1
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Timme RE, Karsch-Mizrachi I, Waheed Z, Arita M, MacCannell D, Maguire F, Petit III R, Page AJ, Mendes CI, Nasar MI, Oluniyi P, Tyler AD, Raphenya AR, Guthrie JL, Olawoye I, Rinck G, O’Cathail C, Lees J, Cochrane G, Cummins C, Brister JR, Klimke W, Feldgarden M, Griffiths E. Putting everything in its place: using the INSDC compliant Pathogen Data Object Model to better structure genomic data submitted for public health applications. Microb Genom 2023; 9:001145. [PMID: 38085797 PMCID: PMC10763499 DOI: 10.1099/mgen.0.001145] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Accepted: 11/13/2023] [Indexed: 12/18/2023] Open
Abstract
Fast, efficient public health actions require well-organized and coordinated systems that can supply timely and accurate knowledge. Public databases of pathogen genomic data, such as the International Nucleotide Sequence Database Collaboration (INSDC), have become essential tools for efficient public health decisions. However, these international resources began primarily for academic purposes, rather than for surveillance or interventions. Now, queries need to access not only the whole genomes of multiple pathogens but also make connections using robust contextual metadata to identify issues of public health relevance. Databases that over time developed a patchwork of submission formats and requirements need to be consistently organized and coordinated internationally to allow effective searches.To help resolve these issues, we propose a common pathogen data structure called the Pathogen Data Object Model (DOM) that will formalize the minimum pieces of sequence data and contextual data necessary for general public health uses, while recognizing that submitters will likely withhold a wide range of non-public contextual data. Further, we propose contributors use the Pathogen DOM for all pathogen submissions (bacterial, viral, fungal, and parasites), which will simplify data submissions and provide a consistent and transparent data structure for downstream data analyses. We also highlight how improved submission tools can support the Pathogen DOM, offering users additional easy-to-use methods to ensure this structure is followed.
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Affiliation(s)
- Ruth E. Timme
- Center for Food Safety and Applied Nutrition, U.S. Food and Drug Administration, College Park, MD, USA
| | - Ilene Karsch-Mizrachi
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA
| | - Zahra Waheed
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, UK
| | - Masanori Arita
- DNA Data Bank of Japan, National Institute of Genetics, Mishima, Japan
| | - Duncan MacCannell
- National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Finlay Maguire
- Department of Community Health & Epidemiology, Faculty of Medicine, Dalhousie University, Halifax, Canada
- Faculty of Computer Science, Dalhousie University, Halifax, Canada
| | | | - Andrew J. Page
- Quadram Institute Bioscience, Norwich, Norfolk, UK
- Theiagen Genomics LLC, Highlands Ranch, CO, USA
| | | | - Muhammad Ibtisam Nasar
- Department of Biology, College of Science, United Arab Emirates University- Al Ain, Abu Dhabi, UAE
| | - Paul Oluniyi
- Chan Zuckerberg Biohub Network, San Francisco, CA, USA
| | - Andrea D. Tyler
- Science Technology Cores and Services, National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, Canada
| | - Amogelang R. Raphenya
- Department of Biochemistry and Biomedical Sciences and the Michael G. DeGroote Institute for Infectious Disease Research, McMaster University, Hamilton, Ontario, Canada
| | - Jennifer L. Guthrie
- Schulich School of Medicine & Dentistry, University of Western Ontario, London, Ontario, Canada
| | - Idowu Olawoye
- Schulich School of Medicine & Dentistry, University of Western Ontario, London, Ontario, Canada
| | - Gabriele Rinck
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, UK
| | - Colman O’Cathail
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, UK
| | - John Lees
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, UK
| | - Guy Cochrane
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, UK
| | - Carla Cummins
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, UK
| | - J. Rodney Brister
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA
| | - William Klimke
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA
| | - Michael Feldgarden
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA
| | - Emma Griffiths
- Faculty of Health Sciences, Simon Fraser University, Burnaby, British Columbia, Canada
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2
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Bhandari M, Poelstra JW, Kauffman M, Varghese B, Helmy YA, Scaria J, Rajashekara G. Genomic Diversity, Antimicrobial Resistance, Plasmidome, and Virulence Profiles of Salmonella Isolated from Small Specialty Crop Farms Revealed by Whole-Genome Sequencing. Antibiotics (Basel) 2023; 12:1637. [PMID: 37998839 PMCID: PMC10668983 DOI: 10.3390/antibiotics12111637] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2023] [Revised: 11/10/2023] [Accepted: 11/15/2023] [Indexed: 11/25/2023] Open
Abstract
Salmonella is the leading cause of death associated with foodborne illnesses in the USA. Difficulty in treating human salmonellosis is attributed to the development of antimicrobial resistance and the pathogenicity of Salmonella strains. Therefore, it is important to study the genetic landscape of Salmonella, such as the diversity, plasmids, and presence antimicrobial resistance genes (AMRs) and virulence genes. To this end, we isolated Salmonella from environmental samples from small specialty crop farms (SSCFs) in Northeast Ohio from 2016 to 2021; 80 Salmonella isolates from 29 Salmonella-positive samples were subjected to whole-genome sequencing (WGS). In silico serotyping revealed the presence of 15 serotypes. AMR genes were detected in 15% of the samples, with 75% exhibiting phenotypic and genotypic multidrug resistance (MDR). Plasmid analysis demonstrated the presence of nine different types of plasmids, and 75% of AMR genes were located on plasmids. Interestingly, five Salmonella Newport isolates and one Salmonella Dublin isolate carried the ACSSuT gene cassette on a plasmid, which confers resistance to ampicillin, chloramphenicol, streptomycin, sulfonamide, and tetracycline. Overall, our results show that SSCFs are a potential reservoir of Salmonella with MDR genes. Thus, regular monitoring is needed to prevent the transmission of MDR Salmonella from SSCFs to humans.
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Affiliation(s)
- Menuka Bhandari
- Center for Food Animal Health, Department of Animal Sciences, College of Food, Agricultural, and Environmental Sciences, The Ohio State University, Wooster, OH 44691, USA; (M.B.); (M.K.)
| | - Jelmer W. Poelstra
- Molecular and Cellular Imaging Center, College of Food, Agricultural, and Environmental Sciences, The Ohio State University, Wooster, OH 44691, USA;
| | - Michael Kauffman
- Center for Food Animal Health, Department of Animal Sciences, College of Food, Agricultural, and Environmental Sciences, The Ohio State University, Wooster, OH 44691, USA; (M.B.); (M.K.)
| | - Binta Varghese
- Department of Veterinary Pathobiology, Oklahoma State University, Stillwater, OK 74074, USA; (B.V.); (J.S.)
| | - Yosra A. Helmy
- Department of Veterinary Science, Martin-Gatton College of Agriculture, Food and Environment, University of Kentucky, Lexington, KY 40546, USA;
| | - Joy Scaria
- Department of Veterinary Pathobiology, Oklahoma State University, Stillwater, OK 74074, USA; (B.V.); (J.S.)
| | - Gireesh Rajashekara
- Center for Food Animal Health, Department of Animal Sciences, College of Food, Agricultural, and Environmental Sciences, The Ohio State University, Wooster, OH 44691, USA; (M.B.); (M.K.)
