Distribution and factors associated with Salmonella enterica genotypes in a diverse population of humans and animals in Qatar using multi-locus sequence typing (MLST)

Yu C. Chang, Joy Scaria, Mariamma Ibraham, Sanjay Doiphode, Yung Fu Chang, Ali Sultan, Hussni O. Mohammed

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

Salmonella enterica is one of the most commonly reported causes of bacterial foodborne illness around the world. Understanding the sources of this pathogen and the associated factors that exacerbate its risk to humans will help in developing risk mitigation strategies. The genetic relatedness among Salmonella isolates recovered from human gastroenteritis cases and food animals in Qatar were investigated in the hope of shedding light on these sources, their possible transmission routes, and any associated factors. A repeat cross-sectional study was conducted in which the samples and associated data were collected from both populations (gastroenteritis cases and animals). Salmonella isolates were initially analyzed using multi-locus sequence typing (MLST) to investigate the genetic diversity and clonality. The relatedness among the isolates was assessed using the minimum spanning tree (MST). Twenty-seven different sequence types (STs) were identified in this study; among them, seven were novel, including ST1695, ST1696, ST1697, ST1698, ST1699, ST1702, and ST1703. The pattern of overall ST distribution was diverse; in particular, it was revealed that ST11 and ST19 were the most common sequence types, presenting 29.5% and 11.5% within the whole population. In addition, 20 eBurst Groups (eBGs) were identified in our data, which indicates that ST11 and ST19 belonged to eBG4 and eBG1, respectively. In addition, the potential association between the putative risk factors and eBGs were evaluated. There was no significant clustering of these eBGs by season; however, a significant association was identified in terms of nationality in that Qataris were six times more likely to present with eBG1 compared to non-Qataris. In the MST analysis, four major clusters were presented, namely, ST11, ST19, ST16, and ST31. The linkages between the clusters alluded to a possible transmission route. The results of the study have provided insight into the ST distributions of S. enterica and their possible zoonotic associations in Qatar.

Original languageEnglish
Pages (from-to)315-323
Number of pages9
JournalJournal of Infection and Public Health
Volume9
Issue number3
DOIs
Publication statusPublished - 1 May 2016

Fingerprint

Qatar
Salmonella enterica
Gastroenteritis
Salmonella
Genotype
Foodborne Diseases
Zoonoses
Ethnic Groups
Population
Cluster Analysis
Cross-Sectional Studies
Food

Keywords

  • EBGs
  • Minimum spanning tree
  • Multi-locus sequence typing
  • Salmonella enterica
  • STs

ASJC Scopus subject areas

  • Public Health, Environmental and Occupational Health
  • Infectious Diseases

Cite this

Distribution and factors associated with Salmonella enterica genotypes in a diverse population of humans and animals in Qatar using multi-locus sequence typing (MLST). / Chang, Yu C.; Scaria, Joy; Ibraham, Mariamma; Doiphode, Sanjay; Chang, Yung Fu; Sultan, Ali; Mohammed, Hussni O.

In: Journal of Infection and Public Health, Vol. 9, No. 3, 01.05.2016, p. 315-323.

Research output: Contribution to journalArticle

Chang, Yu C. ; Scaria, Joy ; Ibraham, Mariamma ; Doiphode, Sanjay ; Chang, Yung Fu ; Sultan, Ali ; Mohammed, Hussni O. / Distribution and factors associated with Salmonella enterica genotypes in a diverse population of humans and animals in Qatar using multi-locus sequence typing (MLST). In: Journal of Infection and Public Health. 2016 ; Vol. 9, No. 3. pp. 315-323.
@article{62c3227ec00f42f69ea6b7f6fc64607b,
title = "Distribution and factors associated with Salmonella enterica genotypes in a diverse population of humans and animals in Qatar using multi-locus sequence typing (MLST)",
abstract = "Salmonella enterica is one of the most commonly reported causes of bacterial foodborne illness around the world. Understanding the sources of this pathogen and the associated factors that exacerbate its risk to humans will help in developing risk mitigation strategies. The genetic relatedness among Salmonella isolates recovered from human gastroenteritis cases and food animals in Qatar were investigated in the hope of shedding light on these sources, their possible transmission routes, and any associated factors. A repeat cross-sectional study was conducted in which the samples and associated data were collected from both populations (gastroenteritis cases and animals). Salmonella isolates were initially analyzed using multi-locus sequence typing (MLST) to investigate the genetic diversity and clonality. The relatedness among the isolates was assessed using the minimum spanning tree (MST). Twenty-seven different sequence types (STs) were identified in this study; among them, seven were novel, including ST1695, ST1696, ST1697, ST1698, ST1699, ST1702, and ST1703. The pattern of overall ST distribution was diverse; in particular, it was revealed that ST11 and ST19 were the most common sequence types, presenting 29.5{\%} and 11.5{\%} within the whole population. In addition, 20 eBurst Groups (eBGs) were identified in our data, which indicates that ST11 and ST19 belonged to eBG4 and eBG1, respectively. In addition, the potential association between the putative risk factors and eBGs were evaluated. There was no significant clustering of these eBGs by season; however, a significant association was identified in terms of nationality in that Qataris were six times more likely to present with eBG1 compared to non-Qataris. In the MST analysis, four major clusters were presented, namely, ST11, ST19, ST16, and ST31. The linkages between the clusters alluded to a possible transmission route. The results of the study have provided insight into the ST distributions of S. enterica and their possible zoonotic associations in Qatar.",
keywords = "EBGs, Minimum spanning tree, Multi-locus sequence typing, Salmonella enterica, STs",
author = "Chang, {Yu C.} and Joy Scaria and Mariamma Ibraham and Sanjay Doiphode and Chang, {Yung Fu} and Ali Sultan and Mohammed, {Hussni O.}",
year = "2016",
month = "5",
day = "1",
doi = "10.1016/j.jiph.2015.10.013",
language = "English",
volume = "9",
pages = "315--323",
journal = "Journal of Infection and Public Health",
issn = "1876-0341",
publisher = "Elsevier BV",
number = "3",

