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

We used whole-genome sequencing data to investigate historical Listeria monocytogenes clinical (n = 1,046) and nonclinical (n = 1,325) isolates from New York, USA. Applying a threshold of <20 single-nucleotide polymorphism differences for single-linkage clustering, 321 clinical isolates clustered into 85 clusters ranging from 2–33 isolates per cluster. Fourteen clusters included isolates with outbreak codes (4 clusters with New York codes and 10 with multistate codes). Three New York outbreak codes were assigned to isolates that were genetically highly related and from cases <2 months apart. Fifteen clusters included isolates that were obtained >10 years apart; 33 clusters included isolates from the same or contiguous counties. Seventeen clusters included food and environmental isolates highly related to clinical isolates. These findings suggest that some listeriosis clusters can be local and span a long period, demonstrating the importance of investigating small, localized listeriosis cases with closely related isolates, even over long timeframes.

Listeria monocytogenes (Lm) is an opportunistic foodborne pathogen responsible for gastrointestinal illnesses and life-threatening invasive infections. Antimicrobial resistance, virulence, and rapid adaptation to stressful environments in Lm lie in part on its mobile genetic elements (MGE). Here, we aim to characterize the MGE pool of a clinical Lm population using 936 genomes sampled across New York State (USA) from 2000 – 2021. We built a network based on sequence homology among putative MGEs. Within the network are communities of densely interconnected MGEs indicating high genetic similarity in their DNA regions. Although most connections involve the same MGE type, subsets within the network link different MGE types (plasmid-transposon, phage-plasmid). Phages and transposons did not share any genetic connections, suggesting impermeable barriers of exchange between them. Genes involved in stress tolerance are overrepresented in plasmids and transposons, and are mobile between vehicles. Analysis of long-read sequences of a subset of our dataset ( n  = 37) and publicly available, globally distributed complete genomes ( n  = 425) recapitulated the MGE connections we observed. Our findings reveal a structured but interconnected network of genetic exchanges between different mobile DNA vehicles. Genetic exchanges between MGEs shape Lm intra-species variation, adaptive potential, and rapid dissemination of clinically relevant traits at short timescales. This study shows that the mobile genetic elements of Listeria monocytogenes exhibit a structured but interconnected network of genetic exchanges. The authors found dense interconnections of similar sequences among phages, plasmids and transposons.

The holistic approach of One Health, which sees human, animal, plant, and environmental health as a unit, rather than discrete parts, requires not only interdisciplinary cooperation, but standardized methods for communicating and archiving data, enabling participants to easily share what they have learned and allow others to build upon their findings. Ongoing work by NCBI and the GenomeTrakr project illustrates how open data platforms can help meet the needs of federal and state regulators, public health laboratories, departments of agriculture, and universities. Here we describe how microbial pathogen surveillance can be transformed by having an open access database along with Best Practices for contributors to follow. First, we describe the open pathogen surveillance framework, hosted on the NCBI platform. We cover the current community standards for WGS quality, provide an SOP for assessing your own sequence quality and recommend QC thresholds for all submitters to follow. We then provide an overview of NCBI data submission along with step by step details. And finally, we provide curation guidance and an SOP for keeping your public data current within the database. These Best Practices can be models for other open data projects, thereby advancing the One Health goals of Findable, Accessible, Interoperable and Re-usable (FAIR) data.

Background The foodborne bacterium Listeria monocytogenes ( Lm ) causes a range of diseases, from mild gastroenteritis to invasive infections that have high fatality rate in vulnerable individuals. Understanding the population genomic structure of invasive Lm is critical to informing public health interventions and infection control policies that will be most effective especially in local and regional communities. Methods We sequenced the whole draft genomes of 936 Lm isolates from human clinical samples obtained in a two-decade active surveillance program across 58 counties in New York State, USA. Samples came mostly from blood and cerebrospinal fluid. We characterized the phylogenetic relationships, population structure, antimicrobial resistance genes, virulence genes, and mobile genetic elements. Results The population is genetically heterogenous, consisting of lineages I–IV, 89 clonal complexes, 200 sequence types, and six known serogroups. In addition to intrinsic antimicrobial resistance genes ( fosX , lin , norB , and sul ), other resistance genes tetM , tetS , ermG , msrD , and mefA were sparsely distributed in the population. Within each lineage, we identified clusters of isolates with ≤ 20 single nucleotide polymorphisms in the core genome alignment. These clusters may represent isolates that share a most recent common ancestor, e.g., they are derived from the same contamination source or demonstrate evidence of transmission or outbreak. We identified 38 epidemiologically linked clusters of isolates, confirming eight previously reported disease outbreaks and the discovery of cryptic outbreaks and undetected chains of transmission, even in the rarely reported Lm lineage III (ST3171). The presence of animal-associated lineages III and IV may suggest a possible spillover of animal-restricted strains to humans. Many transmissible clones persisted over several years and traversed distant sites across the state. Conclusions Our findings revealed the bacterial determinants of invasive listeriosis, driven mainly by the diversity of locally circulating lineages, intrinsic and mobile antimicrobial resistance and virulence genes, and persistence across geographical and temporal scales. Our findings will inform public health efforts to reduce the burden of invasive listeriosis, including the design of food safety measures, source traceback, and outbreak detection.

