Part I: Enzyme replacement versus neurotrophic factor viral vector-mediated gene therapy of Parkinson’s disease, Part II: The effects of orally dosed tolcapone and entacapone on dopamine metabolism in the dorsal striatum and nucleus accumbens in rats

Part I: Parkinson’s disease is a slowly progressive neurodegenerative disorder in which particularly the dopaminergic neurons of the substantia nigra pars compacta degenerate and die. Current conventional treatment is based on restraining symptoms but it has no effect on the progression of the disease. Gene therapy research has focused on the possibility of restoring the lost brain function by at least two means: substitution of critical enzymes needed for the synthesis of dopamine and slowing down the progression of the disease by supporting the functions of the remaining nigral dopaminergic neurons by neurotrophic factors. The striatal levels of enzymes such as tyrosine hydroxylase, dopadecarboxylase and GTP-CH1 are decreased as the disease progresses. By replacing one or all of the enzymes, dopamine levels in the striatum may be restored to normal and behavioral impairments caused by the disease may be ameliorated especially in the later stages of the disease. The neurotrophic factors glial cell derived neurotrophic factor (GDNF) and neurturin have shown to protect and restore functions of dopaminergic cell somas and terminals as well as improve behavior in animal lesion models. This therapy may be best suited at the early stages of the disease when there are more dopaminergic neurons for neurotrophic factors to reach. Viral vector-mediated gene transfer provides a tool to deliver proteins with complex structures into specific brain locations and provides long-term protein over-expression. Part II: The aim of our study was to investigate the effects of two orally dosed COMT inhibitors entacapone (10 and 30 mg/kg) and tolcapone (10 and 30 mg/kg) with a subsequent administration of a peripheral dopadecarboxylase inhibitor carbidopa (30 mg/kg) and L- dopa (30 mg/kg) on dopamine and its metabolite levels in the dorsal striatum and nucleus accumbens of freely moving rats using dual-probe in vivo microdialysis. Earlier similarly designed studies have only been conducted in the dorsal striatum. We also confirmed the result of earlier ex vivo studies regarding the effects of intraperitoneally dosed tolcapone (30 mg/kg) and entacapone (30 mg/kg) on striatal and hepatic COMT activity. The results obtained from the dorsal striatum were generally in line with earlier studies, where tolcapone tended to increase dopamine and DOPAC levels and decrease HVA levels. Entacapone tended to keep striatal dopamine and HVA levels elevated longer than in controls and also tended to elevate the levels of DOPAC. Surprisingly in the nucleus accumbens, dopamine levels after either dose of entacapone or tolcapone were not elevated. Accumbal DOPAC levels, especially in the tolcapone 30 mg/kg group, were elevated nearly to the same extent as measured in the dorsal striatum. Entacapone 10 mg/kg elevated accumbal HVA levels more than the dose of 30 mg/kg and the effect was more pronounced in the nucleus accumbens than in the dorsal striatum. This suggests that entacapone 30 mg/kg has minor central effects. Also our ex vivo study results obtained from the dorsal striatum suggest that entacapone 30 mg/kg has minor and transient central effects, even though central HVA levels were not suppressed below those of the control group in either brain area in the microdialysis study. Both entacapone and tolcapone suppressed hepatic COMT activity more than striatal COMT activity. Tolcapone was more effective than entacapone in the dorsal striatum. The differences between dopamine and its metabolite levels in the dorsal striatum and nucleus accumbens may be due to different properties of the two brain areas.

