Genetics of Cardiovascular Disease: A Candidate Gene Study of USF1

Cardiovascular diseases (CVD) are major contributors to morbidity and mortality worldwide. Several interacting environmental, biochemical, and genetic risk factors can increase disease susceptibility. While some of the genes involved in the etiology of CVD are known, many are yet to be discovered. During the last few decades, scientists have searched for these genes with genome-wide linkage and association methods, and with more targeted candidate gene studies. This thesis investigates variation within the upstream transcription factor 1 (USF1) gene locus in relation to CVD risk factors, atherosclerosis, and incidence and prevalence of CVD. This candidate gene was first identified in Finnish families ascertained for familial combined hyperlipidemia, a common dyslipidemia predisposing to coronary heart disease. The gene is a ubiquitously expressed transcription factor regulating expression of several genes from lipid and glucose metabolism, inflammation, and endothelial function. First, we examined association between USF1 variants and several CVD risk factors, such as lipid phenotypes, body composition measures, and metabolic syndrome, in two prospective population cohorts. Our data suggested that USF1 contributes to these CVD risk factors at the population level. Notably, the associations with quantitative measurements were mostly detected among study subjects with CVD or metabolic syndrome, suggesting complex interactions between USF1 effects and the pathophysiological state of an individual. Second, we investigated how variation at the USF1 locus contributes to atherosclerotic lesions of the coronary arteries and abdominal aorta. For this, we used two study samples of middle-aged men with detailed measurements of atherosclerosis obtained in autopsy. USF1 variation significantly associated with areas of several types of lesions, especially with calcification of the arteries. Next, we tested what effect the USF1 risk variants have on sudden cardiac death and incidence of CVD. The atherosclerosis-associated risk variant increased the risk of sudden cardiac death of the same study subjects. Furthermore, USF1 alleles associated with incidence of CVD in the Finnish population follow-up cohorts. These associations were especially prominent among women, suggesting a sex specific effect, which has also been detected in subsequent studies. Finally, as some of the low-yield DNA samples of the Finnish follow-up study cohort needed to be whole-genome amplified (WGA) prior to genotyping, we evaluated whether the produced WGA genotypes were of good quality. Although the samples giving genotype discrepancies could not be detected before genotyping with standard laboratory quality control methods, our results suggested that enhanced quality control at the time of the genotyping could identify such samples. In addition, combining two WGA reactions into one pooled DNA sample for genotyping markedly reduced the number of discrepancies and samples showing them. In conclusion, USF1 seems to have a role in the etiology of CVD. Additional studies are warranted to identify functional variants and to study interactions between USF1 and other genetic or environmental factors. This USF1 study, and other studies with low DNA yield of some samples, can benefit from whole genome amplification of the low-yield samples prior to genotyping. Careful quality control procedures are, however, needed in WGA genotyping.

Molecular Interactions Underlying Neuronal Ceroid Lipofuscinoses CLN1 and CLN5

Disorders resulting from degenerative changes in the nervous system are progressive and incurable. Both environmental and inherited factors affect neuron function, and neurodegenerative diseases are often the sum of both factors. The cellular events leading to neuronal death are still mostly unknown. Monogenic diseases can offer a model for studying the mechanisms of neurodegeneration. Neuronal ceroid lipofuscinoses, or NCLs, are a group of monogenic, recessively inherited diseases affecting mostly children. NCLs cause severe and specific loss of neurons in the central nervous system, resulting in the deterioration of motor and mental skills and leading to premature death. In this thesis, the focus has been on two forms of NCL, the infantile NCL (INCL, CLN1) and the Finnish variant of late infantile NCL (vLINCLFin, CLN5). INCL is caused by mutations in the CLN1 gene encoding for the PPT1 (palmitoyl protein thioesterase 1) enzyme. PPT1 removes a palmitate moiety from proteins in experimental conditions, but its substrates in vivo are not known. In the Finnish variant of late infantile NCL (vLINCLFin), the CLN5 gene is defective, but the function of the encoded CLN5 has remained unknown. The aim of this thesis was to elucidate the disease mechanisms of these two NCL diseases by focusing on the molecular interactions of the defective proteins. In this work, the first interaction partner for PPT1, the mitochondrial F1-ATP synthase, was described. This protein has been linked to HDL metabolism in addition to its well-known role in the mitochondrial energy production. The connection between PPT1 and the F1-ATP synthase was studied utilizing the INCL-disease model, the genetically modified Ppt1-deficient mice. The levels of F1-ATP synthase subunits were increased on the surface of Ppt1-deficient neurons when compared to controls. We also detected several changes in lipid metabolism both at the cellular and systemic levels in Ppt1-deficient mice when compared to controls. The interactions between different NCL proteins were also elucidated. We were able to detect novel interactions between CLN5 and other NCL proteins, and to replicate the previously reported interactions. Some of the novel interactions influenced the intracellular trafficking of the proteins. The multiple interactions between CLN5 and other NCL proteins suggest a connection between the NCL subtypes at the cellular level. The main results of this thesis elicit information about the neuronal function of PPT1. The connection between INCL and neuronal lipid metabolism introduces a new perspective to this rather poorly characterized subject. The evidence of the interactions between NCL proteins provides the basis for future research trying to untangle the NCL disease mechanisms and to develop strategies for therapies.