Misfolded neuronal proteins have been identified in a number of neurodegenerative disorders and have been implicated in the pathogenesis of diseases that include Alzheimer's disease, Parkinson's disease, prion-based dementia, Huntington's disease (HD), and other polyglutamine diseases. Although underlying mechanisms remain the subject of ongoing research, it is clear that aberrant processing, protein degradation, and aggregate formation or spurious protein association of the abnormal neuronal proteins may be critical factors in disease progression. Recent work in these diseases has demonstrated in vitro that specific engineered antibody species, peptides, or other general agents may suppress the formation of aggregates. We have modified an approach with intracellularly expressed single-chain Fv (sFv) antibodies (intrabodies) that bind with unique HD protein epitopes. In cell and tissue culture models of HD, anti-N-terminal huntingtin intrabodies (C4 sFv) reduce aggregation and cellular toxicity. Here, we present the crucial experiment of intrabody-mediated in vivo suppression of neuropathology, using a Drosophila model of HD. In the presence of the C4 sFv intrabody, the proportion of HD flies surviving to adulthood increases from 23% to 100%, and the mean and maximum lifespan of adult HD flies is significantly prolonged. Neurodegeneration and formation of visible huntingtin aggregates are slowed. We conclude from this investigation that engineered intrabodies are a potential new class of therapeutic agents for the treatment of neurodegenerative diseases. They may also serve as tools for drug discovery and validation of sites on mutant neuronal proteins that could be exploited for rational drug design.

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.

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.

We used whole-genome sequencing data to investigate historical Listeria monocytogenes clinical (n = 1,046) and nonclinical (n = 1,325) isolates from New York, USA. Applying a threshold of <20 single-nucleotide polymorphism differences for single-linkage clustering, 321 clinical isolates clustered into 85 clusters ranging from 2-33 isolates per cluster. Fourteen clusters included isolates with outbreak codes (4 clusters with New York codes and 10 with multistate codes). Three New York outbreak codes were assigned to isolates that were genetically highly related and from cases <2 months apart. Fifteen clusters included isolates that were obtained >10 years apart; 33 clusters included isolates from the same or contiguous counties. Seventeen clusters included food and environmental isolates highly related to clinical isolates. These findings suggest that some listeriosis clusters can be local and span a long period, demonstrating the importance of investigating small, localized listeriosis cases with closely related isolates, even over long timeframes.We used whole-genome sequencing data to investigate historical Listeria monocytogenes clinical (n = 1,046) and nonclinical (n = 1,325) isolates from New York, USA. Applying a threshold of <20 single-nucleotide polymorphism differences for single-linkage clustering, 321 clinical isolates clustered into 85 clusters ranging from 2-33 isolates per cluster. Fourteen clusters included isolates with outbreak codes (4 clusters with New York codes and 10 with multistate codes). Three New York outbreak codes were assigned to isolates that were genetically highly related and from cases <2 months apart. Fifteen clusters included isolates that were obtained >10 years apart; 33 clusters included isolates from the same or contiguous counties. Seventeen clusters included food and environmental isolates highly related to clinical isolates. These findings suggest that some listeriosis clusters can be local and span a long period, demonstrating the importance of investigating small, localized listeriosis cases with closely related isolates, even over long timeframes.

The advent of next-generation sequencing (NGS) has revolutionised public health microbiology. Given the potential impact of NGS, it is paramount to ensure standardisation of ‘wet’ laboratory and bioinformatic protocols and promote comparability of methods employed by different laboratories and their outputs. Therefore, one of the ambitious goals of the Global Microbial Identifier (GMI) initiative ( http://www.globalmicrobialidentifier.org/ ) has been to establish a mechanism for inter-laboratory NGS proficiency testing (PT). This report presents findings from the survey recently conducted by Working Group 4 among GMI members in order to ascertain NGS end-use requirements and attitudes towards NGS PT. The survey identified the high professional diversity of laboratories engaged in NGS-based public health projects and the wide range of capabilities within institutions, at a notable range of costs. The priority pathogens reported by respondents reflected the key drivers for NGS use (high burden disease and ‘high profile’ pathogens). The performance of and participation in PT was perceived as important by most respondents. The wide range of sequencing and bioinformatics practices reported by end-users highlights the importance of standardisation and harmonisation of NGS in public health and underpins the use of PT as a means to assuring quality. The findings of this survey will guide the design of the GMI PT program in relation to the spectrum of pathogens included, testing frequency and volume as well as technical requirements. The PT program for external quality assurance will evolve and inform the introduction of NGS into clinical and public health microbiology practice in the post-genomic era.