Quantifying the development, size, and repertoire diversity of T cell populations

Lee, Edward S. (2018) Quantifying the development, size, and repertoire diversity of T cell populations. PhD thesis, University of Glasgow.

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The adaptive immune system must be able to respond to virtually any pathogen that the body encounters. T cell immunity is able to do so by developing a diverse repertoire of T cell receptors and maintaining large numbers of T cells. These two quantitative properties are fundamental for the ability of T cell-mediated immunity to clear infections and generate memory cells for future protection. The aims of this thesis are to quantify the sizes of T cell populations, to develop tools to measure the diversity of T cell repertoires, and to describe how T cell populations develop in neonatal mice.

We studied the development of T cell populations in neonatal mice by measuring cell counts and Ki67 expression in thymocyte and peripheral T cell subsets from mice soon after birth to late adulthood. The presumed lymphopenic environment of the neonatal mouse is thought to cause T cells to undergo lymphopenia-induced proliferation, and we wanted to quantify the balance between thymic output and peripheral expansion in the naive T cell compartment during development with mathematical modeling. We also used modeling to find the most parsimonious description of differentiation within the thymus that explains the dynamically growing thymus.

We then sought to quantify the sizes of the peripheral T cell compartments in the adult mouse. Understanding the characteristics of healthy T cell immunity requires knowing the precise numbers of the different T cell subsets found in the body. We performed thoracic duct cannulations in adult mice to collect recirculating T cells and reduce cell numbers in the lymph nodes and spleens; by counting the number of collected T cells and its effect on cell numbers on the secondary lymphoid organs, we sought to back-calculate the total number of T cells in the mouse. Finally, we developed tools that provide high-throughput and cost-effective methods for identifying paired TCR sequences. By using computational techniques, we were able to adapt standard sequencing protocols to identify many paired TCR sequences without resorting to large and expensive single-cell sequencing techniques. By leveraging experimental design with mathematical methods, we were able to quantify and characterize many properties of effective T cell immunity.

Item Type: Thesis (PhD)
Qualification Level: Doctoral
Keywords: Immunology, T cells, mathematical modeling, mathematical biology, computational biology, sequencing.
Subjects: Q Science > QR Microbiology > QR180 Immunology
Colleges/Schools: College of Medical Veterinary and Life Sciences > Institute of Infection Immunity and Inflammation > Immunology
Supervisor's Name: Yates, Professor Andrew
Date of Award: 2018
Depositing User: Dr. Edward Lee
Unique ID: glathesis:2018-31002
Copyright: Copyright of this thesis is held by the author.
Date Deposited: 12 Nov 2018 10:57
Last Modified: 12 Nov 2018 11:02
URI: http://theses.gla.ac.uk/id/eprint/31002
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