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.

Water stress induced alterations in ornithine aminotransferase of ragi (Eleusine coracana): Protection by proline against heat inactivation and denaturation by urea and guanidinium chloride

Water stress resulted in a specific response leading to a large and significant increase (80-fold) in free proline content of ragi (Eleusine coracana) leaves and seedlings. L-Proline protected ornithine aminotransferase, an enzyme in the pathway for proline biosynthesis, isolated from normal and stressed ragi leaves against heat inactivation and denaturation by urea and guanidinium chloride. The protection of the stressed enzyme by L-proline was much more complete than that of the enzyme isolated from normal leaves. While L-ornithine, one of the substrates, protected the stressed enzyme against inactivation, it enhanced the rate of inactivation of the normal enzyme. α-Ketoglutarate protected both the normal and stressed enzyme against inactivation and denaturation. These results support the suggestion that ornithine aminotransferase has undergone a structural alteration during water stress. In view of the causal relationship between elevated temperature and water stress of plants under natural conditions, the protection afforded by proline against inactivation and denaturation of the enzyme from stressed leaves assumes significance. These results provide an explanation for a possible functional importance of proline accumulation during water stress.

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.

The use of metabolomics to monitor simultaneous changes in metabolic variables following supramaximal low volume high intensity exercise

High Intensity Exercise (HIE) stimulates greater physiological remodeling when compared to workload matched low-moderate intensity exercise. This study utilized an untargeted metabolomics approach to examine the metabolic perturbations that occur following two workload matched supramaximal low volume HIE trials. In a randomized order, 7 untrained males completed two exercise protocols separated by one week; 1) HIE150%: 30 x 20s cycling at 150% VO2peak, 40s passive rest; 2) HIE300%: 30 x 10s cycling at 300% VO2peak, 50 s passive rest. Total exercise duration was 30 minutes for both trials. Blood samples were taken at rest, during and immediately following exercise and at 60 minutes post exercise. Gas chromatography-mass spectrometry (GC-MS) analysis of plasma identified 43 known metabolites of which 3 demonstrated significant fold changes (HIE300% compared to the HIE150% value) during exercise, 14 post exercise and 23 at the end of the recovery period. Significant changes in plasma metabolites relating to lipid metabolism [fatty acids: dodecanoate (p=0.042), hexadecanoate (p=0.001), octadecanoate (p=0.001)], total cholesterol (p=0.001), and glycolysis [lactate (p=0.018)] were observed following exercise and during the recovery period. The HIE300% protocol elicited greater metabolic changes relating to lipid metabolism and glycolysis when compared to HIE150% protocol. These changes were more pronounced throughout the recovery period rather than during the exercise bout itself. Data from the current study demonstrate the use of metabolomics to monitor intensity-dependent changes in multiple metabolic pathways following exercise. The small sample size indicates a need for further studies in a larger sample cohort to validate these findings.

Metabolic fate of menthofuran in rats. Novel oxidative pathways

Metabolic fate of menthofuran (II) in rats was investigated. Menthofuran (II) was administered orally (200 mg/kg of the body weight/day) to rats for 3 days. The following metabolites were isolated from the urine of these animals: p-cresol (VI), 5-methyl-2-cyclohexen-1- one (VII), 3-methylcyclohexanone (VIII), 3-methylcyclohexanol (IX), 4- hydroxy-4-methyl-2-cyclohexen-1-one (V), geranic acid (XI), neronic acid (XII), benzoic acid (XIII), and 2-[2'-keto-4'- methylcyclohexyl]propionic acid (X). Incubation of menthofuran (II) with phenobarbital-induced rat liver microsomes in the presence of NADPH and oxygen resulted in the formation of a metabolite tentatively identified as 2-Z-(2'-keto-4'-methylcyclohexylidene)propanal (III; alpha,beta-unsaturated-gamma-keto-aldehyde). The structure assigned was further supported by trapping this metabolite (III) as a cinnoline derivative. Phenobarbital-induced rat liver microsomes also converted 4- methyl-2-cyclohexenone (IV) to 4-hydroxy-4-methyl-2-cyclohexenone (V) and p-cresol (VI) in the presence of NADPH and oxygen. On the basis of both in vivo and in vitro studies, a possible mechanism for the formation of p-cresol from menthofuran has been proposed.

