The plant kingdom has evolved an enormous number of chemically diverse metabolites that protect plants from biotic and abiotic stresses. The large number of metabolites in a given plant indicates... Show moreThe plant kingdom has evolved an enormous number of chemically diverse metabolites that protect plants from biotic and abiotic stresses. The large number of metabolites in a given plant indicates interactions between metabolites are very likely. The co-occurrence of plant metabolites comprise a natural background where these metabolites have to function and this is often overlooked or ignored in ecological studies. The main goal of this thesis is to understand the importance of metabolite interactions I used assays with a generalist herbivore to study the interactions between chlorogenic acid (CGA), pyrrolizidine alkaloids (PAs) and fractions from Jacobaea plants. I found that PA free bases, PA N-oxides (the oxidized form of free base) and CGA decreased thrips survival. Although PA free bases and CGA decreased thrips survival, the combination of the two toxins was less toxic than the single toxins. In contrast, the combination of PA N-oxides with CGA enhanced the toxicity against thrips in a synergistic way. Adding PAs to different plant fractions showed that metabolite interactions on thrips survival are common as in all tested combinations we found antagonistic and synergistic effects. Clearly, bioactivity of a metabolite is strongly dependent upon the co-occurrence of metabolites in the plant cell. Show less
With the ever-growing amount of image data on the web, much attention has been devoted to large scale image search. It is one of the most challenging problems in computer vision for several... Show moreWith the ever-growing amount of image data on the web, much attention has been devoted to large scale image search. It is one of the most challenging problems in computer vision for several reasons. First, it must address various appearance transformations such as changes in perspective, rotation and scale existing in the huge amount of image data. Second, it needs to minimize memory requirements and computational cost when generating image representations. Finally, it needs to construct an efficient index space and a suitable similarity measure to reduce the response time to the users. This thesis aims to provide robust image representations that are less sensitive to above mentioned appearance transformations and are suitable for large scale image retrieval. Although this thesis makes a substantial number of contributions to large scale image retrieval, we also presented additional challenges and future research based on the contributions in this thesis. Show less
The presence of a small parameter can reduce the complexity of the stability analysis of pattern solutions. This reduction manifests itself through the complex-analytic Evans function, which... Show moreThe presence of a small parameter can reduce the complexity of the stability analysis of pattern solutions. This reduction manifests itself through the complex-analytic Evans function, which vanishes on the spectrum of the linearization about the pattern. For certain 'slowly linear' prototype models it has been shown, via geometric arguments, that the Evans function factorizes in accordance with the scale separation. This leads to asymptotic control over the spectrum through simpler, lower-dimensional eigenvalue problems. Recently, the geometric factorization procedure has been generalized to homoclinic pulse solutions in slowly nonlinear reaction-di ffusion systems. In this thesis we study periodic pulse solutions in the slowly nonlinear regime. This seems a straightforward extension. However, the geometric factorization method fails and due to translational invariance there is a curve of spectrum attached to the origin, whereas for homoclinic pulses there is only a simple eigenvalue residing at 0. We develop an alternative, analytic factorization method that works for periodic structures in the slowly nonlinear setting. We derive explicit formulas for the factors of the Evans function, which yields asymptotic spectral control. Moreover, we obtain a leading-order expression for the critical spectral curve attached to origin. Together these approximation results lead to explicit stability criteria. Show less
The theoretical description of fermionic system with strong interaction is a very challenging open problem in physics. The most notable (but far from the only) experimental realization of this... Show moreThe theoretical description of fermionic system with strong interaction is a very challenging open problem in physics. The most notable (but far from the only) experimental realization of this type of systems are the cuprate superconductors which have zero electric resistivity. Even if onehas a good microscopic model for the description of these materials it is very hard to translate it to macroscopic observables which in principle can be experimentally checked. The problem is that in case of a relevant interaction one can not Taylor expand in the coupling constant in the low-energy regime in which we are most interested. On the other hand, because of the fermion sign problem Monte Carlo numerical techniques (which are succesful with bosonic models) do not work for fermions at finite density. This thesis is devoted to the applications of several methods to the research area described above. The common theme of these techniques is that they are (partly) motivated from high-energy physics: the research area which deals with particle physics, string theory etc. Show less
