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      Genomic analysis of Salmonella enterica serotype Paratyphi A during an outbreak in Cambodia, 2013–2015

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          Abstract

          In 2013, an unusual increase in the number of Salmonella enterica serotype Paratyphi A ( Salmonella Paratyphi A) infections was reported in patients in Phnom Penh, Cambodia, and in European, American and Japanese travellers returning from Cambodia. Epidemiological investigations did not identify a common source of exposure. To analyse the population structure and genetic diversity of these Salmonella Paratyphi A isolates, we used whole-genome sequencing on 65 isolates collected from 1999 to 2014: 55 from infections acquired in Cambodia and 10 from infections acquired in other countries in Asia, Africa and Europe. Short-read sequences from 80 published genomes from around the world and from 13 published genomes associated with an outbreak in China were also included. Pulsed-field gel electrophoresis (PFGE) was performed on a subset of isolates. Genomic analyses were found to provide much more accurate information for tracking the individual strains than PFGE. All but 2 of the 36 isolates acquired in Cambodia during 2013–2014 belonged to the same clade, C5, of lineage C. This clade has been isolated in Cambodia since at least 1999. The Chinese outbreak isolates belonged to a different clade (C4) and were resistant to nalidixic acid, whereas the Cambodian outbreak isolates displayed pan-susceptibility to antibiotics. Since 2014, the total number of cases has decreased, but there has been an increase in the frequency with which nalidixic acid-resistant C5 isolates are isolated. The frequency of these isolates should be monitored over time, because they display decreased susceptibility to ciprofloxacin, the first-choice antibiotic for treating paratyphoid fever.

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          Most cited references21

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          ISfinder: the reference centre for bacterial insertion sequences

          ISfinder () is a dedicated database for bacterial insertion sequences (ISs). It has superseded the Stanford reference center. One of its functions is to assign IS names and to provide a focal point for a coherent nomenclature. It is also the repository for ISs. Each new IS is indexed together with information such as its DNA sequence and open reading frames or potential coding sequences, the sequence of the ends of the element and target sites, its origin and distribution together with a bibliography where available. Another objective is to continuously monitor ISs to provide updated comprehensive groupings or families and to provide some insight into their phylogenies. The site also contains extensive background information on ISs and transposons in general. Online tools are gradually being added. At present an online Blast facility against the entire bank is available. But additional features will include alignment capability, PsiBLAST and HMM profiles. ISfinder also includes a section on bacterial genomes and is involved in annotating the IS content of these genomes. Finally, this database is currently recommended by several microbiology journals for registration of new IS elements before their publication.
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            Improving the accuracy of demographic and molecular clock model comparison while accommodating phylogenetic uncertainty.

            Recent developments in marginal likelihood estimation for model selection in the field of Bayesian phylogenetics and molecular evolution have emphasized the poor performance of the harmonic mean estimator (HME). Although these studies have shown the merits of new approaches applied to standard normally distributed examples and small real-world data sets, not much is currently known concerning the performance and computational issues of these methods when fitting complex evolutionary and population genetic models to empirical real-world data sets. Further, these approaches have not yet seen widespread application in the field due to the lack of implementations of these computationally demanding techniques in commonly used phylogenetic packages. We here investigate the performance of some of these new marginal likelihood estimators, specifically, path sampling (PS) and stepping-stone (SS) sampling for comparing models of demographic change and relaxed molecular clocks, using synthetic data and real-world examples for which unexpected inferences were made using the HME. Given the drastically increased computational demands of PS and SS sampling, we also investigate a posterior simulation-based analogue of Akaike's information criterion (AIC) through Markov chain Monte Carlo (MCMC), a model comparison approach that shares with the HME the appealing feature of having a low computational overhead over the original MCMC analysis. We confirm that the HME systematically overestimates the marginal likelihood and fails to yield reliable model classification and show that the AICM performs better and may be a useful initial evaluation of model choice but that it is also, to a lesser degree, unreliable. We show that PS and SS sampling substantially outperform these estimators and adjust the conclusions made concerning previous analyses for the three real-world data sets that we reanalyzed. The methods used in this article are now available in BEAST, a powerful user-friendly software package to perform Bayesian evolutionary analyses.
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              Standardization of pulsed-field gel electrophoresis protocols for the subtyping of Escherichia coli O157:H7, Salmonella, and Shigella for PulseNet.

