NEW YORK (GenomeWeb) – An international team led by investigators in the UK and Germany have developed a web-based resource to bring together whole-genome sequences for methicillin-resistant Staphylococcus aureus (MRSA) isolates characterized during routine surveillance or outbreaks.
As they reported today in mBio, members of the European Staphylococcal Reference Laboratory Working Group catalogued whole-genome sequence data for more than 300 invasive S. aureus strains. Combined with available drug-resistance and epidemiological data, the sequences made it possible to begin predicting features such as virulence and antibiotic resistance.
Based on such results, the team has now come up with a web-based tool called Microreact for sharing, visualizing, mapping, and analyzing S. aureus genomes in an epidemiological surveillance setting. The resource is expected to help those assessing transmission patterns as MRSA spreads from one individual to the next in a single hospital or between hospitals at different European sites.
"Our study demonstrates the potential for combining whole-genome sequencing with internet-based visualisation tools to enable public health workers and doctors to see how an epidemic is spreading and make swift decisions to end it," lead author David Aanensen, an infectious disease researcher affiliated with Imperial College London and the Wellcome Genome Campus' Centre for Genomic Pathogen Surveillance, said in a statement.
While whole-genome sequencing has been touted for its potential as a pathogen surveillance and outbreak-tracking tool, the team explained, appropriate storage, networking, and interpretation infrastructure is needed as the technology becomes more widespread.
"We emphasize the importance of large-scale routine surveys to provide the population context for more targeted or localized investigation," Aanensen and co-authors wrote, "and the development of open-access bioinformatics tools to provide the means to combine and compare independently generated data with publicly available datasets."
To begin laying the foundation for sequencing-based pathogen surveillance, the researchers sequenced 308 invasive S. aureus isolates collected at 186 hospitals from countries across Europe over six months.
Using these data, they explored the phylogenetic approaches for finding high-risk clones in the S. aureus population, along with analyses aimed at identifying antibiotic-resistance features and uncovering mobile elements related to virulence and antibiotic resistance.
While some 60 percent of the sequenced strains were still methicillin susceptible, for example, the team identified 123 MRSA isolates. The isolates clustered into half a dozen major clonal complexes and 10 minor clonal complex or sequence types, based on cues from the more than 235,000 core SNPs found in the genomes.
The majority of the MRSA isolates fell into three of the major clonal complexes, the researchers reported, though MRSA isolates turned up in other clusters as well. The MRSA-rich clonal complexes tended to contain more non-core homology group genes, they found when searching the accessory genome for virulence and resistance-related genetic elements.
In addition to testing all of the isolates for sensitivity to at least 16 different antibiotics, the team did thousands of in silico predictions, successfully predicting sensitivity or resistance nearly 99 percent of the time.
The study's authors argued that the "establishment of cumulative databases will engender a far richer understanding of the detailed dynamics underpinning clonal emergence and replacement, national and international transmission, and the horizontal transfer of core genes and [MGEs]."
"The increasing public health threat from bacterial pathogens is in large part down to the ability of these organisms to rapidly adapt through the dissemination of genes and mobile elements," they explained. "Our best chance of managing these threats in the future is to emulate as far as possible this resource and data sharing through the development of international surveillance networks and a common data exchange infrastructure."