Fusarium oxysporum is a major fungal plant pathogen and emerging human pathogen. It has been hypothesised that conidial anastomosis tube (CAT) fusion may facilitate horizontal gene/chromosome transfer that could result in the acquisition of new genetic traits in fungi lacking sexual reproduction. However, we know little about the mechanistic basis of CAT fusion in fungi lacking sexual stages such as F. oxysporum. In the first part of my research the optimal culture conditions were determined for subsequent studies of CAT fusion in this fungus. CAT fusion was optimal in 1% potato dextrose broth supplemented with one of a diverse range of chemicals inoculated with microconidia of 1 x 106 spores/ml at 22-25 °C and pH 5.5-6.3. Cell adhesion facilitated by the chemical supplement was required for CAT fusion. ~ 40% CAT fusion was routinely observed with these conditions at 12 h post incubation. In the second part of my research live-cell imaging was used to characterize the process of CAT fusion and differentiate between CATs and germ tubes. In particular, the composition of the CAT cell wall surface was shown to be different from that of germ tubes. Nuclei, mitochondria, vacuoles and lipid droplets were also shown to move between germlings following CAT fusion. In the third part of my research quantitative analysis of the influence of various Ca2+ modulators on CAT fusion was done and evidence obtained showed that Ca2+ signalling is important during CAT fusion and involves the uptake of Ca2+ from the external environment by the Cch1 Ca2+ channel, and the involvement of the primary intracellular Ca2+ receptor, calmodulin, and the mitochondrial Ca2+ uniporter. In the final part of my thesis, the morphogenesis of the fungus was analysed during infection of an ex vivo human corneal model. The stages of infection that were characterised were: spore adhesion; bipolar germination; hyphal extension, branching, fusion and penetration into the corneal tissue; and sporulation involving the formation of microconidia and intercalary chlamydospores within the host tissue. Image analysis techniques were developed for the quantification and analysis of branching angles, total hyphal length, number of hyphal branches and hyphal growth units within the infected ex vivo corneal tissue. Using the fusion mutant, ∆fso, CAT fusion was shown not to be required for infection.

This thesis considers Nonparametric Predictive Inference (NPI) for ordinal data and accuracy of diagnostic tests. We introduce NPI for ordinal data, which are categor- ical data with an ordering of the categories. Such data occur in many application areas, for example medical and social studies. The method uses a latent variable representation of the observations and categories on the real line. Lower and upper probabilities for events involving the next observation are presented, with specic attention to comparison of multiple groups of ordinal data. We introduce NPI for accuracy of diagnostic tests with ordinal outcomes, with the inferences based on data for a disease group and a non-disease group. We intro- duce empirical and NPI lower and upper Receiver Operating Characteristic (ROC) curves and the corresponding areas under the curves. We discuss the use of the Youden index related to the NPI lower and upper ROC curves in order to deter- mine the optimal cut-o point for the test. Finally, we present NPI for assessment of accuracy of diagnostic tests involving three groups of real-valued data. This is achieved by developing NPI lower and upper ROC surfaces and the corresponding volumes under these surfaces, and we also consider the choice of cut-o points for classications based on such diagnostic tests.

Vaccine development for intracellular pathogens, where a protective and long lasting T cell response is desirable, has proved to be a significant challenge. Dendritic cell (DC) vaccination has been used to both elucidate mechanisms important in providing protection against a range of pathogens and more recently as a vaccine strategy in its own right. Additionally, targeting of vaccine antigens via monoclonal antibodies specific to DCs has developed as a more clinically appropriate alternative. This thesis investigates whether DC manipulation can enhance survival and reduce bacterial load in murine models of anthrax and melioidosis. Prophylactic DC vaccination for B. anthracis required CpG ODN 1826 for the maturation of antigen-stimulated DCs in vitro. Following their adoptive transfer, DCs failed to induce an antigen-specific response. However, when combined with the rPA and alum anthrax vaccine, DC vaccination enhanced antigen-specific T cell responses. This approach increased murine survival and significantly reduced bacterial load. DC vaccination as a therapeutic strategy for B. pseudomallei again required CpG ODN 1826 for DC maturation and activation. Antigen stimulated DCs migrated to lymph nodes within 48 hours of adoptive transfer where they induced an antigen-specific T cell response with a mixed Th1/Th17 profile. DC vaccination failed to affect survival with increased splenic weight and bacterial load in two out of three murine efficacy studies. Targeting of the protective B. pseudomallei antigen LolC, conjugated to a monoclonal antibody specific for DEC205, an endocytic DC receptor, failed to induce either a specific immune response or impact survival or bacterial load. Overall, DC vaccination reduced B. anthracis bacterial load when used prophylactically in combination with rPA and alum. As a therapeutic strategy the results are suggestive of DC vaccination enhancing B. pseudomallei infection. Future studies should examine the potential for antigen specific immune responses generated by DC vaccination to be used as an adjunct to antibiotic therapy, when B. pseudomallei replication is controlled.

