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This multiagency report developed by the Interagency Collaboration for Genomics for Food and Feed Safety provides an overview of the use of and transition to whole genome sequencing (WGS) technology for detection and characterization of pathogens transmitted commonly by food and for identification of their sources. We describe foodborne pathogen analysis, investigation, and harmonization efforts among the following federal agencies: National Institutes of Health; Department of Health and Human Services, Centers for Disease Control and Prevention (CDC) and U.S. Food and Drug Administration (FDA); and the U.S. Department of Agriculture, Food Safety and Inspection Service, Agricultural Research Service, and Animal and Plant Health Inspection Service. We describe single nucleotide polymorphism, core-genome, and whole genome multilocus sequence typing data analysis methods as used in the PulseNet (CDC) and GenomeTrakr (FDA) networks, underscoring the complementary nature of the results for linking genetically related foodborne pathogens during outbreak investigations while allowing flexibility to meet the specific needs of Interagency Collaboration partners. We highlight how we apply WGS to pathogen characterization (virulence and antimicrobial resistance profiles) and source attribution efforts and increase transparency by making the sequences and other data publicly available through the National Center for Biotechnology Information. We also highlight the impact of current trends in the use of culture-independent diagnostic tests for human diagnostic testing on analytical approaches related to food safety and what is next for the use of WGS in the area of food safety.

In August 2016, the Wisconsin Department of Health Services notified the U.S. Centers for Disease Control and Prevention of multidrug-resistant (MDR) Salmonella enterica serovar Heidelberg infections in people who reported contact with dairy calves. Federal and state partners investigated this to identify the source and scope of the outbreak and to prevent further illnesses. Cases were defined as human Salmonella Heidelberg infection caused by a strain that had one of seven pulsed-field gel electrophoresis (PFGE) patterns or was related by whole genome sequencing (WGS), with illness onset from January 1, 2015, through July 2, 2018. Patient exposure and calf purchase information was collected and analyzed; calves were traced back from the point of purchase. Isolates obtained from animal and environmental samples collected on-farm were supplied by veterinary diagnostic laboratories and compared with patient isolates using PFGE and WGS. Antimicrobial susceptibility testing by standardized broth microdilution was performed. Sixty-eight patients from 17 states were identified. Forty (63%) of 64 patients noted cattle contact before illness. Thirteen (33%) of 40 patients with exposure to calves reported that calves were sick or had died. Seven individuals purchased calves from a single Wisconsin livestock market. One hundred forty cattle from 14 states were infected with the outbreak strain. WGS indicated that human, cattle, and environmental isolates from the livestock market were genetically closely related. Most isolates (88%) had resistance or reduced susceptibility to antibiotics of ≥5 antibiotic classes. This resistance profile included first-line antibiotic treatments for patients with severe salmonellosis, including ampicillin, ceftriaxone, and ciprofloxacin. In this outbreak, MDR Salmonella Heidelberg likely spread from sick calves to humans, emphasizing the importance of illness surveillance in animal populations to prevent future spillover of this zoonotic disease.

Objectives. To investigate a shigellosis outbreak in Genesee County, Michigan (including the City of Flint), and Saginaw County, Michigan, in 2016 and address community concerns about the role of the Flint water system. Methods. We met frequently with community members to understand concerns and develop the investigation. We surveyed households affected by the outbreak, analyzed Shigella isolate data, examined the geospatial distribution of cases, and reviewed available water quality data. Results. We surveyed 83 households containing 158 cases; median age was 10 years. Index case-patients from 55 of 83 households (66%) reported contact with a person outside their household who wore diapers or who had diarrhea in the week before becoming ill; results were similar regardless of household drinking water source. Genomic diversity was not consistent with a point source. In Flint, no space-time clustering was identified, and average free chlorine residual values remained above recommended levels throughout the outbreak period. Conclusions. The outbreak was most likely caused by person-to-person contact and not by the Flint water system. Consistent community engagement was essential to the design and implementation of the investigation.

In this study, our objective was to evaluate the genetic stability of foodborne bacterial pathogens during serial passage

The routine use of whole-genome sequencing (WGS) as part of enteric disease surveillance is substantially enhancing our ability to detect and investigate outbreaks and to monitor disease trends. At the same time, it is revealing as never before the vast complexity of microbial and human interactions that contribute to outbreak ecology. Since WGS analysis is primarily used to characterize and compare microbial genomes with the goal of addressing epidemiological questions, it must be interpreted in an epidemiological context. In this article, we identify common challenges and pitfalls encountered when interpreting sequence data in an enteric disease surveillance and investigation context, and explain how to address them.

Four enzymatic DNA library preparation kits were compared for sequencing Shiga toxin-producing E. coli. All kits produced high quality sequence data which performed equally well in the downstream analyses for surveillance and outbreak detection. Important differences were noted in the workflow user-friendliness and per sample cost.

