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

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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

Research

Genomic Epidemiology of Salmonella enterica Serotype Enteritidis based on Population Structure of Prevalent Lineages

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• Methods
• Results
• Discussion
• Suggested Citation

Figures

• Figure 1
• Figure 2
• Figure 3
• Figure 4

Tables

• Table

Technical Appendicies

• Technical Appendix

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Xiangyu Deng , Prerak T. Desai, Henk C. den Bakker, Matthew Mikoleit, Beth Tolar, Eija Trees, Rene S. Hendriksen, Jonathan G. Frye, Steffen Porwollik, Bart C. Weimer, Martin Wiedmann, George M. Weinstock, Patricia I. Fields1, and Michael McClelland1

Author affiliations: University of Georgia, Griffin, Georgia, USA (X. Deng); University of California Irvine, Irvine, California, USA (P.T. Desai, S. Porwollik, M. McClelland); Cornell University, Ithaca, New York, USA (H.C. den Bakker, M. Wiedmann); Centers for Disease Control and Prevention, Atlanta, Georgia, USA (M. Mikoleit, B. Tolar, E. Trees, P.I. Fields); Technical University of Denmark, Lyngby, Denmark (R.S. Hendriksen); US Department of Agriculture, Athens, Georgia, USA (J.G. Frye); University of California Davis, Davis, California, USA (B.C. Weimer); Washington University School of Medicine, St. Louis, Missouri, USA (G.M. Weinstock)

Suggested citation for this article

Abstract

Salmonella enterica serotype Enteritidis is one of the most commonly reported causes of human salmonellosis. Its low genetic diversity, measured by fingerprinting methods, has made subtyping a challenge. We used whole-genome sequencing to characterize 125 S. enterica Enteritidis and 3 S. entericaserotype Nitra strains. Single-nucleotide polymorphisms were filtered to identify 4,887 reliable loci that distinguished all isolates from each other. Our whole-genome single-nucleotide polymorphism typing approach was robust for S. enterica Enteritidis subtyping with combined data for different strains from 2 different sequencing platforms. Five major genetic lineages were recognized, which revealed possible patterns of geographic and epidemiologic distribution. Analyses on the population dynamics and evolutionary history estimated that major lineages emerged during the 17th–18th centuries and diversified during the 1920s and 1950s.

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.

