods revealed that the microarray effectively determined the presence or absence of adherence genes and identified the specific eae allele in 3 isolates. The array identified most of the stx subtypes carried by all the isolates but had some difficulties in discerning between stx , stx , and stx because of the genetic similarities of these subtypes. The array determined the O and H types of 68 and 96% of the isolates, respectively, and although most serotypes were unremarkable, a few known pathogenic serotypes were also found. These selected STEC traits provided a scientific basis for assessing the potential health risks of STEC strains and also showed the importance of H typing in determining health risks. However, the diversity of the STEC group, the complexity of virulence mechanisms, and the variation in pathotypes among strains continue to pose challenges to assessing the potential of STEC strains to cause severe illness.

Accurate genetic distance estimation from pathogen whole-genome sequence data is critical for public health surveillance, and with respect to food safety it provides crucial information within traceback and outbreak investigations. The computational demands required for contemporary bioinformatics pipelines to extract high resolution single nucleotide polymorphisms (SNPs) grow in parallel with the size of pathogen clusters, where single strains of common pathogens such as and can now contain hundreds or thousands of isolates. To facilitate rapid analysis of whole-genome sequencing (WGS) data for large clusters of foodborne bacterial pathogens, we introduce the CFSAN SNP Pipeline 2 (CSP2). CSP2 is a bioinformatics pipeline coded in Nextflow and Python that extracts SNPs directly from genome assemblies in seconds through rapid MUMmer whole-genome alignment and parallel processing. After genome alignment, most data processing steps mirror the quality control measures used in the CFSAN SNP Pipeline (CSP1), including density filtering and missing data handling. Analysis of simulated data finds that high quality assemblies from the strategic K-mer extension for scrupulous assemblies (SKESA) contain sufficient information for accurate, high resolution SNP distance estimation, while assemblies from the St. Petersburg genome assembler (SPAdes) contained more false positives. CSP2 SNP distances for 150 real-world clusters (50 each of , , and ) were highly correlated with those from CSP1 and the National Center for Biotechnology Information (NCBI) Pathogen Detection pipeline ( r >= 0.98; r = 0.99, r = 0.99). This evaluation of CSP2 demonstrates its comparability to accepted methods and validates its use within future traceback and outbreak investigations.

Escherichia coli O104:H4, a hybrid pathotype reported in a large 2011 foodborne outbreak in Germany, has not been detected in cattle feces. However, cattle harbor and shed in the feces other O104 serotypes, particularly O104:H7, which has been associated with sporadic cases of diarrhea in humans. The objective of our study was to assess the virulence potential of Shiga toxin-producing E. coli (STEC) O104:H7 isolated from feces of feedlot cattle using DNA microarray. Six strains of STEC O104:H7 isolated from cattle feces were analyzed using FDA-E. coli Identification (ECID) DNA microarray to determine their virulence profiles and compare them to the human strains (clinical) of O104:H7, STEC O104:H4 (German outbreak strain), and O104:H21 (milk-associated Montana outbreak strain). Scatter plots were generated from the array data to visualize the gene-level differences between bovine and human O104 strains, and Pearson correlation coefficients (r) were determined. Splits tree was generated to analyze relatedness between the strains. All O104:H7 strains, both bovine and human, similar to O104:H4 and O104:H21 outbreak strains were negative for intimin (eae). The bovine strains were positive for Shiga toxin 1 subtype c (stx1c), enterohemolysin (ehxA), tellurite resistance gene (terD), IrgA homolog protein (iha), type 1 fimbriae (fimH), and negative for genes that code for effector proteins of type III secretory system. The six cattle O104 strains were closely related (r = 0.86-0.98) to each other, except for a few differences in phage related and non-annotated genes. One of the human clinical O104:H7 strains (2011C-3665) was more closely related to the bovine O104:H7 strains (r = 0.81-0.85) than the other four human clinical O104:H7 strains (r = 0.75-0.79). Montana outbreak strain (O104:H21) was more closely related to four of the human clinical O104:H7 strains than the bovine O104:H7 strains. None of the bovine E. coli O104 strains carried genes characteristic of E. coli O104:H4 German outbreak strain and unlike other human strains were also negative for Shiga toxin 2. Because cattle E. coli O104:H7 strains possess stx1c and genes that code for enterohemolysin and a variety of adhesins, the serotype has the potential to be a diarrheagenic foodborne pathogen in humans.

Bacteria belonging to the genus Cronobacter have been recognized as causative agents of life-threatening systemic infections primarily in premature, low-birth weight and immune-compromised neonates. Apparently not all Cronobacter species are linked to infantile infections and it has been proposed that virulence varies among strains. Whole genome comparisons and in silico analysis have proven to be powerful tools in elucidating potential virulence determinants, the presence/absence of which may explain the differential virulence behaviour of strains. However, validation of these factors has in the past been hampered by the availability of a suitable neonatal animal model. In the present study we have used zebrafish embryos to model Cronobacter infections in vivo using wild type and genetically engineered strains. Our experiments confirmed the role of the RepF1B-like plasmids as \"virulence plasmids\" in Cronobacter and underpinned the importantce of two putative virulence factors-cpa and zpx-in in vivo pathogenesis. We propose that by using this model in vivo infection studies are now possible on a large scale level which will boost the understanding on the virulence strategies employed by these pathogens.

