TY - JOUR
T1 - Whole-genome sequencing for routine pathogen surveillance in Public Health
T2 - a population snapshot of invasive staphylococcus aureus in Europe
AU - ESCMID Study Group on Molecular Epidemiological Markers (ESGEM)
AU - European Staphylococcal Reference Laboratory Working Group
AU - Aanensen, David M
AU - Feil, Edward
AU - Holden, Matthew T G
AU - Dordel, Janina
AU - Yeats, Corin A.
AU - Fedosejev, Artemij
AU - Goater, Richard
AU - Castillo-Ramirez, Santiago
AU - Corander, Jukka
AU - Colijn, Caroline
AU - Chlebowicz, Monika A
AU - Schouls, Leo
AU - Heck, Max
AU - Pluister, Gerlinde
AU - Ruimy, R
AU - Kahlmeter, Gunnar
AU - Ahman, Jenny
AU - Matuschek, Erika
AU - Friedrich, Alexander W.
AU - Parkhill, Julian
AU - Bentley, Stephen D
AU - Spratt, Brian G
AU - Grundmann, Hajo
PY - 2016/6/30
Y1 - 2016/6/30
N2 - 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.
AB - 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.
KW - microbiology
KW - epidemiology
UR - http://dx.doi.org/10.1128/mBio.00444-16
UR - http://dx.doi.org/10.1128/mBio.00444-16
U2 - 10.1128/mBio.00444-16
DO - 10.1128/mBio.00444-16
M3 - Article
VL - 7
JO - mBio
JF - mBio
SN - 2161-2129
IS - 3
M1 - e00444-16
ER -