Please use this identifier to cite or link to this item: http://theses.ncl.ac.uk/jspui/handle/10443/4304
Title: Profiling the human dendritic cell system by multiplexed gene expression analysis
Authors: Green, Kile James
Issue Date: 2018
Publisher: Newcastle University
Abstract: Dendritic cells (DCs) are rare immune cell populations that play a significant role in phagocytosis, antigen presentation and pathogen response. While extensive research has produced robust models of murine DC biology and development, the human dendritic cell system remains relatively unexplored due to the inherent difficulty in obtaining the required cell numbers for analysis. Furthermore, with the widespread expansion of gene expression technologies now available to researchers, much of the historical knowledge of human DC biology has begun to be revised and revisited with a fresh approach. In this thesis, flow cytometry, multiplexed hybridisation-based expression analysis and microarray experiments have been used in combination with cutting-edge single-cell transcriptomics to reveal the nature of mature dendritic cells subsets, their relation to monocytes and their developmental heterogeneity. Initially, a previously published microarray dataset (GEO:GSE35457) was interrogated to identify robust mononuclear cell signatures applicable across experimental platforms and tissue origin to address the fickle nature of currently known surface markers of DC subtypes. This dataset was then used as a surrogate in a feasibility study to determine the efficacy of the immune-focused nCounter platform with validation of the in-silico results confirmed using the NanoString platform. NanoString technology was implemented to investigate the correlation of ex-vivo and invitro generated DC populations, culminating in the discovery of a ‘universal culture effect’ influencing global expression in cultured cells. Removal of this signature revealed the underlying equivalence of the cells. Finally, single-cell transcriptomics was employed to expose heterogeneity in pre-DCs, utilising the Illumina and NanoString-derived cell signatures to highlight the early lineage commitment of pre-DC cells. By utilising multiple high-dimensional analysis platforms and covering ex-vivo blood and skin, as well as DCs generated from CD34+ bone marrow progenitor cells, novel insights into the functional roles, expression patterns and molecular signatures of DC subsets have been revealed.
Description: PhD Thesis
URI: http://theses.ncl.ac.uk:8080/jspui/handle/10443/4304
Appears in Collections:Institute of Cellular Medicine

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