Whole genome sequencing options for bacterial strain typing and epidemiologic analysis based on single nucleotide polymorphism versus gene-by-gene–based approaches

Abstract

Background: Whole genome sequence (WGS)-based strain typing finds increasing use in the epidemiologic analysis of bacterial pathogens in both public health as well as more localized infection control settings. Aims: This minireview describes methodologic approaches that have been explored for WGS-based epidemiologic analysis and considers the challenges and pitfalls of data interpretation. Sources: Personal collection of relevant publications. Content: When applying WGS to study the molecular epidemiology of bacterial pathogens, genomic variability between strains is translated into measures of distance by determining single nucleotide polymorphisms in core genome alignments or by indexing allelic variation in hundreds to thousands of core genes, assigning types to unique allelic profiles. Interpreting isolate relatedness from these distances is highly organism specific, and attempts to establish species-specific cutoffs are unlikely to be generally applicable. In cases where single nucleotide polymorphism or core gene typing do not provide the resolution necessary for accurate assessment of the epidemiology of bacterial pathogens, inclusion of accessory gene or plasmid sequences may provide the additional required discrimination. Implications: As with all epidemiologic analysis, realizing the full potential of the revolutionary advances in WGS-based approaches requires understanding and dealing with issues related to the fundamental steps of data generation and interpretation.

Whole‐genome sequencing reveals Listeria monocytogenes diversity and allows identification of long‐term persistent strains in Brazil

“…WGS allows an unprecedented subtyping resolution by analysis of the core genome, as well as the accessory genome. Questions related to potential virulence heterogeneity and antimicrobial resistance genes can also be answered, and outbreak investigations have become more precise by correlating epidemiological data with genetic characteristics of the isolates involved (Nielsen et al, 2017;Lüth et al, 2018;Schürch et al, 2018).…”

Proteomic changes in bacteria caused by exposure to environmental conditions can be detected by Matrix-Assisted Laser Desorption/Ionization – Time of Flight (MALDI-ToF) Mass Spectrometry

“…(rep-PCR), housekeeping gene (e.g., PheS) sequence analysis20, and whole genome sequencing21, 22. Each of these approaches has been shown to have adequately high resolution to distinguish microbial strains from one another; however, these approaches are labor-and time-intensive as well as costly techniques that might lack the required rapid high-throughput nature of MALDI-ToF.…”

Rapid and accurate SNP genotyping of clonal bacterial pathogens with BioHansel

“…Additional non-clonal sources of genetic diversity include recombination and the gain or loss of mobile elements such as transposons, bacteriophage, and plasmids. Several approaches exist that exploit this genomic diversity to estimate the genetic and epidemiological relatedness of infectious diseases, the most popular being the gene-by-gene methods and the SNP-based methods (Schürch et al, 2018). The choice of typing approach depends on its intended application (for a review see Nadon et al, 2017), although in general, gene-by-gene approaches are popular for routine surveillance activities, whereas SNP-based approaches are used when extra discriminatory power is required, or for pathogens that are not amenable to gene-by-gene methods.…”