Cronobacter species are considered an opportunistic group of foodborne pathogenic bacteria capable of causing both intestinal and systemic human disease. This review describes common virulence themes shared among the seven Cronobacter species and describes multiple exoproteins secreted by Cronobacter, many of which are bacterial toxins that may play a role in human disease. The review will particularly concentrate on the virulence factors secreted by C. sakazakii, C. malonaticus, and C. turicensis, which are the primary human pathogens of interest. It has been discovered that various species-specific virulence factors adversely affect a wide range of eukaryotic cell processes including protein synthesis, cell division, and ion secretion. Many of these factors are toxins which have been shown to also modulate the host immune response. These factors are encoded on a variety of mobile genetic elements such as plasmids and transposons; this genomic plasticity implies ongoing re-assortment of virulence factor genes which has complicated our efforts to categorize Cronobacter into sharply defined genomic pathotypes.

Bacillus cereus, a ubiquitous environmental microorganism known to cause foodborne illness, was isolated from samples taken from imported baby wipes from two different countries. These strains were characterized using a comprehensive molecular approach involving endpoint PCR, whole genome sequencing (WGS), comparative genomics, and biochemical analyses. A multiplex endpoint PCR assay was used to identify the enterotoxins: hemolysin BL, nonhemolytic enterotoxin, cytotoxin K, and enterotoxin FM toxin genes. Phylogenetically, the strains clustered into two major groups according to sequence type (ST) and singleton. We used the Center for Food Safety and Applied Nutrition (CFSAN) GalaxyTrakr BTyper computational tool to characterize the strains further. As an additional means of characterization, we investigated the possible role of carbohydrate transport systems and their role in nutrient uptake by performing a BLAST analysis of the 40 B. cereus genomes recovered from baby wipes. This study outlines a multifaceted workflow that uses the analysis of enterotoxigenic potential, bioinformatics, genomic diversity, genotype, phenotype, and carbohydrate utilization as a comprehensive strategy to characterize these B. cereus strains isolated from baby wipes and further our understanding of the phylogenetic relatedness of strains associated with baby wipe production facilities that could potentially pose an infection risk to a vulnerable infant population.

Cronobacter sakazakii is a Gram-negative opportunistic pathogen that causes life- threatening infantile infections, such as meningitis, septicemia, and necrotizing enterocolitis, as well as pneumonia, septicemia, and urinary tract and wound infections in adults. Here, we report 26 draft genome sequences of C. sakazakii, which were obtained from dried spices from the USA, the Middle East, China, and the Republic of Korea. The average genome size of the C. sakazakii genomes was 4393 kb, with an average of 4055 protein coding genes, and an average genome G + C content of 56.9%. The genomes contained genes related to carbohydrate transport and metabolism, amino acid transport and metabolism, and cell wall/membrane biogenesis. In addition, we identified genes encoding proteins involved in osmotic responses such as DnaJ, Aquaproin Z, ProQ, and TreF, as well as virulence-related and heat shock-related proteins. Interestingly, a metabolic island comprised of a variably-sized xylose utilization operon was found within the spice-associated C. sakazakii genomes, which supports the hypothesis that plants may serve as transmission vectors or alternative hosts for Cronobacter species. The presence of the genes identified in this study can support the remarkable phenotypic traits of C. sakazakii such as the organism’s capabilities of adaptation and survival in response to adverse growth environmental conditions (e.g. osmotic and desiccative stresses). Accordingly, the genome analyses provided insights into many aspects of physiology and evolutionary history of this important foodborne pathogen.

Cronobacter sakazakii continues to be isolated from ready-to-eat fresh and frozen produce, flours, dairy powders, cereals, nuts, and spices, in addition to the conventional sources of powdered infant formulae (PIF) and PIF production environments. To understand the sequence diversity, phylogenetic relationship, and virulence of C. sakazakii originating from plant-origin foods, comparative molecular and genomic analyses, and zebrafish infection (ZI) studies were applied to 88 strains. Whole genome sequences of the strains were generated for detailed bioinformatic analysis. PCR analysis showed that all strains possessed a pESA3-like virulence plasmid similar to reference C. sakazakii clinical strain BAA-894. Core genome analysis confirmed a shared genomic backbone with other C. sakazakii strains from food, clinical and environmental strains. Emerging nucleotide diversity in these plant-origin strains was highlighted using single nucleotide polymorphic alleles in 2000 core genes. DNA hybridization analyses using a pan-genomic microarray showed that these strains clustered according to sequence types (STs) identified by multi-locus sequence typing (MLST). PHASTER analysis identified 185 intact prophage gene clusters encompassing 22 different prophages, including three intact Cronobacter prophages: ENT47670, ENT39118, and phiES15. AMRFinderPlus analysis identified the CSA family class C β-lactamase gene in all strains and a plasmid-borne mcr-9.1 gene was identified in three strains. ZI studies showed that some plant-origin C. sakazakii display virulence comparable to clinical strains. Finding virulent plant-origin C. sakazakii possessing significant genomic features of clinically relevant STs suggests that these foods can serve as potential transmission vehicles and supports widening the scope of continued surveillance for this important foodborne pathogen.