Functional and cellular analysis of autoimmune regulator (AIRE) protein

Autoimmune diseases are a major health problem. Usually autoimmune disorders are multifactorial and their pathogenesis involves a combination of predisposing variations in the genome and other factors such as environmental triggers. APECED (autoimmune polyendocrinopathy-candidiasis-ectodermal dystrophy) is a rare, recessively inherited, autoimmune disease caused by mutations in a single gene. Patients with APECED suffer from several organ-specific autoimmune disorders, often affecting the endocrine glands. The defective gene, AIRE, codes for a transcriptional regulator. The AIRE (autoimmune regulator) protein controls the expression of hundreds of genes, representing a substantial subset of tissue-specific antigens which are presented to developing T cells in the thymus and has proven to be a key molecule in the establishment of immunological tolerance. However, the molecular mechanisms by which AIRE mediates its functions are still largely obscure. The aim of this thesis has been to elucidate the functions of AIRE by studying the molecular interactions it is involved in by utilizing different cultured cell models. A potential molecular mechanism for exceptional, dominant, inheritance of APECED in one family, carrying a glycine 228 to tryptophan (G228W) mutation, was described in this thesis. It was shown that the AIRE polypeptide with G228W mutation has a dominant negative effect by binding the wild type AIRE and inhibiting its transactivation capacity in vitro. The data also emphasizes the importance of homomultimerization of AIRE in vivo. Furthermore, two novel protein families interacting with AIRE were identified. The importin alpha molecules regulate the nuclear import of AIRE by binding to the nuclear localization signal of AIRE, delineated as a classical monopartite signal sequence. The interaction of AIRE with PIAS E3 SUMO ligases, indicates a link to the sumoylation pathway, which plays an important role in the regulation of nuclear architecture. It was shown that AIRE is not a target for SUMO modification but enhances the localization of SUMO1 and PIAS1 proteins to nuclear bodies. Additional support for the suggestion that AIRE would preferably up-regulate genes with tissue-specific expression pattern and down-regulate housekeeping genes was obtained from transactivation studies performed with two models: human insulin and cystatin B promoters. Furthermore, AIRE and PIAS activate the insulin promoter concurrently in a transactivation assay, indicating that their interaction is biologically relevant. Identification of novel interaction partners for AIRE provides us information about the molecular pathways involved in the establishment of immunological tolerance and deepens our understanding of the role played by AIRE not only in APECED but possibly also in several other autoimmune diseases.

Unravelling Molecular and Cellular Disease Mechanisms in Infantile Neuronal Ceroid Lipofuscinosis (INCL)

Studying neurodegeneration provides an opportunity to gain insights into normal cell physiology, and not just pathophysiology. In this thesis work the focus is on Infantile Neuronal Ceroid Lipofuscinosis (INCL). It is a recessively inherited lysosomal storage disorder. The disease belongs to the neuronal ceroid lipofuscinoses (NCLs), a group of common progressive neurodegenerative diseases of the childhood. Characteristic accumulation of autofluorescent storage material is seen in most tissues but only neurons of the central nervous system are damaged and eventually lost during the course of the disease leaving most other cell types unaffected. The disease is caused by mutations in the CLN1 gene, but the physiological function of the corresponding protein the palmitoyl protein thioesterase (PPT1) has remained elusive. The aim of this thesis work was to shed light on the molecular and cell biological mechanisms behind INCL. This study pinpointed the localization of PPT1 in axonal presynapses of neurons. It also established the role of PPT1 in early neuronal maturation as well as importance in mature neuronal synapses. This study revealed an endocytic defect in INCL patient cells manifesting itself as delayed trafficking of receptor and non-receptor mediated endocytic markers. Furthermore, this study was the first to connect the INCL storage proteins the sphingolipid activator proteins (SAPs) A and D to pathological events on the cellular level. Abnormal endocytic processing and intracellular re-localization was demonstrated in patient cells and disease model knock-out mouse neurons. To identify early affected cellular and metabolic pathways in INCL, knock-out mouse neurons were studied by global transcript profiling and functional analysis. The gene expression analysis revealed changes in neuronal maturation and cell communication strongly associated with the regulated secretory system. Furthermore, cholesterol metabolic pathways were found to be affected. Functional studies with the knock-out mouse model revealed abnormalities in neuronal maturation as well as key neuronal functions including abnormalities in intracellular calcium homeostasis and cholesterol metabolism. Together the findings, introduced in this thesis work, support the essential role of PPT1 in developing neurons as well as synaptic sites of mature neurons. Results of this thesis also elucidate early events in INCL pathogenesis revealing defective pathways ultimately leading to the neurodegenerative process. These results contribute to the understanding of the vital physiological function of PPT1 and broader knowledge of common cellular mechanisms behind neurodegeneration. These results add to the knowledge of these severe diseases offering basis for new approaches in treatment strategies.

Semi-supervised learning of WLAN radio maps

In this thesis a manifold learning method is applied to the problem of WLAN positioning and automatic radio map creation. Due to the nature of WLAN signal strength measurements, a signal map created from raw measurements results in non-linear distance relations between measurement points. These signal strength vectors reside in a high-dimensioned coordinate system. With the help of the so called Isomap-algorithm the dimensionality of this map can be reduced, and thus more easily processed. By embedding position-labeled strategic key points, we can automatically adjust the mapping to match the surveyed environment. The environment is thus learned in a semi-supervised way; gathering training points and embedding them in a two-dimensional manifold gives us a rough mapping of the measured environment. After a calibration phase, where the labeled key points in the training data are used to associate coordinates in the manifold representation with geographical locations, we can perform positioning using the adjusted map. This can be achieved through a traditional supervised learning process, which in our case is a simple nearest neighbors matching of a sampled signal strength vector. We deployed this system in two locations in the Kumpula campus in Helsinki, Finland. Results indicate that positioning based on the learned radio map can achieve good accuracy, especially in hallways or other areas in the environment where the WLAN signal is constrained by obstacles such as walls.

On cluster approximations of cellular automata

In this thesis I examine one commonly used class of methods for the analytic approximation of cellular automata, the so-called local cluster approximations. This class subsumes the well known mean-field and pair approximations, as well as higher order generalizations of these. While a straightforward method known as Bayesian extension exists for constructing cluster approximations of arbitrary order on one-dimensional lattices (and certain other cases), for higher-dimensional systems the construction of approximations beyond the pair level becomes more complicated due to the presence of loops. In this thesis I describe the one-dimensional construction as well as a number of approximations suggested for higher-dimensional lattices, comparing them against a number of consistency criteria that such approximations could be expected to satisfy. I also outline a general variational principle for constructing consistent cluster approximations of arbitrary order with minimal bias, and show that the one-dimensional construction indeed satisfies this principle. Finally, I apply this variational principle to derive a novel consistent expression for symmetric three cell cluster frequencies as estimated from pair frequencies, and use this expression to construct a quantitatively improved pair approximation of the well-known lattice contact process on a hexagonal lattice.