Concordance and discordance of sequence survey methods for molecular epidemiology.

Eduardo Castro-Nallar,Keith A Crandall,W Evan Johnson,Rita R Colwell,Nur A Hasan,Richard A Robison,Thomas A Cebula

doi:10.7717/peerj.761

Abstract

The post-genomic era is characterized by the direct acquisition and analysis of genomic data with many applications, including the enhancement of the understanding of microbial epidemiology and pathology. However, there are a number of molecular approaches to survey pathogen diversity, and the impact of these different approaches on parameter estimation and inference are not entirely clear. We sequenced whole genomes of bacterial pathogens, Burkholderia pseudomallei, Yersinia pestis, and Brucella spp. (60 new genomes), and combined them with 55 genomes from GenBank to address how different molecular survey approaches (whole genomes, SNPs, and MLST) impact downstream inferences on molecular evolutionary parameters, evolutionary relationships, and trait character associations. We selected isolates for sequencing to represent temporal, geographic origin, and host range variability. We found that substitution rate estimates vary widely among approaches, and that SNP and genomic datasets yielded different but strongly supported phylogenies. MLST yielded poorly supported phylogenies, especially in our low diversity dataset, i.e., Y. pestis. Trait associations showed that B. pseudomallei and Y. pestis phylogenies are significantly associated with geography, irrespective of the molecular survey approach used, while Brucella spp. phylogeny appears to be strongly associated with geography and host origin. We contrast inferences made among monomorphic (clonal) and non-monomorphic bacteria, and between intra- and inter-specific datasets. We also discuss our results in light of underlying assumptions of different approaches.

Highlights

Genomic data coupled with phylogenetic methods have enhanced the ability to track infectious disease epidemics through space and time (Baker, Hanage & Holt, 2010)
Because there are a variety of molecular survey approaches (whole genome sequencing (WGS), multi-locus sequence typing (MLST), and single nucleotide polymorphism (SNP) data) with different costs and resolution abilities, we explored the impact of these different approaches on inferences of population dynamics, transmission patterns, and parameter estimation
The results of analyses reported here show that the molecular survey that is used can have a critical impact on substitution rate and phylogenetic inference

Summary

Introduction

Genomic data coupled with phylogenetic methods have enhanced the ability to track infectious disease epidemics through space and time (Baker, Hanage & Holt, 2010). Studies have tracked and characterized epidemics occurring at different geographic scales, across local, regional, global, and even historical scales; investigating multidrug-resistant Staphylococcus aureus in hospital settings (Kos et al, 2012; Koser et al, 2012), inferring continental origins of food pathogens (Goss et al, 2014), explaining seasonal influenza dynamics (Lemey et al, 2014), and ancient oral pathogens (Warinner et al, 2014), respectively. New technologies make it possible to compile datasets that were not even dreamed of twenty years ago (Chewapreecha et al, 2014; Marttinen et al, 2012; Nasser et al, 2014; Sheppard et al, 2013) which, in turn, is prompting scientists to ask new questions regarding pathogen distribution, diversity, identification, origin, and phenotype (Butler et al, 2013; Castillo-Ramirez et al, 2012; Grad & Waldor, 2013; Holt et al, 2012; Hong et al, 2014; Spoor et al, 2013)

Methods

Results

Conclusion