Asymmetrical flow field-flow fractionation in the study of water-soluble macromolecules

Asymmetrical flow field-flow fractionation (AsFlFFF) was constructed, and its applicability to industrial, biochemical, and pharmaceutical applications was studied. The effect of several parameters, such as pH, ionic strength, temperature and the reactants mixing ratios on the particle sizes, molar masses, and the formation of aggregates of macromolecules was determined by AsFlFFF. In the case of industrial application AsFlFFF proved to be a valuable tool in the characterization of the hydrodynamic particle sizes, molar masses and phase transition behavior of various poly(N-isopropylacrylamide) (PNIPAM) polymers as a function of viscosity and phase transition temperatures. The effect of sodium chloride salt and the molar ratio of cationic and anionic polyelectrolytes on the hydrodynamic particle sizes of poly (methacryloxyethyl trimethylammonium chloride) and poly (ethylene oxide)-block-poly (sodium methacrylate) and their complexes were studied. The particle sizes of PNIPAM polymers, and polyelectrolyte complexes measured by AsFlFFF were in agreement with those obtained by dynamic light scattering. The molar masses of PNIPAM polymers obtained by AsFlFFF and size exclusion chromatography agreed also well. In addition, AsFlFFF proved to be a practical technique in thermo responsive behavior studies of polymers at temperatures up to about 50 oC. The suitability of AsFlFFF for biological, biomedical, and pharmaceutical applications was proved, upon studying the lipid-protein/peptide interactions, and the stability of liposomes at different temperatures. AsFlFFF was applied to the studies on the hydrophobic and electrostatic interactions between cytochrome c (a basic peripheral protein) and anionic lipid, and oleic acid, and sodium dodecyl sulphate surfactant. A miniaturized AsFlFFF constructed in this study was exploited in the elucidation of the effect of copper (II), pH, ionic strength, and vortexing on the particle sizes of low-density lipoproteins.

Weakening of the Gram-negative bacterial outer membrane - A tool for increasing microbiological safety

Gram-negative bacteria are harmful in various surroundings. In the food industy their metabolites are potential cause of spoilage and this group also includes many severe or potential pathogens, such as Salmonella. Due to their ability to produce biofilms Gram-negative bacteria also cause problems in many industrial processes as well as in clinical surroundings. Control of Gram-negative bacteria is hampered by the outer membrane (OM) in the outermost layer of the cells. This layer is an intrinsic barrier for many hydrophobic agents and macromolecules. Permeabilizers are compounds that weaken OM and can thus increase the activity of antimicrobials by facililating entry of hydrophobic compounds and macromolecules into the cell where they can reach their target sites and inhibit or destroy cellular functions. The work described in this thesis shows that lactic acid acts as a permeabilizer and destabilizes the OM of Gram-negative bacteria. In addition, organic acids present in berriers, i.e. malic, sorbic and benzoic acid, were shown to weaken the OM of Gram-negative bacteria. Organic acids can poteniate the antimicrobial activity of other compounds. Microbial colonic degradation products of plant-derived phenolic compounds (3,4-dihydroxyphenylacetic acid, 3-hydroxyphenylacetic acid, 3,4-dihydroxyphenylpropionic acid, 4-hydroxyphenylpropionic acid, 3-phenylpropionic acid and 3-hydroxyphenylpropionic acid) efficiently destabilized OM of Salmonella. The studies increase our understanding of the mechanism of action of the classical chelator, ethylenediaminetetra-acetic acid (EDTA). In addition, the results indicate that the biocidic activity of benzalkonium chloride against Pseudomonas can be increased by combined use with polyethylenimine (PEI). In addition to PEI, several other potential permeabilizers, such as succimer, were shown to destabilize the OM of Gram-negative bacteria. Furthermore, combination of the results obtained from various permeability assays (e.g. uptake of a hydrophobic probe, sensitization to hydrophobic antibiotics and detergents, release of lipopolysaccharide (LPS) and LPS-specific fatty acids) with atomic force microscopy (AFM) image results increases our knowledge of the action of permeabilizers.

