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      Filovirus receptor NPC1 contributes to species-specific patterns of ebolavirus susceptibility in bats

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          Abstract

          Biological factors that influence the host range and spillover of Ebola virus (EBOV) and other filoviruses remain enigmatic. While filoviruses infect diverse mammalian cell lines, we report that cells from African straw-colored fruit bats ( Eidolon helvum) are refractory to EBOV infection. This could be explained by a single amino acid change in the filovirus receptor, NPC1, which greatly reduces the affinity of EBOV-NPC1 interaction. We found signatures of positive selection in bat NPC1 concentrated at the virus-receptor interface, with the strongest signal at the same residue that controls EBOV infection in Eidolon helvum cells. Our work identifies NPC1 as a genetic determinant of filovirus susceptibility in bats, and suggests that some NPC1 variations reflect host adaptations to reduce filovirus replication and virulence. A single viral mutation afforded escape from receptor control, revealing a pathway for compensatory viral evolution and a potential avenue for expansion of filovirus host range in nature.

          DOI: http://dx.doi.org/10.7554/eLife.11785.001

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          Ebola virus and other filoviruses can cause devastating diseases in humans and other apes. Numerous small outbreaks of Ebola virus disease have occurred in Africa over the past 40 years. However, in 2013–2015, the largest outbreak on record took place in three Western African nations with no previous history of the disease.

          Human outbreaks of Ebola virus disease likely begin when a person encounters an infected wild animal. Though it remains unclear precisely which animals harbor Ebola virus between outbreaks, and how they transmit the virus to humans or other primates, recent work showed that some filoviruses do infect specific types of bats in nature.

          Ng, Ndungo, Kaczmarek et al. sought to identify the genes that influence whether or not a type of bat is susceptible to infection by Ebola virus and other filoviruses. Several filoviruses, including Ebola virus, were tested to see if they could infect cells that had been collected from four types of African fruit bats. These bats are all found in areas where outbreaks have occurred in the past.

          The tests revealed that a small change in the sequence of the NPC1 gene in some bat cells greatly reduced their susceptibility to Ebola virus. NPC1 encodes a protein that mammals need in order to move cholesterol within their cells. In humans, the loss of the protein encoded by NPC1 causes a rare but very severe disease called Niemann-Pick type C disease. This protein also turns out to be a receptor that the filoviruses must bind to before they can infect the cells. Further analysis then revealed that NPC1 has evolved rapidly in bats, with changes concentrated in the parts of the receptor that interact with Ebola virus.

          Ng, Ndungo, Kaczmarek et al. went on to discover some changes in the genome sequence of Ebola virus that could compensate for the changes in the bat’s NPC1 gene. These findings hint at one way that a filovirus could evolve to better infect a host with receptors that were less than optimal.

          Following on from this work, the next challenges will be to expand the investigation to include additional types of bats, other types of mammals, and other host genes that could influence filovirus infection and disease. Further studies could also examine the other side of the arms race – that is, the evolution of viral genes in bats. However, such studies would be complicated by the lack of viral sequences that have been collected from bats, because to date most have been isolated from humans and other primates instead.

          DOI: http://dx.doi.org/10.7554/eLife.11785.002

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          Most cited references46

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          Datamonkey 2010: a suite of phylogenetic analysis tools for evolutionary biology.

          Datamonkey is a popular web-based suite of phylogenetic analysis tools for use in evolutionary biology. Since the original release in 2005, we have expanded the analysis options to include recently developed algorithmic methods for recombination detection, evolutionary fingerprinting of genes, codon model selection, co-evolution between sites, identification of sites, which rapidly escape host-immune pressure and HIV-1 subtype assignment. The traditional selection tools have also been augmented to include recent developments in the field. Here, we summarize the analyses options currently available on Datamonkey, and provide guidelines for their use in evolutionary biology. Availability and documentation: http://www.datamonkey.org.
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            Codon-substitution models for heterogeneous selection pressure at amino acid sites.

