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Nouws S, Verhaegen B, Denayer S, Crombé F, Piérard D, Bogaerts B, Vanneste K, Marchal K, Roosens NHC, De Keersmaecker SCJ. Transforming Shiga toxin-producing Escherichia coli surveillance through whole genome sequencing in food safety practices. Front Microbiol 2023; 14:1204630. [PMID: 37520372 PMCID: PMC10381951 DOI: 10.3389/fmicb.2023.1204630] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2023] [Accepted: 06/22/2023] [Indexed: 08/01/2023] Open
Abstract
Introduction Shiga toxin-producing Escherichia coli (STEC) is a gastrointestinal pathogen causing foodborne outbreaks. Whole Genome Sequencing (WGS) in STEC surveillance holds promise in outbreak prevention and confinement, in broadening STEC epidemiology and in contributing to risk assessment and source attribution. However, despite international recommendations, WGS is often restricted to assist outbreak investigation and is not yet fully implemented in food safety surveillance across all European countries, in contrast to for example in the United States. Methods In this study, WGS was retrospectively applied to isolates collected within the context of Belgian food safety surveillance and combined with data from clinical isolates to evaluate its benefits. A cross-sector WGS-based collection of 754 strains from 1998 to 2020 was analyzed. Results We confirmed that WGS in food safety surveillance allows accurate detection of genomic relationships between human cases and strains isolated from food samples, including those dispersed over time and geographical locations. Identifying these links can reveal new insights into outbreaks and direct epidemiological investigations to facilitate outbreak management. Complete WGS-based isolate characterization enabled expanding epidemiological insights related to circulating serotypes, virulence genes and antimicrobial resistance across different reservoirs. Moreover, associations between virulence genes and severe disease were determined by incorporating human metadata into the data analysis. Gaps in the surveillance system were identified and suggestions for optimization related to sample centralization, harmonizing isolation methods, and expanding sampling strategies were formulated. Discussion This study contributes to developing a representative WGS-based collection of circulating STEC strains and by illustrating its benefits, it aims to incite policymakers to support WGS uptake in food safety surveillance.
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Affiliation(s)
- Stéphanie Nouws
- Transversal Activities in Applied Genomics, Sciensano, Brussels, Belgium
- IDlab, Department of Information Technology, Ghent University—IMEC, Ghent, Belgium
| | - Bavo Verhaegen
- National Reference Laboratory for Shiga Toxin-Producing Escherichia coli (NRL STEC) and for Foodborne Outbreaks (NRL FBO), Foodborne Pathogens, Sciensano, Brussels, Belgium
| | - Sarah Denayer
- National Reference Laboratory for Shiga Toxin-Producing Escherichia coli (NRL STEC) and for Foodborne Outbreaks (NRL FBO), Foodborne Pathogens, Sciensano, Brussels, Belgium
| | - Florence Crombé
- National Reference Centre for Shiga Toxin-Producing Escherichia coli (NRC STEC), Universitair Ziekenhuis Brussel, Vrije Universiteit Brussel, Brussels, Belgium
| | - Denis Piérard
- National Reference Centre for Shiga Toxin-Producing Escherichia coli (NRC STEC), Universitair Ziekenhuis Brussel, Vrije Universiteit Brussel, Brussels, Belgium
| | - Bert Bogaerts
- Transversal Activities in Applied Genomics, Sciensano, Brussels, Belgium
| | - Kevin Vanneste
- Transversal Activities in Applied Genomics, Sciensano, Brussels, Belgium
| | - Kathleen Marchal
- IDlab, Department of Information Technology, Ghent University—IMEC, Ghent, Belgium
- Department of Plant Biotechnology and Bioinformatics, Ghent University, Ghent, Belgium
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Petrillo M, Fabbri M, Kagkli DM, Querci M, Van den Eede G, Alm E, Aytan-Aktug D, Capella-Gutierrez S, Carrillo C, Cestaro A, Chan KG, Coque T, Endrullat C, Gut I, Hammer P, Kay GL, Madec JY, Mather AE, McHardy AC, Naas T, Paracchini V, Peter S, Pightling A, Raffael B, Rossen J, Ruppé E, Schlaberg R, Vanneste K, Weber LM, Westh H, Angers-Loustau A. A roadmap for the generation of benchmarking resources for antimicrobial resistance detection using next generation sequencing. F1000Res 2022; 10:80. [PMID: 35847383 PMCID: PMC9243550 DOI: 10.12688/f1000research.39214.2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 03/10/2022] [Indexed: 11/20/2022] Open
Abstract
Next Generation Sequencing technologies significantly impact the field of Antimicrobial Resistance (AMR) detection and monitoring, with immediate uses in diagnosis and risk assessment. For this application and in general, considerable challenges remain in demonstrating sufficient trust to act upon the meaningful information produced from raw data, partly because of the reliance on bioinformatics pipelines, which can produce different results and therefore lead to different interpretations. With the constant evolution of the field, it is difficult to identify, harmonise and recommend specific methods for large-scale implementations over time. In this article, we propose to address this challenge through establishing a transparent, performance-based, evaluation approach to provide flexibility in the bioinformatics tools of choice, while demonstrating proficiency in meeting common performance standards. The approach is two-fold: first, a community-driven effort to establish and maintain “live” (dynamic) benchmarking platforms to provide relevant performance metrics, based on different use-cases, that would evolve together with the AMR field; second, agreed and defined datasets to allow the pipelines’ implementation, validation, and quality-control over time. Following previous discussions on the main challenges linked to this approach, we provide concrete recommendations and future steps, related to different aspects of the design of benchmarks, such as the selection and the characteristics of the datasets (quality, choice of pathogens and resistances, etc.), the evaluation criteria of the pipelines, and the way these resources should be deployed in the community.