Leprosy is a disease caused by Mycobacterium leprae, an acid-fast bacillus whose clinical spectrum correlates with the host immune response. Erythema nodosum leprosum (ENL) is an immune-mediated inflammatory complication causing high morbidity in affected leprosy patients. A case-control follow-up study was conducted in Ethiopia to test the hypothesis that ENL is associated with impaired immune regulation. In 46 patients with ENL and 31 lepromatous leprosy (LL) matched controls, the frequency of regulatory T-cells, memory T-cells and B-cells were analysed by flow cytometry. The in vitro pro-inflammatory cytokines production by peripheral blood mononuclear cells (PBMCs) to the response of M. leprae whole cell sonicate stimulation was determined by Enzyme-linked immunosorbent assay. The gene expression of these cytokines in the blood and skin biopsies was determined by quantitative polymerase chain reaction (qPCR) before and after treatment. Patients with ENL had lower percentage of CD4+ regulatory T-cells than LL controls at recruitment. The percentage of CD3+, CD4+ and CD8+ T-cells expressing activated T-cells were significantly higher in the PBMCs of patients with ENL than in LL controls before treatment. The in vitro production and gene expression of the cytokines: TNF-α, IFN-γ, IL-1β, IL-6, IL-8 and IL-17A were significantly increased in untreated patients with ENL. ENL patients had a higher median percentage of tissue-like memory (TLM) and activated memory (AM) B-cells than LL controls before treatment while the median percentage of total B-cells and resting memory (RM) B-cells did not significantly different in both groups before treatment. The level of anti-PGL-1, LAM and Ag85 antibodies were not significantly different in patients with ENL before treatment. Patients with ENL had significantly lower circulating C1q than LL controls before treatment. However, after treatment, the amount of circulating C1q was not significantly different in both groups. Our findings suggest that ENL is associated with reduced percentage of regulatory T-cells and increased CD4+/CD8+ T-cell ratio and this immune imbalance may lead to the initiation of ENL reactions in either permitting productions of antibodies critical to an immune-complex formation or as a cell-mediated immune response in patients with leprosy. Consequently, this study illuminates the role of T-cell activation in the pathogenesis of ENL reaction and challenges the long-standing dogma of immune-complexes as the sole aetiology of ENL reactions.

The development of manufacturing processes for biopharmaceuticals is carried out by performing experiments in the laboratory and then the pilot plant. These laboratory - scale experiments are often misleading as they do not allow for the effect of the large-scale processing environment on the properties of biological process material. The research contained within this thesis seeks to develop laboratory techniques capable of eliciting the effects of the processing environment on the material and of predicting the performance of large-scale unit operations used in the purification of monoclonal antibody (MAb) biopharmaceuticals using milliliter volumes of process material. Two key interactive stages were examined firstly, an early centrifugation clarification stage designed to prepare material for subsequent filtration which precedes the second stage studied, a high affinity antibody capture step. The first focuses on the whole cell broth, containing the contaminants and the antibody product, the latter on the antibody product itself. A scale-down centrifuge technique which employed a rotating-disc, centrifuge feed zone mimic along with a laboratory-scale centrifugation method were developed to predict the clarification performance of two pilot, disc stack centrifuges with differing feed zone configurations and a manufacturing-scale disc stack centrifuge. The material obtained from the scale-down centrifuge protocol was shown to be equivalent to that from one of the pilot centrifuges to which it had been compared and, hence, could be used for the development of subsequent unit operations, such as chromatography processes. A method was developed to predict the elution profile of an 18 L pilot affinity chromatography column using a scale-down column with a column volume of one milliliter. A regime analysis of the laboratory-scale chromatography system was performed using conductivity transitions to determine the extent of additional zone broadening occurring at the small scale so that the prediction of the large-scale elution volume and eluting product concentration could be significantly improved.

