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      Bats host major mammalian paramyxoviruses

      research-article
      1 , 1 , 1 , 2 , 3 , 1 , 1 , 4 , 5 , 6 , 4 , 7 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 13 , 14 , 14 , 15 , 16 , 17 , 26 , 18 , 12 , 1 , 19 , 5 , 20 , 21 , 22 , 23 , 24 , 2 , 25 , a , 1
      Nature Communications
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          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          The large virus family Paramyxoviridae includes some of the most significant human and livestock viruses, such as measles-, distemper-, mumps-, parainfluenza-, Newcastle disease-, respiratory syncytial virus and metapneumoviruses. Here we identify an estimated 66 new paramyxoviruses in a worldwide sample of 119 bat and rodent species (9,278 individuals). Major discoveries include evidence of an origin of Hendra- and Nipah virus in Africa, identification of a bat virus conspecific with the human mumps virus, detection of close relatives of respiratory syncytial virus, mouse pneumonia- and canine distemper virus in bats, as well as direct evidence of Sendai virus in rodents. Phylogenetic reconstruction of host associations suggests a predominance of host switches from bats to other mammals and birds. Hypothesis tests in a maximum likelihood framework permit the phylogenetic placement of bats as tentative hosts at ancestral nodes to both the major Paramyxoviridae subfamilies ( Paramyxovirinae and Pneumovirinae). Future attempts to predict the emergence of novel paramyxoviruses in humans and livestock will have to rely fundamentally on these data.

          Abstract

          The large virus family, Paramyxoviridae, includes several human and livestock viruses. This study, testing 119 bat and rodent species distributed globally, identifies novel putative paramyxovirus species, providing data with potential uses in predictions of the emergence of novel paramyxoviruses in humans and livestock.

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          Most cited references60

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          New algorithms and methods to estimate maximum-likelihood phylogenies: assessing the performance of PhyML 3.0.

          PhyML is a phylogeny software based on the maximum-likelihood principle. Early PhyML versions used a fast algorithm performing nearest neighbor interchanges to improve a reasonable starting tree topology. Since the original publication (Guindon S., Gascuel O. 2003. A simple, fast and accurate algorithm to estimate large phylogenies by maximum likelihood. Syst. Biol. 52:696-704), PhyML has been widely used (>2500 citations in ISI Web of Science) because of its simplicity and a fair compromise between accuracy and speed. In the meantime, research around PhyML has continued, and this article describes the new algorithms and methods implemented in the program. First, we introduce a new algorithm to search the tree space with user-defined intensity using subtree pruning and regrafting topological moves. The parsimony criterion is used here to filter out the least promising topology modifications with respect to the likelihood function. The analysis of a large collection of real nucleotide and amino acid data sets of various sizes demonstrates the good performance of this method. Second, we describe a new test to assess the support of the data for internal branches of a phylogeny. This approach extends the recently proposed approximate likelihood-ratio test and relies on a nonparametric, Shimodaira-Hasegawa-like procedure. A detailed analysis of real alignments sheds light on the links between this new approach and the more classical nonparametric bootstrap method. Overall, our tests show that the last version (3.0) of PhyML is fast, accurate, stable, and ready to use. A Web server and binary files are available from http://www.atgc-montpellier.fr/phyml/.
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            MrBayes 3: Bayesian phylogenetic inference under mixed models.

            MrBayes 3 performs Bayesian phylogenetic analysis combining information from different data partitions or subsets evolving under different stochastic evolutionary models. This allows the user to analyze heterogeneous data sets consisting of different data types-e.g. morphological, nucleotide, and protein-and to explore a wide variety of structured models mixing partition-unique and shared parameters. The program employs MPI to parallelize Metropolis coupling on Macintosh or UNIX clusters.
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              Global trends in emerging infectious diseases