Background Whole genome sequencing (WGS) has gained increasing importance in responses to enteric bacterial outbreaks. Common analysis procedures for WGS, single nucleotide polymorphisms (SNPs) and genome assembly, are highly dependent upon WGS data quality. Methods Raw, unprocessed WGS reads from Escherichia coli, Salmonella enterica, and Shigella sonnei outbreak clusters were characterized for four quality metrics: PHRED score, read length, library insert size, and ambiguous nucleotide composition. PHRED scores were strongly correlated with improved SNPs analysis results in E. coli and S. enterica clusters. Results Assembly quality showed only moderate correlations with PHRED scores and library insert size, and then only for Salmonella. To improve SNP analyses and assemblies, we compared seven read-healing pipelines to improve these four quality metrics and to see how well they improved SNP analysis and genome assembly. The most effective read healing pipelines for SNPs analysis incorporated quality-based trimming, fixed-width trimming, or both. The Lyve-SET SNPs pipeline showed a more marked improvement than the CFSAN SNP Pipeline, but the latter performed better on raw, unhealed reads. For genome assembly, SPAdes enabled significant improvements in healed E. coli reads only, while Skesa yielded no significant improvements on healed reads. Conclusions PHRED scores will continue to be a crucial quality metric albeit not of equal impact across all types of analyses for all enteric bacteria. While trimming-based read healing performed well for SNPs analyses, different read healing approaches are likely needed for genome assembly or other, emerging WGS analysis methodologies.

The US PulseNet and GenomeTrakr laboratory networks work together within the Genomics for Food Safety (Gen-FS) consortium to collect and analyze genomic data for foodborne pathogen surveillance (species include Salmonella enterica, Listeria monocytogenes, Escherichia coli (STECs), and Campylobactor). In 2017 these two laboratory networks started harmonizing their respective proficiency test exercises, agreeing on distributing a single strain-set and following the same standard operating procedure (SOP) for genomic data collection, running a jointly coordinated annual proficiency test exercise. In this data release we are publishing the reference genomes and raw data submissions for the 2017 and 2018 proficiency test exercises., Measurement(s) DNA • genome • sequence_assembly Technology Type(s) DNA sequencing • sequence assembly process Factor Type(s) species of foodborne pathogen Sample Characteristic - Organism Salmonella enterica • Escherichia coli • Listeria monocytogenes Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.13135046

Background With the efficiency and the decreasing cost of next-generation sequencing, the technology is being rapidly introduced into clinical and public health laboratory practice. Aims The historical background and principles of first-, second- and third-generation sequencing are described, as are the characteristics of the most commonly used sequencing instruments. Sources Peer-reviewed literature, white papers and meeting reports. Content and implications Next-generation sequencing is a technology that could potentially replace many traditional microbiological workflows, providing clinicians and public health specialists with more actionable information than hitherto achievable. Examples of the clinical and public health uses of the technology are provided. The challenge of comparability of different sequencing platforms is discussed. Finally, the future directions of the technology integrating it with laboratory management and public health surveillance systems, and moving it towards performing sequencing directly from the clinical specimen (metagenomics), could lead to yet another fundamental transformation of clinical diagnostics and public health surveillance.

In 2016, a multijurisdictional team investigated an outbreak of Shiga toxin-producing Escherichia coli (STEC) serogroup O121 and O26 infections linked to contaminated flour from a large domestic producer.A case was defined as infection with an outbreak strain in which illness onset was between December 21, 2015, and September 5, 2016. To identify exposures associated with the outbreak, outbreak cases were compared with non-STEC enteric illness cases, matched according to age group, sex, and state of residence. Products suspected to be related to the outbreak were collected for STEC testing, and a common point of contamination was sought. Whole-genome sequencing was performed on isolates from clinical and food samples.A total of 56 cases were identified in 24 states. Univariable exact conditional logistic-regression models of 22 matched sets showed that infection was significantly associated with the use of one brand of flour (odds ratio, 21.04; 95% confidence interval [CI], 4.69 to 94.37) and with tasting unbaked homemade dough or batter (odds ratio, 36.02; 95% CI, 4.63 to 280.17). Laboratory testing isolated the outbreak strains from flour samples, and whole-genome sequencing revealed that the isolates from clinical and food samples were closely related to one another genetically. Trace-back investigation identified a common flour-production facility.This investigation implicated raw flour as the source of an outbreak of STEC infections. Although it is a low-moisture food, raw flour can be a vehicle for foodborne pathogens.

High consumption rates and a multitude of brands make multistate foodborne outbreaks of Salmonella infections associated with chicken challenging to investigate, but whole genome sequencing is a powerful tool that can be used to assist investigators. Whole genome sequencing of pathogens isolated from clinical, environmental, and food samples is increasingly being used in multistate foodborne outbreak investigations to determine with unprecedented resolution how closely related these isolates are to one another genetically. In 2014, federal and state health officials investigated an outbreak of 146 Salmonella Heidelberg infections in 24 states. A follow-up analysis was conducted after the conclusion of the investigation in which 27 clinical and 24 food isolates from the outbreak underwent whole genome sequencing. These isolates formed seven clades, the largest of which contained clinical isolates from a subcluster of case patients who attended a catered party. One isolate from a chicken processed by a large producer was closely related genetically (zero to three single-nucleotide polymorphism differences) to the clinical isolates from these subcluster case patients. Chicken from this large producer was also present in the kitchen of the caterer on the day before the event, thus providing additional evidence that the chicken from this producer was the outbreak source. This investigation highlights how whole genome sequencing can be used with epidemiologic and traceback evidence to identify chicken sources of foodborne outbreaks.