Acknowledgments

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

References

1. Scallan E, Hoekstra RM, Angulo FJ, Tauxe RV, Widdowson MA, Roy SL, Foodborne illness acquired in the United States—major pathogens. Emerg Infect Dis. 2011;17:7–15 . DOIPubMed
2. Hendriksen RS, Vieira AR, Karlsmose S, Lo Fo Wong DM, Jensen AB, Wegener HC, Global monitoring of Salmonella serovar distribution from the World Health Organization Global Foodborne Infections Network Country Data Bank: results of quality assured laboratories from 2001 to 2007.Foodborne Pathog Dis. 2011;8:887–900. DOIPubMed
3. Braden CR. Salmonella enterica serotype Enteritidis and eggs: a national epidemic in the United States. Clin Infect Dis. 2006;43:512–7.DOIPubMed
4. Olson AB, Andrysiak AK, Tracz DM, Guard-Bouldin J, Demczuk W, Ng LK, Limited genetic diversity in Salmonella enterica serovar Enteritidis PT13. BMC Microbiol. 2007;7:87. DOIPubMed
5. Zheng J, Keys CE, Zhao S, Meng J, Brown EW. Enhanced subtyping scheme for Salmonella Enteritidis. Emerg Infect Dis. 2007;13:1932–5.DOIPubMed
6. Boxrud D, Pederson-Gulrud K, Wotton J, Medus C, Lyszkowicz E, Besser J, Comparison of multiple-locus variable-number tandem repeat analysis, pulsed-field gel electrophoresis, and phage typing for subtype analysis of Salmonella enterica serotype Enteritidis. J Clin Microbiol.2007;45:536–43 . DOIPubMed
7. Harris SR, Feil EJ, Holden MT, Quail MA, Nickerson EK, Chantratita N, Evolution of MRSA during hospital transmission and intercontinental spread. Science. 2010;327:469–74 . DOIPubMed
8. Rasko DA, Webster DR, Sahl JW, Bashir A, Boisen N, Scheutz F, Origins of the E. coli strain causing an outbreak of hemolytic-uremic syndrome in Germany. N Engl J Med. 2011;365:709–17. DOIPubMed
9. Eppinger M, Mammel MK, Leclerc JE, Ravel J, Cebula TA. Genomic anatomy of Escherichia coli O157:H7 outbreaks. Proc Natl Acad Sci U S A.2011;108:20142–7. DOIPubMed
10. Chin CS, Sorenson J, Harris JB, Robins WP, Charles RC, Jean-Charles RR, The origin of the Haitian cholera outbreak strain. N Engl J Med.2011;364:33–42. DOIPubMed
11. Thomson NR, Clayton DJ, Windhorst D, Vernikos G, Davidson S, Churcher C, Comparative genome analysis of Salmonella Enteritidis PT4 andSalmonella Gallinarum 287/91 provides insights into evolutionary and host adaptation pathways. Genome Res. 2008;18:1624–37.DOIPubMed
12. Allard MW, Luo Y, Strain E, Pettengill J, Timme R, Wang C, On the evolutionary history, population genetics and diversity among isolates ofSalmonella Enteritidis PFGE pattern JEGX01.0004. PLoS ONE. 2013;8:e55254. DOIPubMed
13. Fitzgerald C, Collins M, van Duyne S, Mikoleit M, Brown T, Fields P. Multiplex, bead-based suspension array for molecular determination of common Salmonella serogroups. J Clin Microbiol. 2007;45:3323–34. DOIPubMed
14. Marttinen P, Hanage WP, Croucher NJ, Connor TR, Harris SR, Bentley SD, Detection of recombination events in bacterial genomes from large population samples. Nucleic Acids Res. 2012;40:e6. DOIPubMed
15. Tamura K, Peterson D, Peterson N, Stecher G, Nei M, Kumar S. MEGA5: molecular evolutionary genetics analysis using maximum likelihood, evolutionary distance, and maximum parsimony methods. Mol Biol Evol. 2011;28:2731–9. DOIPubMed
16. Drummond AJ, Rambaut A. BEAST: Bayesian evolutionary analysis by sampling trees. BMC Evol Biol. 2007;7:214. DOIPubMed
17. Okoro CK, Kingsley RA, Connor TR, Harris SR, Parry CM, Al-Mashhadani MN, Intracontinental spread of human invasive Salmonella Typhimurium pathovariants in sub-Saharan Africa. Nat Genet. 2012;44:1215–21. DOIPubMed
18. Bakker HC, Switt AI, Cummings CA, Hoelzer K, Degoricija L, Rodriguez-Rivera LD, A whole-genome single nucleotide polymorphism–based approach to trace and identify outbreaks linked to a common Salmonella enterica subsp. enterica serovar Montevideo pulsed-field gel electrophoresis type. Appl Environ Microbiol. 2011;77:8648–55. DOIPubMed
19. Baele G, Li WL, Drummond AJ, Suchard MA, Lemey P. Accurate model selection of relaxed molecular clocks in Bayesian phylogenetics. Mol Biol Evol. 2013;30:239–43. DOIPubMed
20. Bruen TC, Philippe H, Bryant D. A simple and robust statistical test for detecting the presence of recombination. Genetics. 2006;172:2665–81.DOIPubMed
21. Suchard MA, Weiss RE, Sinsheimer JS. Bayesian selection of continuous-time Markov chain evolutionary models. Mol Biol Evol. 2001;18:1001–13.DOIPubMed
22. Gill MS, Lemey P, Faria NR, Rambaut A, Shapiro B, Suchard MA. Improving Bayesian population dynamics inference: a coalescent-based model for multiple loci. Mol Biol Evol. 2013;30:713–24. DOIPubMed
23. Drummond AJ, Ho SY, Phillips MJ, Rambaut A. Relaxed phylogenetics and dating with confidence. PLoS Biol. 2006;4:e88. DOIPubMed
24. Morelli G, Didelot X, Kusecek B, Schwarz S, Bahlawane C, Falush D, Microevolution of Helicobacter pylori during prolonged infection of single hosts and within families. PLoS Genet. 2010;6:e1001036. DOIPubMed
25. Didelot X, Eyre DW, Cule M, Ip CL, Ansari MA, Griffiths D, Microevolutionary analysis of Clostridium difficile genomes to investigate transmission. Genome Biol. 2012;13:R118. DOIPubMed
26. Zhou Z, McCann A, Litrup E, Murphy R, Cormican M, Fanning S, Neutral genomic microevolution of a recently emerged pathogen, Salmonella enterica serovar Agona. PLoS Genet. 2013;9:e1003471. DOIPubMed
27. Salmonella Subcommittee of the Nomenclature Committee of the International Society for Microbiology. The genus Salmonella Lignieres. 1900. J Hyg (Lond). 1934;34:333–50 .PubMed
28. Bryant JE, Holmes EC, Barrett AD. Out of Africa: a molecular perspective on the introduction of yellow fever virus into the Americas. PLoS Pathog. 2007;3:e75. DOIPubMed
29. Bäumler AJ, Hargis BM, Tsolis RM. Tracing the origins of Salmonella outbreaks. Science. 2000;287:50–2 . DOIPubMed
30. Porwollik S, Boyd EF, Choy C, Cheng P, Florea L, Proctor E, Characterization of Salmonella enterica subspecies I genovars by use of microarrays. J Bacteriol. 2004;186:5883–98. DOIPubMed
31. Hyytiä-Trees E, Smole SC, Fields PA, Swaminathan B, Ribot EM. Second generation subtyping: a proposed PulseNet protocol for multiple-locus variable-number tandem repeat analysis of Shiga toxin–producing Escherichia coli O157 (STEC O157). Foodborne Pathog Dis. 2006;3:118–31 .DOIPubMed
32. Liu F, Barrangou R, Gerner-Smidt P, Ribot EM, Knabel SJ, Dudley EG. Novel virulence gene and clustered regularly interspaced short palindromic repeat (CRISPR) multilocus sequence typing scheme for subtyping of the major serovars of Salmonella enterica subsp. enterica. Appl Environ Microbiol. 2011;77:1946–56. DOIPubMed
33. Stoddard RA, DeLong RL, Byrne BA, Jang S, Gulland FM. Prevalence and characterization of Salmonella spp. among marine animals in the Channel Islands, California. Dis Aquat Organ. 2008;81:5–11. DOIPubMed
34. Hendriksen RS, Hyytia-Trees E, Pulsrikarn C, Pornruangwong S, Chaichana P, Svendsen CA, Characterization of Salmonella enterica serovar Enteritidis isolates recovered from blood and stool specimens in Thailand. BMC Microbiol. 2012;12:92. DOIPubMed
35. Hendriksen RS, Bangtrakulnonth A, Pulsrikarn C, Pornruangwong S, Noppornphan G, Emborg HD, Risk factors and epidemiology of the ten most common Salmonella serovars from patients in Thailand: 2002–2007. Foodborne Pathog Dis. 2009;6:1009–19. DOIPubMed
36. Graham SM. Nontyphoidal salmonellosis in Africa. Curr Opin Infect Dis. 2010;23:409–14 and. DOIPubMed
37. Heithoff DM, Shimp WR, House JK, Xie Y, Weimer BC, Sinsheimer RL, Intraspecies variation in the emergence of hyperinfectious bacterial strains in nature. PLoS Pathog. 2012;8:e1002647. DOIPubMed
38. Lienau EK, Strain E, Wang C, Zheng J, Ottesen AR, Keys CE, Identification of a salmonellosis outbreak by means of molecular sequencing. N Engl J Med. 2011;364:981–2. DOIPubMed
39. Orsi RH, Borowsky ML, Lauer P, Young SK, Nusbaum C, Galagan JE, Short-term genome evolution of Listeria monocytogenes in a non-controlled environment. BMC Genomics. 2008;9:539. DOIPubMed
40. Wilson MR, Allard MW, Brown EW. The forensic analysis of foodborne bacterial pathogens in the age of whole-genome sequencing. Cladistics.2013;29:449–61. DOI

