Bacterial pathogens are one of the major threats to biosafety and environmental health, and advanced assessment is a prerequisite to combating bacterial pathogens. Currently, 16S rRNA gene sequencing is efficient in the open-view detection of bacterial pathogens. However, the taxonomic resolution and applicability of this method are limited by the domain-specific pathogen database, taxonomic profiling method, and sequencing target of 16S variable regions. Here, we present a pipeline of multiple bacterial pathogen detection (MBPD) to identify the animal, plant, and zoonotic pathogens. MBPD is based on a large, curated database of the full-length 16S genes of 1986 reported bacterial pathogen species covering 72,685 sequences. In silico comparison allowed MBPD to provide the appropriate similarity threshold for both full-length and variable-region sequencing platforms, while the subregion of V3−V4 (mean: 88.37%, accuracy rate compared to V1−V9) outperformed other variable regions in pathogen identification compared to full-length sequencing. Benchmarking on real data sets suggested the superiority of MBPD in a broader range of pathogen detections compared with other methods, including 16SPIP and MIP. Beyond detecting the known causal agent of animal, human, and plant diseases, MBPD is capable of identifying cocontaminating pathogens from biological and environmental samples. Overall, we provide a MBPD pipeline for agricultural, veterinary, medical, and environmental monitoring to achieve One Health. 

MBPD: A multiple bacterial pathogen detection pipeline for One Health practices

Whole genome sequencing (WGS) provides the highest resolution for genome-based species identification and can provide insight into the antimicrobial resistance and virulence potential of a single microbiological isolate during the diagnostic process. In contrast, metagenomic sequencing allows the analysis of DNA segments from multiple microorganisms within a community, either using an amplicon- or shotgun-based approach. However, WGS and shotgun metagenomic data are rarely combined, although such an approach may generate additive or synergistic information, critical for, e.g., patient management, infection control, and pathogen surveillance. To produce a combined workflow with actionable outputs, we need to understand the pre-to-post analytical process of both technologies. This will require specific databases storing interlinked sequencing and metadata, and also involves customized bioinformatic analytical pipelines. This review article will provide an overview of the critical steps and potential clinical application of combining WGS and metagenomics together for microbiological diagnosis.

/pdf/combination-of-whole-genome-sequencing-and-metagenomics-for-3arape73.pdf

Combination of Whole Genome Sequencing and Metagenomics for Microbiological Diagnostics

Open source DNA sequence databases have long been touted as beneficial to public health, including the facilitation of earlier detection and response to infectious disease outbreaks. Of critical importance to harnessing these benefits is the metadata which describes general and other domain specific attributes (e.g., collection location, isolate type, etc.) of a sample. Unlike the sequence data, the metadata is often incomplete and lacks adherence to an international standard. We describe the problem posed by such variable and incomplete metadata in terms of interpretative labor costs (the time and energy necessary to make sense of the signal in the genetic data), and the impact such metadata has on foodborne outbreak detection and response. Improving the quality of sequence-associated metadata would allow for earlier detection of emerging food safety hazards and allow faster response to foodborne outbreaks.

/pdf/interpretative-labor-and-the-bane-of-nonstandardized-5fgx1xu9z7.pdf

Interpretative Labor and the Bane of Nonstandardized Metadata in Public Health Surveillance and Food Safety.

There are many factors affecting the quality and safety of agricultural products in the supply chain of agricultural products. In order to ensure the quality and safety of agricultural products, suppliers and processors need to take their own quality measures to ensure the quality of agricultural products. Quality inspection departments need to strictly supervise suppliers and processors to ensure the implementation of quality measures by both parties. Within the supply chain, the decisions of these three stakeholders are affected by the initial intention, the cost of quality measures, and the penalty amount of the quality inspection department. Outside the supply chain, they are affected by government regulation and consumer feedback. This paper takes the stakeholders in the agricultural product supply chain as the object, brings suppliers, processors, and quality inspection departments into the evolutionary game model, brings the factors that affect the decision-making of these three stakeholders into the model as parameters to analyze the stability of the model in different situations, and then analyzes the factors that affect the decision-making of stakeholders through mathematical simulation according to specific examples. The results show that the enthusiasm of stakeholders to ensure the quality of agricultural products is most affected by the initial intention of each other and the cost of quality measures. At the same time, the punishment of the quality inspection department, the feedback of consumers, and the supervision of the government also play a good role in promoting quality.

