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Understanding Immune Variation Through Computational Multi-Omic Approaches
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Dissertation
Understanding Immune Variation Through Computational Multi-Omic Approaches
2021
Overview
Reductionist approaches to understanding immune activity have relied on fundamental laboratory studies under controlled and isolated conditions. Genetic manipulations and specific perturbations of immune cells in mice have identified the major players and mechanisms for many immune system processes. In an effort to understand the interacting components of the immune system (cytokines, immune cells, microbes), I have adopted a systems immunology approach by simultaneously assessing a variety of immunological parameters as well as environmental and genetic factors that drive immune activation. However, while the density of immune profiling datasets is increasing, the computational tools and resources to assess immune activity are limited and remain underdeveloped. To address this, we have conducted several investigations in multi-omic immune profiling in order to better understand immune variation. This includes deciphering myeloid cell transcriptional signatures following cytokine stimulation and using these signatures to classify M. tuberculosis disease states and predict survival in primary glioma patients. We have also investigated environmental and genetic contributors to immune variation in laboratory mice which were temporarily released in a semi-natural outdoor enclosure. Recently, we extended our findings in humans by studying a cohort of 1,000 healthy adults through several multi-omic profiling assays to assess variation in human immune responses. Additionally, in the context of disease we employed single cell transcriptional profiling to characterize immune cell phenotypes in ulcerative colitis subsets. Finally, we harnessed a novel multi-modal single cell sequencing platform, ECCITE-seq, to describe human immune responses to SARS-CoV-2 infection and vaccination through simultaneous transcriptional profiling, CITE-seq protein quantification and B and T cell receptor sequencing. Through the investigations described here we aim to better understand the interacting components of immune activation through systems immunology and quantitative approaches. The goal of this thesis is to identify the sources and drivers of variation in the immune response and ultimately predict outcomes or treatment.
Publisher
ProQuest Dissertations & Theses
Subject
ISBN
9798496509114
