Lifelong dynamics of human CD4+CD25+ regulatory T cells: Insights from in vivo data and mathematical modeling

Despite their limited proliferation capacity, regulatory T cells (T(regs)) constitute a population maintained over the entire lifetime of a human organism. The means by which T(regs) 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 T(regs): precursor CD4(+)CD25(+)CD45RO(-) and mature CD4(+)CD25(+)CD45RO(+) cells. The lifelong dynamics of T(regs) 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(+)T(regs) population is maintained over both precursor and mature T(regs) pools together, and (2) the ratio between precursor and mature T(regs) 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 T(regs) is the antigen-driven differentiation of precursors that acquire the mature profile in the periphery and the proliferation of T(regs) is essential for the development and the maintenance of the pool; there exist other sources of mature T(regs), such as (2) a homeostatic density-dependent regulation or (3) thymus- or effector-derived T(regs), and in both cases, antigen-induced proliferation is not necessary for the development of a stable pool of T(regs). 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.

Mathematical Modeling of T-Cell Experimental Data

Irina Baltcheva

T lymphocytes (T cells) are key components of the adaptive immune system. These cells are able to recognize an enormous variety of pathogens thanks to the great specificity of their trans-membrane proteins, the T cell receptors (TCRs). TCR diversity is created during T cell maturation in the thymus by somatic gene-segment rearrangements and random nucleotide additions or deletions. Out of all possible T cell clones bearing specific TCRs, only a small fraction are successfully released in peripheral blood as the result of clonal selection. Among the selected clones, some self-reactive cells with the capacity to induce an auto-immune disease are erroneously released in periphery. To compensate for this functional flaw, the immune system has developed peripheral control mechanisms. One of them are regulatory T cells that are specialized in the control of harmful self-reactive clones. In this thesis, we combine mathematical modeling and experimental data to address immunological questions related to the dynamics of regulatory T cells and to the measurement of the structural diversity of T cell receptors. The dissertation is split into two main parts. In the first part, we model the lifelong dynamics of human regulatory T cells (Tregs). Despite their limited proliferation capacity, Tregs constitute a population maintained over the entire lifetime of an individual. The means by which Tregs sustain a stable pool in vivo are controversial. We define a novel mathematical model that we use to evaluate several biological scenarios about 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. Most of the parameters are considered as random variables having an a priori distribution. The likelihood of a scenario is estimated using Monte Carlo simulations. The model dynamics are validated with data from human donors of different ages. Analysis of the data led to the identification of two properties of the dynamics: (a) the equilibrium in the CD4+CD25+ Tregs population is maintained over both precursor and mature Tregs pools together, and (b) the ratio between precursor and mature Tregs is inverted in the early years of adulthood. Then, using the model, we identified four biologically relevant scenarios that have the above properties: (1) if the unique source of mature Tregs is the antigendriven differentiation of precursors that acquire the mature profile in the periphery, then the proliferation of Tregs is essential for the development and the maintenance of the pool; if there exist other sources of mature Tregs, such as (2) a homeostatic regulation, (3) a thymic migration, or (4) a peripheral conversion of effectors into Tregs, then the antigen-induced proliferation is not necessary for the development of a stable pool of Tregs. In the second part of the dissertation, we address the general question of TCR diversity by improving the interpretation of AmpliCot, an experimental technique that aims at the diversity measurement of nucleic acid sequences. This procedure has the advantage over other cloning and sequencing techniques of being time- and expense- effective. In short, a fluorescent dye that binds double-stranded DNA is added to a sample of PCR-amplified DNA. The sample is melted, such that the DNA becomes single-stranded, and then re-annealed under stringent conditions. The annealing kinetics, measured in terms of fluorescence intensity, are a function of the diversity and of the concentration of the sample and have been interpreted assuming second order kinetics. Using mathematical modeling, we show that a more detailed model, involving heteroduplex- and transient-duplex formation, leads to significantly better fits of experimental data. Moreover, the new model accounts for the diversity-dependent fluorescence loss that is typically observed. As a consequence, we show that the original method for interpreting the results of AmpliCot experiments should be applied with caution. We suggest alternative methods for diversity extrapolation of a sample.

EPFL2010

Analysis and numerical simulation of viscoelastic flows

Andrea Bonito

Mathematical and numerical aspects of viscoelastic flows are investigated here. Two simplified mathematical models are considered. They are motivated by a splitting algorithm for solving viscoelastic flows with free surfaces. The first model is a simplified Oldroyd-B model. Existence on a fixed time interval is proved in several Banach spaces provided the data are small enough. Short time existence is also proved for arbitrarily large data in Hölder spaces for the time variable. These results are based on the maximal regularity property of the Stokes operator and on the analycity behavior of the corresponding semi-group. A finite element discretization in space is then proposed. Existence of the numerical solution is proved for small data, as well as a priori error estimates, using an implicit function theorem framework. Then, the extension of these results to a stochastic simplified Hookean dumbbells model is discussed. Because of the presence of the Brownian motion, existence in a fixed time interval, provided the data are small enough, is proved only in some of the Banach spaces considered previously. The dumbbells' elongation is split in two parts, one satisfying a standart stochastic differential equation, the other satisfying a partial differential equation with a stochastic source term. A finite element discretization in space is also proposed. Existence of the numerical solution is proved for small data, as well as a priori error estimates. A numerical algorithm for solving viscoelastic flows with free surfaces is also described. This algorithm is based on a splitting method in time and two different meshes are used for the space discretization. Convergence of the numerical model is checked for the pure extensional flow and the filling of a pipe. Then, numerical results are reported for the stretching of a filament and for jet buckling.

EPFL2006

Statistical modelling of ground temperature in mountain permafrost

Juliette Ferial Blanchet, Anthony Christopher Davison

Permafrost consists of soil and rocks that remain at 0 degrees C or below for at least two consecutive years. In mountains, permafrost ground ice acts like cement, stabilizing rock walls. Its degradation, following climate warming, may lead to slope instability in high mountains and damage to infrastructure, so knowledge about its evolution is essential for risk analysis. In pure solids, heat is transferred by conduction, but permafrost ground is also subject to non-conductive fluxes, and heat transfers are influenced by factors such as air temperature and snow cover, so a deterministic scheme cannot fully describe heat propagation. Current approaches to modelling use numerical models involving heat conduction schemes and energy balance models, requiring data on quantities such as relative humidity and radiation. We describe a stochastic treatment of the heat equation, which adapts to space-time changes in heat transfers driven by factors such as air temperature and snow cover, without requiring corresponding data, as part of a statistical model. The flexibility and performance of our approach are illustrated using data from two boreholes in the Swiss Alps, which show the strong influence of snow cover on ground temperature and the long-term degradation of permafrost produced by the 2003 heat wave.

2012

Mathematical Modeling of T-Cell Experimental Data

Irina Baltcheva

EPFL2010