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) community-oriented database infrastructure and analysis tools.
| Original language | English |
|---|---|
| Article number | e00444-16 |
| Number of pages | 15 |
| Journal | mBio |
| Volume | 7 |
| Issue number | 3 |
| Early online date | 5 May 2016 |
| DOIs | |
| Publication status | Published - 30 Jun 2016 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- microbiology
- epidemiology
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Edward Feil
- Department of Life Sciences - Professor
- Centre for Mathematical Biology - Co-Director
- Milner Centre for Evolution
- Institute of Sustainability and Climate Change
- Centre of Excellence in Water-Based Early-Warning Systems for Health Protection (CWBE)
Person: Research & Teaching, Core staff, Affiliate staff
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