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      Intra-host analysis of hepaciviral glycoprotein evolution reveals signatures associated with viral persistence and clearance

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          Abstract

          Even 30 years after the discovery of the hepatitis C virus (HCV) in humans there is still no vaccine available. Reasons for this include the high mutation rate of HCV, which allows the virus to escape immune recognition and the absence of an immunocompetent animal model for vaccine development. Phylogenetically distinct hepaciviruses (genus Hepacivirus, family Flaviviridae) have been isolated from diverse species, each with a narrow host range: the equine hepacivirus (EqHV) is the closest known relative of HCV. In this study, we used amplicon-based deep-sequencing to investigate the viral intra-host population composition of the genomic regions encoding the surface glycoproteins E1 and E2. Patterns of E1E2 substitutional evolution were compared in longitudinally sampled EqHV-positive sera of naturally and experimentally infected horses and HCV-positive patients. Intra-host virus diversity was higher in chronically than in acutely infected horses, a pattern which was similar in the HCV-infected patients. However, overall glycoprotein variability was higher in HCV compared to EqHV. Additionally, selection pressure in HCV populations was higher, especially within the N-terminal region of E2, corresponding to the hypervariable region 1 (HVR1) in HCV. An alignment of glycoprotein sequences from diverse hepaciviruses identified the HVR1 as a unique characteristic of HCV: hepaciviruses from non-human species lack this region. Together, these data indicate that EqHV infection of horses could represent a powerful surrogate animal model to gain insights into hepaciviral evolution and HCVs HVR1-mediated immune evasion strategy.

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          MEGA11: Molecular Evolutionary Genetics Analysis Version 11

          The Molecular Evolutionary Genetics Analysis (MEGA) software has matured to contain a large collection of methods and tools of computational molecular evolution. Here, we describe new additions that make MEGA a more comprehensive tool for building timetrees of species, pathogens, and gene families using rapid relaxed-clock methods. Methods for estimating divergence times and confidence intervals are implemented to use probability densities for calibration constraints for node-dating and sequence sampling dates for tip-dating analyses. They are supported by new options for tagging sequences with spatiotemporal sampling information, an expanded interactive Node Calibrations Editor , and an extended Tree Explorer to display timetrees. Also added is a Bayesian method for estimating neutral evolutionary probabilities of alleles in a species using multispecies sequence alignments and a machine learning method to test for the autocorrelation of evolutionary rates in phylogenies. The computer memory requirements for the maximum likelihood analysis are reduced significantly through reprogramming, and the graphical user interface has been made more responsive and interactive for very big data sets. These enhancements will improve the user experience, quality of results, and the pace of biological discovery. Natively compiled graphical user interface and command-line versions of MEGA11 are available for Microsoft Windows, Linux, and macOS from www.megasoftware.net .
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            MAFFT online service: multiple sequence alignment, interactive sequence choice and visualization

            Abstract This article describes several features in the MAFFT online service for multiple sequence alignment (MSA). As a result of recent advances in sequencing technologies, huge numbers of biological sequences are available and the need for MSAs with large numbers of sequences is increasing. To extract biologically relevant information from such data, sophistication of algorithms is necessary but not sufficient. Intuitive and interactive tools for experimental biologists to semiautomatically handle large data are becoming important. We are working on development of MAFFT toward these two directions. Here, we explain (i) the Web interface for recently developed options for large data and (ii) interactive usage to refine sequence data sets and MSAs.
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              Biopython: freely available Python tools for computational molecular biology and bioinformatics

              Summary: The Biopython project is a mature open source international collaboration of volunteer developers, providing Python libraries for a wide range of bioinformatics problems. Biopython includes modules for reading and writing different sequence file formats and multiple sequence alignments, dealing with 3D macro molecular structures, interacting with common tools such as BLAST, ClustalW and EMBOSS, accessing key online databases, as well as providing numerical methods for statistical learning. Availability: Biopython is freely available, with documentation and source code at www.biopython.org under the Biopython license. Contact: All queries should be directed to the Biopython mailing lists, see www.biopython.org/wiki/_Mailing_lists peter.cock@scri.ac.uk.
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                Author and article information

