Retracing microbial emergence and spread is essential to understanding the evolution and dynamics of pathogens. The bacterial foodborne pathogen Listeria monocytogenes clonal complex 1 (Lm-CC1) is the most prevalent clonal group associated with listeriosis, and is strongly associated with cattle and dairy products. Here we analysed 2,021 Lm-CC1 isolates collected from 40 countries, since the first Lm isolation to the present day, to define its evolutionary history and population dynamics. Our results suggest that Lm-CC1 spread worldwide from North America following the Industrial Revolution through two waves of expansion, coinciding with the transatlantic livestock trade in the second half of the 19th century and the rapid growth of cattle farming in the 20th century. Lm-CC1 then firmly established at a local level, with limited inter-country spread. This study provides an unprecedented insight into Lm-CC1 phylogeography and dynamics and can contribute to effective disease surveillance to reduce the burden of listeriosis.Competing Interest StatementThe authors have declared no competing interest.

In the past decade, the number of publicly available bacterial genomes has increased dramatically. These genomes have been generated for impactful initiatives, especially in the field of genomic epidemiology (Brown, Dessai, McGarry, & Gerner-Smidt, 2019; Timme et al., 2017). Genomes are sequenced, shared publicly, and subsequently analyzed for phylogenetic relatedness. If two genomes of epidemiological interest are found to be related, further investigation might be prompted. However, comparing the multitudes of genomes for phylogenetic relatedness is computationally expensive and, with large numbers, laborious. Consequently, there are many strategies to reduce the complexity of the data for downstream analysis, especially using nucleotide stretches of length k (kmers).

In the original article, there was a mistake in Figure 1 and Figure 2 as published. The graphics used are different than those originally submitted.

PulseNet International (PNI) is a global network of 88 countries who work together through their regional and national public health laboratories to track foodborne disease around the world. The vision of PNI is to implement globally standardized surveillance using whole genome sequencing (WGS) for real-time identification and subtyping of foodborne pathogens to strengthen preparedness and response and lower the burden of disease. Several countries in North America and Europe have experienced significant benefits in disease mitigation after implementing WGS. To broaden the routine use of WGS around the world, challenges and barriers must be overcome. We conducted this study to determine the challenges and barriers countries are encountering in their attempts to implement WGS and to identify how PNI can provide support to improve and become a better integrated system overall. A survey was designed with a set of qualitative questions to capture the status, challenges, barriers, and successes of countries in the implementation of WGS and was administered to laboratories in Africa, Asia-Pacific, Latin America and the Caribbean, and Middle East. One-third of respondents do not use WGS, and only 8% reported using WGS for routine, real-time surveillance. The main barriers for implementation of WGS were lack of funding, gaps in expertise, and training, especially for data analysis and interpretation. Features of an ideal system to facilitate implementation and global surveillance were identified as an all-in-one software that is free, accessible, standardized and validated. This survey highlights the minimal use of WGS for foodborne disease surveillance outside the United States, Canada, and Europe to date. Although funding remains a major barrier to WGS-based surveillance, critical gaps in expertise and availability of tools must be overcome. Opportunities to seek sustainable funding, provide training, and identify solutions for a globally standardized surveillance platform will accelerate implementation of WGS worldwide.

This multi-agency report developed under the Interagency Collaboration for Genomics for Food and Feed Safety (Gen-FS) provides an overview of the use of and transition to Whole-Genome Sequencing (WGS) technology to detect and characterize pathogens transmitted commonly by food and identify their sources. We describe foodborne pathogen analysis, investigation, and harmonization efforts among federal agencies, including the National Institutes of Health (NIH); the Department of Health and Human Services' Centers for Disease Control and Prevention (CDC) and the Food and Drug Administration (FDA); and the U.S. Department of Agriculture's Food Safety and Inspection Service (FSIS), Agricultural Research Service (ARS), and Animal and Plant Health Inspection Service (APHIS). We describe single nucleotide polymorphism (SNP), core-genome (cg) and whole-genome multi-locus sequence typing (wgMLST) data analysis methods as used in CDC's PulseNet and FDA's GenomeTrakr 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 Gen-FS agency partners. We highlight how we apply WGS to pathogen characterization (virulence and antimicrobial resistance profiles), source attribution efforts, and increasing transparency by making the sequences and other data publicly available through the National Center for Biotechnology Information (NCBI). Finally, we highlight the impact of current trends in the use of culture-independent diagnostics tests (CIDT) for human diagnostic testing on analytical approaches related to food safety. Lastly, we highlight what is next for WGS in food safety.

