ACEstat: A DIY Guide to Unlocking the Potential of Integrated Circuit Potentiostats for Open-Source Electrochemical Analysis.

Miniaturization of analytical instrumentation is paramount to enabling convenient in-field sensing. The recent thrust in potentiostat miniaturization for electrochemical sensing and general use has led to the development of commercial application specific integrated circuits (ASICs) that pack all the power of a benchtop instrument into one 5 mm × 5 mm chip. While the capabilities of these integrated circuits far exceed those of open-source potentiostats in the literature, the activation barrier for their implementation requires extensive electrical and software engineering expertise to overcome. In order to more rapidly bring the utility of ASIC potentiostats to researchers, we present a low size, weight, power, and cost (Low SWaP-C) Army Corps of Engineers potentiostat (ACEstat) based on the widely available ADuCM355 offered by Analog Devices. This potentiostat is a streamlined and fully programmable device that leverages industry-leading integrated hardware to perform electrochemical measurements such as cyclic voltammetry, pulse voltammetry, and electrochemical impedance spectroscopy. The ACEstat enables control over a wide range of test parameters and displays results through an intuitive, open-source graphical user interface available on mobile devices and computers. In this report, we present an approachable, do-it-yourself guide to unlocking the capabilities of this integrated circuit potentiostat by outlining the fabrication and programming details necessary to facilitate electroanalysis. Furthermore, we demonstrate the practicality of this device by detecting 2,4,6-trinitrotoluene (TNT) in water at sub-mg/L detection limits, highlighting its potential for in-field use.

Selecting an Optimal Faraday Cage To Minimize Noise in Electrochemical Experiments.

The ubiquitous Faraday cage, an experimental component particularly essential for nanoelectrochemical measurements, is responsible for neutralizing noise introduced by electromagnetic interference (EMI). Faraday cage designs abound in the literature, often exhibiting varying thicknesses, mesh sizes, and base materials. The fact that the Faraday cage composition most often goes unreported underscores the fact that many electrochemical researchers assume a 100% EMI reduction for any given design. In this work, this assumption is challenged from a theoretical and empirical perspective by highlighting the physical principles producing the Faraday effect. A brief history of the Faraday cage and a simplified theoretical approach introduce fundamental considerations regarding optimal design properties. In practice, time-domain noise profiles and corresponding Fourier transform frequency domain information for custom-built Faraday cages reveal that maximally conductive cages provide more optimal EMI exclusion.

A Generalized Potentiostat Adaptor for Multiplexed Electroanalysis.

Electrochemical measurements over an array of electrodes may be accomplished with one of three potentiostat architectures: a single-channel device which averages the signal from a number of interconnected electrodes, a multichannel device with dedicated circuits for each electrode, or a single-channel device with a multiplexer interface to isolate the signal from specific electrodes. Of these three architectures, the use of a multiplexer interface is best suited to facilitate measurements over individual electrodes without the need for large numbers of dedicated potentiostat channels. We present a versatile strategy for the development of flexible printed circuit (FPC) electrode arrays with accompanying multiplexing hardware to interface with single-channel potentiostats. The FPC array was fabricated with 78 individually addressable 0.3 mm diameter gold working electrodes and characterized using optical and scanning electron microscopy, energy dispersive spectroscopy, profilometry, impedance spectroscopy, and cyclic voltammetry to investigate the morphology, elemental composition, height profile, impedance characteristics, and electrochemical response, respectively. Interfacing the FPC array via a simple connector with three 32-channel ADG731 multiplexers permitted electrochemical measurements using single-channel commercial potentiostats. Voltammetric experiments were conducted to demonstrate the reliability, stability, and reproducibility of the FPC array and interfacing hardware. The combination of these devices represents an accessible hardware platform with robust, functionalizable electrodes, a simple connection interface with commercial potentiostats, and a low cost through the use of off-the-shelf components. Our reported strategy holds great promise to facilitate multiplexed electroanalysis in next-generation sensors to increase statistical sample size and multianalyte detection capabilities.