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Affiliation(s)
| | - Marco Fabbri
- European Commission Joint Research Centre, Ispra, Italy
| | | | | | - Guy Van den Eede
- European Commission Joint Research Centre, Ispra, Italy
- European Commission Joint Research Centre, Geel, Belgium
| | - Erik Alm
- The European Centre for Disease Prevention and Control, Stockholm, Sweden
| | - Derya Aytan-Aktug
- National Food Institute, Technical University of Denmark, Lyngby, Denmark
| | | | - Catherine Carrillo
- Ottawa Laboratory – Carling, Canadian Food Inspection Agency, Ottawa, Ontario, Canada
| | | | - Kok-Gan Chan
- International Genome Centre, Jiangsu University, Zhenjiang, China
- Division of Genetics and Molecular Biology, Institute of Biological Sciences, Faculty of Science, University of Malaya, Kuala Lumpur, Malaysia
| | - Teresa Coque
- Servicio de Microbiología, Hospital Universitario Ramón y Cajal, Instituto Ramón y Cajal de Investigación Sanitaria (IRYCIS), Madrid, Spain
- Spanish Consortium for Research on Epidemiology and Public Health (CIBERESP), Carlos III Health Institute, Madrid, Spain
| | | | - Ivo Gut
- Centro Nacional de Análisis Genómico, Centre for Genomic Regulation (CNAG-CRG), Barcelona Institute of Technology, Barcelona, Spain
- Universitat Pompeu Fabra, Barcelona, Spain
| | - Paul Hammer
- BIOMES. NGS GmbH c/o Technische Hochschule Wildau, Wildau, Germany
| | - Gemma L. Kay
- Quadram Institute Bioscience, Norwich Research Park, Norwich, UK
| | - Jean-Yves Madec
- Unité Antibiorésistance et Virulence Bactériennes, ANSES Site de Lyon, Lyon, France
| | - Alison E. Mather
- Quadram Institute Bioscience, Norwich Research Park, Norwich, UK
- University of East Anglia, Norwich, UK
| | | | - Thierry Naas
- French-NRC for CPEs, Service de Bactériologie-Hygiène, Hôpital de Bicêtre, Le Kremlin-Bicêtre, France
| | | | - Silke Peter
- Institute of Medical Microbiology and Hygiene, University of Tübingen, Tübingen, Germany
| | - Arthur Pightling
- Center for Food Safety and Applied Nutrition, US Food and Drug Administration, College Park, MD, USA
| | | | - John Rossen
- Department of Medical Microbiology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | | | - Robert Schlaberg
- Department of Pathology, University of Utah, Salt Lake City, UT, USA
| | - Kevin Vanneste
- Transversal activities in Applied Genomics, Sciensano, Brussels, Belgium
| | - Lukas M. Weber
- Institute of Molecular Life Sciences, University of Zurich, Zurich, Switzerland
- SIB Swiss Institute of Bioinformatics, University of Zurich, Zurich, Switzerland
- Present address: Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
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Bogaerts B, Winand R, Van Braekel J, Hoffman S, Roosens NHC, De Keersmaecker SCJ, Marchal K, Vanneste K. Evaluation of WGS performance for bacterial pathogen characterization with the Illumina technology optimized for time-critical situations. Microb Genom 2021; 7:000699. [PMID: 34739368 PMCID: PMC8743554 DOI: 10.1099/mgen.0.000699] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2021] [Accepted: 09/30/2021] [Indexed: 12/29/2022] Open
Abstract
Whole genome sequencing (WGS) has become the reference standard for bacterial outbreak investigation and pathogen typing, providing a resolution unattainable with conventional molecular methods. Data generated with Illumina sequencers can however only be analysed after the sequencing run has finished, thereby losing valuable time during emergency situations. We evaluated both the effect of decreasing overall run time, and also a protocol to transfer and convert intermediary files generated by Illumina sequencers enabling real-time data analysis for multiple samples part of the same ongoing sequencing run, as soon as the forward reads have been sequenced. To facilitate implementation for laboratories operating under strict quality systems, extensive validation of several bioinformatics assays (16S rRNA species confirmation, gene detection against virulence factor and antimicrobial resistance databases, SNP-based antimicrobial resistance detection, serotype determination, and core genome multilocus sequence typing) for three bacterial pathogens (Mycobacterium tuberculosis , Neisseria meningitidis , and Shiga-toxin producing Escherichia coli ) was performed by evaluating performance in function of the two most critical sequencing parameters, i.e. read length and coverage. For the majority of evaluated bioinformatics assays, actionable results could be obtained between 14 and 22 h of sequencing, decreasing the overall sequencing-to-results time by more than half. This study aids in reducing the turn-around time of WGS analysis by facilitating a faster response in time-critical scenarios and provides recommendations for time-optimized WGS with respect to required read length and coverage to achieve a minimum level of performance for the considered bioinformatics assay(s), which can also be used to maximize the cost-effectiveness of routine surveillance sequencing when response time is not essential.