Unambiguous sequence variant descriptions are important in reporting the outcome of clinical diagnostic DNA tests. The standard nomenclature of the Human Genome Variation Society (HGVS)... Show moreUnambiguous sequence variant descriptions are important in reporting the outcome of clinical diagnostic DNA tests. The standard nomenclature of the Human Genome Variation Society (HGVS) describes the observed variant sequence relative to a given reference sequence. We propose an efficient algorithm for the extraction of HGVS descriptions from two DNA sequences. Our algorithm is able to compute the HGVS~descriptions of complete chromosomes or other large DNA strings in a reasonable amount of computation time and its resulting descriptions are relatively small. Additional applications include updating of gene variant database contents and reference sequence liftovers. Next, we adapted our method for the extraction of descriptions for protein sequences in particular for describing frame shifted variants. We propose an addition to the HGVS nomenclature for accommodating the (complex) frame shifted variants that can be described with our method. Finally, we applied our method to generate descriptions for Short Tandem Repeats (STRs), a form of self-similarity. We propose an alternative repeat variant that can be added to the existing HGVS nomenclature. The final chapter takes an explorative approach to classification in large cohort studies. We provide a ``cross-sectional'' investigation on this data to see the relative power of the different groups. Show less
Proteins play a crucial role in life, taking part in all vital process in the body, and are therefore used as therapeutic agents in a diverse range of biomedical applications. When... Show more Proteins play a crucial role in life, taking part in all vital process in the body, and are therefore used as therapeutic agents in a diverse range of biomedical applications. When administrated into bodily fluids, most native proteins are prone to degradation or inactivation process. The challenges of protein delivery are overcoming poor stability, low permeability toward cell membrane. Among all existing materials for protein delivery, mesoporous silica nanoparticles (MSNs) are one of the most promising intracellular nanocarriers due to its key properties: biocompatible, straightforward synthesis, and surface modification. For various biomedical applications, monodisperse MSNs with a particle size in the 50-200 nm range,3 controllable surface chemistry,4 and a large pore size (> 5 nm) are desired. This thesis presents a new method to synthesize large disc-like pore (10 ± 1 nm) containing MSNs with an elongated cuboidal-like geometry (90 × 43 nm), which effectively encapsulate and release proteins. Show less
Collaborative innovation processes in unpredictable environments are a challenge for traditional management. But new demands in a global digital society push public and corporate leadership to... Show moreCollaborative innovation processes in unpredictable environments are a challenge for traditional management. But new demands in a global digital society push public and corporate leadership to collaborate ad hoc, without predictable goals and planned working rules. In this study, an actor-network approach (ANT) is combined with critical incident technique (CIT) to elaborate dynamic network principles for a new real-time foresight (RTF). Real-time foresight replaces traditional planning and strategic management in ad hoc multi-sector collaborations. Although ANT originates from science and technologies studies, it is here applied to a management problem due to ist ability to merge voluntaristic and evolutionary managerial components and micro- and macro perspectives. The investigation is placed in an exemplary management field of high dynamics: global disaster management. From process analysis and from comparison of three dynamic innovation networks that emerged around Indian coastal villages after Tsunami 2004, five dynamic network patterns are obtained which underly successful collaborative innovation processes. These dynamic structures build the agenda for a new real-time foresight, and for an instrument to evaluate in real-time the emergence of dynamic innovation networks (DINs). Show less
In this thesis, metabolomics is used to study the role of the host-virus interaction on a metabolic level. A special emphasis is directed on the role of inflammation and oxidative stress on... Show more In this thesis, metabolomics is used to study the role of the host-virus interaction on a metabolic level. A special emphasis is directed on the role of inflammation and oxidative stress on the metabolic level, as part of the innate immune response against viral infection. We chose respiratory syncytial virus (RSV) and hepatitis B virus (HBV) as candidate viruses to metabolically study their role in acute respiratory infection and chronic hepatitis B infection. Secondly we also investigated infant metabolic and immunological consequences of in utero exposure to antiretroviral intervention and human immunodeficiency virus (HIV). Collectively, established targeted metabolomics approaches in conjunction with newly developed metabolomics methodologies and complemented with other “omics” techniques, were used to address pertinent questions related to host metabolic functioning and alterations during viral infection. In vitro RSV studies together with in vivo patient based studies relating to chronic HBV infection and in utero exposure too antiretroviral and HIV were used to address these questions. The work is divided into three research parts containing: i. the analytical methodology development work, ii. in vitro based metabolomics and iii. patient based metabolomics. Show less
