33
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Genetic Analysis of Human Norovirus Strains in Japan in 2016–2017

      research-article

      Read this article at

      Bookmark
          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

          In the 2016/2017 winter season in Japan, HuNoV GII.P16-GII.2 strains (2016 strains) emerged and caused large outbreaks of acute gastroenteritis. To better understand the outbreaks, we examined the molecular evolution of the VP1 gene and RdRp region in 2016 strains from patients by studying their time-scale evolutionary phylogeny, positive/negative selection, conformational epitopes, and phylodynamics. The time-scale phylogeny suggested that the common ancestors of the 2016 strains VP1 gene and RdRp region diverged in 2006 and 1999, respectively, and that the 2016 strain was the progeny of a pre-2016 GII.2. The evolutionary rates of the VP1 gene and RdRp region were around 10 -3 substitutions/site/year. Amino acid substitutions (position 341) in an epitope in the P2 domain of 2016 strains were not found in pre-2016 GII.2 strains. Bayesian skyline plot analyses showed that the effective population size of the VP1 gene in GII.2 strains was almost constant for those 50 years, although the number of patients with NoV GII.2 increased in 2016. The 2016 strain may be involved in future outbreaks in Japan and elsewhere.

          Related collections

          Most cited references15

          • Record: found
          • Abstract: found
          • Article: not found

          Structure validation by Calpha geometry: phi,psi and Cbeta deviation.

          Geometrical validation around the Calpha is described, with a new Cbeta measure and updated Ramachandran plot. Deviation of the observed Cbeta atom from ideal position provides a single measure encapsulating the major structure-validation information contained in bond angle distortions. Cbeta deviation is sensitive to incompatibilities between sidechain and backbone caused by misfit conformations or inappropriate refinement restraints. A new phi,psi plot using density-dependent smoothing for 81,234 non-Gly, non-Pro, and non-prePro residues with B < 30 from 500 high-resolution proteins shows sharp boundaries at critical edges and clear delineation between large empty areas and regions that are allowed but disfavored. One such region is the gamma-turn conformation near +75 degrees,-60 degrees, counted as forbidden by common structure-validation programs; however, it occurs in well-ordered parts of good structures, it is overrepresented near functional sites, and strain is partly compensated by the gamma-turn H-bond. Favored and allowed phi,psi regions are also defined for Pro, pre-Pro, and Gly (important because Gly phi,psi angles are more permissive but less accurately determined). Details of these accurate empirical distributions are poorly predicted by previous theoretical calculations, including a region left of alpha-helix, which rates as favorable in energy yet rarely occurs. A proposed factor explaining this discrepancy is that crowding of the two-peptide NHs permits donating only a single H-bond. New calculations by Hu et al. [Proteins 2002 (this issue)] for Ala and Gly dipeptides, using mixed quantum mechanics and molecular mechanics, fit our nonrepetitive data in excellent detail. To run our geometrical evaluations on a user-uploaded file, see MOLPROBITY (http://kinemage.biochem.duke.edu) or RAMPAGE (http://www-cryst.bioc.cam.ac.uk/rampage). Copyright 2003 Wiley-Liss, Inc.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            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.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Protein structure modeling with MODELLER.

              Genome sequencing projects have resulted in a rapid increase in the number of known protein sequences. In contrast, only about one-hundredth of these sequences have been characterized at atomic resolution using experimental structure determination methods. Computational protein structure modeling techniques have the potential to bridge this sequence-structure gap. In this chapter, we present an example that illustrates the use of MODELLER to construct a comparative model for a protein with unknown structure. Automation of a similar protocol has resulted in models of useful accuracy for domains in more than half of all known protein sequences.
                Bookmark

                Author and article information

                Contributors
                Journal
                Front Microbiol
                Front Microbiol
                Front. Microbiol.
                Frontiers in Microbiology
                Frontiers Media S.A.
                1664-302X
                18 January 2018
                2018
                : 9
                : 1
                Affiliations
                [1] 1Infectious Disease Surveillance Center, National Institute of Infectious Diseases , Musashimurayama, Japan
                [2] 2Department of Pediatrics, Graduate School of Medicine, Chiba University , Chiba, Japan
                [3] 3Division of Virology, Kawasaki City Institute for Public Health , Kawasaki, Japan
                [4] 4Division of Virology, Ibaraki Prefectural Institute of Public Health , Mito, Japan
                [5] 5Department of Microbiology, Tochigi Prefectural Institute of Public Health and Environmental Science , Utsunomiya, Japan
                [6] 6Division of Virology, Department of Microbiology, Miyagi Prefectural Institute of Public Health and Environment , Sendai, Japan
                [7] 7Department of Microbiology, Osaka Institute of Public Health , Osaka, Japan
                [8] 8Yamaguchi Prefectural Institute of Public Health and Environment , Yamaguchi, Japan
                [9] 9Department of Microbiology, Ehime Prefectural Institute of Public Health and Environmental Science , Matsuyama, Japan
                [10] 10Eiken Chemical Co., Ltd., Biochemical Research Laboratory I Department-I , Shimotsuga, Japan
                [11] 11Pathogen Genomics Center, National Institute of Infectious Diseases , Shinjuku, Japan
                [12] 12Division of Biological Science, Department of Information and Basic Science, Graduate School of Natural Sciences, Nagoya City University , Nagoya, Japan
                [13] 13Department of Microbiology, Yokohama City University School of Medicine , Yokohama, Japan
                [14] 14School of Medical Technology, Faculty of Health Science, Gunma Paz University , Takasaki, Japan
                [15] 15Laboratory of Viral Infection I, Kitasato Institute for Life Sciences, Graduate School of Infection Control Sciences, Kitasato University , Minato, Japan
                Author notes

                Edited by: José A. Melero, Instituto de Salud Carlos III, Spain

                Reviewed by: Hirotaka Ode, Nagoya Medical Center (NHO), Japan; Hiroshi Ushijima, Nihon University School of Medicine, Japan

                *Correspondence: Hirokazu Kimura, kimhiro@ 123456nih.go.jp Kazuhiko Katayama, katayama@ 123456lisci.kitasato-u.ac.jp

                These authors have contributed equally to this work.

                This article was submitted to Virology, a section of the journal Frontiers in Microbiology

                Article
                10.3389/fmicb.2018.00001
                5778136
                29403456
                cbc0a01f-5e9c-4523-b5b1-e79d68df8116
                Copyright © 2018 Nagasawa, Matsushima, Motoya, Mizukoshi, Ueki, Sakon, Murakami, Shimizu, Okabe, Nagata, Shirabe, Shinomiya, Suzuki, Kuroda, Sekizuka, Suzuki, Ryo, Fujita, Oishi, Katayama and Kimura.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 07 November 2017
                : 03 January 2018
                Page count
                Figures: 5, Tables: 0, Equations: 0, References: 31, Pages: 9, Words: 0
                Categories
                Microbiology
                Original Research

                Microbiology & Virology
                norovirus,capsid,rna-dependent rna polymerase,phylogeny,molecular evolution,epitope mapping

                Comments

                Comment on this article