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Affiliation(s)
- Bert Bogaerts
- Transversal activities in Applied Genomics, Sciensano, Brussels (1050), Belgium
- Department of Plant Biotechnology and Bioinformatics, Ghent University, Ghent (9000), Belgium
| | - Raf Winand
- Transversal activities in Applied Genomics, Sciensano, Brussels (1050), Belgium
| | - Julien Van Braekel
- Transversal activities in Applied Genomics, Sciensano, Brussels (1050), Belgium
| | - Stefan Hoffman
- Transversal activities in Applied Genomics, Sciensano, Brussels (1050), Belgium
| | - Nancy H. C. Roosens
- Transversal activities in Applied Genomics, Sciensano, Brussels (1050), Belgium
| | | | - Kathleen Marchal
- Department of Plant Biotechnology and Bioinformatics, Ghent University, Ghent (9000), Belgium
- Department of Information Technology, IDLab, imec, Ghent University, Ghent (9000), Belgium
- Department of Genetics, University of Pretoria, 0001 Pretoria, South Africa
| | - Kevin Vanneste
- Transversal activities in Applied Genomics, Sciensano, Brussels (1050), Belgium
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4
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Bogaerts B, Delcourt T, Soetaert K, Boarbi S, Ceyssens PJ, Winand R, Van Braekel J, De Keersmaecker SCJ, Roosens NHC, Marchal K, Mathys V, Vanneste K. A Bioinformatics Whole-Genome Sequencing Workflow for Clinical Mycobacterium tuberculosis Complex Isolate Analysis, Validated Using a Reference Collection Extensively Characterized with Conventional Methods and In Silico Approaches. J Clin Microbiol 2021; 59:e00202-21. [PMID: 33789960 PMCID: PMC8316078 DOI: 10.1128/jcm.00202-21] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2021] [Accepted: 03/27/2021] [Indexed: 01/18/2023] Open
Abstract
The use of whole-genome sequencing (WGS) for routine typing of bacterial isolates has increased substantially in recent years. For Mycobacterium tuberculosis (MTB), in particular, WGS has the benefit of drastically reducing the time required to generate results compared to most conventional phenotypic methods. Consequently, a multitude of solutions for analyzing WGS MTB data have been developed, but their successful integration in clinical and national reference laboratories is hindered by the requirement for their validation, for which a consensus framework is still largely absent. We developed a bioinformatics workflow for (Illumina) WGS-based routine typing of MTB complex (MTBC) member isolates allowing complete characterization, including (sub)species confirmation and identification (16S, csb/RD, hsp65), single nucleotide polymorphism (SNP)-based antimicrobial resistance (AMR) prediction, and pathogen typing (spoligotyping, SNP barcoding, and core genome multilocus sequence typing). Workflow performance was validated on a per-assay basis using a collection of 238 in-house-sequenced MTBC isolates, extensively characterized with conventional molecular biology-based approaches supplemented with public data. For SNP-based AMR prediction, results from molecular genotyping methods were supplemented with in silico modified data sets, allowing us to greatly increase the set of evaluated mutations. The workflow demonstrated very high performance with performance metrics of >99% for all assays, except for spoligotyping, where sensitivity dropped to ∼90%. The validation framework for our WGS-based bioinformatics workflow can aid in the standardization of bioinformatics tools by the MTB community and other SNP-based applications regardless of the targeted pathogen(s). The bioinformatics workflow is available for academic and nonprofit use through the Galaxy instance of our institute at https://galaxy.sciensano.be.