              Standardized rapid pulsed-field gel electrophoresis (PFGE) protocols for the subtyping of Escherichia coli O157:H7, Salmonella serotypes, and Shigella species are described. These protocols are used by laboratories in PulseNet, a network of state and local health departments, and other public health laboratories that perform real-time PFGE subtyping of these bacterial foodborne pathogens for surveillance and outbreak investigations. Development and standardization of these protocols consisted of a thorough optimization of reagents and reaction conditions to ensure that the protocols yielded consistent results and high-quality PFGE pattern data in all the PulseNet participating laboratories. These rapid PFGE protocols are based on the original 3-4-day standardized procedure developed at Centers for Disease Control and Prevention that was validated in 1996 and 1997 by eight independent laboratories. By using these rapid standardized PFGE protocols, PulseNet laboratories are able to subtype foodborne pathogens in approximately 24 h, allowing for the early detection of foodborne disease case clusters and often aiding in the identification of the source responsible for the infections.
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                Author and article information

                Journal
                Microb Genom
                Microb Genom
                MGen
                Microbial Genomics
                Microbiology Society
                2057-5858
                November 2016
                30 November 2016
                : 2
                : 11
                : e000092
                Affiliations
                [ 1]Department of Clinical Sciences, Institute of Tropical Medicine , Antwerp, Belgium
                [ 2]Department of Microbiology and Immunology, KU Leuven , Leuven, Belgium
                [ 3]Institut Pasteur, Unité des Bactéries Pathogènes Entériques, Centre National de Référence des Escherichia coli, Shigella et Salmonella , Paris, France
                [ 4]Santé Publique France, Direction des Maladies Infectieuses , Saint-Maurice, France
                [ 5]Institute of Environmental Science and Research Limited, NCBID , Wallaceville, New Zealand
                [ 6]Sihanouk Hospital Centre of HOPE , Phnom Penh, Cambodia
                [ 7]Department of Tropical Diseases, University Hospital Antwerp , Antwerp, Belgium
                [ 8]Institut Pasteur, Plate-forme Génomique (PF1) , Paris, France
                Author notes
                Correspondence François-Xavier Weill ( francois-xavier.weill@ 123456pasteur.fr )
                [†]

                These authors contributed equally to this work.

                All supporting data, code and protocols have been provided within the article or through supplementary data files.

                Article
                mgen000092
                10.1099/mgen.0.000092
                5320704
                28348832
                830baf65-723b-4a7f-bc7f-8f9ec50fa764
                © 2016 The Authors

                This is an open access article under the terms of the Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution and reproduction in any medium, provided the original author and source are credited.

                History
                : 07 July 2016
                : 05 October 2016
                Funding
                Funded by: Belgian Directorate of Development Cooperation (DGD)
                Award ID: Not applicable
                Funded by: The Institut Pasteur and the Institut Pasteur International Network
                Award ID: Not applicable
                Funded by: Santé Publique France
                Award ID: Not applicable
                Funded by: The French government’s Investissement d’Avenir programme
                Award ID: Not applicable
                Funded by: Laboratoire d’Excellence ‘Integrative Biology of Emerging Infectious Diseases’
                Award ID: ANR-10-LABX-62-IBEID
                Funded by: Fondation Le Roch-Les Mousquetaires
                Award ID: Not applicable
                Funded by: France Génomique” consortium
                Award ID: ANR10-INBS-09-08
                Funded by: The Flemish Ministry of Sciences (EWI)
                Award ID: Not applicable
                Categories
                Research Paper
                Microbial Evolution and Epidemiology
                Communicable Disease Genomics
                Custom metadata
                0

                cambodia,salmonella paratyphi a,whole genome sequencing,resistance

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