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      Relatives of rubella virus in diverse mammals

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          Abstract

          We describe the first known relatives of rubella virus ( Matonaviridae: Rubivirus) 1 in Africa and Europe. Ruhugu virus, the closest relative of rubella virus, was found in apparently healthy cyclops leaf-nosed bats ( Hipposideros cyclops) in Uganda. Rustrela virus, outgroup to the rubella/ruhugu clade of viruses, was found in acutely encephalitic placental and marsupial animals at a zoo in Germany and in wild yellow-necked field mice ( Apodemus flavicollis) at and near the zoo. Ruhugu and rustrela viruses share an identical genomic architecture with rubella virus 2, 3 . Amino acid sequences of rubella, ruhugu, and rustrela viruses are moderately to highly conserved within 4 putative B-cell epitopes in the fusion (EI) protein and, in the case of rubella and ruhugu viruses, within two putative T-cell epitopes in the capsid protein 46 . Modeling of E1 homotrimers in the post-fusion state predicts similar host-cell membrane fusion capacity for ruhugu and rubella viruses 5 . Together, these findings suggest show that some members of the Matonaviridae can cross wide host species barriers and that rubella virus likely had a zoonotic origin. Our findings raise concerns about future zoonotic transmission of rubella-like viruses but open doors for heretofore impossible comparative studies and novel animal models of rubella and congenital rubella syndrome.

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          The Phyre2 web portal for protein modeling, prediction and analysis.

          Phyre2 is a suite of tools available on the web to predict and analyze protein structure, function and mutations. The focus of Phyre2 is to provide biologists with a simple and intuitive interface to state-of-the-art protein bioinformatics tools. Phyre2 replaces Phyre, the original version of the server for which we previously published a paper in Nature Protocols. In this updated protocol, we describe Phyre2, which uses advanced remote homology detection methods to build 3D models, predict ligand binding sites and analyze the effect of amino acid variants (e.g., nonsynonymous SNPs (nsSNPs)) for a user's protein sequence. Users are guided through results by a simple interface at a level of detail they determine. This protocol will guide users from submitting a protein sequence to interpreting the secondary and tertiary structure of their models, their domain composition and model quality. A range of additional available tools is described to find a protein structure in a genome, to submit large number of sequences at once and to automatically run weekly searches for proteins that are difficult to model. The server is available at http://www.sbg.bio.ic.ac.uk/phyre2. A typical structure prediction will be returned between 30 min and 2 h after submission.
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            Protein Identification and Analysis Tools on the ExPASy Server

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              Host and viral traits predict zoonotic spillover from mammals

              The majority of human emerging infectious diseases (EIDs) are zoonotic, with viruses originating in wild mammals of particular concern (e.g. HIV, Ebola, SARS) 1–3 . Understanding patterns of viral diversity in wildlife and determinants of successful cross-species transmission, or spillover, are therefore key goals for pandemic surveillance programs 4 . However, few analytical tools exist to identify which host species likely harbor the next human virus, or which viruses can cross species boundaries 5–7 . Here we conduct the most comprehensive analysis yet of mammalian host-virus relationships and show that both the total number of viruses that infect a given species, and the proportion likely to be zoonotic are predictable. After controlling for research effort, the proportion of zoonotic viruses per species is predicted by phylogenetic relatedness to humans, host taxonomy, and human population within a species range – which may reflect human-wildlife contact. We demonstrate for the first time that bats harbor a significantly higher proportion of zoonotic viruses than all other mammalian orders. We identify the taxa and geographic regions with the largest estimated number of ‘missing viruses’ and ‘missing zoonoses’ and therefore of highest value for future surveillance. We then show that phylogenetic host breadth and other viral traits are significant predictors of zoonotic potential, providing a novel framework to assess if a newly discovered mammalian virus could infect people.
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                Author and article information

                Journal
                0410462
                6011
                Nature
                Nature
                Nature
                0028-0836
                1476-4687
                25 July 2020
                07 October 2020
                October 2020
                07 April 2021
                : 586
                : 7829
                : 424-428
                Affiliations
                [1 ]Department of Pathobiological Sciences, University of Wisconsin-Madison, Madison, WI 53706, USA
                [2 ]Uniformed Services University of the Health Sciences, Bethesda, MD 20814 USA
                [3 ]Leidos, Reston, VA 20190, USA
                [4 ]Genomics and Bioinformatics Department, Biological Defense Research Directorate, Naval Medical Research Center–Frederick, Fort Detrick, Frederick, MD 21702, USA
                [5 ]Institute of Diagnostic Virology, Friedrich-Loeffler-Institut, 17493 Greifswald–Insel Riems, Mecklenburg-Western Pomerania, Germany
                [6 ]State Office for Agriculture, Food Safety and Fisheries, 18059 Rostock, Mecklenburg-Western Pomerania, Germany
                [7 ]Department of Experimental Animal Facilities and Biorisk Management, Friedrich-Loeffler-Institut, 17493 Greifswald–Insel Riems, Mecklenburg-Western Pomerania, Germany
                [8 ]Institute of Novel and Emerging Infectious Diseases, Friedrich-Loeffler-Institut, 17493 Greifswald–Insel Riems, Mecklenburg-Western Pomerania, Germany
                [9 ]German Center for Infection Research (DZIF), Site Hamburg - Lübeck - Borstel - Insel Riems, 17493 Greifswald–Insel Riems, Mecklenburg-Western Pomerania, Germany
                [10 ]Integrated Research Facility at Fort Detrick, National Institute of Allergy and Infectious Diseases, National, Institutes of Health, Fort Detrick, Frederick, MD 21702, USA
                [11 ]Global Health Institute, University of Wisconsin-Madison, Madison, WI 53706, USA
                Author notes
                [*]

                These authors contributed equally to this work

                Author contributions. A.J.B, A.C.P, A.E., J.H.K, K.A.B.-L., M.B., and T.L.G. contributed to the study conception and design. A.B., A.J.B, A.C.P, A.E., E.H., G.P., K.A.B.-L., M.B., R.G.U. and T.L.G. contributed to sample and data collection. A.B., A.J.B, A.C.P, A.E., F.P., D.H., E.H., J.H.K, K.A.B.-L., M.B., R.G.U. and T.L.G. contributed to data analyses, interpretation, and writing. All authors read and approved the final manuscript.

                Correspondence and requests for materials should be addressed to:Tony L. Goldberg, Department of Pathobiological Sciences, University of Wisconsin-Madison, 1656 Linden Drive, Madison, WI 53706, USA, tony.goldberg@ 123456wisc.edu ; Phone: +1-608-890-2618; Fax: +1-608-262-7420, Martin Beer, Institute of Diagnostic Virology, Friedrich-Loeffler-Institut, 17493 Greifswald–Insel Riems, Mecklenburg-West Pomerania, Germany., martin.beer@ 123456fli.de ; Phone: +49-383517-1200; Fax: +49-383517-1156
                Article
                NIHMS1613362
                10.1038/s41586-020-2812-9
                7572621
                33029010
                dcceeaea-4341-4903-b853-5b81e9e912ad

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