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3
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Tran M, Smurthwaite KS, Nghiem S, Cribb DM, Zahedi A, Ferdinand AD, Andersson P, Kirk MD, Glass K, Lancsar E. Economic evaluations of whole-genome sequencing for pathogen identification in public health surveillance and health-care-associated infections: a systematic review. THE LANCET. MICROBE 2023; 4:e953-e962. [PMID: 37683688 DOI: 10.1016/s2666-5247(23)00180-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/01/2023] [Revised: 05/31/2023] [Accepted: 06/05/2023] [Indexed: 09/10/2023]
Abstract
Whole-genome sequencing (WGS) has resulted in improvements to pathogen characterisation for the rapid investigation and management of disease outbreaks and surveillance. We conducted a systematic review to synthesise the economic evidence of WGS implementation for pathogen identification and surveillance. Of the 2285 unique publications identified through online database searches, 19 studies met the inclusion criteria. The economic evidence to support the broader application of WGS as a front-line pathogen characterisation and surveillance tool is insufficient and of low quality. WGS has been evaluated in various clinical settings, but these evaluations are predominantly investigations of a single pathogen. There are also considerable variations in the evaluation approach. Economic evaluations of costs, effectiveness, and cost-effectiveness are needed to support the implementation of WGS in public health settings.
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Affiliation(s)
- My Tran
- National Centre for Epidemiology and Population Health, Australian National University, Canberra ACT, Australia.
| | - Kayla S Smurthwaite
- National Centre for Epidemiology and Population Health, Australian National University, Canberra ACT, Australia
| | - Son Nghiem
- National Centre for Epidemiology and Population Health, Australian National University, Canberra ACT, Australia
| | - Danielle M Cribb
- National Centre for Epidemiology and Population Health, Australian National University, Canberra ACT, Australia
| | - Alireza Zahedi
- Public Health Microbiology, Forensic and Scientific Services, Queensland Health, Brisbane QLD, Australia
| | - Angeline D Ferdinand
- Microbiological Diagnostic Unit, Peter Doherty Institute, University of Melbourne, Melbourne VIC, Australia
| | - Patiyan Andersson
- Microbiological Diagnostic Unit, Peter Doherty Institute, University of Melbourne, Melbourne VIC, Australia
| | - Martyn D Kirk
- National Centre for Epidemiology and Population Health, Australian National University, Canberra ACT, Australia
| | - Kathryn Glass
- National Centre for Epidemiology and Population Health, Australian National University, Canberra ACT, Australia
| | - Emily Lancsar
- National Centre for Epidemiology and Population Health, Australian National University, Canberra ACT, Australia
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4
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Sánchez-Serrano A, Mejía L, Camaró ML, Ortolá-Malvar S, Llácer-Luna M, García-González N, González-Candelas F. Genomic Surveillance of Salmonella from the Comunitat Valenciana (Spain). Antibiotics (Basel) 2023; 12:antibiotics12050883. [PMID: 37237786 DOI: 10.3390/antibiotics12050883] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2023] [Revised: 04/28/2023] [Accepted: 05/05/2023] [Indexed: 05/28/2023] Open
Abstract
Salmonella enterica subspecies enterica is one of the most important foodborne pathogens and the causative agent of salmonellosis, which affects both humans and animals producing numerous infections every year. The study and understanding of its epidemiology are key to monitoring and controlling these bacteria. With the development of whole-genome sequencing (WGS) technologies, surveillance based on traditional serotyping and phenotypic tests of resistance is being replaced by genomic surveillance. To introduce WGS as a routine methodology for the surveillance of food-borne Salmonella in the region, we applied this technology to analyze a set of 141 S. enterica isolates obtained from various food sources between 2010 and 2017 in the Comunitat Valenciana (Spain). For this, we performed an evaluation of the most relevant Salmonella typing methods, serotyping and sequence typing, using both traditional and in silico approaches. We extended the use of WGS to detect antimicrobial resistance determinants and predicted minimum inhibitory concentrations (MICs). Finally, to understand possible contaminant sources in this region and their relationship to antimicrobial resistance (AMR), we performed cluster detection combining single-nucleotide polymorphism (SNP) pairwise distances and phylogenetic and epidemiological data. The results of in silico serotyping with WGS data were highly congruent with those of serological analyses (98.5% concordance). Multi-locus sequence typing (MLST) profiles obtained with WGS information were also highly congruent with the sequence type (ST) assignment based on Sanger sequencing (91.9% coincidence). In silico identification of antimicrobial resistance determinants and minimum inhibitory concentrations revealed a high number of resistance genes and possible resistant isolates. A combined phylogenetic and epidemiological analysis with complete genome sequences revealed relationships among isolates indicative of possible common sources for isolates with separate sampling in time and space that had not been detected from epidemiological information. As a result, we demonstrate the usefulness of WGS and in silico methods to obtain an improved characterization of S. enterica enterica isolates, allowing better surveillance of the pathogen in food products and in potential environmental and clinical samples of related interest.
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Affiliation(s)
- Andrea Sánchez-Serrano
- Joint Research Unit "Infection and Public Health", FISABIO-University of Valencia, 46020 Valencia, Spain
| | - Lorena Mejía
- Joint Research Unit "Infection and Public Health", FISABIO-University of Valencia, 46020 Valencia, Spain
- Institute for Integrative Systems Biology (I2SysBio), CSIC-University of Valencia, 46980 Valencia, Spain
- Instituto de Microbiología, Colegio de Ciencias Biológicas y Ambientales, Universidad San Francisco de Quito, Quito 170901, Ecuador
| | | | | | | | - Neris García-González
- Joint Research Unit "Infection and Public Health", FISABIO-University of Valencia, 46020 Valencia, Spain
- Institute for Integrative Systems Biology (I2SysBio), CSIC-University of Valencia, 46980 Valencia, Spain
| | - Fernando González-Candelas
- Joint Research Unit "Infection and Public Health", FISABIO-University of Valencia, 46020 Valencia, Spain
- Institute for Integrative Systems Biology (I2SysBio), CSIC-University of Valencia, 46980 Valencia, Spain
- CIBER in Epidemiology and Public Health, 28029 Madrid, Spain
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5
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Kaur S, Payne M, Luo L, Octavia S, Tanaka MM, Sintchenko V, Lan R. MGTdb: a web service and database for studying the global and local genomic epidemiology of bacterial pathogens. DATABASE 2022; 2022:6823527. [PMID: 36367311 PMCID: PMC9650772 DOI: 10.1093/database/baac094] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/10/2022] [Revised: 09/30/2022] [Accepted: 10/17/2022] [Indexed: 11/13/2022]
Abstract