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Affiliation(s)
- Bert Bogaerts
- Transversal Activities in Applied Genomics, Sciensano, Brussels, Belgium
- Department of Plant Biotechnology and Bioinformatics, Ghent University, Ghent, Belgium
| | - Thomas Delcourt
- Transversal Activities in Applied Genomics, Sciensano, Brussels, Belgium
| | | | | | | | - Raf Winand
- Transversal Activities in Applied Genomics, Sciensano, Brussels, Belgium
| | - Julien Van Braekel
- Transversal Activities in Applied Genomics, Sciensano, Brussels, Belgium
| | | | - Nancy H C Roosens
- Transversal Activities in Applied Genomics, Sciensano, Brussels, Belgium
| | - Kathleen Marchal
- Department of Information Technology, Internet Technology and Data Science Lab (IDLab), Interuniversity Microelectronics Centre (IMEC), Ghent University, Ghent, Belgium
- Department of Plant Biotechnology and Bioinformatics, Ghent University, Ghent, Belgium
- Department of Genetics, University of Pretoria, Pretoria, South Africa
| | | | - Kevin Vanneste
- Transversal Activities in Applied Genomics, Sciensano, Brussels, Belgium
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5
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Petrillo M, Fabbri M, Kagkli DM, Querci M, Van den Eede G, Alm E, Aytan-Aktug D, Capella-Gutierrez S, Carrillo C, Cestaro A, Chan KG, Coque T, Endrullat C, Gut I, Hammer P, Kay GL, Madec JY, Mather AE, McHardy AC, Naas T, Paracchini V, Peter S, Pightling A, Raffael B, Rossen J, Ruppé E, Schlaberg R, Vanneste K, Weber LM, Westh H, Angers-Loustau A. A roadmap for the generation of benchmarking resources for antimicrobial resistance detection using next generation sequencing. F1000Res 2021; 10:80. [DOI: 10.12688/f1000research.39214.1] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 02/02/2021] [Indexed: 01/12/2023] Open
Abstract
Next Generation Sequencing technologies significantly impact the field of Antimicrobial Resistance (AMR) detection and monitoring, with immediate uses in diagnosis and risk assessment. For this application and in general, considerable challenges remain in demonstrating sufficient trust to act upon the meaningful information produced from raw data, partly because of the reliance on bioinformatics pipelines, which can produce different results and therefore lead to different interpretations. With the constant evolution of the field, it is difficult to identify, harmonise and recommend specific methods for large-scale implementations over time. In this article, we propose to address this challenge through establishing a transparent, performance-based, evaluation approach to provide flexibility in the bioinformatics tools of choice, while demonstrating proficiency in meeting common performance standards. The approach is two-fold: first, a community-driven effort to establish and maintain “live” (dynamic) benchmarking platforms to provide relevant performance metrics, based on different use-cases, that would evolve together with the AMR field; second, agreed and defined datasets to allow the pipelines’ implementation, validation, and quality-control over time. Following previous discussions on the main challenges linked to this approach, we provide concrete recommendations and future steps, related to different aspects of the design of benchmarks, such as the selection and the characteristics of the datasets (quality, choice of pathogens and resistances, etc.), the evaluation criteria of the pipelines, and the way these resources should be deployed in the community.
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6
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Nouws S, Bogaerts B, Verhaegen B, Denayer S, Piérard D, Marchal K, Roosens NHC, Vanneste K, De Keersmaecker SCJ. Impact of DNA extraction on whole genome sequencing analysis for characterization and relatedness of Shiga toxin-producing Escherichia coli isolates. Sci Rep 2020; 10:14649. [PMID: 32887913 PMCID: PMC7474065 DOI: 10.1038/s41598-020-71207-3] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2019] [Accepted: 08/11/2020] [Indexed: 01/28/2023] Open
Abstract
Whole genome sequencing (WGS) has proven to be the ultimate tool for bacterial isolate characterization and relatedness determination. However, standardized and harmonized workflows, e.g. for DNA extraction, are required to ensure robust and exchangeable WGS data. Data sharing between (inter)national laboratories is essential to support foodborne pathogen control, including outbreak investigation. This study evaluated eight commercial DNA preparation kits for their potential influence on: (i) DNA quality for Nextera XT library preparation; (ii) MiSeq sequencing (data quality, read mapping against plasmid and chromosome references); and (iii) WGS data analysis, i.e. isolate characterization (serotyping, virulence and antimicrobial resistance genotyping) and phylogenetic relatedness (core genome multilocus sequence typing and single nucleotide polymorphism analysis). Shiga toxin-producing Escherichia coli (STEC) was selected as a case study. Overall, data quality and inferred phylogenetic relationships between isolates were not affected by the DNA extraction kit choice, irrespective of the presence of confounding factors such as EDTA in DNA solution buffers. Nevertheless, completeness of STEC characterization was, although not substantially, influenced by the plasmid extraction performance of the kits, especially when using Nextera XT library preparation. This study contributes to addressing the WGS challenges of standardizing protocols to support data portability and to enable full exploitation of its potential.