Figures

• Figure 1. Comparison of Salmonella enterica serotype Enteritidis phylogenies inferred from Illumina data and combined data of Illumina (San Diego, CA, USA) and Roche 454 (Indianapolis, IN, USA). The tree on...
• Figure 2. Inferred number of Salmonella enterica serotype Enteritidis lineages over time based on a constant effective population size model using BEAST (16). Blue shading indicates 95% CIs.
• Figure 3. Salmonella enterica serotype Enteritidis genetic lineage III. Isolates from human blood and stool samples are indicated by red and blue, respectively. Four clades are highlighted and designated A–D, representing...
• Figure 4. Salmonella enterica serotype Enteritidis clades associated with the 2010 US shelled eggs outbreak. Red indicates isolates sequenced as part of the outbreak investigation using Roche 454 technology (Indianapolis, IN,...

Table

• Table. Dating of nodes in the maximum-likelihood tree of Salmonella enterica serotype Enteritidis using BEAST and strict and relaxed mutation rates

Technical Appendix

• Technical Appendix. Isolates used in this study; new genomes sequenced for this study; regions flagged as putatively involved in recombination by BratNextGen and excluded from analyses; comparison of 4 models used... 357 KB

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

DOI: 10.3201/eid2009.131095

1These authors contributed equally to this article.