Multilevel genome typing (MGT) enables the genomic characterization of bacterial isolates and the relationships among them. The MGT system describes an isolate using multiple multilocus sequence typing (MLST) schemes, referred to as levels. Thus, for a new isolate, sequence types (STs) assigned at multiple precisely defined levels can be used to type isolates at multiple resolutions. The MGT designation for isolates is stable, and the assignment is faster than the existing approaches. MGT’s utility has been demonstrated in multiple species. This paper presents a publicly accessible web service called MGTdb, which enables the assignment of MGT STs to isolates, along with their storage, retrieval and analysis. The MGTdb web service enables upload of genome data as sequence reads or alleles, which are processed and assigned MGT identifiers. Additionally, any newly sequenced isolates deposited in the National Center for Biotechnology Information’s Sequence Read Archive are also regularly retrieved (currently daily), processed, assigned MGT identifiers and made publicly available in MGTdb. Interactive visualization tools are presented to assist analysis, along with capabilities to download publicly available isolates and assignments for use with external software. MGTdb is currently available for Salmonella enterica serovars Typhimurium and Enteritidis and Vibrio cholerae. We demonstrate the usability of MGTdb through three case studies — to study the long-term national surveillance of S. Typhimurium, the local epidemiology and outbreaks of S. Typhimurium, and the global epidemiology of V. cholerae. Thus, MGTdb enables epidemiological and microbiological investigations at multiple levels of resolution for all publicly available isolates of these pathogens. Database URL: https://mgtdb.unsw.edu.au
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Affiliation(s)
- Sandeep Kaur
- School of Biotechnology and Biomolecular Sciences, University of New South Wales , New South Wales 2052, Australia
- School of Computer Science and Engineering, University of New South Wales , New South Wales 2052, Australia
| | - Michael Payne
- School of Biotechnology and Biomolecular Sciences, University of New South Wales , New South Wales 2052, Australia
| | - Lijuan Luo
- School of Biotechnology and Biomolecular Sciences, University of New South Wales , New South Wales 2052, Australia
| | - Sophie Octavia
- School of Biotechnology and Biomolecular Sciences, University of New South Wales , New South Wales 2052, Australia
| | - Mark M Tanaka
- School of Biotechnology and Biomolecular Sciences, University of New South Wales , New South Wales 2052, Australia
| | - Vitali Sintchenko
- Centre for Infectious Diseases and Microbiology—Public Health, Institute of Clinical Pathology and Medical Research—NSW Health Pathology, Westmead Hospital , New South Wales 2145, Australia
- Marie Bashir Institute for Infectious Diseases and Biosecurity, Sydney Medical School, University of Sydney , New South Wales 2006, Australia
| | - Ruiting Lan
- School of Biotechnology and Biomolecular Sciences, University of New South Wales , New South Wales 2052, Australia
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6
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Pijnacker R, van den Beld M, van der Zwaluw K, Verbruggen A, Coipan C, Segura AH, Mughini-Gras L, Franz E, Bosch T. Comparing Multiple Locus Variable-Number Tandem Repeat Analyses with Whole-Genome Sequencing as Typing Method for Salmonella Enteritidis Surveillance in The Netherlands, January 2019 to March 2020. Microbiol Spectr 2022; 10:e0137522. [PMID: 36121225 PMCID: PMC9603844 DOI: 10.1128/spectrum.01375-22] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Accepted: 08/29/2022] [Indexed: 12/30/2022] Open
Abstract
In the Netherlands, whole-genome sequencing (WGS) was implemented as routine typing tool for Salmonella Enteritidis isolates in 2019. Multiple locus variable-number tandem repeat analyses (MLVA) was performed in parallel. The objective was to determine the concordance of MLVA and WGS as typing methods for S. Enteritidis isolates. We included S. Enteritidis isolates from patients that were subtyped using MLVA and WGS-based core-genome Multilocus Sequence Typing (cgMLST) as part of the national laboratory surveillance of Salmonella during January 2019 to March 2020. The concordance of clustering based on MLVA and cgMLST, with a distance of ≤5 alleles, was assessed using the Fowlkes-Mallows (FM) index, and their discriminatory power using Simpson's diversity index. Of 439 isolates in total, 404 (92%) were typed as 32 clusters based on MLVA, with a median size of 4 isolates (range:2 to 141 isolates). Based on cgMLST, 313 (71%) isolates were typed as 48 clusters, with a median size of 3 isolates (range:2 to 39 isolates). The FM index was 0.34 on a scale from 0 to 1, where a higher value indicates greater similarity between the typing methods. The Simpson's diversity index of MLVA and cgMLST was 0.860 and 0.974, respectively. The median cgMLST distance between isolates with the same MLVA type was 27 alleles (interquartile range [IQR]:17 to 34 alleles), and 2 alleles within cgMLST clusters (IQR:1-5 alleles). This study shows the higher discriminatory power of WGS over MLVA and a poor concordance between both typing methods regarding clustering of S. Enteritidis isolates. IMPORTANCE Salmonella is the most frequently reported agent causing foodborne outbreaks and the second most common zoonoses in the European Union. The incidence of the most dominant serotype Enteritidis has increased in recent years. To differentiate between Salmonella isolates, traditional typing methods such as pulsed-field gel electrophoresis (PFGE) and multiple locus variable-number tandem repeat analyses (MLVA) are increasingly replaced with whole-genome sequencing (WGS). This study compared MLVA and WGS-based core-genome Multilocus Sequence Typing (cgMLST) as typing tools for S. Enteritidis isolates that were collected as part of the national Salmonella surveillance in the Netherlands. We found a higher discriminatory power of WGS-based cgMLST over MLVA, as well as a poor concordance between both typing methods regarding clustering of S. Enteritidis isolates. This is especially relevant for cluster delineation in outbreak investigations and confirmation of the outbreak source in trace-back investigations.
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Affiliation(s)
- Roan Pijnacker
- Centre for Infectious Disease Control, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
| | - Maaike van den Beld
- Centre for Infectious Disease Control, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
| | - Kim van der Zwaluw
- Centre for Infectious Disease Control, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
| | - Anjo Verbruggen
- Centre for Infectious Disease Control, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
| | - Claudia Coipan
- Centre for Infectious Disease Control, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
| | - Alejandra Hernandez Segura
- Centre for Infectious Disease Control, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
| | - Lapo Mughini-Gras
- Centre for Infectious Disease Control, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
- Institute for Risk Assessment Sciences, Utrecht University, Utrecht, the Netherlands
| | - Eelco Franz
- Centre for Infectious Disease Control, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
| | - Thijs Bosch
- Centre for Infectious Disease Control, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
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7
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Davedow T, Carleton H, Kubota K, Palm D, Schroeder M, Gerner-Smidt P, Al-Jardani A, Chinen I, Kam KM, Smith AM, Nadon C. PulseNet International Survey on the Implementation of Whole Genome Sequencing in Low and Middle-Income Countries for Foodborne Disease Surveillance. Foodborne Pathog Dis 2022; 19:332-340. [PMID: 35325576 PMCID: PMC10863729 DOI: 10.1089/fpd.2021.0110] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
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.