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Affiliation(s)
- Stéphanie Nouws
- Transversal Activities in Applied Genomics, Sciensano, Brussels, Belgium.,Department of Information Technology, IDLab, Ghent University, IMEC, Ghent, Belgium
| | - Bert Bogaerts
- Transversal Activities in Applied Genomics, Sciensano, Brussels, Belgium.,Department of Information Technology, IDLab, Ghent University, IMEC, Ghent, Belgium
| | - Bavo Verhaegen
- National Reference Laboratory for Shiga Toxin-Producing Escherichia coli (NRL-STEC), Foodborne Pathogens, Sciensano, Brussels, Belgium
| | - Sarah Denayer
- National Reference Laboratory for Shiga Toxin-Producing Escherichia coli (NRL-STEC), Foodborne Pathogens, Sciensano, Brussels, Belgium
| | - Denis Piérard
- Department of Microbiology and Infection Control, National Reference Center for Shiga Toxin-Producing Escherichia coli (NRC-STEC), Vrije Universiteit Brussel (VUB), Universitair Ziekenhuis Brussel (UZ Brussel), Brussels, Belgium
| | - Kathleen Marchal
- Department of Information Technology, IDLab, Ghent University, IMEC, Ghent, Belgium.,Department of Plant Biotechnology and Bioinformatics, Ghent University, Ghent, Belgium.,Department of Genetics, University of Pretoria, Pretoria, South Africa
| | - Nancy H C Roosens
- Transversal Activities in Applied Genomics, Sciensano, Brussels, Belgium
| | - Kevin Vanneste
- Transversal Activities in Applied Genomics, Sciensano, Brussels, Belgium
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Nouws S, Bogaerts B, Verhaegen B, Denayer S, Crombé F, De Rauw K, Piérard D, Marchal K, Vanneste K, Roosens NHC, De Keersmaecker SCJ. The Benefits of Whole Genome Sequencing for Foodborne Outbreak Investigation from the Perspective of a National Reference Laboratory in a Smaller Country. Foods 2020; 9:E1030. [PMID: 32752159 PMCID: PMC7466227 DOI: 10.3390/foods9081030] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2020] [Revised: 07/24/2020] [Accepted: 07/27/2020] [Indexed: 12/21/2022] Open
Abstract
Gradually, conventional methods for foodborne pathogen typing are replaced by whole genome sequencing (WGS). Despite studies describing the overall benefits, National Reference Laboratories of smaller countries often show slower uptake of WGS, mainly because of significant investments required to generate and analyze data of a limited amount of samples. To facilitate this process and incite policy makers to support its implementation, a Shiga toxin-producing Escherichia coli (STEC) O157:H7 (stx1+, stx2+, eae+) outbreak (2012) and a STEC O157:H7 (stx2+, eae+) outbreak (2013) were retrospectively analyzed using WGS and compared with their conventional investigations. The corresponding results were obtained, with WGS delivering even more information, e.g., on virulence and antimicrobial resistance genotypes. Besides a universal, all-in-one workflow with less hands-on-time (five versus seven actual working days for WGS versus conventional), WGS-based cgMLST-typing demonstrated increased resolution. This enabled an accurate cluster definition, which remained unsolved for the 2013 outbreak, partly due to scarce epidemiological linking with the suspect source. Moreover, it allowed detecting two and one earlier circulating STEC O157:H7 (stx1+, stx2+, eae+) and STEC O157:H7 (stx2+, eae+) strains as closely related to the 2012 and 2013 outbreaks, respectively, which might have further directed epidemiological investigation initially. Although some bottlenecks concerning centralized data-sharing, sampling strategies, and perceived costs should be considered, we delivered a proof-of-concept that even in smaller countries, WGS offers benefits for outbreak investigation, if a sufficient budget is available to ensure its implementation in surveillance. Indeed, applying a database with background isolates is critical in interpreting isolate relationships to outbreaks, and leveraging the true benefit of WGS in outbreak investigation and/or prevention.
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Affiliation(s)
- Stéphanie Nouws
- Department of Expertise and service provision, Transversal activities in Applied Genomics, Sciensano, 1050 Brussels, Belgium; (S.N.); (B.B.); (K.V.); (N.H.C.R.)
- Department of Information Technology, IDLab, imec, Ghent University, 9052 Ghent, Belgium;
| | - Bert Bogaerts
- Department of Expertise and service provision, Transversal activities in Applied Genomics, Sciensano, 1050 Brussels, Belgium; (S.N.); (B.B.); (K.V.); (N.H.C.R.)
- Department of Information Technology, IDLab, imec, Ghent University, 9052 Ghent, Belgium;
| | - Bavo Verhaegen
- National Reference Laboratory for Shiga Toxin-Producing Escherichia coli (NRL-STEC), National Reference Laboratory for Foodborne Outbreaks (NRL-FBO), Department of Infectious diseases in humans, Foodborne Pathogens, Sciensano, 1050 Brussels, Belgium; (B.V.); (S.D.)
| | - Sarah Denayer
- National Reference Laboratory for Shiga Toxin-Producing Escherichia coli (NRL-STEC), National Reference Laboratory for Foodborne Outbreaks (NRL-FBO), Department of Infectious diseases in humans, Foodborne Pathogens, Sciensano, 1050 Brussels, Belgium; (B.V.); (S.D.)