Retracing microbial emergence and spread is essential to understanding the evolution and 40 dynamics of pathogens. The bacterial foodborne pathogen Listeria monocytogenes clonal 41 complex 1 (Lm-CC1) is the most prevalent clonal group associated with listeriosis, and is 42 strongly associated with cattle and dairy products. Here we analysed 2,021 Lm-CC1 43 isolates collected from 40 countries, since the first Lm isolation to the present day, to 44 define its evolutionary history and population dynamics. Our results suggest that Lm-CC1 45 spread worldwide from North America following the Industrial Revolution through two 46 waves of expansion, coinciding with the transatlantic livestock trade in the second half of 47 the 19th century and the rapid growth of cattle farming in the 20th century. Lm-CC1 then 48 firmly established at a local level, with limited inter-country spread. This study provides 49 an unprecedented insight into Lm-CC1 phylogeography and dynamics and can contribute 50 to effective disease surveillance to reduce the burden of listeriosis.

Reptile-associated human salmonellosis cases have increased recently in the United States. It is not uncommon to find healthy chelonians shedding Salmonella enterica. The rate and frequency of bacterial shedding are not fully understood, and most studies have focused on captive vs. free-living chelonians and often in relation to an outbreak. Their ecology and significance as sentinels are important to understanding Salmonella transmission. In 2012-2013, Salmonella prevalence was determined for free-living aquatic turtles in man-made ponds in Clarke and Oconee Counties, in northern Georgia (USA) and the correlation between species, basking ecology, demographics (age/sex), season, or landcover with prevalence was assessed. The genetic relatedness between turtle and archived, human isolates, as well as, other archived animal and water isolates reported from this study area was examined. Salmonella was isolated from 45 of 194 turtles (23.2%, range 14-100%) across six species. Prevalence was higher in juveniles (36%) than adults (20%), higher in females (33%) than males (18%), and higher in bottom-dwelling species (31%; common and loggerhead musk turtles, common snapping turtles) than basking species (15%; sliders, painted turtles). Salmonella prevalence decreased as forest cover, canopy cover, and distance from roads increased. Prevalence was also higher in low-density, residential areas that have 20-49% impervious surface. A total of 9 different serovars of two subspecies were isolated including 3 S. enterica subsp. arizonae and 44 S. enterica subsp. enterica (two turtles had two serotypes isolated from each). Among the S. enterica serovars, Montevideo (n = 13) and Rubislaw (n = 11) were predominant. Salmonella serovars Muenchen, Newport, Mississippi, Inverness, Brazil, and Paratyphi B. var L(+) tartrate positive (Java) were also isolated. Importantly, 85% of the turtle isolates matched pulsed-field gel electrophoresis patterns of human isolates, including those reported from Georgia. Collectively, these results suggest that turtles accumulate Salmonella present in water bodies, and they may be effective sentinels of environmental contamination. Ultimately, the Salmonella prevalence rates in wild aquatic turtles, especially those strains shared with humans, highlight a significant public health concern.

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.