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Affiliation(s)
- Taylor Davedow
- Division of Enteric Diseases, Public Health Agency of Canada, National Microbiology Laboratory, Winnipeg, Canada
- Department of Medical Microbiology and Infectious Diseases, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Canada
| | - Heather Carleton
- Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Kristy Kubota
- Association of Public Health Laboratories, Silver Spring, Maryland, USA
| | - Daniel Palm
- European Centre for Disease Prevention and Control, Stockholm, Sweden
| | - Morgan Schroeder
- Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | | | - Amina Al-Jardani
- Central Public Health Laboratories, Ministry of Health, Muscat, Oman
| | - Isabel Chinen
- Instituto Nacional de Enfermedades Infecciosas, Administracion Nacional del Laboratorios et Institutos de Salud "Dr. Carlos G. Malbrán," Ciudad Autónoma de Buenos Aires, Buenos Aires, Argentina
| | - Kai Man Kam
- Stanley Ho Centre for Emerging Infectious Diseases, School of Public Health and Primary Care, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Anthony M Smith
- National Institute for Communicable Diseases, Johannesburg, South Africa
- Department of Medical Microbiology, School of Medicine, Faculty of Health Sciences, University of Pretoria, Pretoria, South Africa
| | - Celine Nadon
- Division of Enteric Diseases, Public Health Agency of Canada, National Microbiology Laboratory, Winnipeg, Canada
- Department of Medical Microbiology and Infectious Diseases, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Canada
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8
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Li W, Cui Q, Bai L, Fu P, Han H, Liu J, Guo Y. Application of Whole-Genome Sequencing in the National Molecular Tracing Network for Foodborne Disease Surveillance in China. Foodborne Pathog Dis 2021; 18:538-546. [PMID: 34339263 DOI: 10.1089/fpd.2020.2908] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
National Molecular Tracing Network for Foodborne Disease Surveillance (TraNet) was launched in 2013, which is the only real-time whole-genome sequencing (WGS)-based subtyping network in China for effective foodborne disease surveillance. TraNet covers three levels of public health laboratories, national, provincial, and municipal. The TraNet national databases have a total of more than 54,000 entries representing seven common foodborne bacteria from humans, food, and environments. Raw sequence data are uploaded to TraNet by Data Delivery Center. Assembled sequence data, pulsed-field gel electrophoresis (PFGE) profiles, antibiotic resistance patterns, and epidemiological data are submitted to national pathogen-specific databases managed by China National Center for Food Safety Risk Assessment. PFGE patterns and WGS-based subtyping are compared for rapid differentiation of clusters of geographically diverse foodborne infections. WGS-based TraNet has played significant roles in improving foodborne disease surveillance in China for rapid outbreak investigation, source tracking, and cluster analysis of particular pathogens across the country.
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Affiliation(s)
- Weiwei Li
- Division of Risk Surveillance II, China National Center for Food Safety Risk Assessment (CFSA), Beijing, China
| | - Qingpo Cui
- Beijing GenesClouds Information Science and Technology, Beijing, China
| | - Li Bai
- Division of Risk Surveillance II, China National Center for Food Safety Risk Assessment (CFSA), Beijing, China
| | - Ping Fu
- Division of Risk Surveillance II, China National Center for Food Safety Risk Assessment (CFSA), Beijing, China
| | - Haihong Han
- Division of Risk Surveillance II, China National Center for Food Safety Risk Assessment (CFSA), Beijing, China
| | - Jikai Liu
- Division of Risk Surveillance II, China National Center for Food Safety Risk Assessment (CFSA), Beijing, China
| | - Yunchang Guo
- Division of Risk Surveillance II, China National Center for Food Safety Risk Assessment (CFSA), Beijing, China
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9
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Payne M, Octavia S, Luu LDW, Sotomayor-Castillo C, Wang Q, Tay ACY, Sintchenko V, Tanaka MM, Lan R. Enhancing genomics-based outbreak detection of endemic Salmonella enterica serovar Typhimurium using dynamic thresholds. Microb Genom 2021; 7:000310. [PMID: 31682222 PMCID: PMC8627665 DOI: 10.1099/mgen.0.000310] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2019] [Accepted: 10/09/2019] [Indexed: 11/18/2022] Open
Abstract
Salmonella enterica serovar Typhimurium is the leading cause of salmonellosis in Australia, and the ability to identify outbreaks and their sources is vital to public health. Here, we examined the utility of whole-genome sequencing (WGS), including complete genome sequencing with Oxford Nanopore technologies, in examining 105 isolates from an endemic multi-locus variable number tandem repeat analysis (MLVA) type over 5 years. The MLVA type was very homogeneous, with 90 % of the isolates falling into groups with a five SNP cut-off. We developed a new two-step approach for outbreak detection using WGS. The first clustering at a zero single nucleotide polymorphism (SNP) cut-off was used to detect outbreak clusters that each occurred within a 4 week window and then a second clustering with dynamically increased SNP cut-offs were used to generate outbreak investigation clusters capable of identifying all outbreak cases. This approach offered optimal specificity and sensitivity for outbreak detection and investigation, in particular of those caused by endemic MLVA types or clones with low genetic diversity. We further showed that inclusion of complete genome sequences detected no additional mutational events for genomic outbreak surveillance. Phylogenetic analysis found that the MLVA type was likely to have been derived recently from a single source that persisted over 5 years, and seeded numerous sporadic infections and outbreaks. Our findings suggest that SNP cut-offs for outbreak cluster detection and public-health surveillance should be based on the local diversity of the relevant strains over time. These findings have general applicability to outbreak detection of bacterial pathogens.
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Affiliation(s)
- Michael Payne
- School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, New South Wales, Australia
| | - Sophie Octavia
- School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, New South Wales, Australia
| | - Laurence Don Wai Luu
- School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, New South Wales, Australia
| | - Cristina Sotomayor-Castillo
- Centre for Infectious Diseases and Microbiology – Public Health, Institute of Clinical Pathology and Medical Research, Westmead Hospital, New South Wales, Australia
- Marie Bashir Institute for Infectious Diseases and Biosecurity, University of Sydney, Westmead NSW, New South Wales, Australia
| | - Qinning Wang
- Centre for Infectious Diseases and Microbiology – Public Health, Institute of Clinical Pathology and Medical Research, Westmead Hospital, New South Wales, Australia
| | - Alfred Chin Yen Tay
- Pathology and Laboratory Medicine, University of Western Australia, Perth, Western Australia, Australia
| | - Vitali Sintchenko
- Centre for Infectious Diseases and Microbiology – Public Health, Institute of Clinical Pathology and Medical Research, Westmead Hospital, New South Wales, Australia
- Marie Bashir Institute for Infectious Diseases and Biosecurity, University of Sydney, Westmead NSW, New South Wales, Australia
| | - Mark M. Tanaka
- School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, New South Wales, Australia
| | - Ruiting Lan
- School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, New South Wales, Australia
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10
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Ford L, Glass K, Williamson DA, Sintchenko V, Robson JMB, Lancsar E, Stafford R, Kirk MD. Cost of whole genome sequencing for non-typhoidal Salmonella enterica. PLoS One 2021; 16:e0248561. [PMID: 33739986 PMCID: PMC7978342 DOI: 10.1371/journal.pone.0248561] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2020] [Accepted: 03/01/2021] [Indexed: 11/23/2022] Open
Abstract
Background While whole genome sequencing (WGS) may be more expensive than traditional testing and polymerase chain reaction (PCR), simple cost comparisons ignore the potential for WGS to reduce the societal costs of non-typhoidal Salmonella enterica through public health action to prevent illness. Methods We determined how many cases the use of WGS data would need to prevent to be cost-equal to serotyping and MLVA, or culture independent testing based on PCR in Australia. We then examined the costs and cost-savings of current typing methods compared with WGS in outbreak scenarios. Results A median of 275 (90% CrI -55-775) or 1.9% (90% CrI -0.4%-5.4%) of notified serotyped Salmonella cases would need to be prevented for WGS to be cost-equal to current typing methods and 1,550 (90% CrI 820–2,725) or 9.6% of all notified Salmonella cases would need to be prevented to be cost-equal to PCR. WGS is likely to result in cost savings in prolonged outbreaks, where data can support earlier public health action. Conclusions Despite currently having a higher cost per isolate, routine WGS of Salmonella was no more expensive than existing typing methods or PCR where >2% of illness was averted.