Interactions between transgenic trees and mycorrhizal and pathogenic fungi

The development of biotechnology techniques in plant breeding and the new commercial applications have raised public and scientific concerns about the safety of genetically modified (GM) crops and trees. To find out the feasibility of these new technologies in the breeding of commercially important Finnish hardwood species and to estimate the ecological risks of the produced transgenic plants, the experiments of this study have been conducted as a part of a larger project focusing on the risk assessment of GM-trees. Transgenic Betula pendula and Populus trees were produced via Agrobacterium mediated transformation. Stilbene synthase (STS) gene from pine (Pinus sylvestris) and chitinase gene from sugar beet (Beta vulgaris) were transferred to (hybrid) aspen and birch, respectively, to improve disease resistance against fungal pathogens. To modify lignin biosynthesis, a 4-coumarate:coenzyme A ligase (4CL) gene fragment in antisense orientation was introduced into two birch clones. In in vitro test, one transgenic aspen line expressing pine STS gene showed increased resistance to decay fungus Phellinus tremulae. In the field, chitinase transgenic birch lines were more susceptible to leaf spot (Pyrenopeziza betulicola) than the non-transgenic control clone while the resistance against birch rust (Melampsoridium betulinum) was improved. No changes in the content or composition of lignin were detected in the 4CL antisense birch lines. In order to evaluate the ecological effects of the produced GM trees on non-target organisms, an in vitro mycorrhiza experiment with Paxillus involutus and a decomposition experiment in the field were performed. The expression of a transgenic chitinase did not disturb the establishment of mycorrhizal symbiosis between birch and P. involutus in vitro. 4CL antisense transformed birch lines showed retarded root growth but were able to form normal ectomycorrhizal associations with the mycorrhizal fungus in vitro. 4CL lines also showed normal litter decomposition. Unexpected growth reductions resulting from the gene transformation were observed in chitinase transgenic and 4CL antisense birch lines. These results indicate that genetic engineering can provide a tool in increasing disease resistance in Finnish tree species. More extensive data with several ectomycorrhizal species is needed to evaluate the consequences of transgene expression on beneficial plant-fungus symbioses. The potential pleiotropic effects of the transgene should also be taken into account when considering the safety of transgenic trees.

Fatty acids, fibre, carotenoids and tocopherols in relation to glucose metabolism in subjects at high risk for type 2 diabetes : a cross-sectional analysis