In this thesis I studied the functions of the zebrafish orthologs of the human TLR5 and TLR2 genes that were shown to be responsible for recognition of bacterial flagellin and a broad spectrum... Show moreIn this thesis I studied the functions of the zebrafish orthologs of the human TLR5 and TLR2 genes that were shown to be responsible for recognition of bacterial flagellin and a broad spectrum of bacterial cell wall components, respectively. One of the focal points of this thesis is the difference at the transcriptomic level of the downstream pathway of the TLR5 and TLR2 receptors and the roles of TLR signaling in host innate immune responses to infection by Mycobacterium marinum, a close relative to Mycobacterium tuberculosis and a natural pathogen of zebrafish. The new possibilities for analysis of transcriptomes using RNA deep sequencing make it highly attractive to analyze the responses of an entire test animal model at the system biology level. Furthermore, we used genetic knockdown and knockout tools to further analyze the function of TLR5 and TLR2 and downstream signaling partners in innate immunity, infectious disease and insulin resistance. Show less
The nature of the Dark Matter is one of the biggest open questions in modern cosmology and particle physics. The work in this thesis concerns a search for the observational effects of one... Show moreThe nature of the Dark Matter is one of the biggest open questions in modern cosmology and particle physics. The work in this thesis concerns a search for the observational effects of one particular class of hypothetical Dark Matter particles, namely those that are allowed to decay. In decaying, X-ray photons are emitted and should be observable. One part of the thesis details the discovery of a potential Dark Matter decay signal in X-ray spectra of galaxies and galaxy clusters, and the subsequent efforts to identify its origin. To this end archival data and new observations are compared to the respective Dark Matter masses of the observed objects. Interpretations of the signal as an instrumental effect, or due to regular astrophysical processes are unsatisfactory. Although the Dark Matter interpretation remains plausible, definitive conclusions about the origin of the signal can not be drawn yet and will require measurements by next generation observatories. The last chapter of the thesis contains the proof-of-concept of a novel technique to search for such weak signals that combines increased statistical power with the ability to determine the physical origin of a signal, while avoiding some of the disadvantages of traditional methods. Show less
Many scientists are focussed on building models. We nearly process all information we perceive to a model. There are many techniques that enable computers to build models as well. The field... Show more Many scientists are focussed on building models. We nearly process all information we perceive to a model. There are many techniques that enable computers to build models as well. The field of research that develops such techniques is called Machine Learning. Many research is devoted to develop computer programs capable of building models (algorithms). Many of such algorithms exist, and these often consist of various options that subtly influence performance (parameters). Furthermore, there is mathematical proof that there exists no single algorithm that works well on every dataset. This complicates the task of selecting the right algorithm for a given task. The field of meta-learning aims to resolve these problems. The purpose is to determine what kind of algorithms work well on which datasets. In order to do so, we developed OpenML. This is an online database on which researches can share experimental results amongst each other, potentially scaling up the size of meta-learning studies. Having earlier experimental results freely accessible and reusable for others, it is no longer required to conduct time expensive experiments. Rather, researchers can answer such experimental questions by a simple database look-up. This thesis addresses how OpenML can be used to answer fundamental meta-learning questions. Show less