PulseNet, the National Molecular Subtyping Network for Foodborne Disease Surveillance, was established in 1996 through a collaboration with the Centers for Disease Control and Prevention; the US Department of Agriculture, Food Safety and Inspection Service; the US Food and Drug Administration; 4 state public health laboratories; and the Association of Public Health Laboratories. The network has since expanded to include 83 state, local, and food regulatory public health laboratories. In 2016, PulseNet was estimated to be helping prevent an estimated 270 000 foodborne illnesses annually. PulseNet is undergoing a transformation toward whole-genome sequencing (WGS), which provides better discriminatory power and precision than pulsed-field gel electrophoresis (PFGE). WGS improves the detection of outbreak clusters and could replace many traditional reference identification and characterization methods. This article highlights the contributions made by public health laboratories in transforming PulseNet’s surveillance and describes how the transformation is changing local and national surveillance practices. Our data show that WGS is better at identifying clusters than PFGE, especially for clonal organisms such as Salmonella Enteritidis. The need to develop prioritization schemes for cluster follow-up and additional resources for both public health laboratory and epidemiology departments will be critical as PulseNet implements WGS for foodborne disease surveillance in the United States.

Foodborne disease surveillance in the United States is at a critical point. Clinical and diagnostic laboratories are using culture-independent diagnostic tests (CIDTs) to identify the pathogen causing foodborne illness from patient specimens. CIDTs are molecular tests that allow doctors to rapidly identify the bacteria causing illness within hours. CIDTs, unlike previous gold standard methods such as bacterial culture, do not produce an isolate that can be subtyped as part of the national molecular subtyping network for foodborne disease surveillance, PulseNet. Without subtype information, cases can no longer be linked using molecular data to identify potentially related cases that are part of an outbreak. In this review, we discuss the public health needs for a molecular subtyping approach directly from patient specimen and highlight different approaches, including amplicon and shotgun metagenomic sequencing.

Molecular subtyping can be used to study the population structure of a particular bacterial species, to determine the possible evolution of the subject microorganism, or to study the molecular epidemiology of a microbe. The types of methods used for subtyping and the approaches to data analysis and interpretation may vary greatly with the reason for specific subtyping. This chapter focuses almost entirely on subtyping for molecular epidemiology. Molecular epidemiology can be applied to identifying the source of a particular outbreak or to a broader understanding of the role of certain foods or processes in outbreak-related or sporadic infections. Perhaps the most easily appreciated reason for molecular subtyping is to facilitate the identification and investigation of foodborne disease outbreaks. Although the focus of this chapter is on molecular methods, it is important to consider them in the context of earlier phenotypic methods such as serotyping, phage typing, biotyping, and antimicrobial susceptibility typing. Most of these phenotypic methods have long and successful histories of use in subtyping for the same purposes for which molecular methods are now used. Although molecular methods typically provide greater strain discrimination than phenotypic methods, this is not always the case, and it is only one reason why molecular methods are generally preferred. In recent years, the main focus of subtyping method development has been on DNA sequence-based methods. Sequence-based approaches to subtyping of bacteria, such as multiple-locus variable-number tandem repeat (VNTR) analysis (MLVA), are already being widely implemented in the surveillance of foodborne infections.

Non-O157 Shiga toxin-producing Escherichia coli (STEC) are foodborne pathogens of growing concern worldwide that have been associated with several recent multistate and multinational outbreaks of foodborne illness. Rapid and sensitive molecular-based bacterial strain discrimination methods are critical for timely outbreak identification and contaminated food source traceback. One such method, multiple-locus variable-number tandem repeat analysis (MLVA), is being used with increasing frequency in foodborne illness outbreak investigations to augment the current gold standard bacterial subtyping technique, pulsed-field gel electrophoresis (PFGE). The objective of this study was to develop a MLVA assay for intra- and inter-serogroup discrimination of six major non-O157 STEC serogroups-O26, O111, O103, O121, O45, and O145-and perform a preliminary internal validation of the method on a limited number of clinical isolates. The resultant MLVA scheme consists of ten variable number tandem repeat (VNTR) loci amplified in three multiplex PCR reactions. Sixty-five unique MLVA types were obtained among 84 clinical non-O157 STEC strains comprised of geographically diverse sporadic and outbreak related isolates. Compared to PFGE, the developed MLVA scheme allowed similar discrimination among serogroups O26, O111, O103, and O121 but not among O145 and O45. To more fully compare the discriminatory power of this preliminary MLVA method to PFGE and to determine its epidemiological congruence, a thorough internal and external validation needs to be performed on a carefully selected large panel of strains, including multiple isolates from single outbreaks.

Typhoid fever is an illness caused bySalmonella entericaserotype Typhi. In developing regions, it affects an estimated 20 million people annually, causing 200 000 deaths. Although uncommon, cases occur in the USA each year, predominantly due to international travel. During February 2015, the Oklahoma State Department of Health (OSDH) detected an outbreak of typhoid fever among residents of northwestern Oklahoma. OSDH conducted case-patient interviews to identify the source and symptomatic contacts. Whole genome sequencing (WGS) was performed to characterise the genetic relatedness of isolates among the four outbreak-associated pulsed-field gel electrophoresis (PFGE) patterns. We identified 38 cases, 25 confirmed and 13 probable, in two states. WGS revealed a 0–10 single-nucleotide polymorphism variation between isolates. Although we were unable to determine the source, almost all case-patients were members of the Marshallese community that attended a common event in Oklahoma, or were contacts to a confirmed case. This is the largest outbreak of typhoid fever in the USA since 1989, and first to apply WGS to complement interpretation of PFGE results during a typhoid fever outbreak investigation. This investigation illustrates the potential risk of outbreaks among communities comprised of international populations from regions where typhoid fever remains endemic.

Drug-resistant Shigella sonnei poses a clinical and public health challenge. We report here the high-quality draft whole-genome sequences of four outbreak-associated S. sonnei isolates; three were resistant to two or more antibiotics, and one was resistant to streptomycin only.