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Affiliation(s)
- Laura Ford
- Research School of Population Health, The Australian National University, Canberra, Australian Capital Territory, Australia
- * E-mail:
| | - Kathryn Glass
- Research School of Population Health, The Australian National University, Canberra, Australian Capital Territory, Australia
| | - Deborah A. Williamson
- The Peter Doherty Institute for Infection and Immunity, The University of Melbourne, Melbourne, Victoria, Australia
| | - Vitali Sintchenko
- Marie Bashir Institute for Infectious Diseases and Biosecurity, The University of Sydney, Westmead, New South Wales, Australia
- Centre for Infectious Diseases and Microbiology-Public Health, Westmead Hospital, NSW Health Pathology, Sydney, New South Wales, Australia
| | | | - Emily Lancsar
- Research School of Population Health, The Australian National University, Canberra, Australian Capital Territory, Australia
| | | | - Martyn D. Kirk
- Research School of Population Health, The Australian National University, Canberra, Australian Capital Territory, Australia
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11
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Timme RE, Wolfgang WJ, Balkey M, Venkata SLG, Randolph R, Allard M, Strain E. Optimizing open data to support one health: best practices to ensure interoperability of genomic data from bacterial pathogens. ONE HEALTH OUTLOOK 2020; 2:20. [PMID: 33103064 PMCID: PMC7568946 DOI: 10.1186/s42522-020-00026-3] [Citation(s) in RCA: 41] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/27/2020] [Accepted: 08/02/2020] [Indexed: 06/11/2023]
Abstract
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.
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Affiliation(s)
- Ruth E. Timme
- U.S. Food and Drug Administration, Center for Food Safety and Applied Nutrition, 5001 Campus Drive, College Park, MD 20740 USA
| | | | - Maria Balkey
- U.S. Food and Drug Administration, Center for Food Safety and Applied Nutrition, 5001 Campus Drive, College Park, MD 20740 USA
| | | | - Robyn Randolph
- Association of Public Health Laboratories, Silver Spring, MD USA
| | - Marc Allard
- U.S. Food and Drug Administration, Center for Food Safety and Applied Nutrition, 5001 Campus Drive, College Park, MD 20740 USA
| | - Errol Strain
- U.S. Food and Drug Administration, Center for Veterinary Medicine, Laurel, MD USA
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12
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Munck N, Njage PMK, Leekitcharoenphon P, Litrup E, Hald T. Application of Whole-Genome Sequences and Machine Learning in Source Attribution of Salmonella Typhimurium. RISK ANALYSIS : AN OFFICIAL PUBLICATION OF THE SOCIETY FOR RISK ANALYSIS 2020; 40:1693-1705. [PMID: 32515055 PMCID: PMC7540586 DOI: 10.1111/risa.13510] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/24/2019] [Revised: 05/01/2020] [Accepted: 05/04/2020] [Indexed: 06/11/2023]
Abstract
Prevention of the emergence and spread of foodborne diseases is an important prerequisite for the improvement of public health. Source attribution models link sporadic human cases of a specific illness to food sources and animal reservoirs. With the next generation sequencing technology, it is possible to develop novel source attribution models. We investigated the potential of machine learning to predict the animal reservoir from which a bacterial strain isolated from a human salmonellosis case originated based on whole-genome sequencing. Machine learning methods recognize patterns in large and complex data sets and use this knowledge to build models. The model learns patterns associated with genetic variations in bacteria isolated from the different animal reservoirs. We selected different machine learning algorithms to predict sources of human salmonellosis cases and trained the model with Danish Salmonella Typhimurium isolates sampled from broilers (n = 34), cattle (n = 2), ducks (n = 11), layers (n = 4), and pigs (n = 159). Using cgMLST as input features, the model yielded an average accuracy of 0.783 (95% CI: 0.77-0.80) in the source prediction for the random forest and 0.933 (95% CI: 0.92-0.94) for the logit boost algorithm. Logit boost algorithm was most accurate (valid accuracy: 92%, CI: 0.8706-0.9579) and predicted the origin of 81% of the domestic sporadic human salmonellosis cases. The most important source was Danish produced pigs (53%) followed by imported pigs (16%), imported broilers (6%), imported ducks (2%), Danish produced layers (2%), Danish produced cattle and imported cattle (<1%) while 18% was not predicted. Machine learning has potential for improving source attribution modeling based on sequence data. Results of such models can inform risk managers to identify and prioritize food safety interventions.
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Affiliation(s)
- Nanna Munck
- Research Group for Genomic EpidemiologyThe National Food Institute, Technical University of DenmarkKongens LyngbyDenmark
| | - Patrick Murigu Kamau Njage
- Research Group for Genomic EpidemiologyThe National Food Institute, Technical University of DenmarkKongens LyngbyDenmark
| | - Pimlapas Leekitcharoenphon
- Research Group for Genomic EpidemiologyThe National Food Institute, Technical University of DenmarkKongens LyngbyDenmark
| | - Eva Litrup
- Statens Serum InstituteCopenhagenDenmark
| | - Tine Hald
- Research Group for Genomic EpidemiologyThe National Food Institute, Technical University of DenmarkKongens LyngbyDenmark
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13
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Van Goethem N, Struelens MJ, De Keersmaecker SCJ, Roosens NHC, Robert A, Quoilin S, Van Oyen H, Devleesschauwer B. Perceived utility and feasibility of pathogen genomics for public health practice: a survey among public health professionals working in the field of infectious diseases, Belgium, 2019. BMC Public Health 2020; 20:1318. [PMID: 32867727 PMCID: PMC7456758 DOI: 10.1186/s12889-020-09428-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2019] [Accepted: 08/23/2020] [Indexed: 12/18/2022] Open
Abstract
BACKGROUND Pathogen genomics is increasingly being translated from the research setting into the activities of public health professionals operating at different levels. This survey aims to appraise the literacy level and gather the opinions of public health experts and allied professionals working in the field of infectious diseases in Belgium concerning the implementation of next-generation sequencing (NGS) in public health practice. METHODS In May 2019, Belgian public health and healthcare professionals were invited to complete an online survey containing eight main topics including background questions, general attitude towards pathogen genomics for public health practice and main concerns, genomic literacy, current and planned NGS activities, place of NGS in diagnostic microbiology pathways, data sharing obstacles, end-user requirements, and key drivers for the implementation of NGS. Descriptive statistics were used to report on the frequency distribution of multiple choice responses whereas thematic analysis was used to analyze free text responses. A multivariable logistic regression model was constructed to identify important predictors for a positive attitude towards the implementation of pathogen genomics in public health practice. RESULTS 146 out of the 753 invited public health professionals completed the survey. 63% of respondents indicated that public health agencies should be using genomics to understand and control infectious diseases. Having a high level of expertise in the field of pathogen genomics was the strongest predictor of a positive attitude (OR = 4.04, 95% CI = 1.11 - 17.23). A significantly higher proportion of data providers indicated to have followed training in the field of pathogen genomics compared to data end-users (p < 0.001). Overall, 79% of participants expressed interest in receiving further training. Main concerns were related to the cost of sequencing technologies, data sharing, data integration, interdisciplinary working, and bioinformatics expertise. CONCLUSIONS Belgian health professionals expressed favorable views about implementation of pathogen genomics in their work activities related to infectious disease surveillance and control. They expressed the need for suitable training initiatives to strengthen their competences in the field. Their perception of the utility and feasibility of pathogen genomics for public health purposes will be a key driver for its further implementation.
