Chandler Roe | Search bioRxiv

bioRxiv2016

Whole genome SNP typing to investigate methicillin-resistant Staphylococcus aureus carriage in a health-care provider as the source of multiple surgical site infections.

BackgroundPrevention of nosocomial transmission of infections is a central responsibility in the healthcare environment, and accurate identification of transmission events presents the first challenge. Phylogenetic analysis based on whole genome sequencing provides a high-resolution approach for accurately relating isolates to one another, allowing precise identification or exclusion of transmission events and sources for nearly all cases. We sequenced 24 methicillin-resistant Staphylococcus aureus (MRSA) genomes to retrospectively investigate a suspected point source of three surgical site infections (SSIs) that occurred over a one-year period. The source of transmission was believed to be a surgical team member colonized with MRSA, involved in all surgeries preceding the SSI cases, who was subsequently decolonized. Genetic relatedness among isolates was determined using whole genome single nucleotide polymorphism (SNP) data.\n\nResultsWhole genome SNP typing (WGST) revealed 283 informative SNPs between the surgical team members isolate and the closest SSI isolate. The second isolate was 286 and the third was thousands of SNPs different, indicating the nasal carriage strain from the surgical team member was not the source of the SSIs. Given the mutation rates estimated for S. aureus, none of the SSI isolates share a common ancestor within the past 14 years, further discounting any common point source for these infections. The decolonization procedures and resources spent on the point source infection control could have been prevented if WGST was performed at the time of the suspected transmission, instead of retrospectively.\n\nConclusionsWhole genome sequence analysis is an ideal method to exclude isolates involved in transmission events and nosocomial outbreaks, and coupling this method with epidemiological data can determine if a transmission event occurred. These methods promise to direct infection control resources more appropriately.

Genomics↗

bioRxiv2016

The Northern Arizona SNP Pipeline (NASP): accurate, flexible, and rapid identification of SNPs in WGS datasets

Whole genome sequencing (WGS) of bacteria is becoming standard practice in many laboratories. Applications for WGS analysis include phylogeography and molecular epidemiology, using single nucleotide polymorphisms (SNPs) as the unit of evolution. The Northern Arizona SNP Pipeline (NASP) was developed as a reproducible pipeline that scales well with the large amount of WGS data typically used in comparative genomics applications. In this study, we demonstrate how NASP compares to other tools in the analysis of two real bacterial genomics datasets and one simulated dataset. Our results demonstrate that NASP produces comparable, and often better, results to other pipelines, but is much more flexible in terms of data input types, job management systems, diversity of supported tools, and output formats. We also demonstrate differences in results based on the choice of the reference genome and choice of inferring phylogenies from concatenated SNPs or alignments including monomorphic positions. NASP represents a source-available, version-controlled, unit-tested method and can be obtained from tgennorth.github.io/NASP.

Bioinformatics↗