Literature DB >> 23313150

Quantifying T lymphocyte turnover.

Rob J De Boer1, Alan S Perelson.   

Abstract

Peripheral T cell populations are maintained by production of naive T cells in the thymus, clonal expansion of activated cells, cellular self-renewal (or homeostatic proliferation), and density dependent cell life spans. A variety of experimental techniques have been employed to quantify the relative contributions of these processes. In modern studies lymphocytes are typically labeled with 5-bromo-2'-deoxyuridine (BrdU), deuterium, or the fluorescent dye carboxy-fluorescein diacetate succinimidyl ester (CFSE), their division history has been studied by monitoring telomere shortening and the dilution of T cell receptor excision circles (TRECs) or the dye CFSE, and clonal expansion has been documented by recording changes in the population densities of antigen specific cells. Proper interpretation of such data in terms of the underlying rates of T cell production, division, and death has proven to be notoriously difficult and involves mathematical modeling. We review the various models that have been developed for each of these techniques, discuss which models seem most appropriate for what type of data, reveal open problems that require better models, and pinpoint how the assumptions underlying a mathematical model may influence the interpretation of data. Elaborating various successful cases where modeling has delivered new insights in T cell population dynamics, this review provides quantitative estimates of several processes involved in the maintenance of naive and memory, CD4(+) and CD8(+) T cell pools in mice and men.
Copyright © 2013 Elsevier Ltd. All rights reserved.

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Year:  2013        PMID: 23313150      PMCID: PMC3640348          DOI: 10.1016/j.jtbi.2012.12.025

Source DB:  PubMed          Journal:  J Theor Biol        ISSN: 0022-5193            Impact factor:   2.691


  232 in total

1.  Evidence from the generation of immunoglobulin G-secreting cells that stochastic mechanisms regulate lymphocyte differentiation.

Authors:  Jhagvaral Hasbold; Lynn M Corcoran; David M Tarlinton; Stuart G Tangye; Philip D Hodgkin
Journal:  Nat Immunol       Date:  2003-11-30       Impact factor: 25.606

2.  A general mathematical framework to model generation structure in a population of asynchronously dividing cells.

Authors:  Kalet León; Jose Faro; Jorge Carneiro
Journal:  J Theor Biol       Date:  2004-08-21       Impact factor: 2.691

3.  Proliferating CD4+ T cells undergo immediate growth arrest upon cessation of TCR signaling in vivo.

Authors:  Cory A Yarke; Stacy L Dalheimer; Na Zhang; Drew M Catron; Marc K Jenkins; Daniel L Mueller
Journal:  J Immunol       Date:  2008-01-01       Impact factor: 5.422

4.  Simian immunodeficiency virus replicates to high levels in naturally infected African green monkeys without inducing immunologic or neurologic disease.

Authors:  S R Broussard; S I Staprans; R White; E M Whitehead; M B Feinberg; J S Allan
Journal:  J Virol       Date:  2001-03       Impact factor: 5.103

5.  A central role for thymic emigrants in peripheral T cell homeostasis.

Authors:  S P Berzins; D I Godfrey; J F Miller; R L Boyd
Journal:  Proc Natl Acad Sci U S A       Date:  1999-08-17       Impact factor: 11.205

6.  Turnover rates of B cells, T cells, and NK cells in simian immunodeficiency virus-infected and uninfected rhesus macaques.

Authors:  Rob J De Boer; Hiroshi Mohri; David D Ho; Alan S Perelson
Journal:  J Immunol       Date:  2003-03-01       Impact factor: 5.422

7.  The contribution of the thymus to the recovery of peripheral naive T-cell numbers during antiretroviral treatment for HIV infection.