This paper focusses on biological hazards at the global level and considers the challenges to risk assessment (RA) from a One Health perspective. Two topics – vector-borne diseases (VBD) and antimicrobial resistance (AMR) – are used to illustrate the challenges ahead and to explore the opportunities that new methodologies such as next-generation sequencing can offer. Globalisation brings complexity and introduces drivers for infectious diseases. Cooperation and the application of an integrated RA approach – one that takes into consideration food farming and production systems including social and environmental factors – are recommended. Also needed are methodologies to identify emerging risks at a global level and propose prevention strategies. AMR is one of the biggest threats to human health in the infectious disease environment. Whereas new genomic typing techniques such as whole genome sequencing (WGS) provide further insights into the mechanisms of spread of resistance, the role of the environment is not fully elucidated, nor is the role of plants as potential vehicles for spread of resistance. Historical trends and recent experience indicate that (re)-emergence and/or further spread of VBD within the EU is a matter of when rather than if. Standardised and validated vector monitoring programs are required to be implemented at an international level for continuous surveillance and assessment of potential threats. There are benefits to using WGS – such as a quicker and better response to outbreaks and additional evidence for source attribution. However, significant challenges need to be addressed, including method standardisation and validation to fully realise these benefits; barriers to data sharing; and establishing epidemiological capacity for cluster triage and response.

Infections caused by pathogens commonly acquired from consumption of food are not always transmitted by that route. They may also be transmitted through contact to animals, other humans or the environment. Additionally, many outbreaks are associated with food contaminated from these non-food sources. For this reason, such presumed foodborne outbreaks are best investigated through a One Health approach working across human, animal and environmental sectors and disciplines. Outbreak strains or clones that have propagated and continue to evolve in non-human sources and environments often show more sequence variation than observed in typical monoclonal point-source outbreaks. This represents a challenge when using whole genome sequencing (WGS), the new gold standard for molecular surveillance of foodborne pathogens, for outbreak detection and investigation. In this review, using recent examples from outbreaks investigated in the United States (US) some aspects of One Health approaches that have been used successfully to solve such outbreaks are presented. These include using different combinations of flexible WGS based case definition, efficient epidemiological follow-up, traceback, surveillance, and testing of potential food and environmental sources and animal hosts.

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.

Since 1996, PulseNet has served as the national laboratory-based surveillance system for the rapid detection of outbreaks caused by foodborne bacterial pathogens in the United States. For the past two decades, pulsed-field gel electrophoresis was the gold standard subtyping method for the pathogens tracked by PulseNet. A new gold standard is now being implemented with the introduction of cost-effective whole genome sequencing (WGS) for analysis of all the organisms tracked by PulseNet. This transformation is a major undertaking that touches every functional aspect of PulseNet, including laboratory workflows, data storage, analysis management and data interpretation, and language used to communicate information (sequence profile nomenclature system). The benefits of implementing WGS go beyond improved discrimination and precision of the data; it provides an opportunity to determine strain characteristics typically obtained through resource-intensive traditional methodologies, for example, species identification, serotyping, virulence, and antimicrobial resistance profiling, all of which can be consolidated into a single WGS workflow. Such a strategy represents a major shift in the workflows currently practiced in most public health laboratories, but one that brings opportunities for streamlining surveillance activities for the network as a whole. In this study, we provide a brief summary of PulseNet's evolution the past decade along with a general description of the challenges and opportunities that lie ahead.

Whole-genome sequencing (WGS) is increasingly used by food regulatory and public health agencies in the United States to facilitate the detection, investigation, and control of foodborne bacterial outbreaks, and food regulatory and other activities in support of food safety. WGS has added a level of precision to the surveillance leading to faster and more efficient decision making in the preparedness and response to foodborne infections. In this review, we report the history of WGS technology at the Centers for Disease Control & Prevention (CDC), the Food and Drug Administration (FDA), and the United States Department of Agriculture's Food Safety and Inspection Service (USDA/FSIS) as it applies to food safety. The basic principle of the method, the analysis, and interpretation of the data are explained as is its major strengths and limitations. We also describe the benefits and possibilities of the WGS technology to the food industry throughout the farm-to-fork continuum and the prospects of metagenomic sequencing applied directly to the sample specimen with or without pre-enrichment culture.

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.

