Inviting an author to review:
Find an author and click ‘Invite to review selected article’ near their name.
Search for authorsSearch for similar articles
7
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      LymAnalyzer: a tool for comprehensive analysis of next generation sequencing data of T cell receptors and immunoglobulins

      research-article
      1 , 2 , 1 , *
      Nucleic Acids Research
      Oxford University Press

      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

          The adaptive immune system includes populations of B and T cells capable of binding foreign epitopes via antigen specific receptors, called immunoglobulin (IG) for B cells and the T cell receptor (TCR) for T cells. In order to provide protection from a wide range of pathogens, these cells display highly diverse repertoires of IGs and TCRs. This is achieved through combinatorial rearrangement of multiple gene segments in addition, for B cells, to somatic hypermutation. Deep sequencing technologies have revolutionized analysis of the diversity of these repertoires; however, accurate TCR/IG diversity profiling requires specialist bioinformatics tools. Here we present LymAnalzyer, a software package that significantly improves the completeness and accuracy of TCR/IG profiling from deep sequence data and includes procedures to identify novel alleles of gene segments. On real and simulated data sets LymAnalyzer produces highly accurate and complete results. Although, to date we have applied it to TCR/IG data from human and mouse, it can be applied to data from any species for which an appropriate database of reference genes is available. Implemented in Java, it includes both a command line version and a graphical user interface and is freely available at https://sourceforge.net/projects/lymanalyzer/.

          Related collections

          Most cited references11

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

          Convergent antibody signatures in human dengue.

          Dengue is the most prevalent mosquito-borne viral disease in humans, and the lack of early prognostics, vaccines, and therapeutics contributes to immense disease burden. To identify patterns that could be used for sequence-based monitoring of the antibody response to dengue, we examined antibody heavy-chain gene rearrangements in longitudinal peripheral blood samples from 60 dengue patients. Comparing signatures between acute dengue, postrecovery, and healthy samples, we found increased expansion of B cell clones in acute dengue patients, with higher overall clonality in secondary infection. Additionally, we observed consistent antibody sequence features in acute dengue in the highly variable major antigen-binding determinant, complementarity-determining region 3 (CDR3), with specific CDR3 sequences highly enriched in acute samples compared to postrecovery, healthy, or non-dengue samples. Dengue thus provides a striking example of a human viral infection where convergent immune signatures can be identified in multiple individuals. Such signatures could facilitate surveillance of immunological memory in communities. Copyright © 2013 Elsevier Inc. All rights reserved.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Human responses to influenza vaccination show seroconversion signatures and convergent antibody rearrangements.

            B cells produce a diverse antibody repertoire by undergoing gene rearrangements. Pathogen exposure induces the clonal expansion of B cells expressing antibodies that can bind the infectious agent. To assess human B cell responses to trivalent seasonal influenza and monovalent pandemic H1N1 vaccination, we sequenced gene rearrangements encoding the immunoglobulin heavy chain, a major determinant of epitope recognition. The magnitude of B cell clonal expansions correlates with an individual's secreted antibody response to the vaccine, and the expanded clones are enriched with those expressing influenza-specific monoclonal antibodies. Additionally, B cell responses to pandemic influenza H1N1 vaccination and infection in different people show a prominent family of convergent antibody heavy chain gene rearrangements specific to influenza antigens. These results indicate that microbes can induce specific signatures of immunoglobulin gene rearrangements and that pathogen exposure can potentially be assessed from B cell repertoires. Copyright © 2014 Elsevier Inc. All rights reserved.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              IMGT, the international ImMunoGeneTics information system®

              The international ImMunoGeneTics information system® (IMGT) (http://imgt.cines.fr), created in 1989, by the Laboratoire d'ImmunoGénétique Moléculaire LIGM (Université Montpellier II and CNRS) at Montpellier, France, is a high-quality integrated knowledge resource specializing in the immunoglobulins (IGs), T cell receptors (TRs), major histocompatibility complex (MHC) of human and other vertebrates, and related proteins of the immune systems (RPI) that belong to the immunoglobulin superfamily (IgSF) and to the MHC superfamily (MhcSF). IMGT includes several sequence databases (IMGT/LIGM-DB, IMGT/PRIMER-DB, IMGT/PROTEIN-DB and IMGT/MHC-DB), one genome database (IMGT/GENE-DB) and one three-dimensional (3D) structure database (IMGT/3Dstructure-DB), Web resources comprising 8000 HTML pages (IMGT Marie-Paule page), and interactive tools. IMGT data are expertly annotated according to the rules of the IMGT Scientific chart, based on the IMGT-ONTOLOGY concepts. IMGT tools are particularly useful for the analysis of the IG and TR repertoires in normal physiological and pathological situations. IMGT is used in medical research (autoimmune diseases, infectious diseases, AIDS, leukemias, lymphomas, myelomas), veterinary research, biotechnology related to antibody engineering (phage displays, combinatorial libraries, chimeric, humanized and human antibodies), diagnostics (clonalities, detection and follow up of residual diseases) and therapeutical approaches (graft, immunotherapy and vaccinology). IMGT is freely available at http://imgt.cines.fr.
                Bookmark

                Author and article information

                Journal
                Nucleic Acids Res
                Nucleic Acids Res
                nar
                nar
                Nucleic Acids Research
                Oxford University Press
                0305-1048
                1362-4962
                29 February 2016
                07 October 2015
                07 October 2015
                : 44
                : 4
                : e31
                Affiliations
                [1 ]School of Mathematics, Statistics and Applied Mathematics, National University of Ireland Galway, University Road, Galway, Ireland
                [2 ]Biosciences, National University of Ireland Galway, University Road, Dangan, Galway, Ireland
                Author notes
                [* ]To whom correspondence should be addressed. Tel: +353 91 49 2343; Fax: +353 91 494542; Email: cathal.seoighe@ 123456nuigalway.ie
                Article
                10.1093/nar/gkv1016
                4770197
                26446988
                41d4ab77-ba7e-46ce-80d3-51279941badc
                © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 25 September 2015
                : 14 September 2015
                : 17 June 2015
                Page count
                Pages: 9
                Categories
                24
                28
                Methods Online
                Custom metadata
                29 February 2016

                Genetics
                Genetics

                Comments

                Comment on this article