Flight metabolic rate in the Glanville fritillary butterfly

Dispersal is a highly important life history trait. In fragmented landscapes the long-term persistence of populations depends on dispersal. Evolution of dispersal is affected by costs and benefits and these may differ between different landscapes. This results in differences in the strength and direction of natural selection on dispersal in fragmented landscapes. Dispersal has been shown to be a nonrandom process that is associated with traits such as flight ability in insects. This thesis examines genetic and physiological traits affecting dispersal in the Glanville fritillary butterfly (Melitaea cinxia). Flight metabolic rate is a repeatable trait representing flight ability. Unlike in many vertebrates, resting metabolic rate cannot be used as a surrogate of maximum metabolic rate as no strong correlation between the two was found in the Glanville fritillary. Resting and flight metabolic rate are affected by environmental variables, most notably temperature. However, only flight metabolic rate has a strong genetic component. Molecular variation in the much-studied candidate locus phosphoglucose isomerase (Pgi), which encodes the glycolytic enzyme PGI, has an effect on carbohydrate metabolism in flight. This effect is temperature dependent: in low to moderate temperatures individuals with the heterozygous genotype at the single nucleotide polymorphism (SNP) AA111 have higher flight metabolic rate than the common homozygous genotype. At high temperatures the situation is reversed. This finding suggests that variation in enzyme properties is indeed translated to organismal performance. High-resolution data on individual female Glanville fritillaries moving freely in the field were recorded using harmonic radar. There was a strong positive correlation between flight metabolic rate and dispersal rate. Flight metabolic rate explained one third of the observed variation in the one-hour movement distance. A fine-scaled analysis of mobility showed that mobility peaked at intermediate ambient temperatures but the two common Pgi genotypes differed in their reaction norms to temperature. As with flight metabolic rate, heterozygotes at SNP AA111 were the most active genotype in low to moderate temperatures. The results show that molecular variation is associated with variation in dispersal rate through the link of flight physiology under the influence of environmental conditions. The evolutionary pressures for dispersal differ between males and females. The effect of flight metabolic rate on dispersal was examined in both sexes in field and laboratory conditions. The relationship between flight metabolic rate and dispersal rate in the field and flight duration in the laboratory were found to differ between the two sexes. In females the relationship was positive, but in males the longest distances and flight durations were recorded for individuals with low flight metabolic rate. These findings may reflect male investment in mate locating. Instead of dispersing, males with high flight metabolic rate may establish territories and follow a perching strategy when locating females and hence move less on the landscape level. Males with low metabolic rate may be forced to disperse due to low competitive success or may show adaptations to an alternative strategy: patrolling. In the light of life history trade-offs and the rate of living theory having high metabolic rate may carry a cost in the form of shortened lifespan. Experiments relating flight metabolic rate to longevity showed a clear correlation in the opposite direction: high flight metabolic rate was associated with long lifespan. This suggests that individuals with high metabolic rate do not pay an extra physiological cost for their high flight capacity, rather there are positive correlations between different measures of fitness. These results highlight the importance of condition.

Mutations as molecular tools : The metabolic-rate dependent molecular clock and DNA barcoding of allied species