Taxonomic and Functional Shifts in the Sprout Spent Irrigation Water Microbiome in Response to Salmonella Contamination of Alfalfa Seeds.

Despite recent advances in Salmonella-sprout research, little is known about the relationship between Salmonella and the sprout microbiome during sprouting. Sprout spent irrigation water (SSIW) provides an informative representation of the total microbiome of this primarily aquaponic crop. This study was designed to characterize the function and taxonomy of the most actively transcribed genes in SSIW from Salmonella enterica serovar Cubana-contaminated alfalfa seeds throughout the sprouting process. Genomic DNA and total RNA from SSIW was collected at regular intervals and sequenced using Illumina MiSeq and NextSeq platforms. Nucleic acid data were annotated using four different pipelines. Both metagenomic and metatranscriptomic analyses revealed a diverse and highly dynamic SSIW microbiome. A "core" SSIW microbiome comprised Klebsiella, Enterobacter, Pantoea, and Cronobacter The impact, however, of Salmonella contamination on alfalfa seeds influenced SSIW microbial community dynamics not only structurally but also functionally. Changes in genes associated with metabolism, genetic information processing, environmental information processing, and cellular processes were abundant and time dependent. At time points of 24 h, 48 h, and 96 h, totals of 541, 723, and 424 S Cubana genes, respectively, were transcribed at either higher or lower levels than at 0 h in SSIW during sprouting. An array of S Cubana genes (107) were induced at all three time points, including genes involved in biofilm formation and modulation, stress responses, and virulence and tolerance to antimicrobials. Taken together, these findings expand our understanding of the effect of Salmonella seed contamination on the sprout crop microbiome and metabolome.IMPORTANCE Interactions of human enteric pathogens like Salmonella with plants and plant microbiomes remain to be elucidated. The rapid development of next-generation sequencing technologies provides powerful tools enabling investigation of such interactions from broader and deeper perspectives. Using metagenomic and metatranscriptomic approaches, this study identified not only changes in microbiome structure of SSIW associated with sprouting but also changes in the gene expression patterns related to the sprouting process in response to Salmonella contamination of alfalfa seeds. This study advances our knowledge on Salmonella-plant (i.e., sprout) interaction.

Atypical Salmonella enterica Serovars in Murine and Human Macrophage Infection Models.

Nontyphoidal Salmonella species are globally disseminated pathogens and are the predominant cause of gastroenteritis. The pathogenesis of salmonellosis has been extensively studied using in vivo murine models and cell lines, typically challenged with Salmonella enterica serovar Typhimurium. Although S. enterica serovars Enteritidis and Typhimurium are responsible for most of the human infections reported to the Centers for Disease Control and Prevention (CDC), several other serovars also contribute to clinical cases of salmonellosis. Despite their epidemiological importance, little is known about their infection phenotypes. Here, we report the virulence characteristics and genomes of 10 atypical S. enterica serovars linked to multistate foodborne outbreaks in the United States. We show that the murine RAW 264.7 macrophage model of infection is unsuitable for inferring human-relevant differences in nontyphoidal Salmonella infections, whereas differentiated human THP-1 macrophages allowed these isolates to be further characterized in a more human-relevant context.

Epidemiology needs more interdisciplinary teams with expertise in molecular systematics, public health and food safety.

What are considered fundamental principles within the Willi Hennig Society and published in their journal are not always fully appreciated by many other biological fields that have not been schooled in these disciplines of systematics principles and the reasons for why these principles are important (Wenzel, Cladistics, 2020, in press). Natural history museums and their associated programs have been a traditional source of the dissemination and training on the uses of phylogenetic systematics. Systematists should do more to expand these interdisciplinary collaborations by reaching out and supporting their local and international collaborators in public health, food and water safety, and other microbiology applications so that critical life-saving and timely phylogenetic-based decisions can be made.

