Title of article :
Lifelong dynamics of human CD4+CD25+ regulatory T cells: Insights from in vivo data and mathematical modeling
Author/Authors :
Baltcheva، نويسنده , , Irina and Codarri، نويسنده , , Laura and Pantaleo، نويسنده , , Giuseppe and Le Boudec، نويسنده , , Jean-Yves، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2010
Abstract :
Despite their limited proliferation capacity, regulatory T cells (Tregs) constitute a population maintained over the entire lifetime of a human organism. The means by which Tregs sustain a stable pool in vivo are controversial. Using a mathematical model, we address this issue by evaluating several biological scenarios of the origins and the proliferation capacity of two subsets of Tregs: precursor CD4+CD25+CD45RO− and mature CD4+CD25+CD45RO+ cells. The lifelong dynamics of Tregs are described by a set of ordinary differential equations, driven by a stochastic process representing the major immune reactions involving these cells. The model dynamics are validated using data from human donors of different ages. Analysis of the data led to the identification of two properties of the dynamics: (1) the equilibrium in the CD4+CD25+FoxP3+Tregs population is maintained over both precursor and mature Tregs pools together, and (2) the ratio between precursor and mature Tregs is inverted in the early years of adulthood. Then, using the model, we identified three biologically relevant scenarios that have the above properties: (1) the unique source of mature Tregs is the antigen-driven differentiation of precursors that acquire the mature profile in the periphery and the proliferation of Tregs is essential for the development and the maintenance of the pool; there exist other sources of mature Tregs, such as (2) a homeostatic density-dependent regulation or (3) thymus- or effector-derived Tregs, and in both cases, antigen-induced proliferation is not necessary for the development of a stable pool of Tregs. This is the first time that a mathematical model built to describe the in vivo dynamics of regulatory T cells is validated using human data. The application of this model provides an invaluable tool in estimating the amount of regulatory T cells as a function of time in the blood of patients that received a solid organ transplant or are suffering from an autoimmune disease.
Keywords :
Mathematical model , Lifelong in vivo dynamics , Regulatory T cells , Maximum likelihood estimation
Journal title :
Journal of Theoretical Biology
Journal title :
Journal of Theoretical Biology