Mutation and recombination are the fundamental processes leading to genetic variation in natural populations. This variation forms the raw material for evolution through natural selection and drift. Therefore, studying mutation rates may reveal information about evolutionary histories as well as phylogenetic interrelationships of organisms. In this thesis two molecular tools, DNA barcoding and the molecular clock were examined. In the first part, the efficiency of mutations to delineate closely related species was tested and the implications for conservation practices were assessed. The second part investigated the proposition that a constant mutation rate exists within invertebrates, in form of a metabolic-rate dependent molecular clock, which can be applied to accurately date speciation events. DNA barcoding aspires to be an efficient technique to not only distinguish between species but also reveal population-level variation solely relying on mutations found on a short stretch of a single gene. In this thesis barcoding was applied to discriminate between Hylochares populations from Russian Karelia and new Hylochares findings from the greater Helsinki region in Finland. Although barcoding failed to delineate the two reproductively isolated groups, their distinct morphological features and differing life-history traits led to their classification as two closely related, although separate species. The lack of genetic differentiation appears to be due to a recent divergence event not yet reflected in the beetles molecular make-up. Thus, the Russian Hylochares was described as a new species. The Finnish species, previously considered as locally extinct, was recognized as endangered. Even if, due to their identical genetic make-up, the populations had been regarded as conspecific, conservation strategies based on prior knowledge from Russia would not have guaranteed the survival of the Finnish beetle. Therefore, new conservation actions based on detailed studies of the biology and life-history of the Finnish Hylochares were conducted to protect this endemic rarity in Finland. The idea behind the strict molecular clock is that mutation rates are constant over evolutionary time and may thus be used to infer species divergence dates. However, one of the most recent theories argues that a strict clock does not tick per unit of time but that it has a constant substitution rate per unit of mass-specific metabolic energy. Therefore, according to this hypothesis, molecular clocks have to be recalibrated taking body size and temperature into account. This thesis tested the temperature effect on mutation rates in equally sized invertebrates. For the first dataset (family Eucnemidae, Coleoptera) the phylogenetic interrelationships and evolutionary history of the genus Arrhipis had to be inferred before the influence of temperature on substitution rates could be studied. Further, a second, larger invertebrate dataset (family Syrphidae, Diptera) was employed. Several methodological approaches, a number of genes and multiple molecular clock models revealed that there was no consistent relationship between temperature and mutation rate for the taxa under study. Thus, the body size effect, observed in vertebrates but controversial for invertebrates, rather than temperature may be the underlying driving force behind the metabolic-rate dependent molecular clock. Therefore, the metabolic-rate dependent molecular clock does not hold for the here studied invertebrate groups. This thesis emphasizes that molecular techniques relying on mutation rates have to be applied with caution. Whereas they may work satisfactorily under certain conditions for specific taxa, they may fail for others. The molecular clock as well as DNA barcoding should incorporate all the information and data available to obtain comprehensive estimations of the existing biodiversity and its evolutionary history.

Liver fat in the metabolic syndrome and type 2 diabetes

Introduction: The epidemic of obesity has been accompanied by an increase in the prevalence of the metabolic syndrome, type 2 diabetes, and non-alcoholic fatty liver disease (NAFLD). However, not all obese subjects develop these metabolic abnormalities. Hepatic fat accumulation is related to hepatic insulin resistance, which in turn leads to hyperglycemia, hypertriglyceridemia, and a low HDL cholesterol con-centration. The present studies aimed to investigate 1) how intrahepatic as compared to intramyocellular fat is related to insulin resistance in these tissues and to the metabolic syndrome (Study I); 2) the amount of liver fat in subjects with and without the metabolic syndrome, and which clinically available markers best reflect liver fat content (Study II); 3) the effect of liver fat on insulin clearance (Study III); 4) whether type 2 diabetic patients have more liver fat than age-, gender-, and BMI-matched non-diabetic subjects (Study IV); 5) how type 2 diabetic patients using exceptionally high doses of insulin respond to addition of a PPARγ agonist (Study V). Subjects and methods: The study groups consisted of 45 (Study I), 271 (Study II), and 80 (Study III) non-diabetic subjects, and of 70 type 2 diabetic patients and 70 matched control subjects (Study IV). In Study V, a total of 14 poorly controlled type 2 diabetic patients treated with high doses of insulin were studied before and after rosiglitazone treatment (8 mg/day) for 8 months. In all studies, liver fat content was measured by proton magnetic resonance spectroscopy, and sub-cutaneous and intra-abdominal fat content by MRI. In addition, circulating markers of insulin resistance and serum liver enzyme concentrations were determined. Hepatic (i.v. insulin infusion rate 0.3 mU/kg∙min combined with [3-3H]glucose, Studies I, III, and V) and muscle (1.0 mU/kg min, Study I) insulin sensitivities were measured by the euglycemic hyperinsulinemic clamp technique. Results: Fat accumulation in the liver rather than in skeletal muscle was associated with features of insulin resistance, i.e. increased fasting serum (fS) triglycerides and decreased fS-HDL cholesterol, and with hyperinsulinemia and low adiponectin concentrations (Study I). Liver fat content was 4-fold higher in subjects with as compared to those without the metabolic syndrome, independent of age, gender, and BMI. FS-C-peptide was the best correlate of liver fat (Study II). Increased liver fat was associated with both impaired insulin clearance and hepatic insulin resistance independent of age, gender, and BMI (Study III). Type 2 diabetic patients had 80% more liver fat than age-, weight-, and gender-matched non-diabetic subjects. At any given liver fat content, S-ALT underestimated liver fat in the type 2 diabetic patients as compared to the non-diabetic subjects (Study IV). In Study V, hepatic insulin sensitivity increased and glycemic control improved significantly during rosiglitazone treatment. This was associated with lowering of liver fat (on the average by 46%) and insulin requirements (40%). Conclusions: Liver fat is increased both in the metabolic syndrome and type 2 diabetes independent of age, gender, and BMI. A fatty liver is associated with both hepatic insulin resistance and impaired insulin clearance. Rosi-glitazone may be particularly effective in type 2 diabetic patients who are poorly controlled despite using high insulin doses.

