Literature DB >> 22902400

Models and methods for analysis of lymphocyte repertoire generation, development, selection and evolution.

Ramit Mehr1, Michal Sternberg-Simon, Miri Michaeli, Yishai Pickman.   

Abstract

T and B cell receptor repertoires are diversified by variable region gene rearrangement and selected based on functionality and lack of self-reactivity. Repertoires can also be defined based on phenotype and function rather than receptor specificity - such as the diversity of T helper cell subsets. Natural killer (NK) cell repertoires, in which each cell expresses a randomly chosen subset of its inhibitory receptor genes, and is educated based on self-MHC recognition by yet unknown mechanisms, are also phenotypic repertoires. Studying the generation, development and selection of lymphocyte repertoires, and their functions during immune responses, is essential for understanding the function of the immune system in healthy individuals and in immune deficient, autoimmune or cancer patients. The study of lymphocyte repertoires will enable clinical immunologists to develop better therapeutic monoclonal antibodies, vaccines, transplantation donor-recipient matching protocols, and other immune intervention strategies. The recent development of high-throughput methods for repertoire data collection - from multicolor flow cytometry through single-cell imaging to deep sequencing - presents us now, for the first time, with the ability to analyze and compare large samples of lymphocyte repertoires in health, aging and disease. The exponential growth of these datasets, however, challenges the theoretical immunology community to develop methods for data organization and analysis. Furthermore, the need to test hypotheses regarding immune function, and generate predictions regarding the outcomes of medical interventions, necessitates the development of complex mathematical and computational models, covering processes on multiple scales, from the genetic and molecular to the cellular and system scales.
Copyright © 2012 Elsevier B.V. All rights reserved.

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Year:  2012        PMID: 22902400     DOI: 10.1016/j.imlet.2012.08.002

Source DB:  PubMed          Journal:  Immunol Lett        ISSN: 0165-2478            Impact factor:   3.685


  20 in total

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Authors:  O Pabst; H Hazanov; R Mehr
Journal:  Mucosal Immunol       Date:  2014-11-12       Impact factor: 7.313

2.  Methodologic Considerations in the Application of Next-Generation Sequencing of Human TRB Repertoires for Clinical Use.

Authors:  Liwen Xu; Xiaoqing You; PingPing Zheng; Bing M Zhang; Puja K Gupta; Philip Lavori; Everett Meyer; James L Zehnder
Journal:  J Mol Diagn       Date:  2016-11-01       Impact factor: 5.568

Review 3.  Sequencing the functional antibody repertoire--diagnostic and therapeutic discovery.

Authors:  William H Robinson
Journal:  Nat Rev Rheumatol       Date:  2014-12-23       Impact factor: 20.543

Review 4.  Characterizing immune repertoires by high throughput sequencing: strategies and applications.

Authors:  Jorg J A Calis; Brad R Rosenberg
Journal:  Trends Immunol       Date:  2014-10-08       Impact factor: 16.687

5.  Tools for fundamental analysis functions of TCR repertoires: a systematic comparison.

Authors:  Yanfang Zhang; Xiujia Yang; Yanxia Zhang; Yan Zhang; Minhui Wang; Jin Xia Ou; Yan Zhu; Huikun Zeng; Jiaqi Wu; Chunhong Lan; Hong-Wei Zhou; Wei Yang; Zhenhai Zhang
Journal:  Brief Bioinform       Date:  2020-09-25       Impact factor: 11.622

6.  Quantifying evolutionary constraints on B-cell affinity maturation.

Authors:  Connor O McCoy; Trevor Bedford; Vladimir N Minin; Philip Bradley; Harlan Robins; Frederick A Matsen
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2015-09-05       Impact factor: 6.237

7.  A bioinformatic framework for immune repertoire diversity profiling enables detection of immunological status.

Authors:  Victor Greiff; Pooja Bhat; Skylar C Cook; Ulrike Menzel; Wenjing Kang; Sai T Reddy
Journal:  Genome Med       Date:  2015-05-28       Impact factor: 11.117

8.  Natural killer cell inhibitory receptor expression in humans and mice: a closer look.

Authors:  Michal Sternberg-Simon; Petter Brodin; Yishai Pickman; Björn Onfelt; Klas Kärre; Karl-Johan Malmberg; Petter Höglund; Ramit Mehr
Journal:  Front Immunol       Date:  2013-03-26       Impact factor: 7.561

9.  Understanding natural killer cell regulation by mathematical approaches.

Authors:  Carsten Watzl; Michal Sternberg-Simon; Doris Urlaub; Ramit Mehr
Journal:  Front Immunol       Date:  2012-12-12       Impact factor: 7.561

10.  Utilities for High-Throughput Analysis of B-Cell Clonal Lineages.

Authors:  William D Lees; Adrian J Shepherd
Journal:  J Immunol Res       Date:  2015-10-07       Impact factor: 4.818

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