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.

Structural characteristics affecting functions of two actin regulating proteins

Structural biology is a branch of science that concentrates on the relationship between the structure and function of biological macromolecules. The prevalence of a large number of three dimensional structures offers effective tools for bio-scientists to understand the living world. Actin is the most abundant cellular protein and one of its main functions is to produce movement in living cells. Actin forms filaments that are dynamic and which are regulated by a number of different proteins. A class of these regulatory proteins contains actin depolymerizing factor homology (ADF-H) domains. These directly interact with actin through their ADF-H domains. Although ADF-H domains possess very similar three dimensional structures to one another, they vary in their functional properties. One example of this is the ability to bind to actin monomers or filaments. During the work for this thesis two structures of ADF-H domains were solved by nuclear magnetic resonance spectroscopy (NMR). The elucidated structures help us understand the binding specificities of the ADF-H family members.

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.

Lymphatic vessels in health and disease: Role of the VEGF-C/VEGFR-3 pathway and the transcription factor FOXC2

The circulatory system consists of two vessel types, which act in concert but significantly differ from each other in several structural and functional aspects as well as in mechanisms governing their development. The blood vasculature transports oxygen, nutrients and cells to tissues whereas the lymphatic vessels collect extravasated fluid, macromolecules and cells of the immune system and return them back to the blood circulation. Understanding the molecular mechanisms behind the developmental and functional regulation of the lymphatic system long lagged behind that of the blood vasculature. Identification of several markers specific for the lymphatic endothelium, and the discovery of key factors controlling the development and function of the lymphatic vessels have greatly facilitated research in lymphatic biology over the past few years. Recognition of the crucial importance of lymphatic vessels in certain pathological conditions, most importantly in tumor metastasis, lymphedema and inflammation, has increased interest in this vessel type, for so long overshadowed by its blood vascular cousin. VEGF-C (Vascular Endothelial Growth Factor C) and its receptor VEGFR-3 are essential for the development and maintenance of embryonic lymphatic vasculature. Furthermore, VEGF-C has been shown to be upregulated in many tumors and its expression found to positively correlate with lymphatic metastasis. Mutations in the transcription factor FOXC2 result in lymphedema-distichiasis (LD), which suggests a role for FOXC2 in the regulation of lymphatic development or function. This study was undertaken to obtain more information about the role of the VEGF-C/VEGFR-3 pathway and FOXC2 in regulating lymphatic development, growth, function and survival in physiological as well as in pathological conditions. We found that the silk-like carboxyterminal propeptide is not necessary for the lymphangiogenic activity of VEGF-C, but enhances it, and that the aminoterminal propeptide mediates binding of VEGF-C to the neuropilin-2 coreceptor, which we suggest to be involved in VEGF-C signalling via VEGFR-3. Furthermore, we found that overexpression of VEGF-C increases tumor lymphangiogenesis and intralymphatic tumor growth, both of which could be inhibited by a soluble form of VEGFR-3. These results suggest that blocking VEGFR-3 signalling could be used for prevention of lymphatic tumor metastasis. This might prove to be a safe treatment method for human cancer patients, since inhibition of VEGFR-3 activity had no effect on the normal lymphatic vasculature in adult mice, though it did lead to regression of lymphatic vessels in the postnatal period. Interestingly, in contrast to VEGF-C, which induces lymphangiogenesis already during embryonic development, we found that the related VEGF-D promotes lymphatic vessel growth only after birth. These results suggest, that the lymphatic vasculature undergoes postnatal maturation, which renders it independent of ligand induced VEGFR-3 signalling for survival but responsive to VEGF-D for growth. Finally, we show that FOXC2 is necessary for the later stages of lymphatic development by regulating the morphogenesis of lymphatic valves, as well as interactions of the lymphatic endothelium with vascular mural cells, in which it cooperates with VEGFR-3. Furthermore, our study indicates that the absence of lymphatic valves, abnormal association of lymphatic capillaries with mural cells and an increased amount of basement membrane underlie the pathogenesis of LD. These findings have given new insight into the mechanisms of normal lymphatic development, as well as into the pathogenesis of diseases involving the lymphatic vasculature. They also reveal new therapeutic targets for the prevention and treatment of tumor metastasis and lymphatic vascular failure in certain forms of lymphedema. Several interesting questions were posed that still need to be addressed. Most importantly, the mechanism of VEGF-C promoted tumor metastasis and the molecular nature of the postnatal lymphatic vessel maturation remain to be elucidated.

