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Mitochondrial DNA mutations are a major cause of disease in the human population. Understanding the disease associated with these mutations is complicated by heteroplasmy, the mixture of wild-type and mutated mitochondrial DNA. Heteroplasmy can vary between cells, tissues, and organs, and the disease associated individual mutations is hugely varied on account of this. The mitochondrial genome encodes critical proteins of the oxidative phosphorylation system and mutation leads to energy deficits in cells and a wide range of secondary effects. The central and peripheral nervous system are commonly affected in mitochondrial disease and quality of life for patients is severely impaired. Although pathogenic mitochondrial genetic mutations were first identified over twenty five years ago, little progress has been made in understanding the expected progression of disease in patients. The aim of this study was to use statistical modelling to further understanding of disease progression in mitochondrial DNA mutations. The Medical Research Council Mitochondrial Disease Cohort provided the majority of patient data. Patients had been assessed using the Newcastle Mitochondrial Disease Adult Scale, which facilitates quantitative research on mitochondrial disease burden. This project comprises studies of two of the most common mitochondrial DNA mutations. The first study concerns patients with the m.3243A>G mutation, the most common pathogenic point mutation, and considers the effect of age and heteroplasmy on disease progression. Prediction models of both overall disease burden and specific phenotypic features were developed. Important features of the patient cohort were also examined, including heteroplasmy in different tissues and differences in disease expression between sexes. The second study looks at patients with single large-scale mitochondrial DNA mutations. The effect of deletion size, location of the deletion on the genome, and heteroplasmy were investigated, and all three predictors were found to be significant in understanding disease progression.

NF-κB transcription factors play essential roles in regulating the expression of a large array of genes involved in immune and inflammatory responses, cell proliferation, apoptosis and oncogenesis. In recent years, ubiquitination of key components has emerged as a crucial regulatory mechanism in NF-κB signalling pathways. This can either directly modulate the activity of the target substrate or provide a scaffold for the recognition and recruitment of other signalling molecules via their respective ubiquitin binding domains. NEMO, the regulatory subunit of the IKK complex, is a prime example of a signalling component which interacts with ubiquitin chains of different topologies as well as being modified by ubiquitination. These events are thought to regulate the activation of the kinase subunits of the complex, IKKα and IKKβ, which ultimately results in liberation of NF-κB and translocation to the nucleus. NEMO itself possesses two ubiquitin-binding domains: the CoZi/UBAN domain and a C-terminal zinc finger (ZF). The work presented in this thesis shows that the synergistic action of these two domains confers specificity for K63-linked ubiquitin chains. Importantly, chain length plays a crucial role in these binding events. The discovery that NEMO becomes modified by the E3 ligase LUBAC with a novel type of ubiquitin chain, termed linear, opened up a whole new exciting area of research. So far, LUBAC is the only E3 ligase known to synthesize this type of chain. This thesis provides a first glimpse into the mechanistic determinants which allow LUBAC to enforce the formation of linear ubiquitin chains and demonstrates, for the first time, that one of its subunits, HOIL-1L, transfers ubiquitin to a substrate via a thioester intermediate.

The study of the immune system has classically been divided between the innate and the adaptive. Natural antibodies (NAbs) are a class of antibodies produced in response to no well-defined stimuli, with broad-spectrum activity often for conserved carbohydrate antigens. γδ T cells similarly, are a subset of T cells which display oligoclonal T cell receptors specific for conserved microbial antigens. While antibodies and T cells are classically adaptive responses, NAbs and γδ T cells display many non-classical innate interactions. Their interactions with influenza A virus are investigated here with an aim to improve the immune response. Using reverse genetics I have demonstrated here that influenza A viruses can be engineered to express the galα1-3gal and ABO blood group carbohydrate antigens, making them targets for anti-galα1-3gal and anti-ABO antibodies widely expressed in humans. I then investigated the potential of NAbs to enhance the immunity to influenza. In addition, I investigated the presentation of influenza by a novel antigen presenting cell, the γδ T cell. These cells were shown to acquire this antigen by phagocystosis. This surprising capacity for phagocytosis was demonstrated by flow cytometry, by direct observation under confocal and electron microscopy and by functional assays of antigen presentation. γδ T cells could be shown to phagocytose both Escherichia coli and 1μm synthetic beads. This process was at least partly mediated by the receptor for phagocytosis, CD16. Being “adaptive”, γδ T cells retain the capacity for rapid clonal expansion and yet at the same time these cells possess the highly specialized functions of phagocytosis and antigen presentation classically restricted to a small population of innate DCs. Such novel and non-classical immune interactions open new avenues in the development of rapid immunotherapeutic interventions against potential pandemic strains of influenza A.