Diabetes mellitus is one of the most common chronic diseases. The number of cases of diabetes in the world is likely to increase more than two fold in the next 30 years; from 115 million in 2000 to 284 million in 2030. This work is concerned with helping diabetic patients to manage themselves by trying to predict their blood glucose level (BGL) after 30 minutes on the basis of the current levels in order that they can administer insulin. This will enable the diabetic patient to continue living a normal day life activities as much as is possible. In order to achieve this objective, three techniques were developed and evaluated: a Numerical Analysis algorithm, an Artificial Neural Network (ANN), and a Genetic Algorithm (GA). In the case of the ANN and the GA, the variation in Blood Glucose Levels was modelled as a Mass Spring Damper, treating the food intake as a bolus injection of glucose, and thus the impulse force F (f), and the effects of exercise and hypoglycaemic medication were represented by the damping factor, p. The values of F, f$ and the differences in BGL every 5 minutes were used as knowledge features in the training and prediction phases for the ANN and GA. Data was derived for a virtual diabetic patient from a web-based educational simulation package for glucose-insulin levels in human body using the AIDA software. The Dexcom SEVEN System was used to capture the BGLs of two diabetic patients and a normal person for 24 hours with a sampling frequency of 5 minutes. The two databases were used in all prediction algorithms. Newton's Interpolatory Divided Difference (Numerical Analysis) algorithm was used to predict the future BGLs and found to be able to predict the level after 5 minutes from the current value of BGL with a RMSE less than 0.5 mmol/1. Unfortunately, the RMSE increased above 2.5 mmol/1 when trying to predict 15 or 20 minutes ahead. The ANN using Feed Forward Back Propagation was able to predict the BGL after 30 minutes with a RMSE between 0.49 mmol/1 to 1.8 mmol/1, while the GA was found to predict the BGL 30minutes ahead with a RMSE between 0.15 mmol/1 to 0.42 mmol/1. It is concluded that the GA provided the best technique for prediction in this application.

Mitochondrial myopathies are a clinically multifarious group of genetic disorders that affect the central nervous system and skeletal muscles and other organs heavily dependent on aerobic metabolism. They are typically characterised by multi-system involvement and have extensive phenotypic and disease burden variability. These diseases are often relentlessly progressive with high morbidity and mortality. The biochemical and molecular basis of many of the common mitochondrial myopathies has been elucidated over the last decade, yet the association between mitochondrial gene mutations and clinical symptoms, requires further elucidation. I propose to clearly define the clinico-pathological and molecular features of adults with mitochondrial disease and evaluate if there is a clear correlation between clinical phenotype and the underlying genetic defect. Identifying clear clinical features should help guide genetic diagnosis and enable tailored counselling regarding potential disease progression. Unfortunately, to date, there are few effective treatments and no known cure for patients with mitochondrial myopathies. Exercise has been shown to hold significant positive effects upon skeletal muscle function and perceived health- related quality of life in patients with mitochondrial myopathies. The molecular basis of many of the common mitochondrial disorders has been elucidated over the last decade and although there is a vast spectrum of phenotypic expression throughout different genotypes, common symptoms are reported. Perceived fatigue is often a prominent symptom in patients with mitochondrial disease but to date, its prevalence, severity and aetiology is poorly understood. I wish to determine the prevalence and nature of perceived fatigue in a large, genetically heterogeneous group of patients with mitochondrial disease and systematically assess potential covariates of fatigue compared to healthy controls and patients with Myalgic Encephalopathy /Chronic Fatigue Syndrome. Health-related quality of life is important for understanding the impact and progression of chronic disease and is increasingly recognised as a fundamental patient-based outcome measure in both clinical intervention and research. Generic outcome measures have been extensively validated to assess health-related quality of life across populations and different disease states. However, due to their inclusive construct, it is acknowledged that not all relevant aspects of a specific illness may be captured. Hence there is a need to develop a disease-specific health-related quality of life measures that centre on symptoms characteristic of a specific disease or condition and their impact. SF-36 and its abbreviated version SF-12 are currently the only tools used routinely for measuring patient-reported outcomes in our patients with mitochondrial myopathies. I wish to explore the conceptualisation, development and preliminary psychometric evaluation (validity and reliability) of a mitochondrial disease -specific health-related quality of life measure, which may be used both in research and clinical settings. Indeed, in a condition where the natural history of the disease is poorly understood and therapeutic options are limited, long-term preservation of health-related quality of life in patients with mitochondrial disease poses a real challenge.

The biopharmaceutical industry has seen rapid growth over the last 10 years in the area of therapeutic medicines. These include products such as monoclonal antibodies (mAbs) produced using mammalian cell lines such as Chinese Hamster Ovary (CHO). In order to comply with the regulatory authority (FDA) Quality by Design (QbD) and Process Analytical Technology (PAT) requirements, modelling can be used in the development and operation of the bioprocess. A model can assist in both the design, scale up and control of these complex, non-linear processes. A predictive model can be used to identify optimal operating conditions, which is vital for a contract manufacturer. Traditionally industry has approached modelling through the one-unit-at-a-time method, which can fail to capture unit interactions. The research reported in this work addresses this issue by using a whole system approach, which can also capture the interactions between units. Predictive models for each of the process units are combined within an overall framework allowing for the integration of the models, predicting how changes in the output of one unit influence the performance of subsequent units. These predictions can serve as the basis for the modifications to the standard operating procedures to achieve the required performance of the whole process. In this thesis three distinct studies are presented; the first utilises a hybridoma data set and presents a model to predict and characterise the various critical quality attributes (CQAs), such as final product glycosylation profile, and critical process parameters (CPPs) including titre and viable cell count. The second data set concerns the purification of lactoferrin using ion-exchange chromatography as a model system for developing downstream iii processing models. The output of this data set varied widely, and has led to the development of a novel peak isolation methodology, which can ultimately be used to characterise the elution. The final data set contains various CQAs and CPPs for multiple units within one process. This data set has been employed within a proof of concept study to show how an agent based framework can be developed to allow for overall process optimisation. The results showed that it is possible to link process units using a common CPP or CQA. This work shows that using a agent based system of two layers of modelling i.e. individual process unit models connected with a higher level agent model that links via a common measurement allows for the influences between units to be considered. The model presented in this work considers the use of titre, HCP, measure of heterogeneity, and molecular weight as the common measurement. It is shown that it is possible to link the units in this way with the goal of predicting and controlling the glycosylation profile of the Bulk Drug Substance (BDS).

