Whole-genome sequencing for routine pathogen surveillance in public health

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Volume Title
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
Date
2016-05-01
Department
The Centre for Genomic Pathogen Surveillance
University of Bath
University of St Andrews
Drexel University
Universidad Nacional Autónoma de México
Department of Computer Science
Imperial College London
University of Groningen
National Institute of Public Health and the Environment
CHU de Nice
EUCAST Development Laboratory
Wellcome Trust
Albert-Ludwigs-Universität Freiburg
National Reference Centre for Nosocomial Infections and Antimicrobial Resistance
Klinisches Institut für Hygiene und Medizinische Mikrobiologie
Université Libre de Bruxelles
National Center of Infectious and Parasitic Diseases Bulgaria
University of Zagreb
Nicosia General Hospital
Czech National Institute of Public Health
University of Copenhagen
Statens Serum Institut
Institut national de la santé et de la recherche médicale
Robert Koch-Institut
National School of Public Health
National Institute for Health and Welfare
Semmelweis University
Agricultural Biotechnology Center Godollo
Health Protection Surveillance Centre
Trinity College Dublin
Pauls Stradins Clinical University Hospital
University of Iceland
Istituto Superiore di Sanità
Mater Dei Hospital
Norwegian University of Science and Technology
University Hospital of North Norway
Escola Superior de Saude da Cruz Vermelha Portuguesa
Rockefeller University
Centre of Quality Control in Microbiology
National Medicines Institute, Warsaw
Dr. I. Cantacuzino Institute
Instituto de Salud Carlos III
Swedish Institute for Infectious Disease Control
Antimicrobial Resistance and Healthcare Associated Infections Reference Unit
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Mcode
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Language
en
Pages
15
Series
MBIO, Volume 7, issue 3
Abstract
The implementation of routine whole-genome sequencing (WGS) promises to transform our ability to monitor the emergence and spread of bacterial pathogens. Here we combined WGS data from 308 invasive Staphylococcus aureus isolates corresponding to a pan-European population snapshot, with epidemiological and resistance data. Geospatial visualization of the data is made possible by a generic software tool designed for public health purposes that is available at the project URL (http:// www.microreact.org/project/EkUvg9uY?tt=rc). Our analysis demonstrates that high-risk clones can be identified on the basis of population level properties such as clonal relatedness, abundance, and spatial structuring and by inferring virulence and resistance properties on the basis of gene content. We also show that in silico predictions of antibiotic resistance profiles are at least as reliable as phenotypic testing. We argue that this work provides a comprehensive road map illustrating the three vital components for future molecular epidemiological surveillance: (i) large-scale structured surveys, (ii) WGS, and (iii) communityoriented database infrastructure and analysis tools. IMPORTANCE The spread of antibiotic-resistant bacteria is a public health emergency of global concern, threatening medical intervention at every level of health care delivery. Several recent studies have demonstrated the promise of routine wholegenome sequencing (WGS) of bacterial pathogens for epidemiological surveillance, outbreak detection, and infection control. However, as this technology becomes more widely adopted, the key challenges of generating representative national and international data sets and the development of bioinformatic tools to manage and interpret the data become increasingly pertinent. This study provides a road map for the integration of WGS data into routine pathogen surveillance. We emphasize the importance of large-scale routine surveys to provide the population context for more targeted or localized investigation and the development of open-access bioinformatic tools to provide the means to combine and compare independently generated data with publicly available data sets.
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Aanensen , D M , Feil , E J , Holden , M T G , Dordel , J , Yeats , C A , Fedosejev , A , Goater , R , Castillo-Ramírez , S , Corander , J , Colijn , C , Chlebowicz , M A , Schouls , L , Heck , M , Pluister , G , Ruimy , R , Kahlmeter , G , Åhman , J , Matuschek , E , Friedrich , A W , Parkhill , J , Bentley , S D , Spratt , B G , Grundmann , H , Krziwanek , K , Stumvoll , S , Koller , W , Denis , O , Struelens , M , Nashev , D , Budimir , A , Kalenic , S , Pieridou-Bagatzouni , D , Jakubu , V , Zemlickova , H , Westh , H , Larsen , A R , Skov , R , Laurent , F , Ettienne , J , Strommenger , B , Witte , W , Vourli , S , Vatopoulos , A , Vainio , A , Vuopio-Varkila , J , Fuzi , M , Ungvári , E , Murchan , S , Rossney , A , Miklasevics , E , Balode , A , Haraldsson , G , Kristinsson , K G , Monaco , M , Pantosti , A , Borg , M , Van Santen-Verheuvel , M , Huijsdens , X , Marstein , L , Jacobsen , T , Simonsen , G S , Airesde-Sousa , M , De Lencastre , H , Luczak-Kadlubowska , A , Hryniewicz , W , Straut , M , Codita , I , Perez-Vazquez , M , Iglesias , J O , Spik , V C , Mueller-Premru , M , Haeggman , S , Olsson-Liljequist , B , Ellington , M & Kearns , A 2016 , ' Whole-genome sequencing for routine pathogen surveillance in public health : A population snapshot of invasive Staphylococcus aureus in Europe ' , MBIO , vol. 7 , no. 3 , e00444-16 . https://doi.org/10.1128/mBio.00444-16