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Whole-Genome Sequencing for Routine Pathogen Surveillance in Public Health: a Population Snapshot of Invasive
David M Aanensen1, Edward J Feil2, Matthew T G Holden3
1Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, United Kingdom The Centre for Genomic Pathogen Surveillance, Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom.
Routine whole-genome sequencing (WGS) transforms bacterial pathogen surveillance by identifying high-risk clones using population data and gene content. This approach offers reliable antibiotic resistance predictions and a roadmap for future molecular epidemiology.
Area of Science:
- Microbiology
- Genomics
- Epidemiology
Background:
- Antibiotic-resistant bacteria pose a global public health emergency.
- Whole-genome sequencing (WGS) shows promise for pathogen surveillance and outbreak detection.
- Integrating WGS data requires robust datasets and bioinformatic tools.
Purpose of the Study:
- To demonstrate the utility of WGS for identifying high-risk bacterial clones.
- To provide a roadmap for integrating WGS into routine pathogen surveillance.
- To assess the reliability of in silico antibiotic resistance predictions.
Main Methods:
- Combined WGS data from 308 invasive Staphylococcus aureus isolates with epidemiological and resistance data.
- Utilized geospatial visualization software for public health data analysis.
- Inferred virulence and resistance properties based on gene content.
Main Results:
- Identified high-risk clones using population properties like clonal relatedness, abundance, and spatial structuring.
- Demonstrated that in silico antibiotic resistance predictions are as reliable as phenotypic testing.
- Showcased the integration of WGS data for a pan-European population snapshot.
Conclusions:
- WGS is a transformative tool for monitoring bacterial pathogen emergence and spread.
- A comprehensive approach requires large-scale surveys, WGS, and community-oriented database infrastructure.
- This work provides a vital roadmap for future molecular epidemiological surveillance.
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