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Affiliation(s)
- N Van Goethem
- Scientific Directorate of Epidemiology and public health, Sciensano, J. Wytsmanstraat 14, 1050, Brussels, Belgium. .,Department of Epidemiology and Biostatistics, Institut de recherche expérimentale et clinique, Faculty of Public Health, Université catholique de Louvain, Clos Chapelle-aux-champs 30, 1200, Woluwe-Saint-Lambert, Belgium.
| | - M J Struelens
- Surveillance Section, European Centre for Disease Prevention and Control, Gustav den III:s Boulevard, 169 73 Solna, Stockholm, Sweden.,Faculté de Médecine, Université libre de Bruxelles, 808 route de Lennik, 1070, Brussels, Belgium
| | - S C J De Keersmaecker
- Transversal activities in Applied Genomics, Sciensano, J. Wytsmanstraat 14, 1050, Brussels, Belgium
| | - N H C Roosens
- Transversal activities in Applied Genomics, Sciensano, J. Wytsmanstraat 14, 1050, Brussels, Belgium
| | - A Robert
- Department of Epidemiology and Biostatistics, Institut de recherche expérimentale et clinique, Faculty of Public Health, Université catholique de Louvain, Clos Chapelle-aux-champs 30, 1200, Woluwe-Saint-Lambert, Belgium
| | - S Quoilin
- Scientific Directorate of Epidemiology and public health, Sciensano, J. Wytsmanstraat 14, 1050, Brussels, Belgium
| | - H Van Oyen
- Scientific Directorate of Epidemiology and public health, Sciensano, J. Wytsmanstraat 14, 1050, Brussels, Belgium.,Department of Public Health and Primary Care, Faculty of Medicine, Ghent University, De Pintelaan 185, 9000, Ghent, Belgium
| | - B Devleesschauwer
- Scientific Directorate of Epidemiology and public health, Sciensano, J. Wytsmanstraat 14, 1050, Brussels, Belgium.,Department of Veterinary Public Health and Food Safety, Faculty of Veterinary Medicine, Ghent University, Salisburylaan 133, 9820, Merelbeke, Belgium
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14
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Prospective Salmonella Enteritidis surveillance and outbreak detection using whole genome sequencing, Minnesota 2015-2017. Epidemiol Infect 2020; 148:e254. [PMID: 32539900 PMCID: PMC7689598 DOI: 10.1017/s0950268820001272] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
Clusters of Salmonella Enteritidis cases were identified by the Minnesota Department of Health using both pulsed-field gel electrophoresis (PFGE) and whole genome sequencing (WGS) single nucleotide polymorphism analysis from 1 January 2015 through 31 December 2017. The median turnaround time for obtaining WGS results was 11 days longer than for PFGE (12 vs. 1 day). WGS analysis more than doubled the number of clusters compared to PFGE analysis, but reduced the total number of cases included in clusters by 34%. The median cluster size was two cases for WGS compared to four for PFGE, and the median duration of WGS clusters was 27 days shorter than PFGE clusters. While the percentage of PFGE clusters with a confirmed source (46%) was higher than WGS clusters (32%), a higher percentage of cases in clusters that were confirmed as outbreaks reported the vehicle or exposure of interest for WGS (78%) than PFGE (46%). WGS cluster size was a significant predictor of an outbreak source being confirmed. WGS data have enhanced S. Enteritidis cluster investigations in Minnesota by improving the specificity of cluster case definitions and has become an integral part of the S. Enteritidis surveillance process.
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15
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Degeling C, Carter SM, van Oijen AM, McAnulty J, Sintchenko V, Braunack-Mayer A, Yarwood T, Johnson J, Gilbert GL. Community perspectives on the benefits and risks of technologically enhanced communicable disease surveillance systems: a report on four community juries. BMC Med Ethics 2020; 21:31. [PMID: 32334597 PMCID: PMC7183724 DOI: 10.1186/s12910-020-00474-6] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2020] [Accepted: 04/17/2020] [Indexed: 12/18/2022] Open
Abstract
Background Outbreaks of infectious disease cause serious and costly health and social problems. Two new technologies – pathogen whole genome sequencing (WGS) and Big Data analytics – promise to improve our capacity to detect and control outbreaks earlier, saving lives and resources. However, routinely using these technologies to capture more detailed and specific personal information could be perceived as intrusive and a threat to privacy. Method Four community juries were convened in two demographically different Sydney municipalities and two regional cities in New South Wales, Australia (western Sydney, Wollongong, Tamworth, eastern Sydney) to elicit the views of well-informed community members on the acceptability and legitimacy of:
making pathogen WGS and linked administrative data available for public health research using this information in concert with data linkage and machine learning to enhance communicable disease surveillance systems
Fifty participants of diverse backgrounds, mixed genders and ages were recruited by random-digit-dialling and topic-blinded social-media advertising. Each jury was presented with balanced factual evidence supporting different expert perspectives on the potential benefits and costs of technologically enhanced public health research and communicable disease surveillance and given the opportunity to question experts. Results Almost all jurors supported data linkage and WGS on routinely collected patient isolates for the purposes of public health research, provided standard de-identification practices were applied. However, allowing this information to be operationalised as a syndromic surveillance system was highly contentious with three juries voting in favour, and one against by narrow margins. For those in favour, support depended on several conditions related to system oversight and security being met. Those against were concerned about loss of privacy and did not trust Australian governments to run secure and effective systems. Conclusions Participants across all four events strongly supported the introduction of data linkage and pathogenomics to public health research under current research governance structures. Combining pathogen WGS with event-based data surveillance systems, however, is likely to be controversial because of a lack of public trust, even when the potential public health benefits are clear. Any suggestion of private sector involvement or commercialisation of WGS or surveillance data was unanimously rejected.
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Affiliation(s)
- Chris Degeling
- Australian Centre for Health Engagement, Evidence and Values, University of Wollongong, Wollongong, Australia. .,School of Health and Society, University of Wollongong, Wollongong, Australia.