Attribution of Listeria monocytogenes human infections to food and animal sources in Northern Italy.

Listeriosis is a foodborne illness characterized by a relatively low morbidity, but a large disease burden due to the severity of clinical manifestations and the high case fatality rate. Increased listeriosis notifications have been observed in Europe since the 2000s. However, the reasons for this increase are largely unknown, with the sources of sporadic human listerioris often remaining elusive. Here we inferred the relative contributions of several putative sources of Listeria monocytogenes strains from listerioris patients in Northern Italy (Piedmont and Lombardy regions), using two established source attribution models (i.e. 'Dutch' and 'STRUCTURE') in comparative fashion. We compared the Multi-Locus Sequence Typing and Multi-Virulence-Locus Sequence Typing profiles of strains collected from beef, dairy, fish, game, mixed foods, mixed meat, pork, and poultry. Overall, 634 L. monocytogenes isolates were collected from 2005 to 2016. In total, 40 clonal complexes and 51 virulence types were identified, with 36% of the isolates belonging to possible epidemic clones (i.e. genetically related strains from unrelated outbreaks). Source attribution analysis showed that 50% of human listerioris cases (95% Confidence Interval 44-55%) could be attributed to dairy products, followed by poultry and pork (15% each), and mixed foods (15%). Since the contamination of dairy, poultry and pork products are closely linked to primary production, expanding actions currently limited to ready-to-eat products to the reservoir level may help reducing the risk of cross-contamination at the consumer level.

Characterization of Salmonella enterica Isolates from Selected U.S. Swine Feed Mills by Whole-Genome Sequencing.

Every year salmonellosis is responsible for $2.3 billion in costs to the U.S. food industry, with nearly 6% of the reported cases associated with pork and/or pork products. Several studies have demonstrated the role of pigs as Salmonella reservoirs. Furthermore, this pathogen has been identified as a potential biological hazard in many livestock feeds. The overall objective of this research was to characterize Salmonella enterica isolates in selected U.S. swine feed mills by whole-genome sequencing (WGS) and evaluate isolates in association with the season and feed production stages. Salmonella isolates were collected from 11 facilities during a previous study. Samples were analyzed for Salmonella prevalence following the U.S. Department of Agriculture guidelines and confirmed by PCR. WGS was carried out on either the MiSeq or NextSeq sequencer. De novo genome assemblies were obtained with the Shovill pipeline, version 0.9. ResFinder and SPIFinder were used to identify antibiotic resistance genes and pathogenicity islands. Finally, their phylogenetic relationship and diversity were determined by core genome multilocus sequence typing. Overall, our analysis showed the presence of S. enterica in the feed mill environment. Isolates belonged to 16 different serotypes. Salmonella Agona, Salmonella Mbandaka, Salmonella Senfenberg, and Salmonella Scharzengrund were the most frequently found, and 18 single-nucleotide polymorphism clusters were identified. In silico analysis showed that 40% of the strains carried at least one antimicrobial resistance gene. All isolates in this study could be considered of public health concern and pathogenic potential. Our findings underscore the potential role of the feed mill environment as the pathogen entry route into the human food value chain.

Phylogenomic Pipeline Validation for Foodborne Pathogen Disease Surveillance.

Foodborne pathogen surveillance in the United States is transitioning from strain identification using restriction digest technology (pulsed-field gel electrophoresis [PFGE]) to shotgun sequencing of the entire genome (whole-genome sequencing [WGS]). WGS requires a new suite of analysis tools, some of which have long histories in academia but are new to the field of public health and regulatory decision making. Although the general workflow is fairly standard for collecting and analyzing WGS data for disease surveillance, there are a number of differences in how the data are collected and analyzed across public health agencies, both nationally and internationally. This impedes collaborative public health efforts, so national and international efforts are underway to enable direct comparison of these different analysis methods. Ultimately, the harmonization efforts will allow the (mutually trusted and understood) production and analysis of WGS data by labs and agencies worldwide, thus improving outbreak response capabilities globally. This review provides a historical perspective on the use of WGS for pathogen tracking and summarizes the efforts underway to ensure the major steps in phylogenomic pipelines used for pathogen disease surveillance can be readily validated. The tools for doing this will ensure that the results produced are sound, reproducible, and comparable across different analytic approaches.