Background As next generation sequence technology has advanced, there have been parallel advances in genome-scale analysis programs for determining evolutionary relationships as proxies for epidemiological relationship in public health. Most new programs skip traditional steps of ortholog determination and multi-gene alignment, instead identifying variants across a set of genomes, then summarizing results in a matrix of single-nucleotide polymorphisms or alleles for standard phylogenetic analysis. However, public health authorities need to document the performance of these methods with appropriate and comprehensive datasets so they can be validated for specific purposes, e.g., outbreak surveillance. Here we propose a set of benchmark datasets to be used for comparison and validation of phylogenomic pipelines. Methods We identified four well-documented foodborne pathogen events in which the epidemiology was concordant with routine phylogenomic analyses (reference-based SNP and wgMLST approaches). These are ideal benchmark datasets, as the trees, WGS data, and epidemiological data for each are all in agreement. We have placed these sequence data, sample metadata, and “known” phylogenetic trees in publicly-accessible databases and developed a standard descriptive spreadsheet format describing each dataset. To facilitate easy downloading of these benchmarks, we developed an automated script that uses the standard descriptive spreadsheet format. Results Our “outbreak” benchmark datasets represent the four major foodborne bacterial pathogens (Listeria monocytogenes, Salmonella enterica, Escherichia coli, and Campylobacter jejuni) and one simulated dataset where the “known tree” can be accurately called the “true tree”. The downloading script and associated table files are available on GitHub: https://github.com/WGS-standards-and-analysis/datasets. Discussion These five benchmark datasets will help standardize comparison of current and future phylogenomic pipelines, and facilitate important cross-institutional collaborations. Our work is part of a global effort to provide collaborative infrastructure for sequence data and analytic tools—we welcome additional benchmark datasets in our recommended format, and, if relevant, we will add these on our GitHub site. Together, these datasets, dataset format, and the underlying GitHub infrastructure present a recommended path for worldwide standardization of phylogenomic pipelines.

FWD-NEXT Expert Panel - Portugal/INSA - Vítor Borges (Instituto Nacional de Saúde Doutor Ricardo Jorge, Lisbon, Portugal) PulseNet International is a global network dedicated to laboratory-based surveillance for food-borne diseases. The network comprises the national and regional laboratory networks of Africa, Asia Pacific, Canada, Europe, Latin America and the Caribbean, the Middle East, and the United States. The PulseNet International vision is the standardised use of whole genome sequencing (WGS) to identify and subtype food-borne bacterial pathogens worldwide, replacing traditional methods to strengthen preparedness and response, reduce global social and economic disease burden, and save lives. To meet the needs of real-time surveillance, the PulseNet International network will standardise subtyping via WGS using whole genome multilocus sequence typing (wgMLST), which delivers sufficiently high resolution and epidemiological concordance, plus unambiguous nomenclature for the purposes of surveillance. Standardised protocols, validation studies, quality control programmes, database and nomenclature development, and training should support the implementation and decentralisation of WGS. Ideally, WGS data collected for surveillance purposes should be publicly available, in real time where possible, respecting data protection policies. WGS data are suitable for surveillance and outbreak purposes and for answering scientific questions pertaining to source attribution, antimicrobial resistance, transmission patterns, and virulence, which will further enable the protection and improvement of public health with respect to food-borne disease. info:eu-repo/semantics/publishedVersion

Zoonotic transmission of Salmonella infections causes an estimated 11% of salmonellosis annually in the United States. This report describes the epidemiologic, traceback and laboratory investigations conducted in the United States as part of four multistate outbreaks of Salmonella infections linked to small turtles. Salmonella isolates indistinguishable from the outbreak strains were isolated from a total of 143 ill people in the United States, pet turtles, and pond water samples collected from turtle farm A, as well as ill people from Chile and Luxembourg. Almost half (45%) of infections occurred in children aged

Multilocus variable-number tandem repeat analysis (MLVA) is a rapid and reproducible typing method that is an important tool for investigation, as well as detection, of national and multinational outbreaks of a range of food-borne pathogens. Salmonella enterica serovar Enteritidis is the most common Salmonella serovar associated with human salmonellosis in the European Union/European Economic Area and North America. Fourteen laboratories from 13 countries in Europe and North America participated in a validation study for MLVA of S. Enteritidis targeting five loci. Following normalisation of fragment sizes using a set of reference strains, a blinded set of 24 strains with known allele sizes was analysed by each participant. The S. Enteritidis 5-loci MLVA protocol was shown to produce internationally comparable results as more than 90% of the participants reported less than 5% discrepant MLVA profiles. All 14 participating laboratories performed well, even those where experience with this typing method was limited. The raw fragment length data were consistent throughout, and the inter-laboratory validation helped to standardise the conversion of raw data to repeat numbers with at least two countries updating their internal procedures. However, differences in assigned MLVA profiles remain between well-established protocols and should be taken into account when exchanging data.

Major lineages emerged during the 17th–18th centuries and diversified during the 1920s and 1950s., Salmonella enterica serotype Enteritidis is one of the most commonly reported causes of human salmonellosis. Its low genetic diversity, measured by fingerprinting methods, has made subtyping a challenge. We used whole-genome sequencing to characterize 125 S. enterica Enteritidis and 3 S. enterica serotype Nitra strains. Single-nucleotide polymorphisms were filtered to identify 4,887 reliable loci that distinguished all isolates from each other. Our whole-genome single-nucleotide polymorphism typing approach was robust for S. enterica Enteritidis subtyping with combined data for different strains from 2 different sequencing platforms. Five major genetic lineages were recognized, which revealed possible patterns of geographic and epidemiologic distribution. Analyses on the population dynamics and evolutionary history estimated that major lineages emerged during the 17th–18th centuries and diversified during the 1920s and 1950s.

