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      Peste des petits ruminants (PPR): A neglected tropical disease in Maghreb region of North Africa and its threat to Europe

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          Abstract

          Background

          Peste des petits ruminants (PPR) is a contagious disease listed by the World Organisation for Animal health (OIE) as being a specific hazard. It affects sheep, goats, and wild ungulates, and is prevalent throughout the developing world particularly Asia, the Middle East, and Africa. PPR has been targeted for eradication by 2030 by the Food and Agriculture Organization of the United Nations (FAO) and the OIE, after the successful eradication of the related disease, rinderpest in cattle. PPR was first reported in 1942 in the Ivory Coast in Western Africa and has since extended its range in Asia, the Middle East, and Africa posing an immediate threat of incursion into Europe, South East Asia and South Africa. Although robust vaccines are available, the use of these vaccines in a systematic and rational manner is not widespread, resulting in this devastating disease becoming an important neglected tropical disease in the developing world.

          Methodology

          We isolated and characterized the PPR virus from an outbreak in Cheraga, northern Algeria, during October 2015 by analyzing the partial N-gene sequence in comparison with other viruses from the Maghreb region. As well as sequencing the full length viral genome and performing real-time RT-PCR on clinical samples. Maximum-likelihood and Bayesian temporal and phylogeographic analyses were performed to assess the persistence and spread of PPRV circulation from Eastern Africa in the Maghreb region of North Africa.

          Conclusions

          Recent PPR outbreaks in Cheraga, in the northern part of Algiers (October 2015) and North-West Morocco (June, 2015) highlight that PPRV has spread to the northern border of North Africa and may pose a threat of introduction to Europe. Phylogeographic analysis suggests that lineage IV PPRV has spread from Eastern Africa, most likely from the Sudan 2000 outbreak, into Northern Africa resulting in the 2008 Moroccan outbreak. Maximum-likelihood and Bayesian analysis shows that these North African viruses cluster closely together suggesting the existence of continual regional circulation. Considering the same virus is circulating in Algeria, Morocco and Tunisia, implementation of a common Maghreb PPR eradication strategy would be beneficial for the region.

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          Most cited references41

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          Adherens junction protein nectin-4 (PVRL4) is the epithelial receptor for measles virus

          Measles (MV) is an aerosol-transmitted virus that affects more than 10 million children each year and accounts for approximately 120,000 deaths 1,2 . While it was long believed to replicate in the respiratory epithelium before disseminating, it was recently shown to initially infect macrophages and dendritic cells of the airways using the signaling lymphocytic activation molecule (SLAM, CD150) as receptor 3-6 . These cells then cross the respiratory epithelium and ferry the infection to lymphatic organs where MV replicates vigorously 7 . How and where the virus crosses back into the airways has remained unknown. Based on functional analyses of surface proteins preferentially expressed on virus-permissive epithelial cell lines, we identified nectin-4 8 (poliovirus-receptor-like-4) as a candidate host exit receptor. This adherens junction protein of the immunoglobulin superfamily interacts with the viral attachment protein with high affinity through its membrane-distal domain. Nectin-4 sustains MV entry and non-cytopathic lateral spread in well-differentiated primary human airway epithelial sheets infected basolaterally. It is down-regulated in infected epithelial cells, including those of macaque tracheas. While other viruses use receptors to enter hosts or transit through their epithelial barriers, we suggest that MV targets nectin-4 to emerge in the airways. Nectin-4 is a cellular marker of several types of cancer 9-11 , which has implications for ongoing MV-based clinical trials of oncolysis 12 .
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            SPREAD: spatial phylogenetic reconstruction of evolutionary dynamics

            Summary: SPREAD is a user-friendly, cross-platform application to analyze and visualize Bayesian phylogeographic reconstructions incorporating spatial–temporal diffusion. The software maps phylogenies annotated with both discrete and continuous spatial information and can export high-dimensional posterior summaries to keyhole markup language (KML) for animation of the spatial diffusion through time in virtual globe software. In addition, SPREAD implements Bayes factor calculation to evaluate the support for hypotheses of historical diffusion among pairs of discrete locations based on Bayesian stochastic search variable selection estimates. SPREAD takes advantage of multicore architectures to process large joint posterior distributions of phylogenies and their spatial diffusion and produces visualizations as compelling and interpretable statistical summaries for the different spatial projections. Availability: SPREAD is licensed under the GNU Lesser GPL and its source code is freely available as a GitHub repository: https://github.com/phylogeography/SPREAD Contact: filip.bielejec@rega.kuleuven.be
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              Bayesian estimation of concordance among gene trees.