Nuclear Import Mechanisms of STAT and NF-kB Transcription Factors

The eukaryotic cell nucleoplasm is separated from the cytoplasm by the nuclear envelope. This compartmentation of eukaryotic cells requires that all nuclear proteins must be transported from the cytoplasm into the nucleus. Transport of macromolecules between the nucleus and the cytoplasm occurs through nuclear pore complexes (NPCs). Proteins to be targeted into the nucleus by the classical nuclear import system contain nuclear localization signals (NLSs), which are recognized by importin alpha, the NLS receptor. Importin alpha binds to importin beta, which docks the importin-cargo complex on the cytoplasmic side of the NPC and mediates the movement of the complex into the nucleus. Presently six human importin alpha isoforms have been identified. Transcription factors are among the most important regulators of gene expression in eukaryotic organisms. Transcription factors bind to specific DNA sequences on target genes and modulate the activity of the target gene. Many transcription factors, including signal transducers and activators of transcription (STAT) and nuclear factor kB (NF-kB), reside in the cytoplasm in an inactive form, and upon activation they are rapidly transported into the nucleus. In the nucleus STATs and NF-kB regulate the activity of genes whose products are critical in controlling numerous cellular and organismal processes, such as inflammatory and immune responses, cell growth, differentiation and survival. The aim of this study was to investigate the nuclear import mechanisms of STAT and NF-kB transcription factors. This work shows that STAT1 homodimers and STAT1/STAT2 heterodimers bind specifically and directly to importin alpha5 molecule via unconventional dimer-specific NLSs. Importin alpha molecules have two regions, which have been shown to directly interact with the amino acids in the NLS of the cargo molecule. The Arm repeats 2-4 comprise the N-terminal NLS binding site and Arm repeats 7-8 the C-terminal NLS binding site. In this work it is shown that the binding site for STAT1 homodimers and STAT1/STAT2 heterodimers is composed of Arm repeats 8 and 9 of importin alpha5 molecule. This work demonstrates that all NF-kB proteins are transported into the nucleus by importin alpha molecules. In addition, NLS was identified in RelB protein. The interactions between NF-kB proteins and importin alpha molecules were found to be directly mediated by the NLSs of NF-kB proteins. Moreover, we found that p50 binds to the N-terminal and p65 to the C-terminal NLS binding site of importin alpha3. The results from this thesis work identify previously uncharacterized mechanisms in nuclear import of STAT and NF-kB. These findings provide new insights into the molecular mechanisms regulating the signalling cascades of these important transcription factors from the cytoplasm into the nucleus to the target genes.