PulseNet USA is the molecular surveillance network for foodborne disease in the United States. The network consists of state and local public health laboratories, as well as food regulatory agencies, that follow PulseNet's standardized protocols to perform pulsed-field gel electrophoresis (PFGE) and whole genome sequencing (WGS) and analyze the results using standardized software. The raw sequences are uploaded to the GenomeTrakr or PulseNet bioprojects at the National Center for Biotechnology Information. The PFGE patterns and analyzed sequence data are uploaded in real time with associated demographic data to the PulseNet national databases managed at the Centers for Disease Control and Prevention. The PulseNet databases are organism specific and provide a central storage location for molecular and demographic data related to an isolate. Sequences are compared in the databases, thereby facilitating the rapid detection of clusters of foodborne diseases that may represent widespread outbreaks. WGS genotyping data, for example, antibiotic resistance and virulence profiles, are also uploaded in real time to the PulseNet databases to improve food safety surveillance activities.

Next Generation Sequencing (NGS) combined with powerful bioinformatic approaches are revolutionising food microbiology. Whole genome sequencing (WGS) of single isolates allows the most detailed comparison possible hitherto of individual strains. The two principle approaches for strain discrimination, single nucleotide polymorphism (SNP) analysis and genomic multi-locus sequence typing (MLST) are showing concordant results for phylogenetic clustering and are complementary to each other. Metabarcoding and metagenomics, applied to total DNA isolated from either food materials or the production environment, allows the identification of complete microbial populations. Metagenomics identifies the entire gene content and when coupled to transcriptomics or proteomics, allows the identification of functional capacity and biochemical activity of microbial populations. The focus of this review is on the recent use and future potential of NGS in food microbiology and on current challenges. Guidance is provided for new users, such as public health departments and the food industry, on the implementation of NGS and how to critically interpret results and place them in a broader context. The review aims to promote the broader application of NGS technologies within the food industry as well as highlight knowledge gaps and novel applications of NGS with the aim of driving future research and increasing food safety outputs from its wider use.

Background/objectives: Whole genome sequencing (WGS) has proven to be a powerful subtyping tool for foodborne pathogenic bacteria like L. monocytogenes. The interests of genome-scale analysis for national surveillance, outbreak detection or source tracking has been largely documented. The genomic data however can be exploited with many different bioinformatics methods like single nucleotide polymorphism (SNP), core-genome multi locus sequence typing (cgMLST), whole-genome multi locus sequence typing (wgMLST) or multi locus predicted protein sequence typing (MLPPST) on either core-genome (cgMLPPST) or pan-genome (wgMLPPST). Currently, there are little comparisons studies of these different analytical approaches. Our objective was to assess and compare different genomic methods that can be implemented in order to cluster isolates of L. monocytogenes. Methods: The clustering methods were evaluated on a collection of 207 L. monocytogenes genomes of food origin representative of the genetic diversity of the Anses collection. The trees were then compared using robust statistical analyses. Results: The backward comparability between conventional typing methods and genomic methods revealed a near-perfect concordance. The importance of selecting a proper reference when calling SNPs was highlighted, although distances between strains remained identical. The analysis also revealed that the topology of the phylogenetic trees between wgMLST and cgMLST were remarkably similar. The comparison between SNP and cgMLST or SNP and wgMLST approaches showed that the topologies of phylogenic trees were statistically similar with an almost equivalent clustering. Conclusion: Our study revealed high concordance between wgMLST, cgMLST, and SNP approaches which are all suitable for typing of L. monocytogenes. The comparable clustering is an important observation considering that the two approaches have been variously implemented among reference laboratories.

BACKGROUND: With the decreasing cost and efficiency of next generation sequencing, the technology is rapidly introduced into clinical and public health laboratory practice. AIMS: In this review, 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 & IMPLICATIONS: Next generation sequencing is a technology that potentially could 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.

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.