              Multigene sequence data have great potential for elucidating important and interesting evolutionary processes, but statistical methods for extracting information from such data remain limited. Although various biological processes may cause different genes to have different genealogical histories (and hence different tree topologies), we also may expect that the number of distinct topologies among a set of genes is relatively small compared with the number of possible topologies. Therefore evidence about the tree topology for one gene should influence our inferences of the tree topology on a different gene, but to what extent? In this paper, we present a new approach for modeling and estimating concordance among a set of gene trees given aligned molecular sequence data. Our approach introduces a one-parameter probability distribution to describe the prior distribution of concordance among gene trees. We describe a novel 2-stage Markov chain Monte Carlo (MCMC) method that first obtains independent Bayesian posterior probability distributions for individual genes using standard methods. These posterior distributions are then used as input for a second MCMC procedure that estimates a posterior distribution of gene-to-tree maps (GTMs). The posterior distribution of GTMs can then be summarized to provide revised posterior probability distributions for each gene (taking account of concordance) and to allow estimation of the proportion of the sampled genes for which any given clade is true (the sample-wide concordance factor). Further, under the assumption that the sampled genes are drawn randomly from a genome of known size, we show how one can obtain an estimate, with credibility intervals, on the proportion of the entire genome for which a clade is true (the genome-wide concordance factor). We demonstrate the method on a set of 106 genes from 8 yeast species.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                20 April 2017
                2017
                : 12
                : 4
                : e0175461
                Affiliations
                [1 ]National Veterinary Higher School, Algiers, Algeria
                [2 ]The Pirbright Institute, Woking, Surrey, United Kingdom
                Institut National de la Recherche Agronomique, FRANCE
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                • Conceptualization: SP.

                • Data curation: SP BDC MM.

                • Formal analysis: BDC MM SP.

                • Funding acquisition: SP.

                • Investigation: RB MM BDC SP.

                • Methodology: MM RB BDC SP.

                • Project administration: SP.

                • Resources: RB KAO DK BDC MM SP.

                • Supervision: SP.

                • Validation: SP BDC MM.

                • Visualization: SP BDC MM RB.

                • Writing – original draft: MM BDC SP RB.

                • Writing – review & editing: SP BDC MM RB.

                Article
                PONE-D-17-05779
                10.1371/journal.pone.0175461
                5398521
                28426782
                325ecf2c-f5b3-4300-b6c7-17e6678c819f
                © 2017 Baazizi et al

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

                History
                : 14 February 2017
                : 27 March 2017
                Page count
                Figures: 6, Tables: 2, Pages: 16
                Funding
                Funded by: We thank the Biotechnology and Biological Sciences Research Council and the European Commission ANIHWA ERA fund for providing support for PPR epidemiological research under the FADH and IUEPPR projects led by the Pirbright Institute (BB/L004801/1 and BB/L013657/1).The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Award ID: (BB/L004801/1 and BB/L013657/1).
                Award Recipient :
                We thank the Biotechnology and Biological Sciences Research Council and the European Commission ANIHWA ERA fund for providing support for PPR epidemiological research under the FADH and IUEPPR projects led by the Pirbright Institute (SP) (BB/L004801/1 and BB/L013657/1). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                People and Places
                Geographical Locations
                Africa
                People and Places
                Geographical Locations
                Africa
                Algeria
                Biology and Life Sciences
                Organisms
                Animals
                Vertebrates
                Amniotes
                Mammals
                Ruminants
                Goats
                Biology and Life Sciences
                Agriculture
                Farms
                People and Places
                Geographical Locations
                Africa
                Morocco
                Biology and Life Sciences
                Organisms
                Animals
                Vertebrates
                Amniotes
                Mammals
                Ruminants
                Sheep
                Research and Analysis Methods
                Database and Informatics Methods
                Bioinformatics
                Sequence Analysis
                Biology and Life Sciences
                Organisms
                Animals
                Vertebrates
                Amniotes
                Mammals
                Ruminants
                Custom metadata
                All sequences have been submitted to GenBank, and all accession numbers are listed in the manuscript and its Supporting Information files.

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                Uncategorized

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