Retrospective whole-genome comparison of Salmonella enterica serovar Enteritidis from foodborne outbreaks in Southern Brazil

Abstract

Salmonella enterica serovar Enteritidis is frequently isolated from animal-source foods associated with human salmonellosis outbreaks. This serovar was spread to animal (mainly poultry) farms worldwide in the 1980s, and it is still detected in foods produced in many countries, including Brazil. The present study reports a retrospective genome-wide comparison of S. Enteritidis from foodborne outbreaks in Southern Brazil in the last two decades. Fifty-two S. Enteritidis isolates were obtained from foodborne outbreaks occurring in different cities of the Brazilian southernmost State, Rio Grande do Sul (RS), from 2003 to 2015. Whole-genome sequences (WGS) from these isolates were obtained and comparatively analyzed with 65 additional genomes from NCBI. Phylogenetic and Bayesian analyses were performed to study temporal evolution. Genes related to antibiotic resistance and virulence were also evaluated. The results demonstrated that all S. Enteritidis isolates from Southern Brazil clustered in the global epidemic clade disseminated worldwide originally in the 1980s. Temporal analysis demonstrated that all Brazilian isolates had a tMRCA (time to most recent common ancestor) in 1986 with an effective population size (N_e) increase soon after until 1992, then becoming constant up to now. In Southern Brazil, there was a significant decrease in the spreading of S. Enteritidis in the last decade. In addition, three antibiotic resistance genes were detected in all isolates: aac(6')-Iaa, mdfA, and tet(34). These results demonstrate the high frequency of one only specific S. Enteritidis lineage (global epidemic clade) in foodborne outbreaks from Southern Brazil in the last two decades.

Keywords: Brazil; Foodborne outbreaks; Salmonella enterica.

Fig. 1

Geographical distribution of 46 out of 52 S. Enteritidis isolates from foodborne outbreaks in thirty-three cities in the Brazilian state of Rio Grande do Sul (six isolates had no origin information). The circles represent the geographical location of the different cities in the study. The diameter is in accordance with the number of isolates in each city

Fig. 2

Maximum likelihood phylogeny constructed using high-quality SNPs (hqSNPs) identified among 117 S. Enteritidis genomes using the CFSAN SNP Pipeline. Red are isolates sequenced in this study of foodborne outbreaks (n = 52), black are Brazilian isolates downloaded from NCBI (n = 52), pink are isolates from other America countries (USA, Argentina, Colombia, and Uruguay [n = 10]), green are isolates from Europe (UK and Portugal [n = 2]), and brown is P125109. The phylogeny was constructed using IQ-TREE and is midpoint rooted, with branch lengths representing the number of substitutions per site

Fig. 3

Maximum clade credibility tree constructed using high-quality SNPs (hqSNPs) identified among 104 S. Enteritidis genomes using the CFSAN SNP Pipeline, rooted using BEAST. Red are isolates of foodborne outbreaks from RS sequenced in this study (n = 52) and black are genomes downloaded from NCBI from several Brazilian regions (n = 52). Time in years is plotted along the X-axis. Branch labels denote posterior probabilities of branch support, and node bars correspond to 95% highest posterior density (HPD) intervals for node heights

Fig. 4

Maximum clade credibility tree constructed using high-quality SNPs (hqSNPs) identified among 52 S. Enteritidis genomes (red) using the CFSAN SNP Pipeline, rooted using BEAST. Time in years is plotted along the X-axis. Branch labels denote posterior probabilities of branch support, and node bars correspond to 95% highest posterior density (HPD) intervals for node heights

Fig. 5

Effective population size over the time. Bayesian skyline plot, based on a “relaxed clock” coalescent framework analysis, was constructed using 104 sequences from foodborne outbreak isolates of Rio Grande do Sul State (n = 52, sequenced in this study) and genomes downloaded from NCBI from several Brazilian regions (n = 52). X-axis represents time in years, while Y-axis shows the effective population size. The blue band represents 95% highest posterior density (HPD) intervals

Fig. 6

Effective population size and time for most recent common ancestor. Bayesian skyline plot, based on a “relaxed clock” coalescent framework analysis, was constructed using 52 sequences of foodborne outbreaks in Rio Grande do Sul sequenced in this study. X-axis represents time in years, while Y-axis shows the effective population size. The blue band represents 95% highest posterior density (HPD) intervals