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      Ceftriaxone-resistant Salmonella Typhi carries an IncI1-ST31 plasmid encoding CTX-M-15

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          Most cited references30

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          Is Open Access

          The Salmonella In Silico Typing Resource (SISTR): An Open Web-Accessible Tool for Rapidly Typing and Subtyping Draft Salmonella Genome Assemblies

          For nearly 100 years serotyping has been the gold standard for the identification of Salmonella serovars. Despite the increasing adoption of DNA-based subtyping approaches, serotype information remains a cornerstone in food safety and public health activities aimed at reducing the burden of salmonellosis. At the same time, recent advances in whole-genome sequencing (WGS) promise to revolutionize our ability to perform advanced pathogen characterization in support of improved source attribution and outbreak analysis. We present the Salmonella In Silico Typing Resource (SISTR), a bioinformatics platform for rapidly performing simultaneous in silico analyses for several leading subtyping methods on draft Salmonella genome assemblies. In addition to performing serovar prediction by genoserotyping, this resource integrates sequence-based typing analyses for: Multi-Locus Sequence Typing (MLST), ribosomal MLST (rMLST), and core genome MLST (cgMLST). We show how phylogenetic context from cgMLST analysis can supplement the genoserotyping analysis and increase the accuracy of in silico serovar prediction to over 94.6% on a dataset comprised of 4,188 finished genomes and WGS draft assemblies. In addition to allowing analysis of user-uploaded whole-genome assemblies, the SISTR platform incorporates a database comprising over 4,000 publicly available genomes, allowing users to place their isolates in a broader phylogenetic and epidemiological context. The resource incorporates several metadata driven visualizations to examine the phylogenetic, geospatial and temporal distribution of genome-sequenced isolates. As sequencing of Salmonella isolates at public health laboratories around the world becomes increasingly common, rapid in silico analysis of minimally processed draft genome assemblies provides a powerful approach for molecular epidemiology in support of public health investigations. Moreover, this type of integrated analysis using multiple sequence-based methods of sub-typing allows for continuity with historical serotyping data as we transition towards the increasing adoption of genomic analyses in epidemiology. The SISTR platform is freely available on the web at https://lfz.corefacility.ca/sistr-app/.
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            Salmonella serotype determination utilizing high-throughput genome sequencing data.

            Serotyping forms the basis of national and international surveillance networks for Salmonella, one of the most prevalent foodborne pathogens worldwide (1-3). Public health microbiology is currently being transformed by whole-genome sequencing (WGS), which opens the door to serotype determination using WGS data. SeqSero (www.denglab.info/SeqSero) is a novel Web-based tool for determining Salmonella serotypes using high-throughput genome sequencing data. SeqSero is based on curated databases of Salmonella serotype determinants (rfb gene cluster, fliC and fljB alleles) and is predicted to determine serotype rapidly and accurately for nearly the full spectrum of Salmonella serotypes (more than 2,300 serotypes), from both raw sequencing reads and genome assemblies. The performance of SeqSero was evaluated by testing (i) raw reads from genomes of 308 Salmonella isolates of known serotype; (ii) raw reads from genomes of 3,306 Salmonella isolates sequenced and made publicly available by GenomeTrakr, a U.S. national monitoring network operated by the Food and Drug Administration; and (iii) 354 other publicly available draft or complete Salmonella genomes. We also demonstrated Salmonella serotype determination from raw sequencing reads of fecal metagenomes from mice orally infected with this pathogen. SeqSero can help to maintain the well-established utility of Salmonella serotyping when integrated into a platform of WGS-based pathogen subtyping and characterization.
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              Evolutionary history of Salmonella typhi.

              For microbial pathogens, phylogeographic differentiation seems to be relatively common. However, the neutral population structure of Salmonella enterica serovar Typhi reflects the continued existence of ubiquitous haplotypes over millennia. In contrast, clinical use of fluoroquinolones has yielded at least 15 independent gyrA mutations within a decade and stimulated clonal expansion of haplotype H58 in Asia and Africa. Yet, antibiotic-sensitive strains and haplotypes other than H58 still persist despite selection for antibiotic resistance. Neutral evolution in Typhi appears to reflect the asymptomatic carrier state, and adaptive evolution depends on the rapid transmission of phenotypic changes through acute infections.
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                Author and article information

                Journal
                Journal of Medical Microbiology
                Microbiology Society
                0022-2615
                1473-5644
                May 01 2018
                May 01 2018
                : 67
                : 5
                : 620-627
                Affiliations
                [1 ] 1​Laboratory of Microbiology and Virology, Department of Biomedical Sciences, University of Sassari, V. le San Pietro 43/B, 07100 Sassari, Italy
                [2 ] 2​Child Health Research Foundation, Department of Microbiology, Dhaka Shishu Hospital, Dhaka, Bangladesh
                [3 ] 3​Bangladesh Institute of Child Health, Dhaka Shishu Hospital, Dhaka, Bangladesh
                [4 ] 4​Department of Medical Microbiology and Infectious Diseases, Erasmus University Medical Centre, Rotterdam, the Netherlands
                [5 ] 5​Medical Microbiology Research Laboratory, Norwich Medical School, University of East Anglia, Norwich, NR4 7UQ, UK
                [6 ] 6​Laboratoire des Pathogènes Émergents, Fondation Mérieux, Centre International de Recherche en Infectiologie (CIRI), INSERM U1111, Lyon, France
                Article
                10.1099/jmm.0.000727
                29616895
                6dd12a55-2310-4544-8d16-6c2e68b1b5f1
                © 2018
                History

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