| | - Florence Crombé
- Department of Microbiology and Infection Control, National Reference Center for Shiga Toxin-Producing Escherichia coli (NRC-STEC), Vrije Universiteit Brussel (VUB), Universitair Ziekenhuis Brussel (UZ Brussel), 1090 Brussels, Belgium; (F.C.); (K.D.R.); (D.P.)
| | - Klara De Rauw
- Department of Microbiology and Infection Control, National Reference Center for Shiga Toxin-Producing Escherichia coli (NRC-STEC), Vrije Universiteit Brussel (VUB), Universitair Ziekenhuis Brussel (UZ Brussel), 1090 Brussels, Belgium; (F.C.); (K.D.R.); (D.P.)
| | - Denis Piérard
- Department of Microbiology and Infection Control, National Reference Center for Shiga Toxin-Producing Escherichia coli (NRC-STEC), Vrije Universiteit Brussel (VUB), Universitair Ziekenhuis Brussel (UZ Brussel), 1090 Brussels, Belgium; (F.C.); (K.D.R.); (D.P.)
| | - Kathleen Marchal
- Department of Information Technology, IDLab, imec, Ghent University, 9052 Ghent, Belgium;
- Department of Plant Biotechnology and Bioinformatics, Ghent University, 9052 Ghent, Belgium
- Department of Genetics, University of Pretoria, Pretoria 0083, South Africa
| | - Kevin Vanneste
- Department of Expertise and service provision, Transversal activities in Applied Genomics, Sciensano, 1050 Brussels, Belgium; (S.N.); (B.B.); (K.V.); (N.H.C.R.)
| | - Nancy H. C. Roosens
- Department of Expertise and service provision, Transversal activities in Applied Genomics, Sciensano, 1050 Brussels, Belgium; (S.N.); (B.B.); (K.V.); (N.H.C.R.)
| | - Sigrid C. J. De Keersmaecker
- Department of Expertise and service provision, Transversal activities in Applied Genomics, Sciensano, 1050 Brussels, Belgium; (S.N.); (B.B.); (K.V.); (N.H.C.R.)
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Koutsoumanis K, Allende A, Alvarez‐Ordóñez A, Bover‐Cid S, Chemaly M, Davies R, De Cesare A, Herman L, Hilbert F, Lindqvist R, Nauta M, Peixe L, Ru G, Simmons M, Skandamis P, Suffredini E, Jenkins C, Monteiro Pires S, Morabito S, Niskanen T, Scheutz F, da Silva Felício MT, Messens W, Bolton D. Pathogenicity assessment of Shiga toxin‐producing Escherichia coli (STEC) and the public health risk posed by contamination of food with STEC. EFSA J 2020. [DOI: 10.2903/j.efsa.2020.5967] [Citation(s) in RCA: 50] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023] Open
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Aerts M, Battisti A, Hendriksen R, Kempf I, Teale C, Tenhagen BA, Veldman K, Wasyl D, Guerra B, Liébana E, Thomas-López D, Belœil PA. Technical specifications on harmonised monitoring of antimicrobial resistance in zoonotic and indicator bacteria from food-producing animals and food. EFSA J 2019; 17:e05709. [PMID: 32626332 PMCID: PMC7009308 DOI: 10.2903/j.efsa.2019.5709] [Citation(s) in RCA: 63] [Impact Index Per Article: 12.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
Proposals to update the harmonised monitoring and reporting of antimicrobial resistance (AMR) from a public health perspective in Salmonella, Campylobacter coli, Campylobacter jejuni, Escherichia coli, Enterococcus faecalis, Enterococcus faecium and methicillin-resistant Staphylococcus aureus (MRSA) from food-producing animals and derived meat in the EU are presented in this report, accounting for recent trends in AMR, data collection needs and new scientific developments. Phenotypic monitoring of AMR in bacterial isolates, using microdilution methods for testing susceptibility and interpreting resistance using epidemiological cut-off values is reinforced, including further characterisation of those isolates of E. coli and Salmonella showing resistance to extended-spectrum cephalosporins and carbapenems, as well as the specific monitoring of ESBL/AmpC/carbapenemase-producing E. coli. Combinations of bacterial species, food-producing animals and meat, as well as antimicrobial panels have been reviewed and adapted, where deemed necessary. Considering differing sample sizes, numerical simulations have been performed to evaluate the related statistical power available for assessing occurrence and temporal trends in resistance, with a predetermined accuracy, to support the choice of harmonised sample size. Randomised sampling procedures, based on a generic proportionate stratified sampling process, have been reviewed and reinforced. Proposals to improve the harmonisation of monitoring of prevalence, genetic diversity and AMR in MRSA are presented. It is suggested to complement routine monitoring with specific cross-sectional surveys on MRSA in pigs and on AMR in bacteria from seafood and the environment. Whole genome sequencing (WGS) of isolates obtained from the specific monitoring of ESBL/AmpC/carbapenemase-producing E. coli is strongly advocated to be implemented, on a voluntary basis, over the validity period of the next legislation, with possible mandatory implementation by the end of the period; the gene sequences encoding for ESBL/AmpC/carbapenemases being reported to EFSA. Harmonised protocols for WGS analysis/interpretation and external quality assurance programmes are planned to be provided by the EU-Reference Laboratory on AMR.