| | - Stacy M Carter
- Australian Centre for Health Engagement, Evidence and Values, University of Wollongong, Wollongong, Australia.,School of Health and Society, University of Wollongong, Wollongong, Australia
| | - Antoine M van Oijen
- Molecular Horizons and the Illawarra Health and Medical Research Institute, University of Wollongong, Wollongong, Australia
| | | | - Vitali Sintchenko
- The Centre for Infectious Diseases and Microbiology - Public Health, Westmead, Sydney, Australia.,Marie Bashir Institute for Infectious Disease and Biosecurity, The University of Sydney, Sydney, Australia
| | - Annette Braunack-Mayer
- Australian Centre for Health Engagement, Evidence and Values, University of Wollongong, Wollongong, Australia.,School of Health and Society, University of Wollongong, Wollongong, Australia
| | - Trent Yarwood
- Cairns and Hinterland Hospital and Health Service, Cairns, Australia.,Cairns Clinical School, James Cook University, Cairns, Australia.,Rural Clinical School, University of Queensland, Brisbane, Australia
| | - Jane Johnson
- The Centre for Infectious Diseases and Microbiology - Public Health, Westmead, Sydney, Australia.,Sydney Health Ethics, School of Public Health, The University of Sydney, Sydney, Australia
| | - Gwendolyn L Gilbert
- The Centre for Infectious Diseases and Microbiology - Public Health, Westmead, Sydney, Australia.,Marie Bashir Institute for Infectious Disease and Biosecurity, The University of Sydney, Sydney, Australia.,Sydney Health Ethics, School of Public Health, The University of Sydney, Sydney, Australia
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16
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Szarvas J, Ahrenfeldt J, Cisneros JLB, Thomsen MCF, Aarestrup FM, Lund O. Large scale automated phylogenomic analysis of bacterial isolates and the Evergreen Online platform. Commun Biol 2020; 3:137. [PMID: 32198478 PMCID: PMC7083913 DOI: 10.1038/s42003-020-0869-5] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2019] [Accepted: 03/03/2020] [Indexed: 11/09/2022] Open
Abstract
Public health authorities whole-genome sequence thousands of isolates each month for microbial diagnostics and surveillance of pathogenic bacteria. The computational methods have not kept up with the deluge of data and the need for real-time results. We have therefore created a bioinformatics pipeline for rapid subtyping and continuous phylogenomic analysis of bacterial samples, suited for large-scale surveillance. The data is divided into sets by mapping to reference genomes, then consensus sequences are generated. Nucleotide based genetic distance is calculated between the sequences in each set, and isolates are clustered together at 10 single-nucleotide polymorphisms. Phylogenetic trees are inferred from the non-redundant sequences and the clustered isolates are added back. The method is accurate at grouping outbreak strains together, while discriminating them from non-outbreak strains. The pipeline is applied in Evergreen Online, which processes publicly available sequencing data from foodborne bacterial pathogens on a daily basis, updating phylogenetic trees as needed.
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Affiliation(s)
- Judit Szarvas
- Research Group for Genomic Epidemiology, National Food Institute, Technical University of Denmark, Kongens Lyngby, Denmark.
| | - Johanne Ahrenfeldt
- Research Group for Genomic Epidemiology, National Food Institute, Technical University of Denmark, Kongens Lyngby, Denmark
| | - Jose Luis Bellod Cisneros
- Research Group for Genomic Epidemiology, National Food Institute, Technical University of Denmark, Kongens Lyngby, Denmark
| | | | - Frank M Aarestrup
- Research Group for Genomic Epidemiology, National Food Institute, Technical University of Denmark, Kongens Lyngby, Denmark
| | - Ole Lund
- Research Group for Genomic Epidemiology, National Food Institute, Technical University of Denmark, Kongens Lyngby, Denmark
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17
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Status and potential of bacterial genomics for public health practice: a scoping review. Implement Sci 2019; 14:79. [PMID: 31409417 PMCID: PMC6692930 DOI: 10.1186/s13012-019-0930-2] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2018] [Accepted: 07/26/2019] [Indexed: 01/10/2023] Open
Abstract
Background Next-generation sequencing (NGS) is increasingly being translated into routine public health practice, affecting the surveillance and control of many pathogens. The purpose of this scoping review is to identify and characterize the recent literature concerning the application of bacterial pathogen genomics for public health practice and to assess the added value, challenges, and needs related to its implementation from an epidemiologist’s perspective. Methods In this scoping review, a systematic PubMed search with forward and backward snowballing was performed to identify manuscripts in English published between January 2015 and September 2018. Included studies had to describe the application of NGS on bacterial isolates within a public health setting. The studied pathogen, year of publication, country, number of isolates, sampling fraction, setting, public health application, study aim, level of implementation, time orientation of the NGS analyses, and key findings were extracted from each study. Due to a large heterogeneity of settings, applications, pathogens, and study measurements, a descriptive narrative synthesis of the eligible studies was performed. Results Out of the 275 included articles, 164 were outbreak investigations, 70 focused on strategy-oriented surveillance, and 41 on control-oriented surveillance. Main applications included the use of whole-genome sequencing (WGS) data for (1) source tracing, (2) early outbreak detection, (3) unraveling transmission dynamics, (4) monitoring drug resistance, (5) detecting cross-border transmission events, (6) identifying the emergence of strains with enhanced virulence or zoonotic potential, and (7) assessing the impact of prevention and control programs. The superior resolution over conventional typing methods to infer transmission routes was reported as an added value, as well as the ability to simultaneously characterize the resistome and virulome of the studied pathogen. However, the full potential of pathogen genomics can only be reached through its integration with high-quality contextual data. Conclusions For several pathogens, it is time for a shift from proof-of-concept studies to routine use of WGS during outbreak investigations and surveillance activities. However, some implementation challenges from the epidemiologist’s perspective remain, such as data integration, quality of contextual data, sampling strategies, and meaningful interpretations. Interdisciplinary, inter-sectoral, and international collaborations are key for an appropriate genomics-informed surveillance. Electronic supplementary material The online version of this article (10.1186/s13012-019-0930-2) contains supplementary material, which is available to authorized users.
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18
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Wilson A, Fox EM, Fegan N, Kurtböke DÍ. Comparative Genomics and Phenotypic Investigations Into Antibiotic, Heavy Metal, and Disinfectant Susceptibilities of Salmonella enterica Strains Isolated in Australia. Front Microbiol 2019; 10:1620. [PMID: 31379776 PMCID: PMC6646423 DOI: 10.3389/fmicb.2019.01620] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2019] [Accepted: 07/01/2019] [Indexed: 12/20/2022] Open
Abstract
Salmonella enterica is recognized as a major contributor of gastrointestinal illness worldwide. Concerns have been raised over the increasing prevalence of antibiotic resistant strains of Salmonella isolated from animals and food, and the role of antibiotics and other antimicrobial agents such as biocides and heavy metals in the selection and dissemination of antibiotic resistant bacteria to human hosts. In this study the antibiotic, heavy metal and disinfectant resistance genotypes and phenotypes of 19 S. enterica isolates from food-producing animals were established using whole genome sequence analysis, disc diffusion, as well as broth or agar dilution methods. This study also investigated the genomic environment of resistance genes on mobile genetic elements and chromosomal DNA. An ampicillin and streptomycin resistant S. Infantis isolate in this study harbored a β-lactamase (blaTEM–1), and two streptomycin resistance conferring genes (strA and strB) on a class 1 integron mobilized on a large conjugative plasmid. This plasmid also harbored two arsenic resistance gene cassettes. The arsenic resistance cassette, arsRCDAB, was also observed in two S. Singapore isolates with high tolerance to arsenate. A nalidixic acid resistant S. Typhimurium isolate was found to possess a mutation in gyrA resulting in amino acid change Asp87Gly and tetracycline resistant S. Typhimurium isolate was found to harbor efflux pump gene, tetA. No resistance (genotypic or phenotypic) was recorded to the disinfectants screened in this study. Taken together, results of this study showed a good correlation between predicted and measured resistances when comparing genotypic and phenotypic data, respectively. The findings of this study do not suggest resistance to clinically relevant antibiotics are widespread among Salmonella isolated from Australian food-producing animals.
