Genomic Epidemiology of Salmonella enterica Serotype Enteritidis based on Population Structure of Prevalent Lineages - Volume 20, Number 9—September 2014 - Emerging Infectious Disease journal - CDC
Volume 20, Number 9—September 2014
Genomic Epidemiology of Salmonella enterica Serotype Enteritidis based on Population Structure of Prevalent Lineages
Salmonella enterica causes ≈1 million illnesses and >350 deaths annually in the United States (1). Among >2,500 known serotypes, S. enterica serotype Enteritidis is one of the most commonly reported causes of human salmonellosis in most industrialized countries (2). From the 1970s through the mid-1990s, the incidence of serotype Enteritidis infection increased dramatically; shelled eggs were a major vehicle for transmission. Despite a decrease in serotype Enteritidis infection since 1996 in the United States, outbreaks resulting from contaminated eggs continue to occur (3), and Enteritidis remains among the most common serotypes isolated from humans worldwide (2). Epidemiologic surveillance and outbreak investigation of microbial pathogens require subtyping that provides sufficient resolution to discriminate closely related isolates. Differentiation ofS. enterica Enteritidis challenges traditional subtyping methods, such as pulsed-field gel electrophoresis (PFGE), because isolates of serotype Enteritidis are more genetically homogeneous than are isolates of many other serotypes (4,5). Among the serotype Enteritidis isolates reported to PulseNet, ≈45% display a single PFGE XbaI pattern (JEGX01.0004), which renders PFGE ineffective in some investigations (5). Of the second-generation methods evaluated for S. enterica Enteritidis subtyping, multilocus variable number–tandem repeat analysis offers slightly better discrimination, but differentiating common patterns remains a substantial problem (6). Therefore, new methods are needed to better subtype and differentiate this serotype. Recent applications of whole-genome sequencing (WGS) have demonstrated exceptional resolution that enables fine delineation of infectious disease outbreaks (7–10).
In addition to sufficient subtyping resolution, accurately ascribing isolates to epidemiologically meaningful clusters, i.e., grouping isolates associated with an outbreak while discriminating unrelated strains, is critical for pathogen subtyping. Outbreak and epidemiologically unrelated isolates might not be differentiated by using current methods. Despite the high incidence of S. enterica Enteritidis infection in humans, genome sequencing of this serotype has lagged behind sequencing of other major foodborne pathogens. To our knowledge, only 1 finished S. enterica Enteritidis genome is publicly available (11). Recent sequencing of S. enterica Enteritidis genomes of the common PFGE XbaI pattern JEGX01.0004 has provided a valuable resource on the S. enterica Enteritidis genome (12). Here we present a broad sampling of WGS to include diversity of other major lineages.
We expanded the genomic population structure of S. enterica Enteritidis by sequencing a collection of 81 S. enterica Enteritidis genomes and 3 S. enterica serotype Nitra genomes selected to capture epidemiologic and phylogenetic diversity in current domestic and international serotype Enteritidis populations. We included serotype Nitra in the study because it is thought to be a variant of serotype Enteritidis with its O antigen (serogroup O2) being a minor genetic variant of serogroup O9 found in serotype Enteritidis (13). These genomes, along with 44 draft genomes of S. enterica Enteritidis (14 historical strains and 30 isolates selected from the 2010 egg outbreak investigation [http://www.cdc.gov/salmonella/enteritidis/]), provided a phylogenetic framework of diverse circulating serotype Enteritidis lineages. Model-based Bayesian estimation of age and effective population size of major S. enterica Enteritidis lineages showed that the spreading of S. enterica Enteritidis coincided with 2 periods: the 18th century period of colonial trade and the 20th century period of agricultural industrialization. A single-nucleotide polymorphism (SNP) pipeline was developed for high-throughput whole-genome SNP typing and was robust for combining data from different sequencing platforms in the same analysis. This enabled retrospective investigation of recent clinical cases in Thailand and the shelled eggs outbreak in the United States. The ability of whole-genome SNP typing to infer the polyclonal genomic nature of at least some S. enterica Enteritidis strains causing outbreaks, despite high genetic homogeneity among S. enterica Enteritidis genomes, demonstrates the utility and sensitivity of whole-genome SNP typing in epidemiologic surveillance and outbreak investigations. Potential challenges of whole-genome SNP typing, such as ways to accurately define individual outbreaks, were discussed.
Dr Deng is an assistant professor at the Center for Food Safety, University of Georgia, and a guest researcher at the Enteric Diseases Laboratory Branch, Centers for Disease Control and Prevention. His research interests focus on using genomic and molecular biology approaches to better understand the biology, transmission, and evolution of foodborne pathogens.
We thank the PulseNet participating laboratories, Thailand Ministry of Public Health, and the Central Health Laboratory Mauritius for contributing strains used in this study. We thank Mark Allard, Errol Strain, and Eric Brown for providing the 454 sequencing data and editorial suggestions on the manuscript. We thank Jean Guard for many helpful discussions.
X.D. was supported in part by an American Society for Microbiology/Centers for Disease Control and Prevention Fellowship and startup funds from University of Georgia. M.M., S.P., and P.D. were supported in part by National Institutes of Health grant nos. AI039557 AI052237, AI073971, AI075093, AI077645 AI083646, and HHSN272200900040C; US Department of Agriculture (USDA) grant nos. 2009-03579 and 2011-67017-30127; the Binational Agricultural Research and Development Fund; and a grant from the Center for Produce Safety. J.G.F was supported by USDA Agricultural Research Services project no. 6612-32000-006-00. H.dB. and M.W. were supported in part by USDA grant no. 2010-34459-20756
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Suggested citation for this article: Deng X, Desai PT, den Bakker HC, Mikoleit M, Tolar B, Trees F, et al. Genomic epidemiology of Salmonella entericaserotype Enteritidis based on population structure of prevalent lineages. Emerg Infect Dis [Internet]. 2014 Sep [date cited].http://dx.doi.org/10.3201/eid2009.131095
1These authors contributed equally to this article.