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Collineau L, Boerlin P, Carson CA, Chapman B, Fazil A, Hetman B, McEwen SA, Parmley EJ, Reid-Smith RJ, Taboada EN, Smith BA. Integrating Whole-Genome Sequencing Data Into Quantitative Risk Assessment of Foodborne Antimicrobial Resistance: A Review of Opportunities and Challenges. Front Microbiol 2019; 10:1107. [PMID: 31231317 PMCID: PMC6558386 DOI: 10.3389/fmicb.2019.01107] [Citation(s) in RCA: 51] [Impact Index Per Article: 10.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2018] [Accepted: 05/01/2019] [Indexed: 12/20/2022] Open
Abstract
Whole-genome sequencing (WGS) will soon replace traditional phenotypic methods for routine testing of foodborne antimicrobial resistance (AMR). WGS is expected to improve AMR surveillance by providing a greater understanding of the transmission of resistant bacteria and AMR genes throughout the food chain, and therefore support risk assessment activities. At this stage, it is unclear how WGS data can be integrated into quantitative microbial risk assessment (QMRA) models and whether their integration will impact final risk estimates or the assessment of risk mitigation measures. This review explores opportunities and challenges of integrating WGS data into QMRA models that follow the Codex Alimentarius Guidelines for Risk Analysis of Foodborne AMR. We describe how WGS offers an opportunity to enhance the next-generation of foodborne AMR QMRA modeling. Instead of considering all hazard strains as equally likely to cause disease, WGS data can improve hazard identification by focusing on those strains of highest public health relevance. WGS results can be used to stratify hazards into strains with similar genetic profiles that are expected to behave similarly, e.g., in terms of growth, survival, virulence or response to antimicrobial treatment. The QMRA input distributions can be tailored to each strain accordingly, making it possible to capture the variability in the strains of interest while decreasing the uncertainty in the model. WGS also allows for a more meaningful approach to explore genetic similarity among bacterial populations found at successive stages of the food chain, improving the estimation of the probability and magnitude of exposure to AMR hazards at point of consumption. WGS therefore has the potential to substantially improve the utility of foodborne AMR QMRA models. However, some degree of uncertainty remains in relation to the thresholds of genetic similarity to be used, as well as the degree of correlation between genotypic and phenotypic profiles. The latter could be improved using a functional approach based on prediction of microbial behavior from a combination of 'omics' techniques (e.g., transcriptomics, proteomics and metabolomics). We strongly recommend that methodologies to incorporate WGS data in risk assessment be included in any future revision of the Codex Alimentarius Guidelines for Risk Analysis of Foodborne AMR.
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Affiliation(s)
- Lucie Collineau
- Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, Guelph, ON, Canada
| | - Patrick Boerlin
- Department of Pathobiology, Ontario Veterinary College, University of Guelph, Guelph, ON, Canada
| | - Carolee A. Carson
- Centre for Foodborne, Environmental and Zoonotic Infectious Diseases, Public Health Agency of Canada, Guelph, ON, Canada
| | - Brennan Chapman
- Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, Guelph, ON, Canada
- Department of Population Medicine, Ontario Veterinary College, University of Guelph, Guelph, ON, Canada
| | - Aamir Fazil
- Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, Guelph, ON, Canada
| | - Benjamin Hetman
- Department of Population Medicine, Ontario Veterinary College, University of Guelph, Guelph, ON, Canada
- National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, MB, Canada
| | - Scott A. McEwen
- Department of Population Medicine, Ontario Veterinary College, University of Guelph, Guelph, ON, Canada
| | - E. Jane Parmley
- Centre for Foodborne, Environmental and Zoonotic Infectious Diseases, Public Health Agency of Canada, Guelph, ON, Canada
| | - Richard J. Reid-Smith
- Centre for Foodborne, Environmental and Zoonotic Infectious Diseases, Public Health Agency of Canada, Guelph, ON, Canada
- Department of Population Medicine, Ontario Veterinary College, University of Guelph, Guelph, ON, Canada
| | - Eduardo N. Taboada
- National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, MB, Canada
| | - Ben A. Smith
- Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, Guelph, ON, Canada
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Pereira De Martinis EC, Almeida OGGD. Relating next-generation sequencing and bioinformatics concepts to routine microbiological testing. ELECTRONIC JOURNAL OF GENERAL MEDICINE 2019. [DOI: 10.29333/ejgm/108690] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2023]
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12