Salmonella enterica subsp. enterica serovar Newport ( S . Newport) is the third most prevalent cause of food-borne salmonellosis. Rapid, efficient, and accurate methods for identification are required to track specific strains of S . Newport during outbreaks. By exploiting the hypervariable nature of virulence genes and clustered regularly interspaced short palindromic repeats (CRISPRs), we previously developed a sequence-based subtyping approach, designated CRISPR–multi-virulence-locus sequence typing (CRISPR-MVLST). To demonstrate the applicability of this approach, we analyzed a broad set of S . Newport isolates collected over a 5-year period by using CRISPR-MVLST and pulsed-field gel electrophoresis (PFGE). Among 84 isolates, we defined 38 S . Newport sequence types (NSTs), all of which were novel compared to our previous analyses, and 62 different PFGE patterns. Our data suggest that both subtyping approaches have high discriminatory abilities (>0.95) with a potential for clustering cases with common exposures. Importantly, we found that isolates from closely related NSTs were often similar by PFGE profile as well, further corroborating the applicability of CRISPR-MVLST. In the first full application of CRISPR-MVLST, we analyzed isolates from a recent S . Newport outbreak. In this blinded study, we confirmed the utility of CRISPR-MVLST and were able to distinguish the 10 outbreak isolates, as defined by PFGE and epidemiological data, from a collection of 20 S . Newport isolates. Together, our data show that CRISPR-MVLST could be a complementary approach to PFGE subtyping for S . Newport.

Whole genome sequencing shows promise to transform public health microbiology of foodborne pathogens. The technology could replace almost all traditional workflows in a typical public health laboratory with a single cost-efficient whole genome sequencing workflow that includes all organisms. This workflow would include identification and reference characterization, e.g., serotyping, virulence characterization and antimicrobial resistance determination, and high discriminatory subtyping for outbreak detection and investigation. A multi-locus sequence typing (MLST) based analytical approach is the optimal primary subtyping tool for public health because it may be performed by laboratory personnel with little understanding of bioinformatics, be tiered at different level of discrimination for different public health purposes, and all subtypes are stable and may therefore be named definitively. Stable nomenclature is critical for efficient communication between public health partners to follow trends and for outbreak investigations. Unlike MLST, single nucleotide polymorphism based approaches rarely lead to stable nomenclature and should therefore be reserved for situations where MLST does not provide unequivocal answers.

Pathogen genomic data is increasingly important in investigations of infectious disease outbreaks. The objective of this study is to develop methods for using large-scale genomic data to determine the type of the environment an outbreak pathogen came from. Specifically, this study focuses on assessing whether an outbreak strain came from a natural environment or experienced substantial laboratory culturing. The approach uses phylogenetic analyses and machine learning to identify DNA changes that are characteristic of laboratory culturing. The analysis methods include parallelized sequence read alignment, variant identification, phylogenetic tree construction, ancestral state reconstruction, semi-supervised classification, and random forests. These methods were applied to 902 Salmonella enterica serovar Typhimurium genomes from the NCBI Sequence Read Archive database. The analyses identified candidate signatures of laboratory culturing that are highly consistent with genes identified in published laboratory passage studies. In particular, the analysis identified mutations in rpoS, hfq, rfb genes, acrB, and rbsR as strong signatures of laboratory culturing. In leave-one-out cross-validation, the classifier had an area under the receiver operating characteristic (ROC) curve of 0.89 for strains from two laboratory reference sets collected in the 1940’s and 1980’s. The classifier was also used to assess laboratory culturing in foodborne and laboratory acquired outbreak strains closely related to laboratory reference strain serovar Typhimurium 14028. The classifier detected some evidence of laboratory culturing on the phylogeny branch leading to this clade, suggesting all of these strains may have a common ancestor that experienced laboratory culturing. Together, these results suggest that phylogenetic analysis and machine learning could be used to assess whether pathogens collected from patients are naturally occurring or have been extensively cultured in laboratories. The data analysis methods can be applied to any bacterial pathogen species, and could be adapted to assess viral pathogens and other types of source environments.

Shiga toxin-producing Escherichia coli (STEC) is a foodborne pathogen. We report here the high-quality draft whole-genome sequences of five STEC strains isolated from clinical cases in the United States. This report is for STEC of serotypes O55:H7, O79:H7, O91:H14, O153:H2, and O156:H25.

Listeria monocytogenes (Lm) causes severe foodborne illness (listeriosis). Previous molecular subtyping methods, such as pulsed-field gel electrophoresis (PFGE), were critical in detecting outbreaks that led to food safety improvements and declining incidence, but PFGE provides limited genetic resolution. A multiagency collaboration began performing real-time, whole-genome sequencing (WGS) on all US Lm isolates from patients, food, and the environment in September 2013, posting sequencing data into a public repository. Compared with the year before the project began, WGS, combined with epidemiologic and product trace-back data, detected more listeriosis clusters and solved more outbreaks (2 outbreaks in pre-WGS year, 5 in WGS year 1, and 9 in year 2). Whole-genome multilocus sequence typing and single nucleotide polymorphism analyses provided equivalent phylogenetic relationships relevant to investigations; results were most useful when interpreted in context of epidemiological data. WGS has transformed listeriosis outbreak surveillance and is being implemented for other foodborne pathogens.

