Maintaining diverse repertoires of naive and memory T cells provides vital protection against both novel and previously-encountered pathogens, and loss or dysregulation of these populations has catastrophic implications for health. However, while we have qualitative knowledge of the signals that in?uence T cell division and survival, we lack an integrated understanding of the mechanisms that regulate the sizes and T cell receptor (TCR) diversities of T cell compartments. Solving this `immuno-ecology` problem, and developing validated, quantitative models of the dynamics of our T cell repertoires, will give a basis for therapies in many areas; reversing the collapse in TCR diversity with age, which may impair responses to vaccines and infections; aiding T cell reconstitution following bone marrow transplants; treating dis- orders that disrupt homeostasis, such as leukemia's and HIV infection; and designing vaccines that boost immunity without impairing T cell memory to other pathogens. The goals of this project are (i) to fully characterize the rules governing the incorporation of new cells from the thymus into our naive T cell pools, identify age-related heterogeneity in naive T cell kinetics, and establish the impact of such heterogeneity on cell's functional responsiveness; and (ii) to extend this focus to memory T cell subsets to identify the rules governing birth and death within each. To achieve these goals we will use a combination of mathematical modeling and dedicated experiments in mice, connecting our results to mechanisms of T cell homeostasis in humans wherever possible. Achieving the aims of this proposal will be a long stride towards our long-term goal of an integrated, validated and quantitative model of human T cell homeostasis.
T lymphocytes are circulating white blood cells that are essential for immunity to infections. In this project we aim to understand how these cells are maintained. Such an understanding will help us develop better treatments for restoring T lymphocytes that are lost following, for example, radiation therapy or HIV infection.
|Gossel, Graeme; Hogan, Thea; Cownden, Daniel et al. (2017) Memory CD4 T cell subsets are kinetically heterogeneous and replenished from naive T cells at high levels. Elife 6:|
|Lee, Edward S; Thomas, Paul G; Mold, Jeff E et al. (2017) Identifying T Cell Receptors from High-Throughput Sequencing: Dealing with Promiscuity in TCR? and TCR? Pairing. PLoS Comput Biol 13:e1005313|
|Hogan, Thea; Gossel, Graeme; Yates, Andrew J et al. (2015) Temporal fate mapping reveals age-linked heterogeneity in naive T lymphocytes in mice. Proc Natl Acad Sci U S A 112:E6917-26|
|Kadolsky, Ulrich D; Yates, Andrew J (2015) How is the effectiveness of immune surveillance impacted by the spatial distribution of spreading infections? Philos Trans R Soc Lond B Biol Sci 370:|
|Hogan, Thea; Kadolsky, Ulrich; Tung, Sim et al. (2014) Spatial heterogeneity and peptide availability determine CTL killing efficiency in vivo. PLoS Comput Biol 10:e1003805|
|Sinclair, Charles; Bains, Iren; Yates, Andrew J et al. (2013) Asymmetric thymocyte death underlies the CD4:CD8 T-cell ratio in the adaptive immune system. Proc Natl Acad Sci U S A 110:E2905-14|
|Cameron, Angus; Reece, Sarah E; Drew, Damien R et al. (2013) Plasticity in transmission strategies of the malaria parasite, Plasmodium chabaudi: environmental and genetic effects. Evol Appl 6:365-76|
|Bains, Iren; Yates, Andrew J; Callard, Robin E (2013) Heterogeneity in thymic emigrants: implications for thymectomy and immunosenescence. PLoS One 8:e49554|
|Hogan, Thea; Shuvaev, Andrey; Commenges, Daniel et al. (2013) Clonally diverse T cell homeostasis is maintained by a common program of cell-cycle control. J Immunol 190:3985-93|
|Bains, Iren; van Santen, Hisse M; Seddon, Benedict et al. (2013) Models of self-peptide sampling by developing T cells identify candidate mechanisms of thymic selection. PLoS Comput Biol 9:e1003102|
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