lunes, 27 de octubre de 2014

Genomic polish for shoe-leather epidemiology : Article : Nature Reviews Microbiology

Genomic polish for shoe-leather epidemiology : Article : Nature Reviews Microbiology

Nature Reviews Microbiology 118 (January 2013) | doi:10.1038/nrmicro2935

GENOME WATCHGenomic polish for shoe-leather epidemiology

Steven Y. C. Tong1
This month's Genome Watch highlights the advantages of using whole-genome sequencing for infectious-disease surveillance and infection control.
Genomic polish for shoe-leather epidemiology
Whole-genome sequencing has the potential to transform clinical microbiology and is emerging as a useful tool for the detection of infectious agents and for monitoring disease trends and outbreaks. Among the most prominent nosocomial pathogens are Klebsiella pneumoniae and methicillin-resistant Staphylococcus aureus (MRSA). In the United States, approximately 70% of K. pneumoniae strains that harbour the plasmid-encoded K. pneumoniae carbapenemase (KPC) gene belong to sequence type 258 (ST258), and in the United Kingdom, the predominant MRSA clone is ST22 UK EMRSA-15. Both of these multidrug-resistant bacteria are associated with infection outbreaks, but standard genotyping techniques (such as multilocus sequence typing) do not provide sufficient resolution to definitively assign particular strains to an outbreak, much less to specifically infer transmission routes between individuals. However, two recent studies combined whole-genome sequencing and shoe-leather epidemiology to overcome these limitations.
Snitkin et al.1 retrospectively sequenced KPC-encoding K. pneumoniae strains from 18 patients involved in a suspected hospital outbreak in the USA. All of the strains were closely related, with a total of 41 SNPs across their genomes, suggesting that they were likely to be part of an outbreak. The authors sequenced seven strains isolated from the index patient during her 1-month stay at the hospital, revealing that three distinct strains were present at different anatomical sites. By integrating the genomic data with detailed epidemiological information, the authors found that these distinct strains were involved in three independent transmission events from the index patient to other patients.

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