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Bogaerts B, Winand R, Fu Q, Van Braekel J, Ceyssens PJ, Mattheus W, Bertrand S, De Keersmaecker SCJ, Roosens NHC, Vanneste K. Validation of a Bioinformatics Workflow for Routine Analysis of Whole-Genome Sequencing Data and Related Challenges for Pathogen Typing in a European National Reference Center: Neisseria meningitidis as a Proof-of-Concept. Front Microbiol 2019; 10:362. [PMID: 30894839 PMCID: PMC6414443 DOI: 10.3389/fmicb.2019.00362] [Citation(s) in RCA: 32] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2018] [Accepted: 02/12/2019] [Indexed: 12/22/2022] Open
Abstract
Despite being a well-established research method, the use of whole-genome sequencing (WGS) for routine molecular typing and pathogen characterization remains a substantial challenge due to the required bioinformatics resources and/or expertise. Moreover, many national reference laboratories and centers, as well as other laboratories working under a quality system, require extensive validation to demonstrate that employed methods are "fit-for-purpose" and provide high-quality results. A harmonized framework with guidelines for the validation of WGS workflows does currently, however, not exist yet, despite several recent case studies highlighting the urgent need thereof. We present a validation strategy focusing specifically on the exhaustive characterization of the bioinformatics analysis of a WGS workflow designed to replace conventionally employed molecular typing methods for microbial isolates in a representative small-scale laboratory, using the pathogen Neisseria meningitidis as a proof-of-concept. We adapted several classically employed performance metrics specifically toward three different bioinformatics assays: resistance gene characterization (based on the ARG-ANNOT, ResFinder, CARD, and NDARO databases), several commonly employed typing schemas (including, among others, core genome multilocus sequence typing), and serogroup determination. We analyzed a core validation dataset of 67 well-characterized samples typed by means of classical genotypic and/or phenotypic methods that were sequenced in-house, allowing to evaluate repeatability, reproducibility, accuracy, precision, sensitivity, and specificity of the different bioinformatics assays. We also analyzed an extended validation dataset composed of publicly available WGS data for 64 samples by comparing results of the different bioinformatics assays against results obtained from commonly used bioinformatics tools. We demonstrate high performance, with values for all performance metrics >87%, >97%, and >90% for the resistance gene characterization, sequence typing, and serogroup determination assays, respectively, for both validation datasets. Our WGS workflow has been made publicly available as a "push-button" pipeline for Illumina data at https://galaxy.sciensano.be to showcase its implementation for non-profit and/or academic usage. Our validation strategy can be adapted to other WGS workflows for other pathogens of interest and demonstrates the added value and feasibility of employing WGS with the aim of being integrated into routine use in an applied public health setting.
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Affiliation(s)
- Bert Bogaerts
- Transversal Activities in Applied Genomics, Sciensano, Brussels, Belgium
| | - Raf Winand
- Transversal Activities in Applied Genomics, Sciensano, Brussels, Belgium
| | - Qiang Fu
- Transversal Activities in Applied Genomics, Sciensano, Brussels, Belgium
| | - Julien Van Braekel
- Transversal Activities in Applied Genomics, Sciensano, Brussels, Belgium
| | | | | | | | | | - Nancy H C Roosens
- Transversal Activities in Applied Genomics, Sciensano, Brussels, Belgium
| | - Kevin Vanneste
- Transversal Activities in Applied Genomics, Sciensano, Brussels, Belgium
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13
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Llarena A, Ribeiro‐Gonçalves BF, Nuno Silva D, Halkilahti J, Machado MP, Da Silva MS, Jaakkonen A, Isidro J, Hämäläinen C, Joenperä J, Borges V, Viera L, Gomes JP, Correia C, Lunden J, Laukkanen‐Ninios R, Fredriksson‐Ahomaa M, Bikandi J, Millan RS, Martinez‐Ballesteros I, Laorden L, Mäesaar M, Grantina‐Ievina L, Hilbert F, Garaizar J, Oleastro M, Nevas M, Salmenlinna S, Hakkinen M, Carriço JA, Rossi M. INNUENDO: A cross‐sectoral platform for the integration of genomics in the surveillance of food‐borne pathogens. ACTA ACUST UNITED AC 2018. [DOI: 10.2903/sp.efsa.2018.en-1498] [Citation(s) in RCA: 33] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
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14
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Aguilera J, Aguilera‐Gomez M, Barrucci F, Cocconcelli PS, Davies H, Denslow N, Lou Dorne J, Grohmann L, Herman L, Hogstrand C, Kass GEN, Kille P, Kleter G, Nogué F, Plant NJ, Ramon M, Schoonjans R, Waigmann E, Wright MC. EFSA Scientific Colloquium 24 – 'omics in risk assessment: state of the art and next steps. ACTA ACUST UNITED AC 2018. [DOI: 10.2903/sp.efsa.2018.en-1512] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Affiliation(s)
| | | | | | | | | | | | | | | | - Lutz Grohmann
- Federal Office of Consumer Protection and Food Safety
| | | | | | | | | | | | - Fabien Nogué
- French National Institute for Agricultural Research INRA
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