Literature DB >> 20013355

Emergent group dynamics governed by regulatory cells produce a robust primary T cell response.

Peter S Kim1, Peter P Lee, Doron Levy.   

Abstract

The currently accepted paradigm for the primary T cell response is that effector T cells commit to autonomous developmental programs. This concept is based on several experiments that have demonstrated that the dynamics of a T cell response is largely determined shortly after antigen exposure and that T cell dynamics do not depend on the level and duration of antigen stimulation. Another experimental study has also shown that T cell responses are robust to variations in antigen-specific precursor frequency. Various mathematical models have corroborated the first result that programmed T cell responses are insensitive to the level of antigen stimulation. However, this paper proposes that programmed responses do not entirely explain the robustness of T cell dynamics to variations in precursor frequency. This work studies the hypothesis that the dynamics of a T cell response may also be governed by a feedback loop involving adaptive regulatory cells rather than by intrinsic developmental programs. We formulate two mathematical models based on T cell developmental programs. In one model, effector cells undergo a fixed number of divisions before dying. In the second model, effector cells live for a fixed time during which they may divide. The study of these models suggests that developmental programs are not sufficiently robust as they produce an immune response that directly scales with precursor frequencies. Consequently, we derive a third model based on the principle that adaptive regulatory T cells develop in the course of an immune response and suppress effector cells. Our simulations show that this feedback mechanism responds robustly over a range of at least four orders of magnitude of precursor frequencies. We conclude that the proliferation program paradigm does not entirely capture the observed robustness of T cell responses to variations in precursor frequency. We propose an alternative mechanism by which the primary T cell response is governed by an emergent group dynamic and not by individual T cell programs.

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Year:  2009        PMID: 20013355      PMCID: PMC3008572          DOI: 10.1007/s11538-009-9463-1

Source DB:  PubMed          Journal:  Bull Math Biol        ISSN: 0092-8240            Impact factor:   1.758


  37 in total

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Authors:  K León; R Peréz; A Lage; J Carneiro
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2.  Response of naïve and memory CD8+ T cells to antigen stimulation in vivo.

Authors:  H Veiga-Fernandes; U Walter; C Bourgeois; A McLean; B Rocha
Journal:  Nat Immunol       Date:  2000-07       Impact factor: 25.606

3.  Three-cell interactions in T cell-mediated suppression? A mathematical analysis of its quantitative implications.

Authors:  K León; R Peréz; A Lage; J Carneiro
Journal:  J Immunol       Date:  2001-05-01       Impact factor: 5.422

4.  Models of CD8+ responses: 1. What is the antigen-independent proliferation program.

Authors:  Rustom Antia; Carl T Bergstrom; Sergei S Pilyugin; Susan M Kaech; Rafi Ahmed
Journal:  J Theor Biol       Date:  2003-04-21       Impact factor: 2.691

5.  Dynamic programming of CD8+ T lymphocyte responses.

Authors:  Marianne J B van Stipdonk; Gijs Hardenberg; Martijn S Bijker; Edward E Lemmens; Nathalie M Droin; Douglas R Green; Stephen P Schoenberger
Journal:  Nat Immunol       Date:  2003-03-17       Impact factor: 25.606

6.  Early programming of T cell populations responding to bacterial infection.

Authors:  R Mercado; S Vijh; S E Allen; K Kerksiek; I M Pilip; E G Pamer
Journal:  J Immunol       Date:  2000-12-15       Impact factor: 5.422

7.  Estimating the precursor frequency of naive antigen-specific CD8 T cells.

Authors:  Joseph N Blattman; Rustom Antia; David J D Sourdive; Xiaochi Wang; Susan M Kaech; Kaja Murali-Krishna; John D Altman; Rafi Ahmed
Journal:  J Exp Med       Date:  2002-03-04       Impact factor: 14.307

8.  How regulatory CD25+CD4+ T cells impinge on tumor immunobiology: the differential response of tumors to therapies.

Authors:  Kalet Leon; Karina Garcia; Jorge Carneiro; Agustin Lage
Journal:  J Immunol       Date:  2007-11-01       Impact factor: 5.422

9.  Antigen-specific T cell suppression by human CD4+CD25+ regulatory T cells.

Authors:  Leonie S Taams; Milica Vukmanovic-Stejic; Jay Smith; Padraic J Dunne; Jean M Fletcher; Fiona J Plunkett; Saskia B Ebeling; Giovanna Lombardi; Malcolm H Rustin; Johannes W J Bijlsma; Floris P J G Lafeber; Mike Salmon; Arne N Akbar
Journal:  Eur J Immunol       Date:  2002-06       Impact factor: 5.532

10.  A population dynamics analysis of the interaction between adaptive regulatory T cells and antigen presenting cells.

Authors:  David Fouchet; Roland Regoes
Journal:  PLoS One       Date:  2008-05-28       Impact factor: 3.240

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  6 in total

1.  T cell state transition produces an emergent change detector.

Authors:  Peter S Kim; Peter P Lee
Journal:  J Theor Biol       Date:  2011-01-27       Impact factor: 2.691

2.  Design principles of cell circuits with paradoxical components.

Authors:  Yuval Hart; Yaron E Antebi; Avraham E Mayo; Nir Friedman; Uri Alon
Journal:  Proc Natl Acad Sci U S A       Date:  2012-05-04       Impact factor: 11.205

3.  Feedback regulation of proliferation vs. differentiation rates explains the dependence of CD4 T-cell expansion on precursor number.

Authors:  Gennady Bocharov; Juan Quiel; Tatyana Luzyanina; Hagit Alon; Egor Chiglintsev; Valery Chereshnev; Martin Meier-Schellersheim; William E Paul; Zvi Grossman
Journal:  Proc Natl Acad Sci U S A       Date:  2011-02-03       Impact factor: 11.205

4.  A mathematical model of the enhancement of tumor vaccine efficacy by immunotherapy.

Authors:  Shelby Wilson; Doron Levy
Journal:  Bull Math Biol       Date:  2012-03-22       Impact factor: 1.758

5.  A theory of immunodominance and adaptive regulation.

Authors:  Peter S Kim; Peter P Lee; Doron Levy
Journal:  Bull Math Biol       Date:  2010-10-01       Impact factor: 1.758

6.  Modelling and Simulation of the Dynamics of the Antigen-Specific T Cell Response Using Variable Structure Control Theory.

Authors:  Anet J N Anelone; Sarah K Spurgeon
Journal:  PLoS One       Date:  2016-11-18       Impact factor: 3.240

  6 in total

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