Fatty acids, fibre, carotenoids and tocopherols in relation to glucose metabolism in subjects at high risk for type 2 diabetes a cross-sectional analysis Type 2 diabetes (T2D) is a heterogeneous disorder of carbohydrate, lipid and protein metabolism, resulting from genetics, environmental influences and interactions between these. The disease is characterized by insulin resistance, β-cell dysfunction, hepatic glucose overproduction and disordered fat mobilization and storage. The literature on associations between dietary factors and glucose metabolism is inconsistent. One factor behind the discrepant results may be genetic heterogeneity of study populations. Data on nutrient-gene interactions in relation to glucose metabolism are scarce. Thus, investigating high-risk populations and exploring nutrient-gene interactions are essential for improving the understanding of T2D aetiology. Ideally, this information could help to develop prevention programmes that take into account the genetic predisposition to the disease. In this study, associations between measures of glucose metabolism predicting T2D and fatty acids, antioxidative nutrients and fibre were examined in a high-risk population, i.e., in non-diabetic relatives of affected patients. Interactions between the PPARG Pro12Ala polymorphism and fatty acids on glucose metabolism were taken into consideration. This common polymorphism plays an important role in the regulation of glucose metabolism. The inverse associations observed between dietary fibre and insulin resistance are consistent with the prevailing recommendations urging increased intake of fibre to prevent T2D. Beneficial associations observed between the intake of carotenoids and glucose levels stress that a high consumption of vegetables, fruits and berries rich in carotenoids might also play a role in the prevention of T2D. Whether tocopherols have an independent association with glucose metabolism remains questionable. Observed interactions between fatty acids and glucose metabolism suggest that a high intake of palmitic acid is associated with high fasting glucose levels mainly in female Ala allele carriers. Furthermore, the PPARG Pro12Ala polymorphism may modify the metabolic response to dietary marine fat. The beneficial associations of high intake of marine n 3 fatty acids with insulin resistance and glucose levels may be restricted to carriers of the Ala allele. The findings pertain to subjects with a family history of T2D, and the cross-sectional nature of the study precludes inferences about causality. Results nevertheless show that associations of dietary factors with glucose metabolism may be modulated by the genetic makeup of an individual. Additional research is warranted to elucidate the role of probably numerous nutrient-gene interactions, some of which may be sex-specific, in the aetiology of T2D.

Capillary electrochromatography: a versatile instrumental technique for nanodomain interaction studies

This doctoral thesis describes the development of a miniaturized capillary electrochromatography (CEC) technique suitable for the study of interactions between various nanodomains of biological importance. The particular focus of the study was low-density lipoprotein (LDL) particles and their interaction with components of the extracellular matrix (ECM). LDL transports cholesterol to the tissues through the blood circulation, but when the LDL level becomes too high the particles begin to permeate and accumulate in the arteries. Through binding sites on apolipoprotein B-100 (apoB-100), LDL interacts with components of the ECM, such as proteoglycans (PGs) and collagen, in what is considered the key mechanism in the retention of lipoproteins and onset of atherosclerosis. Hydrolytic enzymes and oxidizing agents in the ECM may later successively degrade the LDL surface. Metabolic diseases such as diabetes may provoke damage of the ECM structure through the non-enzymatic reaction of glucose with collagen. In this work, fused silica capillaries of 50 micrometer i.d. were successfully coated with LDL and collagen, and steroids and apoB-100 peptide fragments were introduced as model compounds for interaction studies. The LDL coating was modified with copper sulphate or hydrolytic enzymes, and the interactions of steroids with the native and oxidized lipoproteins were studied. Lipids were also removed from the LDL particle coating leaving behind an apoB-100 surface for further studies. The development of collagen and collagen decorin coatings was helpful in the elucidation of the interactions of apoB-100 peptide fragments with the primary ECM component, collagen. Furthermore, the collagen I coating provided a good platform for glycation studies and for clarification of LDL interactions with native and modified collagen. All methods developed are inexpensive, requiring just small amounts of biomaterial. Moreover, the experimental conditions in CEC are easily modified, and the analyses can be carried out in a reasonable time frame. Other techniques were employed to support and complement the CEC studies. Scanning electron microscopy and atomic force microscopy provided crucial visual information about the native and modified coatings. Asymmetrical flow field-flow fractionation enabled size measurements of the modified lipoproteins. Finally, the CEC results were exploited to develop new sensor chips for a continuous flow quartz crystal microbalance technique, which provided complementary information about LDL ECM interactions. This thesis demonstrates the potential of CEC as a valuable and flexible technique for surface interaction studies. Further, CEC can serve as a novel microreactor for the in situ modification of LDL and collagen coatings. The coatings developed in this study provide useful platforms for a diversity of future investigations on biological nanodomains.

Use of non-specific and specific interactions in the analysis of testosterone and related compounds by capillary electromigration techniques