Assessment of Risk for Type 1 Diabetes in Children of Affected Families and in the General Population : Role of Immunological and Metabolic Markers

Background and aims. Type 1 diabetes (T1D), an autoimmune disease in which the insulin producing beta cells are gradually destroyed, is preceded by a prodromal phase characterized by appearance of diabetes-associated autoantibodies in circulation. Both the timing of the appearance of autoantibodies and their quality have been used in the prediction of T1D among first-degree relatives of diabetic patients (FDRs). So far, no general strategies for identifying individuals at increased disease risk in the general population have been established, although the majority of new cases originate in this population. The current work aimed at assessing the predictive role of diabetes-associated immunologic and metabolic risk factors in the general population, and comparing these factors with data obtained from studies on FDRs. Subjects and methods. Study subjects in the current work were subcohorts of participants of the Childhood Diabetes in Finland Study (DiMe; n=755), the Cardiovascular Risk in Young Finns Study (LASERI; n=3475), and the Finnish Type 1 Diabetes Prediction and Prevention Study (DIPP) Study subjects (n=7410). These children were observed for signs of beta-cell autoimmunity and progression to T1D, and the results obtained were compared between the FDRs and the general population cohorts. --- Results and conclusions. By combining HLA and autoantibody screening, T1D risks similar to those reported for autoantibody-positive FDRs are observed in the pediatric general population. Progression rate to T1D is high in genetically susceptible children with persistent multipositivity. Measurement of IAA affinity failed in stratifying the risk assessment in young IAA-positive children with HLA-conferred disease susceptibility, among whom affinity of IAA did not increase during the prediabetic period. Young age at seroconversion, increased weight-for-height, decreased early insulin response, and increased IAA and IA-2A levels predict T1D in young children with genetic disease susceptibility and signs of advanced beta-cell autoimmunity. Since the incidence of T1D continues to increase, efforts aimed at preventing T1D are important, and reliable disease prediction is needed both for intervention trials and for effective and safe preventive therapies in the future. Our observations confirmed that combined HLA-based screening and regular autoantibody measurements reveal similar disease risks in pediatric general population as those seen in prediabetic FDRs, and that risk assessment can be stratified further by studying glucose metabolism of prediabetic subjects. As these screening efforts are feasible in practice, the knowledge now obtained can be exploited while designing intervention trials aimed at secondary prevention of T1D.

Clinical application of biomarkers in prostate cancer in men with metabolic syndrome project: Prostate Specific Membrane Antigen (PSMA) Positron Emission Tomography (PET) in diagnosing localised prostate cancer

Localised prostate cancer is a heterogenous disease and a multi-modal approach is required to accurately diagnose and stage the disease. Whilst the use of magnetic resonance imaging (MRI) has become more common, small volume and multi-focal disease are oft en diffi cult to characterise. Prostate specifi c membrane antigen is a cell surface protein, which is expressed in nearly all prostate cancer cells. Its expression is signifi cantly higher in high grade prostate cancer cells. In this study, we compare multi-parametric magnetic resonance imaging and 68-Gallinium-PSMA PET with whole-mount pathology of the prostate to evaluate the applicability of multiparameteric (MP) MRI and 68Ga-PSMA PET in detecting and locating tumour foci in patients with localised prostate cancer.