Prognostic importance of the tumour microenvironment in follicular lymphoma patients treated with immunochemotherapy

Follicular lymphoma (FL) is the second most common non-Hodgkin lymphoma. It is an indolent and clinically heterogeneous disease, which is generally considered incurable. Currently, immunochemotherapy has significantly improved the outcome of FL patients. This is based on the combination of rituximab, a monoclonal anti-CD20 antibody, with chemotherapy, and is used at present as a standard first-line therapy in FL. Thus far, however, patients have been selected for treatment based on clinical risk factors and indices that were developed before the rituximab era. Therefore, there is a growing need to understand the molecular mechanisms underlying the disease, which would not only provide information to predict survival in the rituximab era, but also enable the design of more targeted therapeutic strategies. In this study, our aim was to identify genes predicting the outcome in FL patients treated with immunochemotherapy. Thus, we performed a cDNA microarray with 24 FL patients. When gene expression differences from diagnostic tumour samples were related to the clinical outcome, we identified novel genes with a prognostic impact on survival. The expression of selected genes was further characterized with quantitative PCR and immunohistochemistry (IHC). Interestingly, the prognostic influence of these genes was often associated with their expression in non-malignant cells instead of tumour cells. Based on the observed gene expression patterns, we analyzed the abundance and prognostic value of non-malignant immune cells in 95-98 FL patients treated with immunochemotherapy. We observed that a high content of tumour-associated macrophages was a marker of a favourable prognosis. In contrast, the accumulation of mast cells correlated with a poor outcome and was further associated with tumour vascularity. Increased microvessel density also correlated with an inferior outcome. In addition, we used the same microarray data with a systems biology approach to identify signalling pathways or groups of genes capable of separating patients with favourable or adverse outcomes. Among the transcripts, there were many genes associated with signal transducers and activators of the transcription (STAT5a) pathway. When IHC was used as validation, STAT5a expression was mostly observed in T-cells and follicular dendritic cells, and expression was found to predict a favourable outcome. In cell cultures, rituximab was observed to induce the expression of STAT5a-associated interleukins in human lymphoma cell lines, which might provide a possible link for the cross-talk between rituximab-induced FL cells and their microenvironment. In conclusion, we have demonstrated that the microenvironment has a prognostic role in FL patients treated with immunochemotherapy. The results also address the importance of re-evaluating the prognostic markers in the rituximab era of lymphoma therapies.

Genetic variation in the LDL receptor-related protein 5 (LRP5) gene : Association with bone health and metabolic parameters

Bone mass accrual and maintenance are regulated by a complex interplay between genetic and environmental factors. Recent studies have revealed an important role for the low-density lipoprotein receptor-related protein 5 (LRP5) in this process. The aim of this thesis study was to identify novel variants in the LRP5 gene and to further elucidate the association of LRP5 and its variants with various bone health related clinical characteristics. The results of our studies show that loss-of-function mutations in LRP5 cause severe osteoporosis not only in homozygous subjects but also in the carriers of these mutations, who have significantly reduced bone mineral density (BMD) and increased susceptibility to fractures. In addition, we demonstrated for the first time that a common polymorphic LRP5 variant (p.A1330V) was associated with reduced peak bone mass, an important determinant of BMD and osteoporosis in later life. The results from these two studies are concordant with results seen in other studies on LRP5 mutations and in association studies linking genetic variation in LRP5 with BMD and osteoporosis. Several rare LRP5 variants were identified in children with recurrent fractures. Sequencing and multiplex ligation-dependent probe amplification (MLPA) analyses revealed no disease-causing mutations or whole-exon deletions. Our findings from clinical assessments and family-based genotype-phenotype studies suggested that the rare LRP5 variants identified are not the definite cause of fractures in these children. Clinical assessments of our study subjects with LPR5 mutations revealed an unexpectedly high prevalence of impaired glucose tolerance and dyslipidaemia. Moreover, in subsequent studies we discovered that common polymorphic LRP5 variants are associated with unfavorable metabolic characteristics. Changes in lipid profile were already apparent in pre-pubertal children. These results, together with the findings from other studies, suggest an important role for LRP5 also in glucose and lipid metabolism. Our results underscore the important role of LRP5 not only in bone mass accrual and maintenance of skeletal health but also in glucose and lipid metabolism. The role of LRP5 in bone metabolism has long been studied, but further studies with larger study cohorts are still needed to evaluate the specific role of LRP5 variants as metabolic risk factors.

