Characteristics of Staphylococcus aureus Strains Isolated in Poland in 1996 to 2004 That Were Deficient in Species-Specific Proteins

One hundred seventy Staphylococcus aureus isolates, collected in 1996 to 2004, were reidentified by phenotypic and genotypic methods. One hundred ten of these (65%) were confirmed, as previously denoted, to be clumping factor (CF)- or free coagulase-deficient S. aureus, based on their phenotype. Based on the CF or coagulase production, three groups of phenotypically deficient S. aureus isolates were distinguished. Group 1 encompassed CF-positive and coagulase-deficient isolates, group 2 consisted of CF-deficient and coagulase-positive isolates, and group 3 included isolates that were CF positive, had delayed coagulase activity, and were deficient in other species-specific features. All investigated strains harbored the clfA, clfB, coa, spa, and nuc genes, but the presence of their products was not detected by the phenotypic methods. Glycopeptide susceptibility testing showed that 26 isolates (23.6%) were hetero-glycopeptide-intermediate S. aureus(hGISA) or hetero-teicoplanin-intermediate S. aureus (hTISA), based on the population analysis profile. The relatedness of the isolates was evaluated by multiple-locus variable number of tandem repeats analysis, pulsed-field gel electrophoresis (PFGE), and multilocus sequence typing. The phenotypically deficient S. aureus isolates were classified into PFGE types B (ST239-III) and D (ST246-IA) and were related to the common clones, Hungarian and Iberian, respectively, which have been widely disseminated in Poland and globally. The simultaneous occurrence of hGISA/hTISA and the CF-deficient phenotypes was found for 62.1% of isolates belonging to group 2. The majority of these isolates were assigned to the Iberian clone (PFGE type D; ST247-IA). An association between the defect in coagulase and that in thermonuclease production was observed, which concerned 59.2% of isolates of group 1. The majority of these isolates belonged to the Hungarian clone (PFGE type B; ST239-III)

Whole-genome sequencing for routine pathogen surveillance in public health

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) communityoriented database infrastructure and analysis tools. IMPORTANCE The spread of antibiotic-resistant bacteria is a public health emergency of global concern, threatening medical intervention at every level of health care delivery. Several recent studies have demonstrated the promise of routine wholegenome sequencing (WGS) of bacterial pathogens for epidemiological surveillance, outbreak detection, and infection control. However, as this technology becomes more widely adopted, the key challenges of generating representative national and international data sets and the development of bioinformatic tools to manage and interpret the data become increasingly pertinent. This study provides a road map for the integration of WGS data into routine pathogen surveillance. We emphasize the importance of large-scale routine surveys to provide the population context for more targeted or localized investigation and the development of open-access bioinformatic tools to provide the means to combine and compare independently generated data with publicly available data sets.Peer reviewe