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      Convergent Evolution of Escape from Hepaciviral Antagonism in Primates

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          Abstract

          Escape from antagonism by hepatitis C and related viruses has repeatedly evolved in antiviral factor MAVS via convergent evolution, revealing an ancient history of previous viral encounters in primates.

          Abstract

          The ability to mount an interferon response on sensing viral infection is a critical component of mammalian innate immunity. Several viruses directly antagonize viral sensing pathways to block activation of the host immune response. Here, we show that recurrent viral antagonism has shaped the evolution of the host protein MAVS—a crucial component of the viral-sensing pathway in primates. From sequencing and phylogenetic analyses of MAVS from 21 simian primates, we found that MAVS has evolved under strong positive selection. We focused on how this positive selection has shaped MAVS' susceptibility to Hepatitis C virus (HCV). We functionally tested MAVS proteins from diverse primate species for their ability to resist antagonism by HCV, which uses its protease NS3/4A to cleave human MAVS. We found that MAVS from multiple primates are resistant to inhibition by the HCV protease. This resistance maps to single changes within the protease cleavage site in MAVS, which protect MAVS from getting cleaved by the HCV protease. Remarkably, most of these changes have been independently acquired at a single residue 506 that evolved under positive selection. We show that “escape” mutations lower affinity of the NS3 protease for MAVS and allow it to better restrict HCV replication. We further show that NS3 proteases from all other primate hepaciviruses, including the highly divergent GBV-A and GBV-C viruses, are functionally similar to HCV. We conclude that convergent evolution at residue 506 in multiple primates has resulted in escape from antagonism by hepaciviruses. Our study provides a model whereby insights into the ancient history of viral infections in primates can be gained using extant host and virus genes. Our analyses also provide a means by which primates might clear infections by extant hepaciviruses like HCV.

          Author Summary

          Hepatitis C virus (HCV) causes chronic liver disease and is estimated to infect 170 million people worldwide. HCV is able to establish a persistent infection in part by inhibiting the innate immune response. It does so by using its protease, NS3, to cleave the host's antiviral factor MAVS, which normally activates the interferon response. Using an assay that measures MAVS activity, we found that multiple primate species contain a version of MAVS that is resistant to HCV antagonism. Surprisingly, most of these primates have independently converged on changes in the same amino acid residue of MAVS to escape cleavage by the HCV protease. We found that the HCV protease has lower binding affinity for these resistant MAVS variants, which consequently are more effective at restricting HCV infection. Using a combination of phylogenetic and functional analyses of proteases from other HCV-related viruses, we infer that ancestral primates were likely exposed to and adapted to HCV-like viruses. One consequence of this adaptation is that changes that have given rise to extant MAVS variants may now provide protection from modern-day viruses.

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          Most cited references37

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          The V proteins of paramyxoviruses bind the IFN-inducible RNA helicase, mda-5, and inhibit its activation of the IFN-beta promoter.

          Most paramyxoviruses circumvent the IFN response by blocking IFN signaling and limiting the production of IFN by virus-infected cells. Here we report that the highly conserved cysteine-rich C-terminal domain of the V proteins of a wide variety of paramyxoviruses binds melanoma differentiation-associated gene 5 (mda-5) product. mda-5 is an IFN-inducible host cell DExD/H box helicase that contains a caspase recruitment domain at its N terminus. Overexpression of mda-5 stimulated the basal activity of the IFN-beta promoter in reporter gene assays and significantly enhanced the activation of the IFN-beta promoter by intracellular dsRNA. Both these activities were repressed by coexpression of the V proteins of simian virus 5, human parainfluenza virus 2, mumps virus, Sendai virus, and Hendra virus. Similar results to the reporter assays were obtained by measuring IFN production. Inhibition of mda-5 by RNA interference or by dominant interfering forms of mda-5 significantly inhibited the activation of the IFN-beta promoter by dsRNA. It thus appears that mda-5 plays a central role in an intracellular signal transduction pathway that can lead to the activation of the IFN-beta promoter, and that the V proteins of paramyxoviruses interact with mda-5 to block its activity.
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            Genetic diversity and evolution of hepatitis C virus--15 years on.

            In the 15 years since the discovery of hepatitis C virus (HCV), much has been learned about its role as a major causative agent of human liver disease and its ability to persist in the face of host-cell defences and the immune system. This review describes what is known about the diversity of HCV, the current classification of HCV genotypes within the family Flaviviridae and how this genetic diversity contributes to its pathogenesis. On one hand, diversification of HCV has been constrained by its intimate adaptation to its host. Despite the >30 % nucleotide sequence divergence between genotypes, HCV variants nevertheless remain remarkably similar in their transmission dynamics, persistence and disease development. Nowhere is this more evident than in the evolutionary conservation of numerous evasion methods to counteract the cell's innate antiviral defence pathways; this series of highly complex virus-host interactions may represent key components in establishing its 'ecological niche' in the human liver. On the other hand, the mutability and large population size of HCV enables it to respond very rapidly to new selection pressures, manifested by immune-driven changes in T- and B-cell epitopes that are encountered on transmission between individuals with different antigen-recognition repertoires. If human immunodeficiency virus type 1 is a precedent, future therapies that target virus protease or polymerase enzymes may also select very rapidly for antiviral-resistant mutants. These contrasting aspects of conservatism and adaptability provide a fascinating paradigm in which to explore the complex selection pressures that underlie the evolution of HCV and other persistent viruses.
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              A random effects branch-site model for detecting episodic diversifying selection.

              Adaptive evolution frequently occurs in episodic bursts, localized to a few sites in a gene, and to a small number of lineages in a phylogenetic tree. A popular class of "branch-site" evolutionary models provides a statistical framework to search for evidence of such episodic selection. For computational tractability, current branch-site models unrealistically assume that all branches in the tree can be partitioned a priori into two rigid classes--"foreground" branches that are allowed to undergo diversifying selective bursts and "background" branches that are negatively selected or neutral. We demonstrate that this assumption leads to unacceptably high rates of false positives or false negatives when the evolutionary process along background branches strongly deviates from modeling assumptions. To address this problem, we extend Felsenstein's pruning algorithm to allow efficient likelihood computations for models in which variation over branches (and not just sites) is described in the random effects likelihood framework. This enables us to model the process at every branch-site combination as a mixture of three Markov substitution models--our model treats the selective class of every branch at a particular site as an unobserved state that is chosen independently of that at any other branch. When benchmarked on a previously published set of simulated sequences, our method consistently matched or outperformed existing branch-site tests in terms of power and error rates. Using three empirical data sets, previously analyzed for episodic selection, we discuss how modeling assumptions can influence inference in practical situations.
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                Author and article information

                Contributors
                Role: Academic Editor
                Journal
                PLoS Biol
                plos
                plosbiol
                PLoS Biology
                Public Library of Science (San Francisco, USA )
                1544-9173
                1545-7885
                March 2012
                March 2012
                13 March 2012
                : 10
                : 3
                : e1001282
                Affiliations
                [1 ]Division of Basic Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
                [2 ]Department of Immunology, University of Washington School of Medicine, Seattle, Washington, United States of America
                [3 ]Howard Hughes Medical Institute, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
                University of Bath, United Kingdom
                Author notes

                The author(s) have made the following declarations about their contributions: Conceived and designed the experiments: MRP HSM. Performed the experiments: MRP Y-ML SMH. Analyzed the data: MRP Y-ML SMH MG HSM. Contributed reagents/materials/analysis tools: Y-ML SMH MG. Wrote the paper: MRP HSM. Edited the manuscript: MRP Y-ML SMH MG HSM.

                Article
                PBIOLOGY-D-11-03907
                10.1371/journal.pbio.1001282
                3302847
                22427742
                7d780442-67d1-4f39-b723-308327c3a4cb
                Patel 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
                : 27 September 2011
                : 30 January 2012
                Page count
                Pages: 11
                Categories
                Research Article
                Biology
                Evolutionary Biology
                Genetics
                Immunology

                Life sciences
                Life sciences

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