Genomics of an emerging clone of Salmonella serovar Typhimurium ST313 from Nigeria and the Democratic Republic of Congo

Leekitcharoenphon, Pimlapas; Friis, Carsten; Zankari, Ea; Svendsen, Christina C.A.; Price, Lance L.B.; Rahmani, Maral; Herrero-Fresno, Ana; Fashae, Kayode; Vandenberg, Olivier; Aarestrup, Frank Møller; Hendriksen, René S.

doi:10.3855/jidc.3328

Cited by 32 publications

(36 citation statements)

References 44 publications

(52 reference statements)

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“…If SNP is not found in the reference genome or the base coverage is less than a minimum setting (20 coverage), it is interpreted as not being a variation and the corresponding base in the reference is expected [34], [40]. Subsequently, multiple alignments were employed by MUSCLE from MEGA5 [41].…”

Section: Methodsmentioning

confidence: 99%

Evaluation of Whole Genome Sequencing for Outbreak Detection of Salmonella enterica

et al. 2014

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Salmonella enterica is a common cause of minor and large food borne outbreaks. To achieve successful and nearly ‘real-time’ monitoring and identification of outbreaks, reliable sub-typing is essential. Whole genome sequencing (WGS) shows great promises for using as a routine epidemiological typing tool. Here we evaluate WGS for typing of S. Typhimurium including different approaches for analyzing and comparing the data. A collection of 34 S. Typhimurium isolates was sequenced. This consisted of 18 isolates from six outbreaks and 16 epidemiologically unrelated background strains. In addition, 8 S. Enteritidis and 5 S. Derby were also sequenced and used for comparison. A number of different bioinformatics approaches were applied on the data; including pan-genome tree, k-mer tree, nucleotide difference tree and SNP tree. The outcome of each approach was evaluated in relation to the association of the isolates to specific outbreaks. The pan-genome tree clustered 65% of the S. Typhimurium isolates according to the pre-defined epidemiology, the k-mer tree 88%, the nucleotide difference tree 100% and the SNP tree 100% of the strains within S. Typhimurium. The resulting outcome of the four phylogenetic analyses were also compared to PFGE reveling that WGS typing achieved the greater performance than the traditional method. In conclusion, for S. Typhimurium, SNP analysis and nucleotide difference approach of WGS data seem to be the superior methods for epidemiological typing compared to other phylogenetic analytic approaches that may be used on WGS. These approaches were also superior to the more classical typing method, PFGE. Our study also indicates that WGS alone is insufficient to determine whether strains are related or un-related to outbreaks. This still requires the combination of epidemiological data and whole genome sequencing results.

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Section: Methodsmentioning

confidence: 99%

Evaluation of Whole Genome Sequencing for Outbreak Detection of Salmonella enterica

et al. 2014

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“…Moreover, serovar-specific studies on S. enterica subsp. enterica have highlighted microevolutionary differences among clinical, environmental, and food isolates in S. enterica serovars Montevideo (13,14), Enteritidis (4), Newport (15), Typhimurium (16)(17)(18), and Heidelberg (12), which would have been missed by more traditional approaches.…”

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confidence: 99%

Differential Single Nucleotide Polymorphism-Based Analysis of an Outbreak Caused by Salmonella enterica Serovar Manhattan Reveals Epidemiological Details Missed by Standard Pulsed-Field Gel Electrophoresis