The work described in this thesis is mainly focusing on setting up and application of a quantitative activity‐based proteasome profiling method. Chapter 1 provides a general introduction on the... Show moreThe work described in this thesis is mainly focusing on setting up and application of a quantitative activity‐based proteasome profiling method. Chapter 1 provides a general introduction on the ubiquitin proteasome system (UPS) and activity‐based proteasome profiling. Chapter 2 is a literature review of some new achievements in the activity‐based protein profiling field in the recent years, focusing on application in biochemistry, molecular and cellular biology, medicinal chemistry, pathology, physiology and pharmacology research. Chapter 3 is a protocol for performing quantitative activity‐based proteasome profiling experiments. In the protocol, both high throughput fluorescent ABPP and biotinylated probe plus LC/MS approaches are described. Chapter 4 is a brief technical report about bioorthogonal chemistry in ABPP. The commonly used secondary azide group is compared with a primary azide group in proteasome ABPs performing Cu(I) catalyzed azide‐alkyne cycloaddition and Staudinger‐Bertozzi reaction under native/denatured protein conditions Chapter 5 is focusing on the application of quantitative activity‐based proteasome profiling in the prognosis of cancer therapeutics. A combination of ABPP and global proteomics is performed to elucidate the bortezomib sensitivity and resistance mechanisms in leukemia and solid tumor cells. Chapter 6 describes the characterization of the newly discovered proteasome subunit β5t by ABPP and LC/MS proteomics. The subunit is proven to be catalytically active. A hydrophilic Thr residue on the P2 position of the proteasome inhibitor improves the inhibitory efficiency of β5t, which indicates it might prefer to cleave hydrophilic peptides. Chapter 7 describes the identification of O‐GlcNAcylation modifications on the ubiquitin receptor protein hHR23B and characterization of how the sugar moiety influences the conformation and functions of the protein. Show less
Preferences have always been present in many tasks in our daily lives. Buying the right car, choosing a suitable house or even deciding on the food to eat, are trivial examples of decisions that... Show morePreferences have always been present in many tasks in our daily lives. Buying the right car, choosing a suitable house or even deciding on the food to eat, are trivial examples of decisions that reveal information, explicitly or implicitly, about our preferences. The recent trend of collecting increasing amounts of data is also true for preference data. Extracting and modeling preferences can provide us with invaluable information about the choices of groups or individuals. In areas like e-commerce, which typically deal with decisions from thousands of users, the acquisition of preferences can be a difficult task. For these reasons, artificial intelligence (in particular, machine learning) methods have been increasingly important to the discovery and automatic learning of models about preferences. In this Ph.D. project, several approaches were analyzed and proposed to deal with the LR problem. Most of which has focused on pattern mining methods. Show less
Kinases play a role in many diseases including cancer, diabetes and infection diseases. Therefore, kinases are interesting drug targets. Inhibitors for some kinases are already in use as... Show moreKinases play a role in many diseases including cancer, diabetes and infection diseases. Therefore, kinases are interesting drug targets. Inhibitors for some kinases are already in use as clinical drugs, however due to resistance and side effects, but also to target kinases related to diseases for which there is currently no treatment, research on the discovery of new classes of kinase inhibitors is imperative. To achieve this, not only new inhibitor classes need to be designed and synthesized, but also tools to profile kinases in physiological context and to determine the selectivity of inhibitors are required. The research in this thesis has focused on the development of more potent AKT1 and FLT3 kinase inhibitors and on the synthesis and application of new chemical tools for the profiling of kinases involved in various types of cancers and other diseases.In this thesis, new powerful tools and assays have been developed that unite the fields of synthetic chemistry, protein biochemistry and cell biology for the global analysis of kinase expression and function. The value of chemical profiling as a method for functional proteome analysis has been further highlighted by its application as a screen to evaluate the potency and selectivity of kinase inhibitors. Show less
Parkinson’s disease is a neurodegenerative disease characterized by the presence of abnormal deposits of aggregated proteins in the brain tissue, known as Lewy bodies. The major components of Lewy... Show moreParkinson’s disease is a neurodegenerative disease characterized by the presence of abnormal deposits of aggregated proteins in the brain tissue, known as Lewy bodies. The major components of Lewy bodies are aggregated forms of a small presynaptic protein known as α-synuclein (α-syn). In this thesis we report on the intricacies of α-syn aggregation. Using an array of biophysical techniques we were able to observe the formation of the earliest α-syn oligomeric species – relatively stable dimers and tetramers – which are more easily formed than commonly assumed. Fluorescent labelling was shown to significantly affect the morphology of α-syn aggregates, which limits the applicability of this technique. From the growth kinetics of α-syn fibrillar seeds we conclude that the elongation of fibrils proceeds by a different mechanism than primary nucleation. Further, we studied the effect of solution conditions and surface effects on the growth of the α-syn aggregates. Using total internal reflection microscopy and confocal fluorescence imaging we observed the elongation of individual fibrils in real time, showing that this process proceeds by leaps and bounds. Show less