/pdf/evolutionary-game-analysis-of-the-quality-of-agricultural-18rsnfh7.pdf

Evolutionary Game Analysis of the Quality of Agricultural Products in Supply Chain

Clostridium perfringens is the second leading cause of bacterial foodborne illness in the United States. The Wadsworth Center (WC) at the New York State Department of Health enumerates infectious dose from primary patient and food samples and, until recently, identified C. perfringens to the species level only. We investigated whether whole-genome sequence-based subtyping could benefit epidemiological investigations of this pathogen, as it has with other enteric organisms. We retrospectively sequenced 76 patient and food samples received between May 2010 and February 2020, including 52 samples linked epidemiologically to 13 outbreaks and 24 sporadic samples not linked to other samples. Phylogenetic trees were built using two Web-based platforms: National Centers for Biotechnology Information Pathogen Detection (NCBI-PD) and GalaxyTrakr (a Galaxy instance supported by the GenomeTrakr initiative). For GalaxyTrakr analyses, single nucleotide polymorphism (SNP) matrices and maximum-likelihood (ML) trees were generated using 3 different reference genomes. Across the four separate analyses, phylogenetic clustering was generally concordant with epidemiologically identified outbreaks. SNP diversity among phylogenetically linked samples from an outbreak ranged from 0 to 20 SNPs, excepting one outbreak ranging from 4 to 62 SNPs. Importantly, four of the 13 outbreak isolates harbored one or more samples that were phylogenetic outliers, and for two outbreaks, no samples were closely related. Two specimens were found harboring two distinct genotypes. For samples below CDC enumeration dose threshold, phylogenetic clustering was robust and linked patient and/or food samples. We concluded that WGS phylogenetic clusters (i) are largely concordant with epidemiologically defined outbreaks, irrespective of analysis platform or reference genome we employed; (ii) have limited pairwise SNP diversity, allowing phylogenetic clusters to be distinguished from sporadic cases; and (iii) can aid in epidemiological investigations by identifying outlier and polyclonal samples.

Determination of Genomic Epidemiology of Historical Clostridium perfringens Outbreaks in New York State by Use of Two Web-Based Platforms: National Center for Biotechnology Information Pathogen Detection and FDA GalaxyTrakr.

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.

https://link.springer.com/content/pdf/10.1186/s42522-020-00026-3.pdf

Optimizing open data to support one health: best practices to ensure interoperability of genomic data from bacterial pathogens

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.

/pdf/optimizing-open-data-to-support-one-health-best-practices-to-48ujnhlmcl.pdf

Optimizing Open Data to Support One Health: Best Practices to Ensure Interoperability of Genomic Data from Microbial Pathogens

For food safety agencies, the ability to quickly remove an adulterated product from commerce is essential to protecting public health. Often, such removal follows the detection of a contaminant (eg, microbiologic, chemical, radiologic) in a product through rigorous and timely laboratory testing in a government human or animal food testing laboratory. State or federal regulatory agencies, such as the US Food and Drug Administration (FDA), the Centers for Disease Control and Prevention (CDC), the US Department of Agriculture (USDA), and state food safety regulatory programs, rely on data from such testing to support enforcement actions (eg, recalls). A critical component in establishing defensibility of these data is laboratory accreditation. Obtaining International Organization for Standardization/International Electrotechnical Commission (ISO/IEC) 17025 accreditation—an internationally recognized standard of competency to which laboratories are encouraged to adhere to be technically competent—requires a thorough review of a laboratory’s quality management system by an accrediting body that is a full member and signatory of the International Laboratory Accreditation Cooperation, an international organization of various accreditation bodies, including those responsible for ISO/IEC 17025 accreditation (https://ilac. org). The accrediting body reviews the laboratory’s procedures and records, and granting accreditation certifies that the laboratory is competent to perform specific tests that support regulatory decisions about food safety. Regulatory agencies are confident that the data produced by an accredited laboratory are defensible (if challenged in court) and reliable (ie, consistent across repeated measurements), facilitating a rapid response to a contaminated product. Although accreditation is critical to determining the reliability and defensibility of laboratory data, few articles detail the efforts of the assistance programs—such as those federally funded through the cooperative agreement mechanism— that support such accreditation and their effect on food testing laboratories. Here, we describe the accomplishments of the FDA’s cooperative agreements and the partnerships among various stakeholders to support ISO/IEC 17025 accreditation of government human or animal food testing laboratories. We also discuss lessons learned and implications for the food safety community. In 2011, Congress increased the ability of the FDA to protect the nation’s food supply through passage of the Food Safety Modernization Act. The Act shifts the focus from responding to food contamination to preventing it through enhanced partnerships and integration among federal (FDA, CDC, USDA) and state (eg, state regulatory programs and food testing laboratories) food safety stakeholders. Accreditation instills confidence in laboratory data, which facilitates this integration through faster regulatory action. The FDA therefore sought to assist state human and animal food testing laboratories to become accredited or enhance their scope of accreditation by adding more methods or technologies

Strengthening Data Defensibility in Government Human and Animal Food Testing Laboratories Through Accreditation: Lessons Learned From the FDA Accreditation Support Program:

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Optimizing open data to support one health: best practices to ensure interoperability of genomic data from bacterial pathogens

Optimizing Open Data to Support One Health: Best Practices to Ensure Interoperability of Genomic Data from Microbial Pathogens

Strengthening Data Defensibility in Government Human and Animal Food Testing Laboratories Through Accreditation: Lessons Learned From the FDA Accreditation Support Program: