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      Human Influenza A Virus Hemagglutinin Glycan Evolution Follows a Temporal Pattern to a Glycan Limit

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          Abstract

          Frequent mutation of its major antibody target, the glycoprotein hemagglutinin, ensures that the influenza virus is perennially both a rapidly emerging virus and a major threat to public health. One type of mutation escapes immunity by adding a glycan onto an area of hemagglutinin that many antibodies recognize. This study revealed that these glycan changes follow a simple temporal pattern. Every 5 to 7 years, hemagglutinin adds a new glycan, up to a limit. After this limit is reached, no net additions of glycans occur. Instead, glycans are swapped or lost at longer intervals. Eventually, a pandemic replaces the terminally glycosylated hemagglutinin with a minimally glycosylated one from the animal reservoir, restarting the cycle. This pattern suggests the following: (i) some hemagglutinins are evolved for this decades-long process, which is both defined by and limited by successive glycan addition; and (ii) hemagglutinin's antibody dominance and its capacity for mutations are highly adapted features that allow influenza to outpace our antibody-based immunity.

          ABSTRACT

          Human antibody-based immunity to influenza A virus is limited by antigenic drift resulting from amino acid substitutions in the hemagglutinin (HA) head domain. Glycan addition can cause large antigenic changes but is limited by fitness costs to viral replication. Here, we report that glycans are added to H1 and H3 HAs at discrete 5-to-7-year intervals, until they reach a functional glycan limit, after which glycans are swapped at approximately 2-fold-longer intervals. Consistent with this pattern, 2009 pandemic H1N1 added a glycan at residue N162 over the 2015–2016 season, an addition that required two epistatic HA head mutations for complete glycosylation. These strains rapidly replaced H1N1 strains globally, by 2017 dominating H3N2 and influenza B virus strains for the season. The pattern of glycan modulation that we outline should aid efforts for tracing the epidemic potential of evolving human IAV strains.

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          Most cited references35

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          Role of receptor binding specificity in influenza A virus transmission and pathogenesis.

          The recent emergence of a novel avian A/H7N9 influenza virus in poultry and humans in China, as well as laboratory studies on adaptation and transmission of avian A/H5N1 influenza viruses, has shed new light on influenza virus adaptation to mammals. One of the biological traits required for animal influenza viruses to cross the species barrier that received considerable attention in animal model studies, in vitro assays, and structural analyses is receptor binding specificity. Sialylated glycans present on the apical surface of host cells can function as receptors for the influenza virus hemagglutinin (HA) protein. Avian and human influenza viruses typically have a different sialic acid (SA)-binding preference and only few amino acid changes in the HA protein can cause a switch from avian to human receptor specificity. Recent experiments using glycan arrays, virus histochemistry, animal models, and structural analyses of HA have added a wealth of knowledge on receptor binding specificity. Here, we review recent data on the interaction between influenza virus HA and SA receptors of the host, and the impact on virus host range, pathogenesis, and transmission. Remaining challenges and future research priorities are also discussed.
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            Many-core algorithms for statistical phylogenetics.

            Statistical phylogenetics is computationally intensive, resulting in considerable attention meted on techniques for parallelization. Codon-based models allow for independent rates of synonymous and replacement substitutions and have the potential to more adequately model the process of protein-coding sequence evolution with a resulting increase in phylogenetic accuracy. Unfortunately, due to the high number of codon states, computational burden has largely thwarted phylogenetic reconstruction under codon models, particularly at the genomic-scale. Here, we describe novel algorithms and methods for evaluating phylogenies under arbitrary molecular evolutionary models on graphics processing units (GPUs), making use of the large number of processing cores to efficiently parallelize calculations even for large state-size models. We implement the approach in an existing Bayesian framework and apply the algorithms to estimating the phylogeny of 62 complete mitochondrial genomes of carnivores under a 60-state codon model. We see a near 90-fold speed increase over an optimized CPU-based computation and a >140-fold increase over the currently available implementation, making this the first practical use of codon models for phylogenetic inference over whole mitochondrial or microorganism genomes. Source code provided in BEAGLE: Broad-platform Evolutionary Analysis General Likelihood Evaluator, a cross-platform/processor library for phylogenetic likelihood computation (http://beagle-lib.googlecode.com/). We employ a BEAGLE-implementation using the Bayesian phylogenetics framework BEAST (http://beast.bio.ed.ac.uk/).
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              Tracking global patterns of N-linked glycosylation site variation in highly variable viral glycoproteins: HIV, SIV, and HCV envelopes and influenza hemagglutinin.

              Human and simian immunodeficiency viruses (HIV and SIV), influenza virus, and hepatitis C virus (HCV) have heavily glycosylated, highly variable surface proteins. Here we explore N-linked glycosylation site (sequon) variation at the population level in these viruses, using a new Web-based program developed to facilitate the sequon tracking and to define patterns (www.hiv.lanl.gov). This tool allowed rapid visualization of the two distinctive patterns of sequon variation found in HIV-1, HIV-2, and SIV CPZ. The first pattern (fixed) describes readily aligned sites that are either simply present or absent. These sites tend to be occupied by high-mannose glycans. The second pattern (shifting) refers to sites embedded in regions of extreme local length variation and is characterized by shifts in terms of the relative position and local density of sequons; these sites tend to be populated by complex carbohydrates. HIV, with its extreme variation in number and precise location of sequons, does not have a net increase in the number of sites over time at the population level. Primate lentiviral lineages have host species-dependent levels of sequon shifting, with HIV-1 in humans the most extreme. HCV E1 and E2 proteins, despite evolving extremely rapidly through point mutation, show limited sequon variation, although two shifting sites were identified. Human influenza A hemagglutinin H3 HA1 is accumulating sequons over time, but this trend is not evident in any other avian or human influenza A serotypes.
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                Author and article information

                Contributors
                Role: Editor
                Role: Solicited external reviewer
                Role: Solicited external reviewer
                Journal
                mBio
                MBio
                mbio
                mbio
                mBio
                mBio
                American Society for Microbiology (1752 N St., N.W., Washington, DC )
                2150-7511
                2 April 2019
                Mar-Apr 2019
                : 10
                : 2
                : e00204-19
                Affiliations
                [a ]Cellular Biology Section, Laboratory of Viral Diseases NIAID, NIH, Bethesda, Maryland, USA
                [b ]Division of International Epidemiology and Population Studies, Fogarty International Center, NIH, Bethesda, Maryland, USA
                [c ]Global Health and Emerging Pathogens Institute, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
                [d ]Department of Microbiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
                [e ]Department of Chemistry and Biochemistry and the National Biomedical Computation Resource, University of California, San Diego, La Jolla, California, USA
                Johns Hopkins Bloomberg School of Public Health
                The Scripps Research Institute
                Utrecht University
                Author notes
                Address correspondence to Meghan O. Altman, meghan@ 123456altmans.org , or Jonathan W. Yewdell, jyewdell@ 123456niaid.nih.gov .
                Author information
                https://orcid.org/0000-0002-8910-9074
                https://orcid.org/0000-0001-5756-5182
                https://orcid.org/0000-0001-6712-5076
                https://orcid.org/0000-0003-3581-1148
                https://orcid.org/0000-0002-2928-7506
                https://orcid.org/0000-0003-4814-0179
                https://orcid.org/0000-0002-3826-1906
                Article
                mBio00204-19
                10.1128/mBio.00204-19
                6445938
                30940704
                9321644f-6d5c-4856-84fa-2ddf25334190

                This is a work of the U.S. Government and is not subject to copyright protection in the United States. Foreign copyrights may apply.

                History
                : 25 January 2019
                : 15 February 2019
                Page count
                supplementary-material: 10, Figures: 7, Tables: 0, Equations: 0, References: 57, Pages: 15, Words: 10712
                Categories
                Research Article
                Host-Microbe Biology
                Custom metadata
                March/April 2019

                Life sciences
                influenza,viral evolution,hemagglutinin,immune evasion,glycosylation
                Life sciences
                influenza, viral evolution, hemagglutinin, immune evasion, glycosylation

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