Outbreaks of human salmonellosis associated with live poultry contact have been reported since 1955. Multiple Salmonella serotypes have been associated with these outbreaks, and specific outbreak strains have been repeatedly linked to single hatcheries over multiple years. During 2009, four multistate outbreaks of human Salmonella infections associated with direct and indirect exposure to live poultry purchased from mail-order hatcheries and agricultural feed stores were identified, resulting in 165 culture-confirmed cases in 30 states. This report describes the epidemiologic, environmental and laboratory investigations conducted by state and local health departments, state departments of agriculture, the U.S. Department of Agriculture (USDA), Animal and Plant Health Inspection Service (APHIS), National Poultry Improvement Plan (NPIP) and National Veterinary Services Laboratories (NVSL), and the Centers for Disease Control and Prevention (CDC). Case-patients were identified through PulseNet, the national molecular subtyping network for foodborne disease surveillance, and interviewed using the CDC standard live poultry contact questionnaire that asks about poultry-related exposures during the 7 days before illness onset. These outbreaks highlight the need to focus efforts on strategies to decrease and prevent human illness associated with live poultry contact through comprehensive interventions at the mail-order hatchery, agricultural feed store and consumer levels. Additional consumer education and interventions at mail-order hatcheries and venues where live poultry are sold, including agricultural feed stores, are necessary to prevent transmission of Salmonella from poultry to humans.

OBJECTIVE: Turtle-associated salmonellosis (TAS), especially in children, is a reemerging public health issue. In 1975, small pet turtles (shell length METHODS: We conducted epidemiologic, environmental, and traceback investigations. Cases were defined as infection with ≥1 of 10 molecular subtypes of Salmonella Sandiego, Pomona, Poona, Typhimurium, and I 4,[5],12:i:-. Water samples from turtle habitats linked to human illnesses were cultured for Salmonella. RESULTS: We identified 8 outbreaks totaling 473 cases from 41 states, Washington DC, and Puerto Rico with illness onsets during May 2011–September 2013. The median patient age was 4 years (range: 1 month–94 years); 45% percent were Hispanic; and 28% were hospitalized. In the week preceding illness, 68% (187 of 273) of case-patients reported turtle exposure; among these, 88% (124 of 141) described small turtles. Outbreak strains were isolated from turtle habitats linked to human illnesses in seven outbreaks. Traceback investigations identified 2 Louisiana turtle farms as the source of small turtles linked to 1 outbreak; 1 outbreak strain was isolated from turtle pond water from 1 turtle farm. CONCLUSIONS: Eight multistate outbreaks associated with small turtles were investigated during 2011–2013. Children

Introduction: Recently, Salmonella enterica serovar Poona caused a multistate outbreak, with 245 out of 907 cases occurring in California. We report a comparison of pulsed-field gel electrophoresis (PFGE) results with whole genome sequencing (WGS) for genotyping of Salmonella Poona isolates. Methods: CA Salmonella Poona isolates, collected from July to August 2015, were genotyped by PFGE using XbaI restriction enzyme. WGS was done using Nextera XT library kit with 2x300 bp or 2x250 bp sequencing chemistry on the Illumina MiSeq Sequencer. Reads were mapped to the de novo assembled serovar Poona draft genome (48 contigs, N50= 223,917) from the outbreak using CLCbio GW 8.0.2. The phylogenetic tree was generated based on hqSNPs calling. Genomes were annotated with CGE and PHAST online tools. In silico MLST was performed using the CGE online tool. Results: Human (14) and cucumber (2) Salmonella Poona isolates exhibited 3 possibly related PFGE patterns (JL6X01.0018 [predominant], JL6X01.0375, JL6X01.0778). All isolates that were related by PFGE also clustered together according to the WGS. One isolate with a divergent PFGE pattern (JL6X01.0776) served as an outlier in the phylogenetic analysis and substantially differed from the outbreak clade by WGS. All outbreak isolates were assigned to MLST sequence type 447. The majority of the outbreak-related isolates possessed the same set of Salmonella Pathogenicity Islands with few variations. One outbreak isolate was sequenced and analyzed independently by CDC and CDPH laboratories; there was 0 SNP difference in results. Additional two isolates were sequenced by CDC and the raw data was processed through CDPH and CDC analysis pipelines. Both data analysis pipelines also generated concordant results. Discussion: PFGE and WGS results for the recent CA Salmonella enterica serovar Poona outbreak provided concordant assignment of the isolates to the outbreak cluster. WGS allowed more robust determination of genetic relatedness, provided information regarding MLST-type, pathogenicity genes, and bacteriophage content. WGS data obtained independently at two laboratories showed complete agreement.

SUMMARYListeria monocytogenesis a foodborne pathogen that can cause bacteraemia, meningitis, and complications during pregnancy. In July 2012, molecular subtyping identified indistinguishableL. monocytogenesisolates from six patients and two samples of different cut and repackaged cheeses. A multistate outbreak investigation was initiated. Initial analyses identified an association between eating soft cheese and outbreak-related illness (odds ratio 17·3, 95% confidence interval 2·0–825·7) but no common brand. Cheese inventory data from locations where patients bought cheese and an additional location where repackaged cheese yielded the outbreak strain were compared to identify cheeses for microbiological sampling. Intact packages of imported ricotta salata yielded the outbreak strain. Fourteen jurisdictions reported 22 cases from March–October 2012, including four deaths and a fetal loss. Six patients ultimately reported eating ricotta salata; another reported eating cheese likely cut with equipment also used for contaminated ricotta salata, and nine more reported eating other cheeses that might also have been cross-contaminated. An FDA import alert and US and international recalls followed. Epidemiology-directed microbiological testing of suspect cheeses helped identify the outbreak source. Cross-contamination of cheese highlights the importance of using validated disinfectant protocols and routine cleaning and sanitizing after cutting each block or wheel.