                Contributors
                Journal
                Virus Evol
                Virus Evol
                vevolu
                Virus Evolution
                Oxford University Press (UK )
                2057-1577
                2022
                02 February 2022
                02 February 2022
                : 8
                : 1
                : veac007
                Affiliations
                departmentDepartment for Molecular and Medical Virology, Ruhr University Bochum , Universitätsstr. 150, Bochum 44801, Germany
                departmentInstitute of Virology, University of Veterinary Medicine Hannover, Foundation , Bünteweg 9, Hannover 30559, Germany
                departmentDivision of Veterinary Medicine, Paul Ehrlich Institute , Paul-Ehrlich-Straße 51-59, Langen 63225, Germany
                departmentDepartment for Molecular and Medical Virology, Ruhr University Bochum , Universitätsstr. 150, Bochum 44801, Germany
                departmentDepartment of Gastroenterology, Hepatology and Endocrinology, Hannover Medical School , Carl-Neuberg-Straße 1, Hannover 30625, Germany
                German Center for Infectious Disease Research (DZIF) , HepNet Study-House, Hannover 30625, Germany
                departmentDepartment of Medical Microbiology and Immunology, Medical School, University of Pécs , Szigeti út 12., Pécs 7624, Hungary
                MRC-University of Glasgow, Centre for Virus Research , Garscube Campus, 464 Bearsden Road, Glasgow G61 1QH, United Kingdom
                departmentDepartment of Infectious Diseases, Molecular Virology, University of Heidelberg , Heidelberg 69120, Germany
                departmentDivision of Viral Gastroenteritis and Hepatitis Pathogens and Enteroviruses, Department of Infectious Diseases, Robert Koch Institute , Berlin 13353, Germany
                Clinical Unit of Equine Internal Medicine , University of Veterinary Medicine Vienna, Veterinärplatz 1, Vienna 1210, Austria
                departmentTwincore, Centre for Experimental and Clinical Infection Research , Institute of Experimental Virology, Hannover 30625, Germany
                departmentGerman Centre for Infection Research (DZIF), Partner Site Hannover-Braunschweig Site , Hannover 30625, Germany
                departmentCluster of Excellence RESIST (EXC 2155), Hannover Medical School , Hannover 30625, Germany
                departmentDepartment of Gastroenterology, Hepatology and Endocrinology, Hannover Medical School , Carl-Neuberg-Straße 1, Hannover 30625, Germany
                German Center for Infectious Disease Research (DZIF) , HepNet Study-House, Hannover 30625, Germany
                departmentDepartment for Molecular and Medical Virology, Ruhr University Bochum , Universitätsstr. 150, Bochum 44801, Germany
                departmentDepartment for Molecular and Medical Virology, Ruhr University Bochum , Universitätsstr. 150, Bochum 44801, Germany
                departmentTwincore, Centre for Experimental and Clinical Infection Research , Institute of Experimental Virology, Hannover 30625, Germany
                European Virus Bioinformatics Centre (EVBC) , Jena 07743, Germany
                Author notes
                Author information
                https://orcid.org/0000-0002-4567-0441
                https://orcid.org/0000-0002-3292-6671
                https://orcid.org/0000-0002-3389-4325
                https://orcid.org/0000-0002-3564-1014
                Article
                veac007
                10.1093/ve/veac007
                8887644
                35242360
                7622d114-2710-4fd2-ae5c-5e401ad008c2
                © The Author(s) 2022. Published by Oxford University Press.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License ( https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com

                History
                : 30 July 2021
                : 28 January 2022
                : 31 January 2022
                : 28 January 2022
                : 01 March 2022
                Page count
                Pages: 14
                Funding
                Funded by: Deutsche Forschungsgemeinschaft, DOI 10.13039/501100001659;
                Award ID: 39087428
                Funded by: Deutsche Forschungsgemeinschaft, DOI 10.13039/501100001659;
                Award ID: 398066876/GRK 2485/1
                Funded by: Hungarian Scientific Research Fund, DOI 10.13039/501100003549;
                Award ID: OTKA/NKFIH FK134311
                Categories
                Research Article
                AcademicSubjects/MED00860
                AcademicSubjects/SCI01130
                AcademicSubjects/SCI02285

                hepatitis c virus,equine hepacivirus,intra-host evolution,glycoprotein variability,hypervariable region

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