Role and function of nonmuscle alpha-actinin-1 and -4 in regulating distinct subcategories of actin stress fibers in mammalian cells

Actin stress fibers are dynamic structures in the cytoskeleton, which respond to mechanical stimuli and affect cell motility, adhesion and invasion of cancer cells. In nonmuscle cells, stress fibers have been subcategorized to three distinct stress fiber types: dorsal and ventral stress fibers and transverse arcs. These stress fibers are dissimilar in their subcellular localization, connection to substratum as well as in their dynamics and assembly mechanisms. Still uncharacterized is how they differ in their function and molecular composition. Here, I have studied involvement of nonmuscle alpha-actinin-1 and -4 in regulating distinct stress fibers as well as their localization and function in human U2OS osteosarcoma cells. Except for the correlation of upregulation of alpha-actinin-4 in invasive cancer types very little is known about whether these two actinins are redundant or have specific roles. The availability of highly specific alpha-actinin-1 antibody generated in the lab, revealed localization of alpha-actinin-1 along all three categories of stress fibers while alphaactinin-4 was detected at cell edge, distal ends of stress fibers as well as perinuclear regions. Strikingly, by utilizing RNAi-mediated gene silencing of alpha-actinin-1 resulted in specific loss of dorsal stress fibers and relocalization of alpha-actinin-4 to remaining transverse arcs and ventral stress fibers. Unexpectedly, aberrant migration was not detected in cells lacking alpha-actinin-1 even though focal adhesions were significantly smaller and fewer. Whereas, silencing of alpha-actinin-4 noticeably affected overall cell migration. In summary, as part of my master thesis study I have been able to demonstrate distinct localization and functional patterns for both alpha-actinin-1 and -4. I have identified alpha-actinin-1 to be a selective dorsal stress fiber crosslinking protein as well as to be required for focal adhesion maturation, while alpha-actinin-4 was demonstrated to be fundamental for cell migration.

Models of Dispersal and Diversification

Ecology and evolutionary biology is the study of life on this planet. One of the many methods applied to answering the great diversity of questions regarding the lives and characteristics of individual organisms, is the utilization of mathematical models. Such models are used in a wide variety of ways. Some help us to reason, functioning as aids to, or substitutes for, our own fallible logic, thus making argumentation and thinking clearer. Models which help our reasoning can lead to conceptual clarification; by expressing ideas in algebraic terms, the relationship between different concepts become clearer. Other mathematical models are used to better understand yet more complicated models, or to develop mathematical tools for their analysis. Though helping us to reason and being used as tools in the craftmanship of science, many models do not tell us much about the real biological phenomena we are, at least initially, interested in. The main reason for this is that any mathematical model is a simplification of the real world, reducing the complexity and variety of interactions and idiosynchracies of individual organisms. What such models can tell us, however, both is and has been very valuable throughout the history of ecology and evolution. Minimally, a model simplifying the complex world can tell us that in principle, the patterns produced in a model could also be produced in the real world. We can never know how different a simplified mathematical representation is from the real world, but the similarity models do strive for, gives us confidence that their results could apply. This thesis deals with a variety of different models, used for different purposes. One model deals with how one can measure and analyse invasions; the expanding phase of invasive species. Earlier analyses claims to have shown that such invasions can be a regulated phenomena, that higher invasion speeds at a given point in time will lead to a reduction in speed. Two simple mathematical models show that analysis on this particular measure of invasion speed need not be evidence of regulation. In the context of dispersal evolution, two models acting as proof-of-principle are presented. Parent-offspring conflict emerges when there are different evolutionary optima for adaptive behavior for parents and offspring. We show that the evolution of dispersal distances can entail such a conflict, and that under parental control of dispersal (as, for example, in higher plants) wider dispersal kernels are optimal. We also show that dispersal homeostasis can be optimal; in a setting where dispersal decisions (to leave or stay in a natal patch) are made, strategies that divide their seeds or eggs into fractions that disperse or not, as opposed to randomized for each seed, can prevail. We also present a model of the evolution of bet-hedging strategies; evolutionary adaptations that occur despite their fitness, on average, being lower than a competing strategy. Such strategies can win in the long run because they have a reduced variance in fitness coupled with a reduction in mean fitness, and fitness is of a multiplicative nature across generations, and therefore sensitive to variability. This model is used for conceptual clarification; by developing a population genetical model with uncertain fitness and expressing genotypic variance in fitness as a product between individual level variance and correlations between individuals of a genotype. We arrive at expressions that intuitively reflect two of the main categorizations of bet-hedging strategies; conservative vs diversifying and within- vs between-generation bet hedging. In addition, this model shows that these divisions in fact are false dichotomies.