et al. 2015

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We retrospectively analyzed a rare Salmonella enterica serovar Manhattan outbreak that occurred in Italy in 2009 to evaluate the potential of new genomic tools based on differential single nucleotide polymorphism (SNP) analysis in comparison with the gold standard genotyping method, pulsed-field gel electrophoresis. A total of 39 isolates were analyzed from patients (n ‫؍‬ 15) and food, feed, animal, and environmental sources (n ‫؍‬ 24), resulting in five different pulsed-field gel electrophoresis (PFGE) profiles. Isolates epidemiologically related to the outbreak clustered within the same pulsotype, SXB_BS.0003, without any further differentiation. Thirty-three isolates were considered for genomic analysis based on different sets of SNPs, core, synonymous, nonsynonymous, as well as SNPs in different codon positions, by Bayesian and maximum likelihood algorithms. Trees generated from core and nonsynonymous SNPs, as well as SNPs at the second and first plus second codon positions detailed four distinct groups of isolates within the outbreak pulsotype, discriminating outbreak-related isolates of human and food origins. Conversely, the trees derived from synonymous and third-codon-position SNPs clustered food and human isolates together, indicating that all outbreak-related isolates constituted a single clone, which was in line with the epidemiological evidence. Further experiments are in place to extend this approach within our regional enteropathogen surveillance system. Salmonellosis is a major food-borne disease worldwide, with an estimated 93.8 million cases occurring each year, resulting in 155,000 deaths (1). The European Union summary report on trends and sources of zoonoses, zoonotic agents and food-borne outbreaks (2) indicated that nontyphoid salmonellosis was the second most reported food-borne zoonosis in Europe in 2012, trailing only behind Campylobacter jejuni infection. The 2012 overall notification rate for human salmonellosis in the European Union (EU) was 22.2 episodes per 100,000 population, for a total of 91,034 confirmed cases, with hospitalization and mortality rates of 45.1% and 0.14%, respectively. The highest proportions of Salmonella-positive foodstuff samples were reported for fresh turkey, poultry, and pork at 4.4%, 4.1%, and 0.7%, respectively (2). In order to manage this food-borne infection and to limit its health and economic burdens, surveillance programs have developed and implemented DNA-based subtyping methods to identify outbreaks in a timely manner and to trace infections back to their food sources. Over the past decades, the two most intensively used protocols for Salmonella subtyping have been pulsed-field gel electrophoresis (PFGE) and multilocus variable-number tandemrepeat analysis (MLVA) (3). Unfortunately, these methods rely on just few features of the entire bacterial genome (rare restriction sites for PFGE or few polymorphic loci for MLVA) to assess the relatedness of different isolates. During epidemiological investigations of food-borne outbreaks, this limitation mi...

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“…This was not unexpected, as ST34 is a conventional ST and commonly found in Salmonella Typhimurium; ST34 and ST19 are the 2 most commonly described STs in Salmonella Typhimurium worldwide, including Africa (13,14). It was noteworthy that our investigation found no occurrence of ST313; this was also not unexpected, as ST313 is more commonly associated with invasive disease, and there are reports of ST313 causing epidemic invasive disease in sub-Saharan Africa (15,16).…”

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confidence: 38%

Nosocomial Outbreak of Salmonella enterica Serovar Typhimurium Primarily Affecting a Pediatric Ward in South Africa in 2012

et al. 2014

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eWe describe a nosocomial outbreak of diarrheal disease caused by extended-spectrum ␤-lactamase-producing multidrug-resistant Salmonella enterica serovar Typhimurium, focused on a pediatric ward in South Africa. The outbreak peaked between May 2012 and July 2012. Person-to-person transmission was the most likely mechanism of spread of the infection, expedited due to a breakdown in hand-washing and hygiene, suboptimal infection control practices, overcrowding of hospital wards, and an undesirable nurse-to-patient ratio.

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Genomics of an emerging clone of Salmonella serovar Typhimurium ST313 from Nigeria and the Democratic Republic of Congo

Cited by 32 publications

References 44 publications

Evaluation of Whole Genome Sequencing for Outbreak Detection of Salmonella enterica

Evaluation of Whole Genome Sequencing for Outbreak Detection of Salmonella enterica

Differential Single Nucleotide Polymorphism-Based Analysis of an Outbreak Caused by Salmonella enterica Serovar Manhattan Reveals Epidemiological Details Missed by Standard Pulsed-Field Gel Electrophoresis

Nosocomial Outbreak of Salmonella enterica Serovar Typhimurium Primarily Affecting a Pediatric Ward in South Africa in 2012

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