During September to October, 2006, state and local health departments and the Centers for Disease Control and Prevention investigated a large, multistate outbreak of Escherichia coli O157:H7 infections. Case patients were interviewed regarding specific foods consumed and other possible exposures. E. coli O157:H7 strains isolated from human and food specimens were subtyped using pulsed-field gel electrophoresis and multiple-locus variable-number tandem repeat analyses (MLVA). Two hundred twenty-five cases (191 confirmed and 34 probable) were identified in 27 states; 116 (56%) case patients were hospitalized, 39 (19%) developed hemolytic uremic syndrome, and 5 (2%) died. Among 176 case patients from whom E. coli O157:H7 with the outbreak genotype (MLVA outbreak strain) was isolated and who provided details regarding spinach exposure, 161 (91%) reported fresh spinach consumption during the 10 days before illness began. Among 116 patients who provided spinach brand information, 106 (91%) consumed bagged brand A. E. coli O157:H7 strains were isolated from 13 bags of brand A spinach collected from patients' homes; isolates from 12 bags had the same MLVA pattern. Comprehensive epidemiologic and laboratory investigations associated this large multistate outbreak of E. coli O157:H7 infections with consumption of fresh bagged spinach. MLVA, as a supplement to pulsed-field gel electrophoresis genotyping of case patient isolates, was important to discern outbreak-related cases. This outbreak resulted in enhanced federal and industry guidance to improve the safety of leafy green vegetables and launched an independent collaborative approach to produce safety research in 2007.

Worldwide, Salmonella spp. is a significant cause of disease for both humans and wildlife, with wild birds adapted to urban environments having different opportunities for pathogen exposure, infection, and transmission compared to their natural conspecifics. Food provisioning by people may influence these factors, especially when high-density mixed species flocks aggregate. White Ibises (Eudocimus albus), an iconic Everglades species in decline in Florida, are becoming increasingly common in urbanized areas of south Florida where most are hand-fed. We examined the prevalence of Salmonella shedding by ibises to determine the role of landscape characteristics where ibis forage and their behavior, on shedding rates. We also compared Salmonella isolated from ibises to human isolates to better understand non-foodborne human salmonellosis. From 2010-2013, 13% (n = 261) adult/subadult ibises and 35% (n = 72) nestlings sampled were shedding Salmonella. The prevalence of Salmonella shedding by ibises significantly decreased as the percent of Palustrine emergent wetlands and herbaceous grasslands increased, and increased as the proportion of open-developed land types (e.g. parks, lawns, golf courses) increased, suggesting that natural ecosystem land cover types supported birds with a lower prevalence of infection. A high diversity of Salmonella serotypes (n = 24) and strain types (43 PFGE types) were shed by ibises, of which 33% of the serotypes ranked in the top 20 of high significance for people in the years of the study. Importantly, 44% of the Salmonella Pulsed-Field Gel Electrophoresis patterns for ibis isolates (n = 43) matched profiles in the CDC PulseNet USA database. Of these, 20% came from Florida in the same three years we sampled ibis. Importantly, there was a negative relationship between the amount of Palustrine emergent wetland and the number of Salmonella isolates from ibises that matched human cases in the PulseNet database (p = 0.056). Together, our results indicate that ibises are good indicators of salmonellae strains circulating in their environment and they have both the potential and opportunity to transmit salmonellae to people. Finally, they may act as salmonellae carriers to natural environments where other more highly-susceptible groups (nestlings) may be detrimentally affected.

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

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.

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 U.S.Lmisolates 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.

Shiga toxin-producing Escherichia coli (STEC) is an important foodborne pathogen. Here, we report complete whole-genome sequences for two STEC strains of serotypes O119:H4 and O165:H25 isolated from clinical cases in the United States.