Associations of interleukin-1 (IL-1) gene variation and IL-1 receptor antagonist phenotypes with immunological responses, metabolic dysregulation and type 2 diabetes

The upstream proinflammatory interleukin-1 (IL-1) cytokines, together with a naturally occurring IL-1 receptor antagonist (IL-1Ra), play a significant role in several diseases and physiologic conditions. The IL-1 proteins affect glucose homeostasis at multiple levels contributing to vascular injuries and metabolic dysregulations that precede diabetes. An association between IL-1 gene variations and IL-1Ra levels has been suggested, and genetic studies have reported associations with metabolic dysregulation and altered inflammatory responses. The principal aims of this study were to: 1) examine the associations of IL-1 gene variation and IL-1Ra expression in the development and persistence of thyroid antibodies in subacute thyroiditis; 2) investigate the associations of common variants in the IL-1 gene family with plasma glucose and insulin concentrations, glucose homeostasis measures and prevalent diabetes in a representative population sample; 3) investigate genetic and non-genetic determinants of IL-1Ra phenotypes in a cross-sectional setting in three independent study populations; 4) investigate in a prospective setting (a) whether variants of the IL-1 gene family are predictors for clinically incident diabetes in two population-based observational cohort studies; and (b) whether the IL-1Ra levels predict the progression of metabolic syndrome to overt diabetes during the median follow-up of 10.8 and 7.1 years. Results from on patients with subacte thyroiditis showed that the systemic IL-1Ra levels are elevated during a specific proinflammatory response and they correlated with C-reactive protein (CRP) levels. Genetic variation in the IL-1 family seemed to have an association with the appearance of thyroid peroxidase antibodies and persisting local autoimmune responses during the follow-up. Analysis of patients suffering from diabetes and metabolic traits suggested that genetic IL-1 variation and IL-1Ra play a role in glucose homeostasis and in the development of type 2 diabetes. The coding IL-1 beta SNP rs1143634 was associated with traits related to insulin resistance in cross-sectional analyses. Two haplotype variants of the IL-1 beta gene were associated with prevalent diabetes or incident diabetes in a prospective setting and both of these haplotypes were tagged by rs1143634. Three variants of the IL-1Ra gene and one of the IL-1 beta gene were consistently identified as significant, independent determinants of the IL-1Ra phenotype in two or three populations. The proportion of the phenotypic variation explained by the genetic factors was modest however, while obesity and other metabolic traits explained a larger part. Body mass index was the strongest predictor of systemic IL-1Ra concentration overall. Furthermore, the age-adjusted IL-1Ra concentrations were elevated in individuals with metabolic syndrome or diabetes when compared to those free of metabolic dysregulation. In prospective analyses the systemic IL-1Ra levels were found as independent predictors for the development of diabetes in people with metabolic syndrome even after adjustment for multiple other factors, including plasma glucose and CRP levels. The predictive power of IL-1Ra was better than that of CRP. The prospective results also provided some evidence for a role of common IL-1 alpha promoter SNP rs1800587 in the development of type 2 diabetes among men and suggested that the role may be gender specific. Likewise, common variations in the IL-1 beta coding region may have a gender specific association with diabetes development. Further research on the potential benefits of IL-1Ra measurements in identifying individuals at high risk for diabetes, who then could be targeted for specific treatment interventions, is warranted. It has been reported in the recent literature that IL-1Ra secreted from adipose tissue has beneficial effects on glucose homeostasis. Furthermore, treatment with recombinant human IL-1Ra has been shown to have a substantial therapeutic potential. The genetic results from the prospective analyses performed in this study remain inconclusive, but together with the cross-sectional analyses they suggest gender-specific effects of the IL-1 variants on the risk of diabetes. Larger studies with more extensive genotyping and resequencing may help to pinpoint the exact variants responsible and to further elucidate the biological mechanisms for the observed associations. This would improve our understanding of the pathways linking inflammation and obesity with glucose and insulin metabolism.