Determination of testosterone and related compounds in body fluids is of utmost importance in doping control and the diagnosis of many diseases. Capillary electromigration techniques are a relatively new approach for steroid research. Owing to their electrical neutrality, however, separation of steroids by capillary electromigration techniques requires the use of charged electrolyte additives that interact with the steroids either specifically or non-specifically. The analysis of testosterone and related steroids by non-specific micellar electrokinetic chromatography (MEKC) was investigated in this study. The partial filling (PF) technique was employed, being suitable for detection by both ultraviolet spectrophotometry (UV) and electrospray ionization mass spectrometry (ESI-MS). Efficient, quantitative PF-MEKC UV methods for steroid standards were developed through the use of optimized pseudostationary phases comprising surfactants and cyclodextrins. PF-MEKC UV proved to be a more sensitive, efficient and repeatable method for the steroids than PF-MEKC ESI-MS. It was discovered that in PF-MEKC analyses of electrically neutral steroids, ESI-MS interfacing sets significant limitations not only on the chemistry affecting the ionization and detection processes, but also on the separation. The new PF-MEKC UV method was successfully employed in the determination of testosterone in male urine samples after microscale immunoaffinity solid-phase extraction (IA-SPE). The IA-SPE method, relying on specific interactions between testosterone and a recombinant anti-testosterone Fab fragment, is the first such method described for testosterone. Finally, new data for interactions between steroids and human and bovine serum albumins were obtained through the use of affinity capillary electrophoresis. A new algorithm for the calculation of association constants between proteins and neutral ligands is introduced.

Molecular Interactions Chlorin Assemblies and NMR Separations

Photosynthesis is a chemical process in which the energy of the light quanta is transformed into chemical energy. Chlorophyll (Chl) molecules play a key role in photosynthesis; they function in the antennae systems and in the photosynthetic reaction center where the primary charge separation (CS) takes place. Bio-inspired mimicry of the CS is an essential unit in dye-sensitized solar cells. Aim of this study was to design and develop electron donor-acceptor (EDA) pairs from Chls and fullerenes (C60) or carbon nanotubes (CNT). The supramolecular approach was chosen, as long synthetic sequences required by the covalent approach lead to long reaction schemes and low yields. Here, a π-interaction between soluble CNTs and Chl was used in EDA construction. Also, a beta-face selective two-point bound Chl-C60 EDA was introduced. In addition, the photophysical properties of the supramolecular EDA dyads were analyzed. In organic chemistry, nuclear magnetic resonance (NMR) spectroscopy is the most vital analytical technique in use. Multi-dimensional NMR experiments have enabled a structural analysis of complex natural products and proteins. However, in mixture analysis NMR is still facing difficulties. In many cases overlapping signals can t be resolved even with the help of multi-dimensional experiments. In this work, an NMR tool based on simple host-guest chemistry between analytes and macromolecules was developed. Diffusion ordered NMR spectroscopy (DOSY) measures the mobilities of compounds in an NMR sample. In a liquid state NMR sample, each of the analytes has a characteristic diffusion coefficient, which is proportional to the size of the analyte. With normal DOSY experiment, provided that the diffusion coefficients of the analytes differ enough, individual spectra of analytes can be extracted. When similar sized analytes differ chemically, an additive can be introduced into the sample. Since macromolecules in a liquid state NMR sample can be considered practically stationary, even faint supramolecular interaction can change the diffusion coefficient of the analyte sufficiently for a successful resolution in DOSY. In this thesis, polyvinylpyrrolidone and polyethyleneglycol enhanced DOSY NMR techniques, which enable mixture analysis of similar in size but chemically differing natural products, are introduced.

Quantum Chemical Studies of Intermolecular Interactions

This thesis studies the intermolecular interactions in (i) boron-nitrogen based systems for hydrogen splitting and storage, (ii) endohedral complexes, A@C60, and (iii) aurophilic dimers. We first present an introduction of intermolecular interactions. The theoretical background is then described. The research results are summarized in the following sections. In the boron-nitrogen systems, the electrostatic interaction is found to be the leading contribution, as 'Coulomb Pays for Heitler and London' (CHL). For the endohedral complex, the intermolecular interaction is formulated by a one-center expansion of the Coulomb operator 1/rab. For the aurophilic attraction between two C2v monomers, a London-type formula was derived by fully accounting for the anisotropy and point-group symmetry of the monomers.