How Cognitive Machines Can Augment Medical Imaging.

OBJECTIVE: Artificial intelligence (AI) neural networks rapidly convert disparate facts and data into highly predictive analytic models. Machine learning maps image-patient phenotype correlations opaque to standard statistics. Deep learning performs accurate image-derived tissue characterization and can generate virtual CT images from MRI datasets. Natural language processing reads medical literature and efficiently reconfigures years of PACS and electronic medical record information. CONCLUSION: AI logistics solve radiology informatics workflow pain points. Imaging professionals and companies will drive health care AI technology insertion. Data science and computer science will jointly potentiate the impact of AI applications for medical imaging.

Plant-Microbe and Abiotic Factors Influencing Salmonella Survival and Growth on Alfalfa Sprouts and Swiss Chard Microgreens.

Microgreens, like sprouts, are relatively fast-growing products and are generally consumed raw. Moreover, as observed for sprouts, microbial contamination from preharvest sources may also be present in the production of microgreens. In this study, two Salmonella enterica serovars (Hartford and Cubana), applied at multiple inoculation levels, were evaluated for survival and growth on alfalfa sprouts and Swiss chard microgreens by using the most-probable-number (MPN) method. Various abiotic factors were also examined for their effects on Salmonella survival and growth on sprouts and microgreens. Community-level physiological profiles (CLPPs) of sprout/microgreen rhizospheres with different levels of S. enterica inoculation at different growth stages were characterized by use of Biolog EcoPlates. In the seed contamination group, the ability of S. enterica to grow on sprouting alfalfa seeds was affected by both seed storage time and inoculation level but not by serovar. However, the growth of S. enterica on Swiss chard microgreens was affected by serovar and inoculation level. Seed storage time had little effect on the average level of Salmonella populations in microgreens. In the irrigation water contamination group, the growth of Salmonella on both alfalfa sprouts and microgreens was largely affected by inoculation level. Surprisingly, the growth medium was found to play an important role in Salmonella survival and growth on microgreens. CLPP analysis showed significant changes in the microbial community metabolic diversity during sprouting for alfalfa sprouts, but few temporal changes were seen with microgreens. The data suggest that the change in rhizosphere bacterial functional diversity was dependent on the host but independent of Salmonella contamination.IMPORTANCE Sprouts and microgreens are considered "functional foods," i.e., foods containing health-promoting or disease-preventing properties in addition to normal nutritional values. However, the microbial risk associated with microgreens has not been well studied. This study evaluated Salmonella survival and growth on microgreens compared to those on sprouts, as well as other abiotic factors that could affect Salmonella survival and growth on microgreens. This work provides baseline data for risk assessment of microbial contamination of sprouts and microgreens. Understanding the risks of Salmonella contamination and its effects on rhizosphere microbial communities enables a better understanding of host-pathogen dynamics in sprouts and microgreens. The data also contribute to innovative preventive control strategies for Salmonella contamination of sprouts and microgreens.

Avoiding Patient Harm With Parenteral Nutrition During Electrolyte Shortages.