Structure and Dynamics of Coil-like Molecules by Residual Dipolar Couplings

Nuclear magnetic resonance (NMR) spectroscopy provides us with many means to study biological macromolecules in solution. Proteins in particular are the most intriguing targets for NMR studies. Protein functions are usually ascribed to specific three-dimensional structures but more recently tails, long loops and non-structural polypeptides have also been shown to be biologically active. Examples include prions, -synuclein, amylin and the NEF HIV-protein. However, conformational preferences in coil-like molecules are difficult to study by traditional methods. Residual dipolar couplings (RDCs) have opened up new opportunities; however their analysis is not trivial. Here we show how to interpret RDCs from these weakly structured molecules. The most notable residual dipolar couplings arise from steric obstruction effects. In dilute liquid crystalline media as well as in anisotropic gels polypeptides encounter nematogens. The shape of a polypeptide conformation limits the encounter with the nematogen. The most elongated conformations may come closest whereas the most compact remain furthest away. As a result there is slightly more room in the solution for the extended than for the compact conformations. This conformation-dependent concentration effect leads to a bias in the measured data. The measured values are not arithmetic averages but essentially weighted averages over conformations. The overall effect can be calculated for random flight chains and simulated for more realistic molecular models. Earlier there was an implicit thought that weakly structured or non-structural molecules would not yield to any observable residual dipolar couplings. However, in the pioneering study by Shortle and Ackerman RDCs were clearly observed. We repeated the study for urea-denatured protein at high temperature and also observed indisputably RDCs. This was very convincing to us but we could not possibly accept the proposed reason for the non-zero RDCs, namely that there would be some residual structure left in the protein that to our understanding was fully denatured. We proceeded to gain understanding via simulations and elementary experiments. In measurements we used simple homopolymers with only two labelled residues and we simulated the data to learn more about the origin of RDCs. We realized that RDCs depend on the position of the residue as well as on the length of the polypeptide. Investigations resulted in a theoretical model for RDCs from coil-like molecules. Later we extended the studies by molecular dynamics. Somewhat surprisingly the effects are small for non-structured molecules whereas the bias may be large for a small compact protein. All in all the work gave clear and unambiguous results on how to interpret RDCs as structural and dynamic parameters of weakly structured proteins.

Characterisation of cellulose- and lignin-based materials using x-ray scattering methods

Wood is an important material for the construction and pulping industries. Using x-ray diffraction the microfibril angle of Sitka spruce wood was studied in the first part of this thesis. Sitka spruce (Picea sitchensis [Bong.] Carr.) is native to the west coast of North America, but due to its fast growth rate, it has also been imported to Europe. So far, its nanometre scale properties have not been systematically characterised. In this thesis the microfibril angle of Sitka spruce was shown to depend significantly on the origin of the tree in the first annual rings near the pith. Wood can be further processed to separate lignin from cellulose and hemicelluloses. Solid cellulose can act as a reducer for metal ions and it is also a porous support for nanoparticles. By chemically reducing nickel or copper in the solid cellulose support it is possible to get small nanoparticles on the surfaces of the cellulose fibres. Cellulose supported metal nanoparticles can potentially be used as environmentally friendly catalysts in organic chemistry reactions. In this thesis the size of the nickel and copper containing nanoparticles were studied using anomalous small-angle x-ray scattering and wide-angle x-ray scattering. The anomalous small-angle x-ray scattering experiments showed that the crystallite size of the copper oxide nanoparticles was the same as the size of the nanoparticles, so the nanoparticles were single crystals. The nickel containing nanoparticles were amorphous, but crystallised upon heating. The size of the nanoparticles was observed to be smaller when the reduction of nickel was done in aqueous ammonium hydrate medium compared to reduction made in aqueous solution. Lignin is typically seen as the side-product of wood industries. Lignin is the second most abundant natural polymer on Earth, and it possesses potential to be a useful material for many purposes in addition to being an energy source for the pulp mills. In this thesis, the morphology of several lignins, which were produced by different separation methods from wood, was studied using small-angle and ultra small-angle x-ray scattering. It was shown that the fractal model previously proposed for the lignin structure does not apply to most of the extracted lignin types. The only lignin to which the fractal model could be applied was kraft lignin. In aqueous solutions the average shape of the low molar mass kraft lignin particles was observed to be elongated and flat. The average shape does not necessarily correspond to the shape of the individual particles because of the polydispersity of the fraction and due to selfassociation of the particles. Lignins, and especially lignosulfonate, have many uses as dispersants, binders and emulsion stabilisers. In this thesis work the selfassociation of low molar mass lignosulfonate macromolecules was observed using small-angle x-ray scattering. By taking into account the polydispersity of the studied lignosulfonate fraction, the shape of the lignosulfonate particles was determined to be flat by fitting an oblate ellipsoidal model to the scattering intensity.