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Whole-Genome Sequencing for Routine Pathogen Surveillance in Public Health: a Population Snapshot of Invasive Staphylococcus aureus in Europe

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 epidemiologic...

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Detalles Bibliográficos
Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Society for Microbiology 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4959656/
https://www.ncbi.nlm.nih.gov/pubmed/27150362
http://dx.doi.org/10.1128/mBio.00444-16
Descripción
Sumario: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) community-oriented database infrastructure and analysis tools.