A metabolomic approach to studying mechanisms of polymeric gene delivery to retinal pigment epithelial cells

Tiivistelmä ReferatAbstract Metabolomics is a rapidly growing research field that studies the response of biological systems to environmental factors, disease states and genetic modifications. It aims at measuring the complete set of endogenous metabolites, i.e. the metabolome, in a biological sample such as plasma or cells. Because metabolites are the intermediates and end products of biochemical reactions, metabolite compositions and metabolite levels in biological samples can provide a wealth of information on on-going processes in a living system. Due to the complexity of the metabolome, metabolomic analysis poses a challenge to analytical chemistry. Adequate sample preparation is critical to accurate and reproducible analysis, and the analytical techniques must have high resolution and sensitivity to allow detection of as many metabolites as possible. Furthermore, as the information contained in the metabolome is immense, the data set collected from metabolomic studies is very large. In order to extract the relevant information from such large data sets, efficient data processing and multivariate data analysis methods are needed. In the research presented in this thesis, metabolomics was used to study mechanisms of polymeric gene delivery to retinal pigment epithelial (RPE) cells. The aim of the study was to detect differences in metabolomic fingerprints between transfected cells and non-transfected controls, and thereafter to identify metabolites responsible for the discrimination. The plasmid pCMV-β was introduced into RPE cells using the vector polyethyleneimine (PEI). The samples were analyzed using high performance liquid chromatography (HPLC) and ultra performance liquid chromatography (UPLC) coupled to a triple quadrupole (QqQ) mass spectrometer (MS). The software MZmine was used for raw data processing and principal component analysis (PCA) was used in statistical data analysis. The results revealed differences in metabolomic fingerprints between transfected cells and non-transfected controls. However, reliable fingerprinting data could not be obtained because of low analysis repeatability. Therefore, no attempts were made to identify metabolites responsible for discrimination between sample groups. Repeatability and accuracy of analyses can be influenced by protocol optimization. However, in this study, optimization of analytical methods was hindered by the very small number of samples available for analysis. In conclusion, this study demonstrates that obtaining reliable fingerprinting data is technically demanding, and the protocols need to be thoroughly optimized in order to approach the goals of gaining information on mechanisms of gene delivery.

Mammalian Mat1 subunit of Transcription Factor IIH in gene-specific and general transcription

All protein-encoding genes in eukaryotes are transcribed into messenger RNA (mRNA) by RNA Polymerase II (RNAP II), whose activity therefore needs to be tightly controlled. An important and only partially understood level of regulation is the multiple phosphorylations of RNAP II large subunit C-terminal domain (CTD). Sequential phosphorylations regulate transcription initiation and elongation, and recruit factors involved in co-transcriptional processing of mRNA. Based largely on studies in yeast models and in vitro, the kinase activity responsible for the phosphorylation of the serine-5 (Ser5) residues of RNAP II CTD has been attributed to the Mat1/Cdk7/CycH trimer as part of Transcription Factor IIH. However, due to the lack of good mammalian genetic models, the roles of both RNAP II Ser5 phosphorylation as well as TFIIH kinase in transcription have provided ambiguous results and the in vivo kinase of Ser5 has remained elusive. The primary objective of this study was to elucidate the role of mammalian TFIIH, and specifically the Mat1 subunit in CTD phosphorylation and general RNAP II-mediated transcription. The approach utilized the Cre-LoxP system to conditionally delete murine Mat1 in cardiomyocytes and hepatocytes in vivo and and in cell culture models. The results identify the TFIIH kinase as the major mammalian Ser5 kinase and demonstrate its requirement for general transcription, noted by the use of nascent mRNA labeling. Also a role for Mat1 in regulating general mRNA turnover was identified, providing a possible rationale for earlier negative findings. A secondary objective was to identify potential gene- and tissue-specific roles of Mat1 and the TFIIH kinase through the use of tissue-specific Mat1 deletion. Mat1 was found to be required for the transcriptional function of PGC-1 in cardiomyocytes. Transriptional activation of lipogenic SREBP1 target genes following Mat1 deletion in hepatocytes revealed a repressive role for Mat1apparently mediated via co-repressor DMAP1 and the DNA methyltransferase Dnmt1. Finally, Mat1 and Cdk7 were also identified as a negative regulators of adipocyte differentiation through the inhibitory phosphorylation of Peroxisome proliferator-activated receptor (PPAR) γ. Together, these results demonstrate gene- and tissue-specific roles for the Mat1 subunit of TFIIH and open up new therapeutic possibilities in the treatment of diseases such as type II diabetes, hepatosteatosis and obesity.