In August 2014, PulseNet, the national molecular subtyping network for foodborne disease surveillance, detected a multistate cluster of Salmonella enterica serotype Newport infections with an indistinguishable pulse-field gel electrophoresis (PFGE) pattern (XbaI PFGE pattern JJPX01.0061). Outbreaks of illnesses associated with this PFGE pattern have previously been linked to consumption of tomatoes harvested from Virginia's Eastern Shore in the Delmarva region and have not been linked to cucumbers or other produce items. To identify the contaminated food and find the source of the contamination, CDC, state and local health and agriculture departments and laboratories, and the Food and Drug Administration (FDA) conducted epidemiologic, traceback, and laboratory investigations. A total of 275 patients in 29 states and the District of Columbia were identified, with illness onsets occurring during May 20-September 30, 2014. Whole genome sequencing (WGS), a highly discriminating subtyping method, was used to further characterize PFGE pattern JJPX01.0061 isolates. Epidemiologic, microbiologic, and product traceback evidence suggests that cucumbers were a source of Salmonella Newport infections in this outbreak. The epidemiologic link to a novel outbreak vehicle suggests an environmental reservoir for Salmonella in the Delmarva region that should be identified and mitigated to prevent future outbreaks.

A retrospective investigation was performed to evaluate whole-genome sequencing as a benchmark for comparing molecular subtyping methods for Salmonella enterica serotype Enteritidis and survey the population structure of commonly encountered S. enterica serotype Enteritidis outbreak isolates in the United States. A total of 52 S. enterica serotype Enteritidis isolates representing 16 major outbreaks and three sporadic cases collected between 2001 and 2012 were sequenced and subjected to subtyping by four different methods: (i) whole-genome single-nucleotide-polymorphism typing (WGST), (ii) multiple-locus variable-number tandem-repeat (VNTR) analysis (MLVA), (iii) clustered regularly interspaced short palindromic repeats combined with multi-virulence-locus sequence typing (CRISPR-MVLST), and (iv) pulsed-field gel electrophoresis (PFGE). WGST resolved all outbreak clusters and provided useful robust phylogenetic inference results with high epidemiological correlation. While both MLVA and CRISPR-MVLST yielded higher discriminatory power than PFGE, MLVA outperformed the other methods in delineating outbreak clusters whereas CRISPR-MVLST showed the potential to trace major lineages and ecological origins of S. enterica serotype Enteritidis. Our results suggested that whole-genome sequencing makes a viable platform for the evaluation and benchmarking of molecular subtyping methods.

Shiga toxin-producing Escherichia coli (STEC) are a common cause for food-borne diarrheal illness outbreaks and sporadic cases. Here, we report the availability of the draft genome sequences of 228 STEC strains representing 32 serotypes with known pulsed-field gel electrophoresis (PFGE) types and epidemiological relationships, as well as 12 strains representing other diarrheagenic E. coli pathotypes.

Shiga toxin-producing Escherichia coli (STEC) is an important food-borne pathogen. Here, we report the draft whole-genome sequences of nine STEC strains isolated from clinical cases in the United States. This is the first report of such information for STEC of serotypes O69, H11, O145:H25, O118:H16, O91:H21, O146:H21, O45:H2, O128:H2, and O121:H19.

SUMMARYWe investigated an outbreak of 396Salmonella entericaserotype I 4,5,12:i:- infections to determine the source. After 7 weeks of extensive hypothesis-generation interviews, no refined hypothesis was formed. Nevertheless, a case-control study was initiated. Subsequently, an iterative hypothesis-generation approach used by a single interviewing team identified brand A not-ready-to-eat frozen pot pies as a likely vehicle. The case-control study, modified to assess this new hypothesis, along with product testing indicated that the turkey variety of pot pies was responsible. Review of product labels identified inconsistent language regarding preparation, and the cooking instructions included undefined microwave wattage categories. Surveys found that most patients did not follow the product's cooking instructions and did not know their oven's wattage. The manufacturer voluntarily recalled pot pies and improved the product's cooking instructions. This investigation highlights the value of careful hypothesis-generation and the risks posed by frozen not-ready-to-eat microwavable foods.

Background Shiga toxin-producing Escherichia coli (STEC) O157:H7 is the causal agent for more than 96,000 cases of diarrheal illness and 3,200 infection-attributable hospitalizations annually in the United States. Materials and methods We defined a confirmed case as a compatible illness in a person with the outbreak strain during 10/07/2011-11/30/2011. Investigation included hypothesis generation, a case-control study utilizing geographically-matched controls, and a case series investigation. Environmental inspections and tracebacks were conducted. Results We identified 58 cases in 10 states; 67% were hospitalized and 6.4% developed hemolytic uremic syndrome. Any romaine consumption was significantly associated with illness (matched Odds Ratio (mOR) = 10.0, 95% Confidence Interval (CI) = 2.1-97.0). Grocery Store Chain A salad bar was significantly associated with illness (mOR = 18.9, 95% CI = 4.5-176.8). Two separate traceback investigations for romaine lettuce converged on Farm A. Case series results indicate that cases (64.9%) were more likely than the FoodNet population (47%) to eat romaine lettuce (p-value = 0.013); 61.3% of cases reported consuming romaine lettuce from the Grocery Store Chain A salad bar. Conclusions This multistate outbreak of STEC O157:H7 infections was associated with consumption of romaine lettuce. Traceback analysis determined that a single common lot of romaine lettuce harvested from Farm A was used to supply Grocery Store Chain A and a university campus linked to a case with the outbreak strain. An investigation at Farm A did not identify the source of contamination. Improved ability to trace produce from the growing fields to the point of consumption will allow more timely prevention and control measures to be implemented.