Purpose: We report a case of a patient with gastrointestinal dysmotility and substantial drainage losses who required parenteral nutrition (PN) and developed a non-anion gap metabolic acidosis secondary to a shortage of concurrent potassium acetate and sodium acetate PN additives. We describe how severe PN-associated metabolic consequences were averted during this acetate shortage. Summary: The patient with inability to swallow and significant weight loss was admitted to the hospital and given PN after failure to tolerate either gastric or jejunal feeding due to dysmotility and severe abdominal distension and discomfort. PN was initiated and the nasogastric and jejunal tubes were left to low intermittent suction or gravity drainage (average losses of 800 mL and 1600 mL daily, respectively) to reduce abdominal distension. The patient had been stable on PN for approximately 2 months prior to when a shortage in potassium acetate and sodium acetate occurred. As a result, potassium and sodium requirements had to be met with chloride and phosphate salts. The patient developed a non-anion gap metabolic acidosis after 11 days of acetate-free PN. Progression to severe acidemia was avoided by administration of sodium bicarbonate daily for 3 days and replacement of 0.9% sodium chloride supplemental intravenous fluid with lactated ringers solution. Conclusion: This case report illustrates that PN component shortages require clinicians to closely monitor patients who require PN. In addition, clinicians may need to use creative therapeutic strategies to avoid potential serious patient harm during PN component shortages.

Singleton Sequence Type 382, an Emerging Clonal Group of Listeria monocytogenes Associated with Three Multistate Outbreaks Linked to Contaminated Stone Fruit, Caramel Apples, and Leafy Green Salad.

Three multistate outbreaks between 2014 and 2016, involving case patients in and outside the United States, were linked to stone fruit, caramel apples, and packaged leafy green salad contaminated with Listeria monocytogenes singleton sequence type 382 (ST382), a serotype IVb-v1 clone with limited genomic divergence. Isolates from these outbreaks and other ST382 isolates not associated with these outbreaks were analyzed by whole-genome sequencing (WGS) analysis. The primary differences among ST382 strains were single nucleotide polymorphisms (SNPs). WGS analysis differentiated ST382 from a clonal complex 1 outbreak strain co-contaminating the caramel apples. WGS clustered food, environmental, and clinical isolates within each outbreak, and also differentiated among the three outbreak strains and epidemiologically unrelated ST382 isolates, which were indistinguishable by pulsed-field gel electrophoresis. ST382 appeared to be an emerging clone that began to diverge from its ancestor approximately 32 years before 2016. We estimated that there was 1.29 nucleotide substitution per genome (2.94 Mbp) per year for this clone.

Whole Genome and Core Genome Multilocus Sequence Typing and Single Nucleotide Polymorphism Analyses of Listeria monocytogenes Isolates Associated with an Outbreak Linked to Cheese, United States, 2013.

Epidemiological findings of a listeriosis outbreak in 2013 implicated Hispanic-style cheese produced by company A, and pulsed-field gel electrophoresis (PFGE) and whole genome sequencing (WGS) were performed on clinical isolates and representative isolates collected from company A cheese and environmental samples during the investigation. The results strengthened the evidence for cheese as the vehicle. Surveillance sampling and WGS 3 months later revealed that the equipment purchased by company B from company A yielded an environmental isolate highly similar to all outbreak isolates. The whole genome and core genome multilocus sequence typing and single nucleotide polymorphism (SNP) analyses results were compared to demonstrate the maximum discriminatory power obtained by using multiple analyses, which were needed to differentiate outbreak-associated isolates from a PFGE-indistinguishable isolate collected in a nonimplicated food source in 2012. This unrelated isolate differed from the outbreak isolates by only 7 to 14 SNPs, and as a result, the minimum spanning tree from the whole genome analyses and certain variant calling approach and phylogenetic algorithm for core genome-based analyses could not provide differentiation between unrelated isolates. Our data also suggest that SNP/allele counts should always be combined with WGS clustering analysis generated by phylogenetically meaningful algorithms on a sufficient number of isolates, and the SNP/allele threshold alone does not provide sufficient evidence to delineate an outbreak. The putative prophages were conserved across all the outbreak isolates. All outbreak isolates belonged to clonal complex 5 and serotype 1/2b and had an identical inlA sequence which did not have premature stop codons.IMPORTANCE In this outbreak, multiple analytical approaches were used for maximum discriminatory power. A PFGE-matched, epidemiologically unrelated isolate had high genetic similarity to the outbreak-associated isolates, with as few as 7 SNP differences. Therefore, the SNP/allele threshold should not be used as the only evidence to define the scope of an outbreak. It is critical that the SNP/allele counts be complemented by WGS clustering analysis generated by phylogenetically meaningful algorithms to distinguish outbreak-associated isolates from epidemiologically unrelated isolates. Careful selection of a variant calling approach and phylogenetic algorithm is critical for core-genome-based analyses. The whole-genome-based analyses were able to construct the highly resolved phylogeny needed to support the findings of the outbreak investigation. Ultimately, epidemiologic evidence and multiple WGS analyses should be combined to increase confidence levels during outbreak investigations.