Simulation and graph mining tools for improving gene mapping efficiency

Gene mapping is a systematic search for genes that affect observable characteristics of an organism. In this thesis we offer computational tools to improve the efficiency of (disease) gene-mapping efforts. In the first part of the thesis we propose an efficient simulation procedure for generating realistic genetical data from isolated populations. Simulated data is useful for evaluating hypothesised gene-mapping study designs and computational analysis tools. As an example of such evaluation, we demonstrate how a population-based study design can be a powerful alternative to traditional family-based designs in association-based gene-mapping projects. In the second part of the thesis we consider a prioritisation of a (typically large) set of putative disease-associated genes acquired from an initial gene-mapping analysis. Prioritisation is necessary to be able to focus on the most promising candidates. We show how to harness the current biomedical knowledge for the prioritisation task by integrating various publicly available biological databases into a weighted biological graph. We then demonstrate how to find and evaluate connections between entities, such as genes and diseases, from this unified schema by graph mining techniques. Finally, in the last part of the thesis, we define the concept of reliable subgraph and the corresponding subgraph extraction problem. Reliable subgraphs concisely describe strong and independent connections between two given vertices in a random graph, and hence they are especially useful for visualising such connections. We propose novel algorithms for extracting reliable subgraphs from large random graphs. The efficiency and scalability of the proposed graph mining methods are backed by extensive experiments on real data. While our application focus is in genetics, the concepts and algorithms can be applied to other domains as well. We demonstrate this generality by considering coauthor graphs in addition to biological graphs in the experiments.

Development of tissue culture and virus-induced gene silencing for Calendula officinalis

Calendula officinalis is grown widely as an ornamental plant across Europe. It belongs to the large. Asteraceae family. In this study, the aim was to explore the possibilities to use Calendula officinalis as a new model organism for flower development and secondary mechanism studies in Asteraceae. Tissue culture of Calendula officinalis was established using nine different cultivars. Murashige & Skoog (MS) medium with four different combinations of plant growth regulators were tested. Of all these combinations, the medium containing 1mg/l BAP, 0.1 mg/l IAA, and 1mg/l Zeatin achieved highest frequency of adventitious shoot regeneration from hypocotyl and cotyledon explants. Virus-induced gene silencing is a recent developed genetic tool for charactering the gene functions in plants, and extends the range of host plants that are not accessible for Agrobacterium transformation. Here, tobacco rattle virus (TRV)-based VIGS technique was tested in calendula (cv. Single Orange). We used TRV carrying Gerbera hybrid phytoene desaturase (PDS) gene fragment to induce PDS silencing in calendula. Vacuum infiltration and syringe infiltration methods both resulted in photo-bleaching phenotypes in leaves, bracts and petals. Loss-of-function phenotypes occurred on calendula 13 days post-infiltration. In conclusion, the data indicates that calendula explants can be regenerated through tissue culture which is a prerequisite for development of stable transformation methods. However, further optimization is still needed to improve the frequency. In addition, VIGS was applied to silence PDS marker gene expression indicating that this method has potential for gene functional studies in future.