Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.798565
Title: Computational analysis of innate and adaptive immune responses
Author: Tkacz, Claire
ISNI:       0000 0004 8507 7815
Awarding Body: UCL (University College London)
Current Institution: University College London (University of London)
Date of Award: 2019
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Abstract:
Both innate and adaptive immune processes rely on the activation of differentiated haematopoietic stem cell lineages to affect an appropriate response to pathogens. This thesis employs a largely network biology focused approach to better understand the specificity of immune cell responses in two distinct cases of pathogenic challenge. In the context of adaptive immunity, I studied the transcriptional responses of T cells during Graft-versus-Host Disease (GvHD). GvHD represents one of the major complications to arise following allogeneic hematopoietic stem cell transplantation and yet why only particular organs are damaged as a result of this pathology is still unclear. To investigate whether key GvHD transcriptional signatures seen in effector CD8+ T cells compared to naïve T cells are triggered in target organs or the secondary lymphoid organs, a module-based association test was developed to combine the output of gene clustering algorithms with that of differential expression analysis. This methodology significantly aided the identification of skin specific effector T cell transcriptional programs believed to drive murine GvHD pathogenesis at this site. Turning to the innate immune response, I investigated the transcriptional profiles of resting and activated macrophages in the setting of Tuberculosis (TB), the second leading cause of death from infectious disease worldwide. Regression-based analyses and clustering of macrophage expression data provided insight into the variations in gene expression profiles of naïve macrophages compared to those infected with Mycobacterium tuberculosis (MTB) or a vaccine strain of mycobacteria (BCG). The availability of genotype data as part of the macrophage dataset facilitated an expression quantitative trait loci (eQTL) study which highlighted a novel association between the cytoskeleton gene BCAR1 and TB risk, together with a previously undescribed trans-eQTL module specific to MTB infected macrophages. Potential genetic variants impacting expression of the aforementioned GvHD specific T cell transcriptional signatures were additionally investigated using external trans-eQTL datasets.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.798565  DOI: Not available
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