Whole genome sequencing analyses of Listeria monocytogenes that persisted in a milkshake machine for a year and caused illnesses in Washington State.

BACKGROUND: In 2015, in addition to a United States multistate outbreak linked to contaminated ice cream, another outbreak linked to ice cream was reported in the Pacific Northwest of the United States. It was a hospital-acquired outbreak linked to milkshakes, made from contaminated ice cream mixes and milkshake maker, served to patients. Here we performed multiple analyses on isolates associated with this outbreak: pulsed-field gel electrophoresis (PFGE), whole genome single nucleotide polymorphism (SNP) analysis, species-specific core genome multilocus sequence typing (cgMLST), lineage-specific cgMLST and whole genome-specific MLST (wgsMLST)/outbreak-specific cgMLST. We also analyzed the prophages and virulence genes. RESULTS: The outbreak isolates belonged to sequence type 1038, clonal complex 101, genetic lineage II. There were no pre-mature stop codons in inlA. Isolates contained Listeria Pathogenicity Island 1 and multiple internalins. PFGE and multiple whole genome sequencing (WGS) analyses all clustered together food, environmental and clinical isolates when compared to outgroup from the same clonal complex, which supported the finding that L. monocytogenes likely persisted in the soft serve ice cream/milkshake maker from November 2014 to November 2015 and caused 3 illnesses, and that the outbreak strain was transmitted between two ice cream production facilities. The whole genome SNP analysis, one of the two species-specific cgMLST, the lineage II-specific cgMLST and the wgsMLST/outbreak-specific cgMLST showed that L. monocytogenes cells persistent in the milkshake maker for a year formed a unique clade inside the outbreak cluster. This clustering was consistent with the cleaning practice after the outbreak was initially recognized in late 2014 and early 2015. Putative prophages were conserved among prophage-containing isolates. The loss of a putative prophage in two isolates resulted in the loss of the AscI restriction site in the prophage, which contributed to their AscI-PFGE banding pattern differences from other isolates. CONCLUSIONS: The high resolution of WGS analyses allowed the differentiation of epidemiologically unrelated isolates, as well as the elucidation of the microevolution and persistence of isolates within the scope of one outbreak. We applied a wgsMLST scheme which is essentially the outbreak-specific cgMLST. This scheme can be combined with lineage-specific cgMLST and species-specific cgMLST to maximize the resolution of WGS.

Tracing Origins of the Salmonella Bareilly Strain Causing a Food-borne Outbreak in the United States.

BACKGROUND: Using a novel combination of whole-genome sequencing (WGS) analysis and geographic metadata, we traced the origins of Salmonella Bareilly isolates collected in 2012 during a widespread food-borne outbreak in the United States associated with scraped tuna imported from India. METHODS: Using next-generation sequencing, we sequenced the complete genome of 100 Salmonella Bareilly isolates obtained from patients who consumed contaminated product, from natural sources, and from unrelated historically and geographically disparate foods. Pathogen genomes were linked to geography by projecting the phylogeny on a virtual globe and produced a transmission network. RESULTS: Phylogenetic analysis of WGS data revealed a common origin for outbreak strains, indicating that patients in Maryland and New York were infected from sources originating at a facility in India. CONCLUSIONS: These data represent the first report fully integrating WGS analysis with geographic mapping and a novel use of transmission networks. Results showed that WGS vastly improves our ability to delimit the scope and source of bacterial food-borne contamination events. Furthermore, these findings reinforce the extraordinary utility that WGS brings to global outbreak investigation as a greatly enhanced approach to protecting the human food supply chain as well as public health in general.

