Distribution and factors associated with Salmonella enterica genotypes in a diverse population of humans and animals in Qatar using multi-locus sequence typing (MLST). Issue 3 (May 2016)

• Record Type: Journal Article
• Authors: Chang, Yu C.; Scaria, Joy; Ibraham, Mariamma; Doiphode, Sanjay; Chang, Yung-Fu; Sultan, Ali; Mohammed, Hussni O.
• Is Part Of: Journal of infection and public health. Volume 9:Issue 3(2016)
• Page Start: 315
• Page End: 323
• Publication Date: 2016-05
• Subjects: Salmonella enterica -- Multi-locus sequence typing -- STs -- eBGs -- Minimum spanning tree; Communicable diseases -- Periodicals; Public health -- Periodicals; Epidemiology -- Periodicals; Nosocomial infections -- Prevention -- Periodicals; Medical microbiology -- Periodicals; 614.4
• DOI: 10.1016/j.jiph.2015.10.013
• Languages: English
• ISSNs: 1876-0341

Abstract

Summary: 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.