Authors:  Ruy M Ribeiro; Rob J de Boer
Journal:  J Acquir Immune Defic Syndr       Date:  2008-09-01       Impact factor: 3.731

8.  The involution of the ageing human thymic epithelium is independent of puberty. A morphometric study.

Authors:  G G Steinmann; B Klaus; H K Müller-Hermelink
Journal:  Scand J Immunol       Date:  1985-11       Impact factor: 3.487

9.  Changes in thymic function with age and during the treatment of HIV infection.

Authors:  D C Douek; R D McFarland; P H Keiser; E A Gage; J M Massey; B F Haynes; M A Polis; A T Haase; M B Feinberg; J L Sullivan; B D Jamieson; J A Zack; L J Picker; R A Koup
Journal:  Nature       Date:  1998-12-17       Impact factor: 49.962

10.  Naive precursor frequencies and MHC binding rather than the degree of epitope diversity shape CD8+ T cell immunodominance.

Authors:  Maya F Kotturi; Iain Scott; Tom Wolfe; Bjoern Peters; John Sidney; Hilde Cheroutre; Matthias G von Herrath; Michael J Buchmeier; Howard Grey; Alessandro Sette
Journal:  J Immunol       Date:  2008-08-01       Impact factor: 5.422

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  93 in total

1.  Fluctuating fitness shapes the clone-size distribution of immune repertoires.

Authors:  Jonathan Desponds; Thierry Mora; Aleksandra M Walczak
Journal:  Proc Natl Acad Sci U S A       Date:  2015-12-28       Impact factor: 11.205

Review 2.  The memory of a killer T cell: models of CD8(+) T cell differentiation.

Authors:  Bram Gerritsen; Aridaman Pandit
Journal:  Immunol Cell Biol       Date:  2015-12-24       Impact factor: 5.126

3.  Inferring average generation via division-linked labeling.

Authors:  Tom S Weber; Leïla Perié; Ken R Duffy
Journal:  J Math Biol       Date:  2016-01-05       Impact factor: 2.259

4.  Post-treatment control of HIV infection.

Authors:  Jessica M Conway; Alan S Perelson
Journal:  Proc Natl Acad Sci U S A       Date:  2015-04-13       Impact factor: 11.205

5.  Mathematical models for CFSE labelled lymphocyte dynamics: asymmetry and time-lag in division.

Authors:  Tatyana Luzyanina; Jovana Cupovic; Burkhard Ludewig; Gennady Bocharov
Journal:  J Math Biol       Date:  2013-12-13       Impact factor: 2.259

6.  Simultaneous quantification of T-cell receptor excision circles (TRECs) and K-deleting recombination excision circles (KRECs) by real-time PCR.

Authors:  Alessandra Sottini; Federico Serana; Diego Bertoli; Marco Chiarini; Monica Valotti; Marion Vaglio Tessitore; Luisa Imberti
Journal:  J Vis Exp       Date:  2014-12-06       Impact factor: 1.355

7.  Sample path properties of the average generation of a Bellman-Harris process.

Authors:  Gianfelice Meli; Tom S Weber; Ken R Duffy
Journal:  J Math Biol       Date:  2019-05-08       Impact factor: 2.259

8.  Quantifying the Dynamics of Hematopoiesis by In Vivo IdU Pulse-Chase, Mass Cytometry, and Mathematical Modeling.

Authors:  Amir Erez; Ratnadeep Mukherjee; Grégoire Altan-Bonnet
Journal:  Cytometry A       Date:  2019-05-31       Impact factor: 4.355

9.  Human immune compartment comparisons: Optimization of proliferative assays for blood and gut T lymphocytes.

Authors:  Jeffrey Dock; Lance Hultin; Patricia Hultin; Julie Elliot; Otto O Yang; Peter A Anton; Beth D Jamieson; Rita B Effros
Journal:  J Immunol Methods       Date:  2017-03-21       Impact factor: 2.303

Review 10.  Machine learning applications in cell image analysis.

Authors:  Andrey Kan
Journal:  Immunol Cell Biol       Date:  2017-03-15       Impact factor: 5.126

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