Intermolecular Interactions of Noble-Gas-Containing Species

The importance of intermolecular interactions to chemistry, physics, and biology is difficult to overestimate. Without intermolecular forces, condensed phase matter could not form. The simplest way to categorize different types of intermolecular interactions is to describe them using van der Waals and hydrogen bonded (H-bonded) interactions. In the H-bond, the intermolecular interaction appears between a positively charged hydrogen atom and electronegative fragments and it originates from strong electrostatic interactions. H-bonding is important when considering the properties of condensed phase water and in many biological systems including the structure of DNA and proteins. Vibrational spectroscopy is a useful tool for studying complexes and the solvation of molecules. Vibrational frequency shift has been used to characterize complex formation. In an H-bonded system A∙∙∙H-X (A and X are acceptor and donor species, respectively), the vibrational frequency of the H-X stretching vibration usually decreases from its value in free H-X (red-shift). This frequency shift has been used as evidence for H-bond formation and the magnitude of the shift has been used as an indicator of the H-bonding strength. In contrast to this normal behavior are the blue-shifting H-bonds, in which the H-X vibrational frequency increases upon complex formation. In the last decade, there has been active discussion regarding these blue-shifting H-bonds. Noble-gases have been considered inert due to their limited reactivity with other elements. In the early 1930 s, Pauling predicted the stable noble-gas compounds XeF6 and KrF6. It was not until three decades later Neil Bartlett synthesized the first noble-gas compound, XePtF6, in 1962. A renaissance of noble-gas chemistry began in 1995 with the discovery of noble-gas hydride molecules at the University of Helsinki. The first hydrides were HXeCl, HXeBr, HXeI, HKrCl, and HXeH. These molecules have the general formula of HNgY, where H is a hydrogen atom, Ng is a noble-gas atom (Ar, Kr, or Xe), and Y is an electronegative fragment. At present, this class of molecules comprises 23 members including both inorganic and organic compounds. The first and only argon-containing neutral chemical compound HArF was synthesized in 2000 and its properties have since been investigated in a number of studies. A helium-containing chemical compound, HHeF, was predicted computationally, but its lifetime has been predicted to be severely limited by hydrogen tunneling. Helium and neon are the only elements in the periodic table that do not form neutral, ground state molecules. A noble-gas matrix is a useful medium in which to study unstable and reactive species including ions. A solvated proton forms a centrosymmetric NgHNg+ (Ng = Ar, Kr, and Xe) structure in a noble-gas matrix and this is probably the simplest example of a solvated proton. Interestingly, the hypothetical NeHNe+ cation is isoelectronic with the water-solvated proton H5O2+ (Zundel-ion). In addition to the NgHNg+ cations, the isoelectronic YHY- (Y = halogen atom or pseudohalogen fragment) anions have been studied with the matrix-isolation technique. These species have been known to exist in alkali metal salts (YHY)-M+ (M = alkali metal e.g. K or Na) for more than 80 years. Hydrated HF forms the FHF- structure in aqueous solutions, and these ions participate in several important chemical processes. In this thesis, studies of the intermolecular interactions of HNgY molecules and centrosymmetric ions with various species are presented. The HNgY complexes show unusual spectral features, e.g. large blue-shifts of the H-Ng stretching vibration upon complexation. It is suggested that the blue-shift is a normal effect for these molecules, and that originates from the enhanced (HNg)+Y- ion-pair character upon complexation. It is also found that the HNgY molecules are energetically stabilized in the complexed form, and this effect is computationally demonstrated for the HHeF molecule. The NgHNg+ and YHY- ions also show blue-shifts in their asymmetric stretching vibration upon complexation with nitrogen. Additionally, the matrix site structure and hindered rotation (libration) of the HNgY molecules were studied. The librational motion is a much-discussed solid state phenomenon, and the HNgY molecules embedded in noble-gas matrices are good model systems to study this effect. The formation mechanisms of the HNgY molecules and the decay mechanism of NgHNg+ cations are discussed. A new electron tunneling model for the decay of NgHNg+ absorptions in noble-gas matrices is proposed. Studies of the NgHNg+∙∙∙N2 complexes support this electron tunneling mechanism.

Livelihood, land use and environment interactions in the highlands of East Africa