            Comparison of relative fixation rates of synonymous (silent) and nonsynonymous (amino acid-altering) mutations provides a means for understanding the mechanisms of molecular sequence evolution. The nonsynonymous/synonymous rate ratio (omega = d(N)d(S)) is an important indicator of selective pressure at the protein level, with omega = 1 meaning neutral mutations, omega 1 diversifying positive selection. Amino acid sites in a protein are expected to be under different selective pressures and have different underlying omega ratios. We develop models that account for heterogeneous omega ratios among amino acid sites and apply them to phylogenetic analyses of protein-coding DNA sequences. These models are useful for testing for adaptive molecular evolution and identifying amino acid sites under diversifying selection. Ten data sets of genes from nuclear, mitochondrial, and viral genomes are analyzed to estimate the distributions of omega among sites. In all data sets analyzed, the selective pressure indicated by the omega ratio is found to be highly heterogeneous among sites. Previously unsuspected Darwinian selection is detected in several genes in which the average omega ratio across sites is 1. Genes undergoing positive selection include the beta-globin gene from vertebrates, mitochondrial protein-coding genes from hominoids, the hemagglutinin (HA) gene from human influenza virus A, and HIV-1 env, vif, and pol genes. Tests for the presence of positively selected sites and their subsequent identification appear quite robust to the specific distributional form assumed for omega and can be achieved using any of several models we implement. However, we encountered difficulties in estimating the precise distribution of omega among sites from real data sets.
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              We describe Trans-ABySS, a de novo short-read transcriptome assembly and analysis pipeline that addresses variation in local read densities by assembling read substrings with varying stringencies and then merging the resulting contigs before analysis. Analyzing 7.4 gigabases of 50-base-pair paired-end Illumina reads from an adult mouse liver poly(A) RNA library, we identified known, new and alternative structures in expressed transcripts, and achieved high sensitivity and specificity relative to reference-based assembly methods.
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                Author and article information

                Contributors
                Role: Reviewing editor
                Journal
                eLife
                eLife
                eLife
                eLife
                eLife Sciences Publications, Ltd
                2050-084X
                23 December 2015
                2015
                : 4
                : e11785
                Affiliations
                [1 ]deptDepartment of Microbiology and Immunology , Albert Einstein College of Medicine , Bronx, United States
                [2 ]deptDepartment of Integrative Biology , University of Texas at Austin , Austin, United States
                [3 ]deptUnited States Army Medical Research Institute of Infectious Diseases , Fort Detrick , Frederick, United States
                [4 ]deptInstitute of Virology , University of Bonn Medical Center , Bonn, Germany
                [5 ]deptInstitute for Computational Engineering and Sciences , University of Texas at Austin , Austin, United States
                [6 ]University of Glasgow MRC Virology Unit , Glasgow, United Kingdom
                [7 ]deptDepartment of Molecular Biosciences , University of Texas at Austin , Austin, United States
                [8 ]deptProgram in Emerging Infectious Diseases , Duke-NUS Graduate Medical School , Singapore
                [9 ]Netherlands Cancer Institute , Plesmanlaan, The Netherlands
                [10 ]German Centre for Infectious Diseases Research , Bonn, Germany
                [11 ]deptIntegrated Research Facility at Fort Detrick, National Institute for Allergy and Infectious Diseases, National Institutes of Health , Fort Detrick , Frederick, United States
                [12 ]deptBioFrontiers Institute , University of Colorado Boulder , Boulder, United States
                [13 ]deptDepartment of Molecular, Cellular and Developmental Biology , University of Colorado Boulder , Boulder, United States
                [14]Max Planck Institute for Developmental Biology , Germany
                [15]Max Planck Institute for Developmental Biology , Germany
                Author notes
                [†]

                These authors contributed equally to this work.

                Author information
                http://orcid.org/0000-0002-7800-6045
                http://orcid.org/0000-0003-0232-7077
                Article
                11785
                10.7554/eLife.11785
                4709267
                26698106
                fdb0cb6f-aa70-44ef-b7b4-e9e1b310c750

                This is an open-access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.

                History
                : 23 September 2015
                : 19 November 2015
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100000002, National Institutes of Health;
                Award ID: AI101436
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000774, Defense Threat Reduction Agency;
                Award ID: CB3948
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100000780, European Commission;
                Award ID: EU FP-7 Antigone
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100002347, Bundesministerium für Bildung und Forschung;
                Award ID: EBOKON Project
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100001381, National Research Foundation-Prime Minister's office, Republic of Singapore;
                Award ID: CRP001-056
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000002, National Institutes of Health;
                Award ID: GM093086
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000774, Defense Threat Reduction Agency;
                Award ID: HDTRA1-11-C-0061
                Award Recipient :
                The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
                Categories
                Research Article
                Genomics and Evolutionary Biology
                Microbiology and Infectious Disease
                Custom metadata
                2.5
                NPC1 is a genetic determinant of filovirus susceptibility in bats, and some variations in bat NPC1 may reflect host adaptations to reduce filovirus replication and virulence.

                Life sciences
                ebola virus,filovirus,viral receptor,niemann-pick c1,virus-host co-evolution,positive selection,npc1,host range,viruses,other,bats

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