BACKGROUND Over 30 outbreaks of human salmonellosis linked to contact with live poultry from mail-order hatcheries were reported to Centers for Disease Control and Prevention between 1990 and 2010. In May 2009, we investigated an outbreak of human Salmonella Typhimurium infections, primarily affecting children. METHODS A case was defined as a person with the outbreak strain of Salmonella Typhimurium, as determined by pulsed-field gel electrophoresis and multiple-locus variable-number tandem repeat analysis, in a Pennsylvania or New York resident with illness onset between May 1 and September 1, 2009. We conducted a case-control study to examine the relationship between illness and live poultry contact. Controls were age-matched and geographically-matched. Traceback and environmental investigations were conducted. RESULTS We identified 36 case-patients in Pennsylvania and New York; 36% were children aged ≤5 years. Case-patients were more likely than controls to report live baby poultry contact (matched odds ratio [mOR]: 17.0; 95% confidence interval [CI]: 2.7-710.5), contact with chicks (mOR: 14.0; 95% CI: 2.1-592.0), ducklings (mOR: 8.0; 95% CI: 1.1-355.0) and visiting agricultural feed stores (mOR: 6.0; 95% CI: 1.3-55.2). Most (83%) visited agricultural Feed Store Chain Y, a national agricultural feed store chain, which received poultry from Hatchery C, which is supplied by multiple egg sources. Salmonella Typhimurium was isolated from a source duck flock, but had a different pulsed-field gel electrophoresis pattern than the outbreak strain. CONCLUSIONS Live baby poultry remain an important source of human salmonellosis, particularly among children. Preventing these infections requires comprehensive interventions at hatcheries and agricultural feed stores; pediatricians should inform patients of risks associated with live poultry contact.

Salmonella enterica subsp. enterica serovar Typhimurium is responsible for the majority of salmonellosis cases worldwide. This Salmonella serovar is also responsible for die-offs in songbird populations. In 2009, there was an S . Typhimurium epizootic reported in pine siskins in the eastern United States. At the time, there was also a human outbreak with this serovar that was associated with contaminated peanuts. As peanuts are also used in wild-bird food, it was hypothesized that the pine siskin epizootic was related to this human outbreak. A comparison of songbird and human S . Typhimurium pulsed-field gel electrophoresis (PFGE) patterns revealed that the epizootic was attributed not to the peanut-associated strain but, rather, to a songbird strain first characterized from an American goldfinch in 1998. This same S . Typhimurium strain (PFGE type A3) was also identified in the PulseNet USA database, accounting for 137 of 77,941 total S . Typhimurium PFGE entries. A second molecular typing method, multiple-locus variable-number tandem-repeat analysis (MLVA), confirmed that the same strain was responsible for the pine siskin epizootic in the eastern United States but was distinct from a genetically related strain isolated from pine siskins in Minnesota. The pine siskin A3 strain was first encountered in May 2008 in an American goldfinch and later in a northern cardinal at the start of the pine siskin epizootic. MLVA also confirmed the clonal nature of S . Typhimurium in songbirds and established that the pine siskin epizootic strain was unique to the finch family. For 2009, the distribution of PFGE type A3 in passerines and humans mirrored the highest population density of pine siskins for the East Coast.

Escherichia coli O157:H7 is a Shiga toxin-producing E. coli (STEC) associated with numerous foodborne outbreaks in the United States and is an important cause of bacterial gastrointestinal illness. In May 2009, we investigated a multistate outbreak of E. coli O157:H7 infections. Outbreak-associated cases were identified using serotyping and molecular subtyping procedures. Traceback investigation and product testing were performed. A matched case-control study was conducted to identify exposures associated with illness using age-, sex-, and state-matched controls. Seventy-seven patients with illnesses during the period 16 March-8 July 2009 were identified from 30 states; 35 were hospitalized, 10 developed hemolytic-uremic syndrome, and none died. Sixty-six percent of patients were19 years; 71% were female. In the case-control study, 33 of 35 case patients (94%) consumed ready-to-bake commercial prepackaged cookie dough, compared with 4 of 36 controls (11%) (matched odds ratio = 41.3; P.001); no other reported exposures were significantly associated with illness. Among case patients consuming cookie dough, 94% reported brand A. Three nonoutbreak STEC strains were isolated from brand A cookie dough. The investigation led to a recall of 3.6 million packages of brand A cookie dough and a product reformulation. This is the first reported STEC outbreak associated with consuming ready-to-bake commercial prepackaged cookie dough. Despite instructions to bake brand A cookie dough before eating, case patients consumed the product uncooked. Manufacturers should consider formulating ready-to-bake commercial prepackaged cookie dough to be as safe as a ready-to-eat product. More effective consumer education about the risks of eating unbaked cookie dough is needed.