Bioinformatic Analyses of Whole-Genome Sequence Data in a Public Health Laboratory

Abstract

The ability to generate high-quality sequence data in a public health laboratory enables the identification of pathogenic strains, the determination of relatedness among outbreak strains, and the analysis of genetic information regarding virulence and antimicrobial-resistance genes. However, the analysis of whole-genome sequence data depends on bioinformatic analysis tools and processes. Many public health laboratories do not have the bioinformatic capabilities to analyze the data generated from sequencing and therefore are unable to take full advantage of the power of whole-genome sequencing. The goal of this perspective is to provide a guide for laboratories to understand the bioinformatic analyses that are needed to interpret whole-genome sequence data and how these in silico analyses can be implemented in a public health laboratory setting easily, affordably, and, in some cases, without the need for intensive computing resources and infrastructure.

Fatal Sepsis Associated with Bacterial Contamination of Platelets — Utah and California, August 2017

“…DNA was isolated from cultures that had growth (donor axillae and both antecubital fossae swabs, patient A’s blood, two isolates of patient B’s platelet bag residual, and one control [an unrelated C. perfringens isolate]). WGS indicated all six epidemiologically linked isolates were highly related, with an average pairwise nucleotide difference of 3.35e-10 compared with an average pairwise nucleotide difference of 0.02 to the unrelated control isolate ( 1 ) (Supplementary Figure 1, https://stacks.cdc.gov/view/cdc/56097 ).…”

Whole-Genome Sequencing and Bioinformatic Analysis of Isolates from Foodborne Illness Outbreaks of Campylobacter jejuni and Salmonella enterica

“…Bioinformatic analysis was performed using a previously described pipeline ( 16 ), as briefly described below.…”

Contribution of whole-genome sequencing to understanding of the epidemiology and control of meticillin-resistant Staphylococcus aureus

“…A recent review by Carriço et al (2018) provides an excellent overview of bioinformatics as applied to WGS data for the non-expert [20]. Some of the more frequently used bioinformatics approaches and software for microbial genome assembly and subsequent analysis have been recently reviewed [20,21,12]. Many software packages used for the analysis of WGS data are freely available and several commercially available and easy to use software packages including BioNumerics (Applied Maths, Ghent, Belgium) and SeqSphere (Ridom GmBH, Münster, Germany) are widely used for this purpose [12,14,16]…”