              The next new disease Emerging infectious diseases are a major threat to health: AIDS, SARS, drug-resistant bacteria and Ebola virus are among the more recent examples. By identifying emerging disease 'hotspots', the thinking goes, it should be possible to spot health risks at an early stage and prepare containment strategies. An analysis of over 300 examples of disease emerging between 1940 and 2004 suggests that these hotspots can be accurately mapped based on socio-economic, environmental and ecological factors. The data show that the surveillance effort, and much current research spending, is concentrated in developed economies, yet the risk maps point to developing countries as the more likely source of new diseases. Supplementary information The online version of this article (doi:10.1038/nature06536) contains supplementary material, which is available to authorized users.
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                Author and article information

                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Pub. Group
                2041-1723
                24 April 2012
                : 3
                : 796
                Affiliations
                [1 ]simpleInstitute of Virology, University of Bonn Medical Centre , Bonn 53127, Germany.
                [2 ]simpleCentre International de Recherches Médicales de Franceville , Franceville, Gabon.
                [3 ]simpleInstitute of Vertebrate Biology, Academy of Sciences of the Czech Republic, v.v.i. , Brno, Czech Republic.
                [4 ]simpleNoctalis, Centre for Bat Protection and Information , Bad Segeberg, Germany.
                [5 ]simpleInstitute of Virology, University of Veterinary Medicine Hannover Foundation , Hannover, Germany.
                [6 ]simpleForestry Board Directorate of Strandja Natural Park , Malko Tarnovo, Bulgaria.
                [7 ]simpleKwame Nkrumah University of Science and Technology , Kumasi, Ghana.
                [8 ]simpleUniversity of Lubumbashi , Lubumbashi, Democratic Republic of Congo.
                [9 ]simpleChumakov Institute of Poliomyelitis and Viral Encephalitides , Moscow, Russia.
                [10 ]simpleDepartment of Virology, Bernhard Nocht Institute for Tropical Medicine , Hamburg, Germany.
                [11 ]simpleInfectious Diseases Research Laboratory, University Hospital Professor Edgard Santos, Federal University of Bahia , Salvador, Brazil.
                [12 ]simpleSchool of Veterinary Medicine, Federal University of Bahia , Salvador, Brazil.
                [13 ]simpleInstitute of Virology, Philipps University of Marburg , Marburg, Germany.
                [14 ]simpleInstitute of Pathology, University of Bonn Medical Centre , Bonn, Germany.
                [15 ]simpleInstitute of Pathology, University of Cologne Medical Centre , Cologne, Germany.
                [16 ]simpleInstitute of Experimental Ecology, University of Ulm , Ulm, Germany.
                [17 ]simpleSmithsonian Tropical Research Institute , Balboa, Panama.
                [18 ]simpleKumasi Centre for Collaborative Research in Tropical Medicine (KCCR) , Kumasi, Ghana.
                [19 ]simplePasteur Institute , Bangui, Central African Republic.
                [20 ]simpleNetherlands Center for Infectious Disease Control , Bilthoven, The Netherlands.
                [21 ]simpleMuséum National d'Histoire Naturelle/Centre National de la Recherche Scientifique, UMR 7205 , Paris, France.
                [22 ]simpleInstitute of Medical Virology (Helmut Ruska Haus), Charité Medical School , Berlin, Germany.
                [23 ]simpleDepartment of Conservation Ecology and Entomology, Stellenbosch University , Stellenbosch, South Africa.
                [24 ]simpleInstitute for Novel and Emerging Infections Diseases, Friedrich-Loeffler-Institut, Institute for Novel and Emerging Infectious Diseases , Greifswald–Insel Riems, Germany.
                [25 ]simpleInstitut de Recherche pour le Développement, UMR 224 (MIVEGEC), IRD/CNRS/UM1 , Montpellier, France.
                [26 ]Deceased.
                Author notes
                Article
                ncomms1796
                10.1038/ncomms1796
                3343228
                22531181
                c1c207c1-5a0e-4809-b521-ec9584e78c9b
                Copyright © 2012, Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved.

                This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-nd/3.0/

                History
                : 14 September 2011
                : 19 March 2012
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