Literature DB >> 12413874

Antigen-driven T-cell turnover.

Christophe Fraser1, Neil M Ferguson, Frank De Wolf, Azra C Ghani, Geoff P Garnett, Roy M Anderson.   

Abstract

A mathematical model is developed to characterize the distribution of cell turnover rates within a population of T lymphocytes. Previous models of T-cell dynamics have assumed a constant uniform turnover rate; here we consider turnover in a cell pool subject to clonal proliferation in response to diverse and repeated antigenic stimulation. A basic framework is defined for T-cell proliferation in response to antigen, which explicitly describes the cell cycle during antigenic stimulation and subsequent cell division. The distribution of T-cell turnover rates is then calculated based on the history of random exposures to antigens. This distribution is found to be bimodal, with peaks in cell frequencies in the slow turnover (quiescent) and rapid turnover (activated) states. This distribution can be used to calculate the overall turnover for the cell pool, as well as individual contributions to turnover from quiescent and activated cells. The impact of heterogeneous turnover on the dynamics of CD4(+) T-cell infection by HIV is explored. We show that our model can resolve the paradox of high levels of viral replication occurring while only a small fraction of cells are infected.

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Year:  2002        PMID: 12413874     DOI: 10.1006/jtbi.2002.3085

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


  3 in total

1.  Modelling the human immune system by combining bioinformatics and systems biology approaches.

Authors:  Nicolas Rapin; Can Kesmir; Sune Frankild; Morten Nielsen; Claus Lundegaard; Søren Brunak; Ole Lund
Journal:  J Biol Phys       Date:  2006-10-27       Impact factor: 1.365

2.  Role of avidity and breadth of the CD4 T cell response in progression to AIDS.

Authors:  Hester Korthals Altes; Rob de Boer; Maarten Boerlijst
Journal:  Proc Biol Sci       Date:  2006-07-07       Impact factor: 5.349

3.  The race between initial T-helper expansion and virus growth upon HIV infection influences polyclonality of the response and viral set-point.

Authors:  H Korthals Altes; R M Ribeiro; R J de Boer
Journal:  Proc Biol Sci       Date:  2003-07-07       Impact factor: 5.349

  3 in total

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