Doherty Institute - Theses
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ItemInteraction of mouse norovirus (MNV) with the cellular immune response of host cells( 2017)Human noroviruses (HuNoV) cause the majority of non-bacterial gastroenteritis cases worldwide and generate an economic burden of 60 billion USD every year. Noroviruses are highly infectious and predominantly cause issues in closed environments such as cruise ships, hospitals and nursing homes. Due to the lack of a tissue culture or small animal model, HuNoV research has been impaired and so far no drug treatment or vaccine is available. Despite recent advances in the field and the successful replication of HuNoV in B cells and human intestinal organoids, models of HuNoV replication in vitro still remain to be established. Fortunately, murine norovirus (MNV) was discovered in 2003 and has since been used as a model system to investigate NoV infections. In this study we show that MNV infection reduces the surface expression of MHC class I proteins. The reduction in MHC class I levels on the cell surface is based on reduced intracellular levels of the protein. We reveal that MHC class I transcription is not reduced during MNV infection, implying that either MHC class I translation is affected or MHC class I proteins are degraded during MNV infections. We were able to partially rescue the surface expression of MHC class I proteins on MNV infected cells with MG132, a proteasome inhibitor. These findings indicate that MNV interferes with the MHC class I pathway in either directly degrading the protein or targeting it for the degradation pathway within the cell. Furthermore, we identified MNV NS3 as the viral protein which is essential and sufficient for the MHC class I surface reduction when separately expressed in cells. Additionally, we investigated the effect of MNV on cytokine secretion. The secretion of the cytokines IFNβ and TNFα is significantly reduced in MNV infected cells, which is not due to a down regulation of cytokine mRNA transcription. Analysis of the intracellular expression of cytokines and host cell translation in general, revealed a continuous decrease in global host cell translation in MNV infected cells. The translational shutdown seems to be induced by the dsRNA-sensitive regulator PKR. PKR becomes phosphorylated and phosphorylates the translation initiation factor eIF2α, impeding host cell translation. Whilst the translation of host proteins is stalled, viral proteins are still able to be translated due to a cap-independent mechanism. Furthermore, we interrogated the interaction of MNV with the microtubules and the microtubule-associated protein GEF-H1. We discovered an interaction of GEF-H1 with the viral protein MNV NS3, which leads to changes in the expression levels and location of GEF-H1 within the cell and prevents the formation of GEF-H1 induced microtubule fibres. This indicates a potential interference of MNV NS3 with GEF-H1, which has been proposed to play a major role in the immune detection of viral replication. Despite various approaches to identify a similar role of GEF-H1 during MNV infection, we have so far not been able to support the proposed function of the protein. Considering the multiple roles of GEFs like GEF-H1, it is possible that MNV and specifically NS3 acts on a different GEF-H1-regulated pathway during MNV infection.
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ItemIntegrative genomics to understand immune function and regulation( 2017)Characterising the mechanistic principles underlying immune function and regulation will help us understand how the immune system provides effective host defence. However, the highly complex and multi-level nature of the immune system requires a systems-level analysis to gain multi-dimensional insight and unravel its complexity. High-throughput profiling technologies allow quantitative measurement of various immunological parameters that capture system-wide information. This has led to the generation of large-scale multi-omics datasets from human populations, experimental set-ups, and a compendium of immune cell types. Developments in bioinformatics offer integrative approaches to explore the functional and regulatory relationships within and between various organisational levels of the immune system as well as across other biological systems. For this thesis, multi-omic analysis was used to characterise immune processes in terms of genetics, transcriptional networks and interactions with metabolism. First, I mapped the genetics and interactions of immune gene networks with circulating metabolites in in a population-based study. I integrated blood transcriptomic, metabolomic, and genomic profiles from two population-based cohorts, including a subset with 7-year follow-up sampling. I identified topologically robust gene networks enriched for immune functions including cytotoxicity, viral response, B cell, platelet, neutrophil, and mast cell/basophil activity. These immune gene modules showed complex patterns of association with 158 circulating metabolites, including lipoprotein subclasses, lipids, fatty acids, amino acids, and CRP. Genome-wide scans for module expression quantitative trait loci (mQTLs) revealed five modules with mQTLs with both cis and trans effects. Then, I explored the underlying shared genetic architecture between correlated cytokines, the regulatory agents of the immune system. Multivariate genome-wide association scan was performed to identify genetic variants regulating circulating cytokines in ~9,000 individuals from three independent population studies. Eight loci were identified as regulating this network, including two previously undetected loci. Expression quantitative loci (eQTL) analysis revealed that these loci harbour eQTLs. Further linking these loci with genetic variants associated with disease risk provided insight into the possible inflammatory pathways underlying these common diseases. Thirdly, I explored a particular component of the immune system, immunological memory; with emphasis on tissue resident memory T-cells (TRM cells). I employed a network-based approach to identify a transcriptional sub-network related to the residency of murine TRM cells isolated from various tissues. Comparative analysis further revealed that expression profiles of tissue resident immune cells from different lineages share transcriptional similarity. Finally, the role of TGF-β, an extrinsic tissue-derived factor in influencing the transcriptional signature of TRM cells was investigated. I compared the global transcription of T-cells induced in vitro by TGF-β with the residency-related transcription signature previously established in TRM cells. This demonstrated that the transcriptional signature of TRM cells is largely driven by TGF-β. Findings from this thesis demonstrate the power of integrative bioinformatics analyses to gain novel insights into the immune system, which can assist in predicting its response to perturbations. It also may help explain how inter-individual variability in immune function contributes to differential disease susceptibility and treatment outcomes. This thesis offers a general framework to systematically integrate and analyse multi-omics data to answer important biological questions.