Salmonellosis cases in the in the United States show distinct geographical trends, with the southeast reporting among the highest rates of illness. In the state of Georgia, USA, non-outbreak associated salmonellosis is especially high in the southern low-lying coastal plain. Here we examined the distribution of Salmonella enterica in environmental waters and associated wildlife in two distinct watersheds, one in the Atlantic Coastal Plain (a high case rate rural area) physiographic province and one in the Piedmont (a lower case rate rural area). Salmonella were isolated from the two regions and compared for serovar and strain diversity, as well as distribution, between the two study areas, using both a retrospective and prospective design. Thirty-seven unique serovars and 204 unique strain types were identified by pulsed-field gel electrophoresis (PFGE). Salmonella serovars Braenderup, Give, Hartford, and Muenchen were dominant in both watersheds. Two serovars, specifically S. Muenchen and S. Rubislaw, were consistently isolated from both systems, including water and small mammals. Conversely, 24 serovars tended to be site-specific (64.8%, n = 37). Compared to the other Salmonella serovars isolated from these sites, S. Muenchen and S. Rubislaw exhibited significant genetic diversity. Among a subset of PFGE patterns, approximately half of the environmental strain types matched entries in the USA PulseNet database of human cases. Ninety percent of S. Muenchen strains from the Little River basin (the high case rate area) matched PFGE entries in PulseNet compared to 33.33% of S. Muenchen strains from the North Oconee River region (the lower case rate area). Underlying the diversity and turnover of Salmonella strains observed for these two watersheds is the persistence of specific Salmonella serovars and strain types that may be adapted to these watersheds and landscapes.

The objective of this study was to develop a canonical, parsimoniously-informative SNP panel for subtyping Shiga-toxin producing Escherichia coli (STEC) O157:H7 that would be consistent with epidemiological, PFGE, and MLVA clustering of human specimens. Our group had previously identified 906 putative discriminatory SNPs, which were pared down to 391 SNPs based on their prevalence in a test set. The 391 SNPs were screened using a high-throughput form of TaqMan PCR against a set of clinical isolates that represent the most diverse collection of O157:H7 isolates from outbreaks and sporadic cases examined to date. Another 30 SNPs identified by others were also screened using the same method. Two additional targets were tested using standard TaqMan PCR endpoint analysis. These 423 SNPs were reduced to a 32 SNP panel with the almost the same discriminatory value. While the panel partitioned our diverse set of isolates in a manner that was consistent with epidemiological data and PFGE and MLVA phylogenies, it resulted in fewer subtypes than either existing method and insufficient epidemiological resolution in 10 of 47 clusters. Therefore, another round of SNP discovery was undertaken using comparative genomic resequencing of pooled DNA from the 10 clusters with insufficient resolution. This process identified 4,040 potential SNPs and suggested one of the ten clusters was incorrectly grouped. After its removal, there were 2,878 SNPs, of which only 63 were previously identified and 438 occurred across multiple clusters. Among highly clonal bacteria like STEC O157:H7, linkage disequilibrium greatly limits the number of parsimoniously informative SNPs. Therefore, it is perhaps unsurprising that our panel accounted for the potential discriminatory value of numerous other SNPs reported in the literature. We concluded published O157:H7 SNPs are insufficient for effective epidemiological subtyping. However, the 438 multi-cluster SNPs we identified may provide the additional information required.

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.

To assess the spectrum of illness from toxigenic Vibrio cholerae O1 and risk factors for severe cholera in Haiti, we conducted a cross-sectional survey in a rural commune with more than 21,000 residents. During March 22-April 6, 2011, we interviewed 2,622 residents ≥ 2 years of age and tested serum specimens from 2,527 (96%) participants for vibriocidal and antibodies against cholera toxin; 18% of participants reported a cholera diagnosis, 39% had vibriocidal titers ≥ 320, and 64% had vibriocidal titers ≥ 80, suggesting widespread infection. Among seropositive participants (vibriocidal titers ≥ 320), 74.5% reported no diarrhea and 9.0% had severe cholera (reported receiving intravenous fluids and overnight hospitalization). This high burden of severe cholera is likely explained by the lack of pre-existing immunity in this population, although the virulence of the atypical El Tor strain causing the epidemic and other factors might also play a role.