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Affiliation(s)
- Annaleise Wilson
- Genecology Research Centre and the School of Science and Engineering, University of the Sunshine Coast, Maroochydore, QLD, Australia.,Food Safety and Stability Group, Agriculture and Food, CSIRO, Werribee, VIC, Australia
| | - Edward M Fox
- Food Safety and Stability Group, Agriculture and Food, CSIRO, Werribee, VIC, Australia.,Department of Applied Sciences, Northumbria University, Newcastle upon Tyne, United Kingdom
| | - Narelle Fegan
- Food Safety and Stability Group, Agriculture and Food, CSIRO, Werribee, VIC, Australia
| | - D Ípek Kurtböke
- Genecology Research Centre and the School of Science and Engineering, University of the Sunshine Coast, Maroochydore, QLD, Australia
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19
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Grundmann H, Gelband H. Antimicrobial resistance surveillance with whole genome sequencing in Africa: It's (about) time. Afr J Lab Med 2018; 7:761. [PMID: 30568897 PMCID: PMC6295830 DOI: 10.4102/ajlm.v7i2.761] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2018] [Accepted: 06/12/2018] [Indexed: 11/01/2022] Open
Affiliation(s)
- Hajo Grundmann
- Institute for Infection Prevention and Hospital Epidemiology, Medical Centre, University of Freiburg, Freiburg, Germany
| | - Hellen Gelband
- Centre for Global Health Research, University of Toronto, Ontario, Canada.,Global Public Health Consulting, Takoma Park, Maryland, United States
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Ford L, Wang Q, Stafford R, Ressler KA, Norton S, Shadbolt C, Hope K, Franklin N, Krsteski R, Carswell A, Carter GP, Seemann T, Howard P, Valcanis M, Castillo CFS, Bates J, Glass K, Williamson DA, Sintchenko V, Howden BP, Kirk MD. Seven Salmonella Typhimurium Outbreaks in Australia Linked by Trace-Back and Whole Genome Sequencing. Foodborne Pathog Dis 2018; 15:285-292. [PMID: 29638170 DOI: 10.1089/fpd.2017.2353] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023] Open
Abstract
Salmonella Typhimurium is a common cause of foodborne illness in Australia. We report on seven outbreaks of Salmonella Typhimurium multilocus variable-number tandem-repeat analysis (MLVA) 03-26-13-08-523 (European convention 2-24-12-7-0212) in three Australian states and territories investigated between November 2015 and March 2016. We identified a common egg grading facility in five of the outbreaks. While no Salmonella Typhimurium was detected at the grading facility and eggs could not be traced back to a particular farm, whole genome sequencing (WGS) of isolates from cases from all seven outbreaks indicated a common source. WGS was able to provide higher discriminatory power than MLVA and will likely link more Salmonella Typhimurium cases between states and territories in the future. National harmonization of Salmonella surveillance is important for effective implementation of WGS for Salmonella outbreak investigations.
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Affiliation(s)
- Laura Ford
- 1 National Centre for Epidemiology and Population Health, Research School of Population Health, The Australian National University , Canberra, Australia .,2 OzFoodNet, Health Protection Service , Population Health Protection and Prevention, ACT Health, Canberra, Australia
| | - Qinning Wang
- 3 Centre for Infectious Diseases and Microbiology Laboratory Services, Pathology West-Institute of Clinical Pathology and Medical Research , Sydney, Australia
| | - Russell Stafford
- 4 Communicable Diseases Branch, Prevention Division, Queensland Health , Brisbane, Australia
| | - Kelly-Anne Ressler
- 5 South Eastern Sydney Local Health District , NSW Health, Sydney, Australia
| | - Sophie Norton
- 6 Western Sydney Local Health District , NSW Health, Penrith, Australia
| | | | - Kirsty Hope
- 8 New South Wales Ministry of Health , Sydney, Australia
| | - Neil Franklin
- 8 New South Wales Ministry of Health , Sydney, Australia
| | - Radomir Krsteski
- 2 OzFoodNet, Health Protection Service , Population Health Protection and Prevention, ACT Health, Canberra, Australia
| | - Adrienne Carswell
- 2 OzFoodNet, Health Protection Service , Population Health Protection and Prevention, ACT Health, Canberra, Australia
| | - Glen P Carter
- 9 Doherty Applied Microbial Genomics, Department of Microbiology and Immunology, The University of Melbourne at The Peter Doherty Institute for Infection and Immunity , Melbourne, Australia
| | - Torsten Seemann
- 9 Doherty Applied Microbial Genomics, Department of Microbiology and Immunology, The University of Melbourne at The Peter Doherty Institute for Infection and Immunity , Melbourne, Australia
| | - Peter Howard
- 3 Centre for Infectious Diseases and Microbiology Laboratory Services, Pathology West-Institute of Clinical Pathology and Medical Research , Sydney, Australia
| | - Mary Valcanis
- 10 Microbiological Diagnostic Unit Public Health Laboratory, Department of Microbiology and Immunology, The University of Melbourne at The Peter Doherty Institute for Infection and Immunity , Melbourne, Australia
| | - Cristina Fabiola Sotomayor Castillo
- 3 Centre for Infectious Diseases and Microbiology Laboratory Services, Pathology West-Institute of Clinical Pathology and Medical Research , Sydney, Australia .,11 Sydney Medical School-Westmead, The University of Sydney , Sydney, Australia .,12 Instituto de Salud Publica , Facultad de Medicina, Universidad Austral de Chile, Valdivia, Chile .,13 Centre for Infectious Diseases and Microbiology-Public Health, Marie Bashir Institute for Infectious Diseases and Biosecurity, The University of Sydney , Sydney, Australia
| | - John Bates
- 14 Public Health Microbiology , Public & Environmental Health, Forensic and Scientific Services, Health Support Queensland, Department of Health, Coopers Plains, Australia
| | - Kathryn Glass
- 1 National Centre for Epidemiology and Population Health, Research School of Population Health, The Australian National University , Canberra, Australia
| | - Deborah A Williamson
- 9 Doherty Applied Microbial Genomics, Department of Microbiology and Immunology, The University of Melbourne at The Peter Doherty Institute for Infection and Immunity , Melbourne, Australia .,10 Microbiological Diagnostic Unit Public Health Laboratory, Department of Microbiology and Immunology, The University of Melbourne at The Peter Doherty Institute for Infection and Immunity , Melbourne, Australia
| | - Vitali Sintchenko
- 3 Centre for Infectious Diseases and Microbiology Laboratory Services, Pathology West-Institute of Clinical Pathology and Medical Research , Sydney, Australia .,13 Centre for Infectious Diseases and Microbiology-Public Health, Marie Bashir Institute for Infectious Diseases and Biosecurity, The University of Sydney , Sydney, Australia
| | - Benjamin P Howden
- 9 Doherty Applied Microbial Genomics, Department of Microbiology and Immunology, The University of Melbourne at The Peter Doherty Institute for Infection and Immunity , Melbourne, Australia .,10 Microbiological Diagnostic Unit Public Health Laboratory, Department of Microbiology and Immunology, The University of Melbourne at The Peter Doherty Institute for Infection and Immunity , Melbourne, Australia .,15 Infectious Diseases Department, Austin Health , Heidelberg, Australia
| | - Martyn D Kirk
- 1 National Centre for Epidemiology and Population Health, Research School of Population Health, The Australian National University , Canberra, Australia
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