Whole-Genome Sequencing Reveals the Contribution of Long-Term Carriers in Staphylococcus aureus Outbreak Investigation.

Whole-genome sequencing (WGS) makes it possible to determine the relatedness of bacterial isolates at a high resolution, thereby helping to characterize outbreaks. However, for Staphylococcus aureus, the accumulation of within-host diversity during carriage might limit the interpretation of sequencing data. In this study, we hypothesized the converse, namely, that within-host diversity can in fact be exploited to reveal the involvement of long-term carriers (LTCs) in outbreaks. We analyzed WGS data from 20 historical outbreaks and applied phylogenetic methods to assess genetic relatedness and to estimate the time to most recent common ancestor (TMRCA). The findings were compared with the routine investigation results and epidemiological evidence. Outbreaks with epidemiological evidence for an LTC source had a mean estimated TMRCA (adjusted for outbreak duration) of 243 days (95% highest posterior density interval [HPD], 143 to 343 days) compared with 55 days (95% HPD, 28 to 81 days) for outbreaks lacking epidemiological evidence for an LTC (P = 0.004). A threshold of 156 days predicted LTC involvement with a sensitivity of 0.875 and a specificity of 1. We also found 6/20 outbreaks included isolates with differing antimicrobial susceptibility profiles; however, these had only modestly increased pairwise diversity (mean 17.5 single nucleotide variants [SNVs] [95% confidence interval {CI}, 17.3 to 17.8]) compared with isolates with identical antibiograms (12.7 SNVs [95% CI, 12.5 to 12.8]) (P < 0.0001). Additionally, for 2 outbreaks, WGS identified 1 or more isolates that were genetically distinct despite having the outbreak pulsed-field gel electrophoresis (PFGE) pulsotype. The duration-adjusted TMRCA allowed the involvement of LTCs in outbreaks to be identified and could be used to decide whether screening for long-term carriage (e.g., in health care workers) is warranted. Requiring identical antibiograms to trigger investigation could miss important contributors to outbreaks.

Extensive Within-Host Diversity in Fecally Carried Extended-Spectrum-Beta-Lactamase-Producing Escherichia coli Isolates: Implications for Transmission Analyses.

Studies of the transmission epidemiology of antimicrobial-resistant Escherichia coli, such as strains harboring extended-spectrum beta-lactamase (ESBL) genes, frequently use selective culture of rectal surveillance swabs to identify isolates for molecular epidemiological investigation. Typically, only single colonies are evaluated, which risks underestimating species diversity and transmission events. We sequenced the genomes of 16 E. coli colonies from each of eight fecal samples (n = 127 genomes; one failure), taken from different individuals in Cambodia, a region of high ESBL-producing E. coli prevalence. Sequence data were used to characterize both the core chromosomal diversity of E. coli isolates and their resistance/virulence gene content as a proxy measure of accessory genome diversity. The 127 E. coli genomes represented 31 distinct sequence types (STs). Seven (88%) of eight subjects carried ESBL-positive isolates, all containing blaCTX-M variants. Diversity was substantial, with a median of four STs/individual (range, 1 to 10) and wide genetic divergence at the nucleotide level within some STs. In 2/8 (25%) individuals, the same blaCTX-M variant occurred in different clones, and/or different blaCTX-M variants occurred in the same clone. Patterns of other resistance genes and common virulence factors, representing differences in the accessory genome, were also diverse within and between clones. The substantial diversity among intestinally carried ESBL-positive E. coli bacteria suggests that fecal surveillance, particularly if based on single-colony subcultures, will likely underestimate transmission events, especially in high-prevalence settings.

Prediction of Staphylococcus aureus antimicrobial resistance by whole-genome sequencing.

Whole-genome sequencing (WGS) could potentially provide a single platform for extracting all the information required to predict an organism's phenotype. However, its ability to provide accurate predictions has not yet been demonstrated in large independent studies of specific organisms. In this study, we aimed to develop a genotypic prediction method for antimicrobial susceptibilities. The whole genomes of 501 unrelated Staphylococcus aureus isolates were sequenced, and the assembled genomes were interrogated using BLASTn for a panel of known resistance determinants (chromosomal mutations and genes carried on plasmids). Results were compared with phenotypic susceptibility testing for 12 commonly used antimicrobial agents (penicillin, methicillin, erythromycin, clindamycin, tetracycline, ciprofloxacin, vancomycin, trimethoprim, gentamicin, fusidic acid, rifampin, and mupirocin) performed by the routine clinical laboratory. We investigated discrepancies by repeat susceptibility testing and manual inspection of the sequences and used this information to optimize the resistance determinant panel and BLASTn algorithm. We then tested performance of the optimized tool in an independent validation set of 491 unrelated isolates, with phenotypic results obtained in duplicate by automated broth dilution (BD Phoenix) and disc diffusion. In the validation set, the overall sensitivity and specificity of the genomic prediction method were 0.97 (95% confidence interval [95% CI], 0.95 to 0.98) and 0.99 (95% CI, 0.99 to 1), respectively, compared to standard susceptibility testing methods. The very major error rate was 0.5%, and the major error rate was 0.7%. WGS was as sensitive and specific as routine antimicrobial susceptibility testing methods. WGS is a promising alternative to culture methods for resistance prediction in S. aureus and ultimately other major bacterial pathogens.

Healthcare-associated outbreak of meticillin-resistant Staphylococcus aureus bacteraemia: role of a cryptic variant of an epidemic clone.

BACKGROUND: New strains of meticillin-resistant Staphylococcus aureus (MRSA) may be associated with changes in rates of disease or clinical presentation. Conventional typing techniques may not detect new clonal variants that underlie changes in epidemiology or clinical phenotype. AIM: To investigate the role of clonal variants of MRSA in an outbreak of MRSA bacteraemia at a hospital in England. METHODS: Bacteraemia isolates of the major UK lineages (EMRSA-15 and -16) from before and after the outbreak were analysed by whole-genome sequencing in the context of epidemiological and clinical data. For comparison, EMRSA-15 and -16 isolates from another hospital in England were sequenced. A clonal variant of EMRSA-16 was identified at the outbreak hospital and a molecular signature test designed to distinguish variant isolates among further EMRSA-16 strains. FINDINGS: By whole-genome sequencing, EMRSA-16 isolates during the outbreak showed strikingly low genetic diversity (P < 1 × 10(-6), Monte Carlo test), compared with EMRSA-15 and EMRSA-16 isolates from before the outbreak or the comparator hospital, demonstrating the emergence of a clonal variant. The variant was indistinguishable from the ancestral strain by conventional typing. This clonal variant accounted for 64/72 (89%) of EMRSA-16 bacteraemia isolates at the outbreak hospital from 2006. CONCLUSIONS: Evolutionary changes in epidemic MRSA strains not detected by conventional typing may be associated with changes in disease epidemiology. Rapid and affordable technologies for whole-genome sequencing are becoming available with the potential to identify and track the emergence of variants of highly clonal organisms.