The innate immune system is a first line defence mechanism against infection of the lower respiratory tract by pathogenic microorganisms. Pulmonary alveolar epithelial type 1 (TT1) and type-2 (AT-II) cells and macrophages (AMs) express Toll-like receptors (TLRs), which recognize microbial ligands and initiate the innate immune response by signalling synthesis and release of mediators, including cytokines. We hypothesized that activation of specific TLRs would elicit a unique profile of cytokine release from each cell type which would be enhanced in co-culture of pulmonary alveolar epithelial cells and macrophages. Mono-cultures of each cell type, and co-cultures, were incubated with either Lipopolysaccharide (LPS, TLR-4 ligand), MALP-2 (TLR-2 ligand) or Poly I:C (TLR-3 ligand) for 24 hours. There was, as hypothesised, potentiation of IL-6, IL-8, and IP-10 release from cells in co-culture compared to mono-culture following LPS and Poly I:C. However, there was no additional effect of co-culture on IL-6 and IL-8 release following MALP-2 exposure. Further studies using antibody eutralisation demonstrated that a significant proportion of the potentiation was initiated by soluble factors, released by AMs, acting on the epithelial cells. Furthermore, neutralization of inflammasome -related cytokines, IL-1? and IL-18, significantly inhibited release of IL-8 and IP-10. Although exacerbations due to pathogen infection enhance lung function impairment, cigarette smoking is the major risk factor for COPD. We hypothesized that cigarette smoke e xtract (CSE) would moderate inflammatory response in the cells. 1% CSE caused inhibition of mediator release, suggesting that this may increase risk of infection among smokers. Subsequent studies demonstrated that concentrations < 0.01% were stimulatory and resulted in the release of chemokines involved in the recruitment of dendritic cells. In conclusion, cytokine release at the alveolar interface will be up-regulated by interactions between alveolar epithelial cells and macrophages, via paracellular proces ses involving release of soluble factors by macrophages, including TNF-, IL-1 and IP-10.

Autophagosomes are specialised, double membrane-bound organelles that participate in the bulk degradation of cytoplasmic proteins and organelles during autophagy. Autophagy is required for the maintenance of general cellular health and survival and is particularly important in stress conditions such as nutrient starvation. As critical participants in membrane trafficking events, Rab GTPases, along with their positive (GEF) and negative (GAP) regulators are indispensable for autophagy. Indeed, a number of RabGAP proteins have been implicated in the control of autophagy and increasingly it appears that their contribution exceeds that of just inactivating Rab GTPases. Armus is a TBC/RabGAP protein that specifically inactivates Rab7 and can also bind active Rac, a member of the Rho family of small GTPases. By mediating cross-talk between these two small GTPases, Armus participates in the regulation of E-cadherin degradation during cell scattering. I have identified that during nutrient starvation, Armus is required for efficient autophagy to occur in normal human keratinocytes. Furthermore, the activities of Rab7 and Rac are inversely correlated during starvation; Rab7 is transiently activated while Rac is potently inactivated. This inactivation is required but not sufficient to induce autophagosome formation and occurs independently of signaling via mTORC1. Rather, we hypothesise that Rac is out-competed for binding to Armus by the autophagosome-specific protein, LC3. Armus is able to directly interact with LC3 via two complementary, LC3-interacting region (LIR) motifs. This interaction is required for the recruitment of Armus to autophagosomes and away from cell-cell contacts, which remain unperturbed during nutrient starvation. The subsequent localisation of Armus at autophagosome membranes provides it with the appropriate spatial distribution to facilitate autophagosome maturation in a RabGAP-dependent manner. We have observed that autophagy occurs at disparate levels in epithelial tumour cell lines. Further understanding of the specific signaling and trafficking events that regulate autophagy will have important future implications in health and disease.