This study aims at improving understanding of the interactions of livelihoods and the environment focusing on both socio-economic and biodiversity implications of land use change in the context of population pressure, global and local markets, climate change, cultural and regional historical factors in the highlands of East Africa. The study is based on three components (1) two extensive livelihood surveys, one on Mt. Kilimanjaro in Tanzania and the other in the Taita Hills of Kenya, (2) a land use change study of the southern slopes of Mt. Kilimanjaro focusing on land use trends between 1960s and 1980s and 1980s and 2000 and (3) a bird diversity study focusing on the potential impacts of the future land use change on birds in the main land use types on the slopes and the adjacent plains of Mt. Kilimanjaro. In addition, information on the highlands in Embu and the adjacent lowlands in Mbeere of Kenya are added to the discussion. Some general patterns of livelihood, land use and environment interactions can be found in the three sites. However, the linkages are very complex. Various external factors at different times in history have influenced most of the major turning points. Farmers continually make small adaptations to their farming practices, but the locally conceived alternatives are too few. Farmers lack specific information and knowledge on the most suitable crops, market opportunities and the quality requirements for growing the crops for markets. Population growth emerges as the most forceful driver of land use and environmental change. The higher altitudes have become extremely crowded with population densities in some areas higher than typical urban population densities. Natural vegetation has almost totally been replaced by farmland. Decreasing farm size due to population pressure is currently threatening the viability of whole farming systems. In addition, capital-poor intensification has lead to soil fertility depletion. Agricultural expansion to the agriculturally marginal lowlands has created a new and distinct group of farmers struggling constantly with climate variability causing frequent crop failures. Extensification to the fragile drylands is the major cause of fragmentation and loss of wildlife habitat. The linkages between livelihoods, land use and the environment generally point to degradation of the environment leading to reduced environmental services and ecosystem functions. There is no indication that the system is self-regulating in this respect. Positive interventions will be needed to maintain ecosystem integrity.

Computational Methods for Reconstruction and Analysis of Genome-Scale Metabolic Networks

Metabolism is the cellular subsystem responsible for generation of energy from nutrients and production of building blocks for larger macromolecules. Computational and statistical modeling of metabolism is vital to many disciplines including bioengineering, the study of diseases, drug target identification, and understanding the evolution of metabolism. In this thesis, we propose efficient computational methods for metabolic modeling. The techniques presented are targeted particularly at the analysis of large metabolic models encompassing the whole metabolism of one or several organisms. We concentrate on three major themes of metabolic modeling: metabolic pathway analysis, metabolic reconstruction and the study of evolution of metabolism. In the first part of this thesis, we study metabolic pathway analysis. We propose a novel modeling framework called gapless modeling to study biochemically viable metabolic networks and pathways. In addition, we investigate the utilization of atom-level information on metabolism to improve the quality of pathway analyses. We describe efficient algorithms for discovering both gapless and atom-level metabolic pathways, and conduct experiments with large-scale metabolic networks. The presented gapless approach offers a compromise in terms of complexity and feasibility between the previous graph-theoretic and stoichiometric approaches to metabolic modeling. Gapless pathway analysis shows that microbial metabolic networks are not as robust to random damage as suggested by previous studies. Furthermore the amino acid biosynthesis pathways of the fungal species Trichoderma reesei discovered from atom-level data are shown to closely correspond to those of Saccharomyces cerevisiae. In the second part, we propose computational methods for metabolic reconstruction in the gapless modeling framework. We study the task of reconstructing a metabolic network that does not suffer from connectivity problems. Such problems often limit the usability of reconstructed models, and typically require a significant amount of manual postprocessing. We formulate gapless metabolic reconstruction as an optimization problem and propose an efficient divide-and-conquer strategy to solve it with real-world instances. We also describe computational techniques for solving problems stemming from ambiguities in metabolite naming. These techniques have been implemented in a web-based sofware ReMatch intended for reconstruction of models for 13C metabolic flux analysis. In the third part, we extend our scope from single to multiple metabolic networks and propose an algorithm for inferring gapless metabolic networks of ancestral species from phylogenetic data. Experimenting with 16 fungal species, we show that the method is able to generate results that are easily interpretable and that provide hypotheses about the evolution of metabolism.