Two pertinent questions in T cell immunology are addressed by using techniques from machine learning to describe T cell migration dynamics and characteristics of the T cell receptor repertoire. Naive T lymphocytes exhibit extensive antigen-independent recirculation between blood and lymph nodes, where they may encounter dendritic cells carrying cognate antigen. The time T cells may spend in an individual lymph node is estimated by analysing data from long term cannulation of blood and efferent lymphatics of a single lymph node in sheep. The distribution of transit times of migrating T cells is determined empirically by applying the Least Absolute Shrinkage & Selection Operator to experimental data. The results demonstrate that the rapid recirculation of lymphocytes observed at a macro level is compatible with predominantly randomised movement within lymph nodes. High throughput sequencing provides an opportunity to analyse the repertoire of antigen specific receptors with an unprecedented breadth and depth. However, the quantity of raw data produced by this technology requires efficient ways to categorise and store the output for subsequent analysis. A novel application of a finite state automaton is implemented to characterise T cell receptor sequences for the purpose of downstream analysis. Finally, the clonal theory of adaptive immunity proposes that immunological responses are encoded by increases in the frequency of lymphocytes carrying antigen-specific receptors. Both unsupervised (hierarchical clustering) and supervised (support vector machine) learning techniques are successfully used to track changes in the T cell receptor repertoire induced by immunization, using contiguous stretches of amino acids within the T cell receptor complementarity determining region 3 repertoire of different mice.

Members of the serpin (serine protease inhibitor) superfamily of proteins regulate key physiological processes through their ability to undergo major conformational transitions. In conformational diseases, native protein conformers convert to pathological species that polymerise. Structural characterization of these key transitions is challenging. Mechanistic intermediates are unstable and minimally populated in dynamic equilibria that may be perturbed by many analytical techniques. I use Nuclear Magnetic Resonance (NMR), and Circular Dichroism (CD) spectroscopy, to investigate the interrelated processes of serpin folding, misfolding and polymerisation in solution using the 45kDa prototypic serpin á1-antitrypsin, the recent assignment of the backbone resonances of á1-antitrypsin by our group, allows us to ask more sophisticated questions by a range of NMR techniques to study its structure and dynamics. In this study, I analysed early unfolding behaviour of á1-antitrypsin across a urea titration within what is apparently the largest two-states system yet characterised. In order to assess the dynamics of the native state, I have used hydrogen/deuterium exchange nuclear magnetic resonance spectroscopy (HDXNMR) to characterise motions on the slow (ms) timescale. I have conducted a detailed analysis of residue-specific changes in protection from exchange across a pH titration using SOFAST-HMQC. This is complemented by a detailed a preliminary analysis of fast motions (ps-ns) using NMR relaxation experiments. Moreover, a forme fruste deficiency variant of á1-antitrypsin (Lys154Asn) that forms polymers recapitulating the conformer-specific neo-epitope observed in polymers that form in vivo was characterized in this study. Lys154Asn á1-antitrypsin populates an intermediate ensemble along the polymerisation pathway at physiological temperatures. Together, this study shows how the use of powerful but minimally perturbing techniques, mild disease mutants, and physiological conditions, provides novel insights into pathological conformational behaviour.

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