Practical Value of Food Pathogen Traceability through Building a Whole-Genome Sequencing Network and Database.

The FDA has created a United States-based open-source whole-genome sequencing network of state, federal, international, and commercial partners. The GenomeTrakr network represents a first-of-its-kind distributed genomic food shield for characterizing and tracing foodborne outbreak pathogens back to their sources. The GenomeTrakr network is leading investigations of outbreaks of foodborne illnesses and compliance actions with more accurate and rapid recalls of contaminated foods as well as more effective monitoring of preventive controls for food manufacturing environments. An expanded network would serve to provide an international rapid surveillance system for pathogen traceback, which is critical to support an effective public health response to bacterial outbreaks.

Whole-Genome Sequencing Analysis of Salmonella enterica Serovar Enteritidis Isolates in Chile Provides Insights into Possible Transmission between Gulls, Poultry, and Humans.

Salmonella enterica subsp. enterica serotype Enteritidis is a major cause of human salmonellosis worldwide; however, little is known about the genetic relationships between S Enteritidis clinical strains and S Enteritidis strains from other sources in Chile. We compared the whole genomes of 30 S Enteritidis strains isolated from gulls, domestic chicken eggs, and humans in Chile, to investigate their phylogenetic relationships and to establish their relatedness to international strains. Core genome multilocus sequence typing (cgMLST) analysis showed that only 246/4,065 shared loci differed among these Chilean strains, separating them into two clusters (I and II), with cluster II being further divided into five subclusters. One subcluster (subcluster 2) contained strains from all surveyed sources that differed at 1 to 18 loci (of 4,065 loci) with 1 to 18 single-nucleotide polymorphisms (SNPs), suggesting interspecies transmission of S Enteritidis in Chile. Moreover, clusters were formed by strains that were distant geographically, which could imply that gulls might be spreading the pathogen throughout the country. Our cgMLST analysis, using other S Enteritidis genomes available in the National Center for Biotechnology Information (NCBI) database, showed that S Enteritidis strains from Chile and the United States belonged to different lineages, which suggests that S Enteritidis regional markers might exist and could be used for trace-back investigations. IMPORTANCE: This study highlights the importance of gulls in the spread of Salmonella Enteritidis in Chile. We revealed a close genetic relationship between some human and gull S Enteritidis strains (with as few as 2 of 4,065 genes being different), and we also found that gull strains were present in clusters formed by strains isolated from other sources or distant locations. Together with previously published evidence, this suggests that gulls might be spreading this pathogen between different regions in Chile and that some of those strains have been transmitted to humans. Moreover, we discovered that Chilean S Enteritidis strains clustered separately from most of S Enteritidis strains isolated throughout the world (in the GenBank database) and thus it might be possible to distinguish the geographical origins of strains based on specific genomic features. This could be useful for trace-back investigations of foodborne illnesses throughout the world.

Core Genome Multilocus Sequence Typing for Identification of Globally Distributed Clonal Groups and Differentiation of Outbreak Strains of Listeria monocytogenes.