Algorithms for 13C metabolic flux analysis

The metabolism of an organism consists of a network of biochemical reactions that transform small molecules, or metabolites, into others in order to produce energy and building blocks for essential macromolecules. The goal of metabolic flux analysis is to uncover the rates, or the fluxes, of those biochemical reactions. In a steady state, the sum of the fluxes that produce an internal metabolite is equal to the sum of the fluxes that consume the same molecule. Thus the steady state imposes linear balance constraints to the fluxes. In general, the balance constraints imposed by the steady state are not sufficient to uncover all the fluxes of a metabolic network. The fluxes through cycles and alternative pathways between the same source and target metabolites remain unknown. More information about the fluxes can be obtained from isotopic labelling experiments, where a cell population is fed with labelled nutrients, such as glucose that contains 13C atoms. Labels are then transferred by biochemical reactions to other metabolites. The relative abundances of different labelling patterns in internal metabolites depend on the fluxes of pathways producing them. Thus, the relative abundances of different labelling patterns contain information about the fluxes that cannot be uncovered from the balance constraints derived from the steady state. The field of research that estimates the fluxes utilizing the measured constraints to the relative abundances of different labelling patterns induced by 13C labelled nutrients is called 13C metabolic flux analysis. There exist two approaches of 13C metabolic flux analysis. In the optimization approach, a non-linear optimization task, where candidate fluxes are iteratively generated until they fit to the measured abundances of different labelling patterns, is constructed. In the direct approach, linear balance constraints given by the steady state are augmented with linear constraints derived from the abundances of different labelling patterns of metabolites. Thus, mathematically involved non-linear optimization methods that can get stuck to the local optima can be avoided. On the other hand, the direct approach may require more measurement data than the optimization approach to obtain the same flux information. Furthermore, the optimization framework can easily be applied regardless of the labelling measurement technology and with all network topologies. In this thesis we present a formal computational framework for direct 13C metabolic flux analysis. The aim of our study is to construct as many linear constraints to the fluxes from the 13C labelling measurements using only computational methods that avoid non-linear techniques and are independent from the type of measurement data, the labelling of external nutrients and the topology of the metabolic network. The presented framework is the first representative of the direct approach for 13C metabolic flux analysis that is free from restricting assumptions made about these parameters.In our framework, measurement data is first propagated from the measured metabolites to other metabolites. The propagation is facilitated by the flow analysis of metabolite fragments in the network. Then new linear constraints to the fluxes are derived from the propagated data by applying the techniques of linear algebra.Based on the results of the fragment flow analysis, we also present an experiment planning method that selects sets of metabolites whose relative abundances of different labelling patterns are most useful for 13C metabolic flux analysis. Furthermore, we give computational tools to process raw 13C labelling data produced by tandem mass spectrometry to a form suitable for 13C metabolic flux analysis.

Food intake, growth and social interactions of signal crayfish, Pacifastacus leniusculus (Dana)

The knowledge about the optimal rearing conditions, such as water temperature and quality, photoperiod and density, with the understanding of animal nutritional requirements forms the basis of economically stable aquaculture for freshwater crayfish. However, the shift from a natural environment to effective culture conditions induces several changes, not only at the population level, but also at the individual level. The social contacts between conspecifics increase with increasing animal density. The competition for limited resources (e.g. food, shelter, mates) is more severe with the presence of agonistic behaviour and may lead to unequal distribution of these. The objectives of this study were to: 1) study the distribution of a common food resource between communally reared signal crayfish (Pacifastacus leniusculus) and to assign potential feeding hierarchy on the basis of individual food intake measurements, 2) explore the possibilities of size distribution manipulations to affect population dynamics and food intake to improve growth and survival in culture and 3) study the effect of food ration and spatial distribution on food intake and to explore the effect of temperature and food ration on growth and body composition of freshwater crayfish. The feeding ranks between animals were assigned with a new method for individual food intake measurement of communally reared crayfish. This technique has a high feasibility and a great potential to be applied in crayfish aquaculture studies. In this study, signal crayfish showed high size-related variability in food consumption both among individuals within a group (inter-individual) and within individual day-to-day variation (intra-individual). Increased competition for food led to an unequal distribution of this resource and this may be a reason for large growth differences between animals. The consumption was significantly higher when reared individually in comparison with communal housing. These results suggest that communally housed crayfish form a feeding hierarchy and that the animal size is the major factor controlling the position in this hierarchy. The optimisation of the social environment ( social conditions ) was evaluated in this study as a new approach to crayfish aquaculture. The results showed that the absence of conspecifics (individual rearing vs. communal housing) affects growth rate, food intake and the proportion of injured animals, whereas size variation between animals influences the number and duration of agonistic encounters. In addition, animal size had a strong influence on the fighting success of signal crayfish reared in a social milieu with a wide size variation of conspecifics. Larger individuals initiated and won most of the competitions, which suggests size-based social hierarchy of P. leniusculus. This is further supported by the fact that the length and weight gain of smaller animals increased after size grading, maybe because of a better access to the food resource due to diminished social pressure. However, the high dominance index was not based on size under conditions of limited size variation, e.g. those characteristic of restocked natural populations and aquaculture, indicating the important role of behaviour on social hierarchy.