}

TY - JOUR

T1 - Distribution and factors associated with Salmonella enterica genotypes in a diverse population of humans and animals in Qatar using multi-locus sequence typing (MLST)

AU - Chang, Yu C.

AU - Scaria, Joy

AU - Ibraham, Mariamma

AU - Doiphode, Sanjay

AU - Chang, Yung Fu

AU - Sultan, Ali

AU - Mohammed, Hussni O.

PY - 2016/5/1

Y1 - 2016/5/1

N2 - Salmonella enterica is one of the most commonly reported causes of bacterial foodborne illness around the world. Understanding the sources of this pathogen and the associated factors that exacerbate its risk to humans will help in developing risk mitigation strategies. The genetic relatedness among Salmonella isolates recovered from human gastroenteritis cases and food animals in Qatar were investigated in the hope of shedding light on these sources, their possible transmission routes, and any associated factors. A repeat cross-sectional study was conducted in which the samples and associated data were collected from both populations (gastroenteritis cases and animals). Salmonella isolates were initially analyzed using multi-locus sequence typing (MLST) to investigate the genetic diversity and clonality. The relatedness among the isolates was assessed using the minimum spanning tree (MST). Twenty-seven different sequence types (STs) were identified in this study; among them, seven were novel, including ST1695, ST1696, ST1697, ST1698, ST1699, ST1702, and ST1703. The pattern of overall ST distribution was diverse; in particular, it was revealed that ST11 and ST19 were the most common sequence types, presenting 29.5% and 11.5% within the whole population. In addition, 20 eBurst Groups (eBGs) were identified in our data, which indicates that ST11 and ST19 belonged to eBG4 and eBG1, respectively. In addition, the potential association between the putative risk factors and eBGs were evaluated. There was no significant clustering of these eBGs by season; however, a significant association was identified in terms of nationality in that Qataris were six times more likely to present with eBG1 compared to non-Qataris. In the MST analysis, four major clusters were presented, namely, ST11, ST19, ST16, and ST31. The linkages between the clusters alluded to a possible transmission route. The results of the study have provided insight into the ST distributions of S. enterica and their possible zoonotic associations in Qatar.

AB - Salmonella enterica is one of the most commonly reported causes of bacterial foodborne illness around the world. Understanding the sources of this pathogen and the associated factors that exacerbate its risk to humans will help in developing risk mitigation strategies. The genetic relatedness among Salmonella isolates recovered from human gastroenteritis cases and food animals in Qatar were investigated in the hope of shedding light on these sources, their possible transmission routes, and any associated factors. A repeat cross-sectional study was conducted in which the samples and associated data were collected from both populations (gastroenteritis cases and animals). Salmonella isolates were initially analyzed using multi-locus sequence typing (MLST) to investigate the genetic diversity and clonality. The relatedness among the isolates was assessed using the minimum spanning tree (MST). Twenty-seven different sequence types (STs) were identified in this study; among them, seven were novel, including ST1695, ST1696, ST1697, ST1698, ST1699, ST1702, and ST1703. The pattern of overall ST distribution was diverse; in particular, it was revealed that ST11 and ST19 were the most common sequence types, presenting 29.5% and 11.5% within the whole population. In addition, 20 eBurst Groups (eBGs) were identified in our data, which indicates that ST11 and ST19 belonged to eBG4 and eBG1, respectively. In addition, the potential association between the putative risk factors and eBGs were evaluated. There was no significant clustering of these eBGs by season; however, a significant association was identified in terms of nationality in that Qataris were six times more likely to present with eBG1 compared to non-Qataris. In the MST analysis, four major clusters were presented, namely, ST11, ST19, ST16, and ST31. The linkages between the clusters alluded to a possible transmission route. The results of the study have provided insight into the ST distributions of S. enterica and their possible zoonotic associations in Qatar.

KW - EBGs

KW - Minimum spanning tree

KW - Multi-locus sequence typing

KW - Salmonella enterica

KW - STs

UR - http://www.scopus.com/inward/record.url?scp=84961784263&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84961784263&partnerID=8YFLogxK

U2 - 10.1016/j.jiph.2015.10.013

DO - 10.1016/j.jiph.2015.10.013

M3 - Article

VL - 9

SP - 315

EP - 323

JO - Journal of Infection and Public Health

JF - Journal of Infection and Public Health

SN - 1876-0341

IS - 3

ER -