Many listeriosis outbreaks are caused by a few globally distributed clonal groups, designated clonal complexes or epidemic clones, of Listeria monocytogenes, several of which have been defined by classic multilocus sequence typing (MLST) schemes targeting 6 to 8 housekeeping or virulence genes. We have developed and evaluated core genome MLST (cgMLST) schemes and applied them to isolates from multiple clonal groups, including those associated with 39 listeriosis outbreaks. The cgMLST clusters were congruent with MLST-defined clonal groups, which had various degrees of diversity at the whole-genome level. Notably, cgMLST could distinguish among outbreak strains and epidemiologically unrelated strains of the same clonal group, which could not be achieved using classic MLST schemes. The precise selection of cgMLST gene targets may not be critical for the general identification of clonal groups and outbreak strains. cgMLST analyses further identified outbreak strains, including those associated with recent outbreaks linked to contaminated French-style cheese, Hispanic-style cheese, stone fruit, caramel apple, ice cream, and packaged leafy green salad, as belonging to major clonal groups. We further developed lineage-specific cgMLST schemes, which can include accessory genes when core genomes do not possess sufficient diversity, and this provided additional resolution over species-specific cgMLST. Analyses of isolates from different common-source listeriosis outbreaks revealed various degrees of diversity, indicating that the numbers of allelic differences should always be combined with cgMLST clustering and epidemiological evidence to define a listeriosis outbreak. IMPORTANCE: Classic multilocus sequence typing (MLST) schemes targeting internal fragments of 6 to 8 genes that define clonal complexes or epidemic clones have been widely employed to study L. monocytogenes biodiversity and its relation to pathogenicity potential and epidemiology. We demonstrated that core genome MLST schemes can be used for the simultaneous identification of clonal groups and the differentiation of individual outbreak strains and epidemiologically unrelated strains of the same clonal group. We further developed lineage-specific cgMLST schemes that targeted more genomic regions than the species-specific cgMLST schemes. Our data revealed the genome-level diversity of clonal groups defined by classic MLST schemes. Our identification of U.S. and international outbreaks caused by major clonal groups can contribute to further understanding of the global epidemiology of L. monocytogenes.

Listeria monocytogenes in Stone Fruits Linked to a Multistate Outbreak: Enumeration of Cells and Whole-Genome Sequencing.

In 2014, the identification of stone fruits contaminated with Listeria monocytogenes led to the subsequent identification of a multistate outbreak. Simultaneous detection and enumeration of L. monocytogenes were performed on 105 fruits, each weighing 127 to 145 g, collected from 7 contaminated lots. The results showed that 53.3% of the fruits yielded L. monocytogenes (lower limit of detection, 5 CFU/fruit), and the levels ranged from 5 to 2,850 CFU/fruit, with a geometric mean of 11.3 CFU/fruit (0.1 CFU/g of fruit). Two serotypes, IVb-v1 and 1/2b, were identified by a combination of PCR- and antiserum-based serotyping among isolates from fruits and their packing environment; certain fruits contained a mixture of both serotypes. Single nucleotide polymorphism (SNP)-based whole-genome sequencing (WGS) analysis clustered isolates from two case-patients with the serotype IVb-v1 isolates and distinguished outbreak-associated isolates from pulsed-field gel electrophoresis (PFGE)-matched, but epidemiologically unrelated, clinical isolates. The outbreak-associated isolates differed by up to 42 SNPs. All but one serotype 1/2b isolate formed another WGS cluster and differed by up to 17 SNPs. Fully closed genomes of isolates from the stone fruits were used as references to maximize the resolution and to increase our confidence in prophage analysis. Putative prophages were conserved among isolates of each WGS cluster. All serotype IVb-v1 isolates belonged to singleton sequence type 382 (ST382); all but one serotype 1/2b isolate belonged to clonal complex 5. IMPORTANCE: WGS proved to be an excellent tool to assist in the epidemiologic investigation of listeriosis outbreaks. The comparison at the genome level contributed to our understanding of the genetic diversity and variations among isolates involved in an outbreak or isolates associated with food and environmental samples from one facility. Fully closed genomes increased our confidence in the identification and comparison of accessory genomes. The diversity among the outbreak-associated isolates and the inclusion of PFGE-matched, but epidemiologically unrelated, isolates demonstrate the high resolution of WGS. The prevalence and enumeration data could contribute to our further understanding of the risk associated with Listeria monocytogenes contamination, especially among high-risk populations.