Browsing by Author "Dordel, Janina"
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Item Whole-genome sequencing for routine pathogen surveillance in public health: A population snapshot of invasive Staphylococcus aureus in Europe(2016-05-01) Aanensen, David M.; Feil, Edward J.; Holden, Matthew T G; Dordel, Janina; Yeats, Corin A.; Fedosejev, Artemij; Goater, Richard; Castillo-Ramírez, Santiago; Corander, Jukka; Colijn, Caroline; Chlebowicz, Monika A.; Schouls, Leo; Heck, Max; Pluister, Gerlinde; Ruimy, Raymond; Kahlmeter, Gunnar; Åhman, Jenny; Matuschek, Erika; Friedrich, Alexander W.; Parkhill, Julian; Bentley, Stephen D.; Spratt, Brian G.; Grundmann, Hajo; Krziwanek, Karina; Stumvoll, Sabine; Koller, Walter; Denis, Olivier; Struelens, Marc; Nashev, Dimitr; Budimir, Ana; Kalenic, Smilja; Pieridou-Bagatzouni, Despo; Jakubu, Vladislav; Zemlickova, Helena; Westh, Henrik; Larsen, Anders Rhod; Skov, Robert; Laurent, Frederic; Ettienne, Jerome; Strommenger, Birgit; Witte, Wolfgang; Vourli, Sofia; Vatopoulos, Alkis; Vainio, Anni; Vuopio-Varkila, Jaana; Fuzi, Miklos; Ungvári, Erika; Murchan, Stephan; Rossney, Angela; Miklasevics, Edvins; Balode, Arta; Haraldsson, Gunnsteinn; Kristinsson, Karl G.; Monaco, Monica; Pantosti, Annalisa; Borg, Michael; Van Santen-Verheuvel, Marga; Huijsdens, Xander; Marstein, Lillian; Jacobsen, Trond; Simonsen, Gunnar Skov; Airesde-Sousa, Marta; De Lencastre, Herminia; Luczak-Kadlubowska, Agnieszka; Hryniewicz, Waleria; Straut, Monica; Codita, Irina; Perez-Vazquez, Maria; Iglesias, Jesus Oteo; Spik, Vesna Cvitkovic; Mueller-Premru, Manica; Haeggman, Sara; Olsson-Liljequist, Barbro; Ellington, Matthew; Kearns, Angela; Department of Computer Science; Myllymäki Petri group (HIIT); Helsinki Institute for Information Technology (HIIT); Centre for Genomic Pathogen Surveillance; University of Bath; University of St Andrews; Drexel University; Universidad Nacional Autónoma de México; 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; Finnish Institute for Health and Welfare (THL); 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 UnitThe 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.