Therapeutic proteins have become very successful in the treatment of various chronic and life-threatening diseases. However, besides their benefits, therapeutic proteins seem to have a common... Show moreTherapeutic proteins have become very successful in the treatment of various chronic and life-threatening diseases. However, besides their benefits, therapeutic proteins seem to have a common problem - the response of a patient’s immune system against the protein. This means that the immune system of the patient actively removes the drug from the body, thereby potentially decreasing or reversing the effect of the therapy. By now there is strong consensus that damaged and aggregated proteins are important risk factors. Protein aggregates are, due to their heterogeneity and often low quantity, challanging to characterize. Further, there is a large academic interest in understanding the mechanisms of aggregation and the role of non-proteinaceous particles in the process of protein aggregation and unwanted immunogenicity in order to design more effective and safe protein-based medicines. This PhD thesis supported that research effort by developing and improving analytical methodologies to detect the size, quantity and other properties of protein aggregates and particles, especially in the relevant nano- and micrometer size range. These techniques were then applied to study a so far unknown nanoparticulate impurity in pharmaceutical-grade sugars. Further, the results shown in this thesis revealed that these nanoparticulate impurities pose a threat to protein stability. Show less
The glycosylation, the reaction which forms a bond between sugar molecules (the donor and the acceptor), is the central reaction in carbohydrate chemistry. Despite tremendous advances in... Show more The glycosylation, the reaction which forms a bond between sugar molecules (the donor and the acceptor), is the central reaction in carbohydrate chemistry. Despite tremendous advances in the past decades, however, the glycosylation reaction remains relatively poorly understood. Especially the formation of 1,2-cis glycosidic linkages remains a significant challenge. This thesis describes an investigation of the influence of reactivity and selectivity of several classes of carbohydrate donors and –acceptors on the selectivity in glycosylation reactions. Special emphasis was placed on the influence of protecting groups on the donor, and nucleophilicity of the acceptor, two major factors that play a tremendous role in the outcome of a glycosylation reaction. The obtained knowledge has been applied in the synthesis of complex carbohydrate molecules, native to pathogens such as Staphylococcus aureus, of which antibiotic-resistant forms such as MRSA present significant danger in hospitals, and the parasite Schistosoma mansoni, causative agent of the neglected tropical disease schistosomiasis. The synthesis of these molecules can play a part in the development of vaccines targeted against these pathogens. Show less
The interplay between evolution and its role in diversification of Nepenthes binds the studies of this thesis. How evolutionary mechanisms and timing relate to molecular divergence and... Show more The interplay between evolution and its role in diversification of Nepenthes binds the studies of this thesis. How evolutionary mechanisms and timing relate to molecular divergence and phylogenetic signal in the genus Nepenthes were investigated. This in conjunction with distribution modeling and mapping anatomical characters – an approach that led to a broad understanding of why and how best to protect specific geographical areas for conservation of Nepenthes. All work was framed with an interdisciplinary approach, each chapter furthering exploration of the connective ties in how past evolutionary history and its impact on diversity helps us to predict future diversity. Show less
The main theme of this thesis, allosteric modulation effectuated through the sodium ion site of GPCRs, is inspired by the important role that this site appears to play in GPCR signaling. As... Show moreThe main theme of this thesis, allosteric modulation effectuated through the sodium ion site of GPCRs, is inspired by the important role that this site appears to play in GPCR signaling. As sodium ions are abundant under physiological conditions they may affect GPCR signaling considerably. Receptor activation causes a substantial rearrangement of the sodium ion site, suggesting an important role in this process. Chapter 2 reviews the current knowledge on allosteric modulation of amiloride and its derivatives binding to the sodium ion site of Class A GPCRs. Chapters 3 to 5 follow-up on the recent crystal structure of the adenosine A2A receptor with a sodium ion bound. Chapters 3 and 4 complement the crystal structure with additional results from combined biochemistry, biophysical, molecular dynamics, and mutational studies. Chapter 5 describes the synthesis of novel amiloride derivatives that bind in the sodium ion site but also protrude into the orthosteric binding site. In Chapters 3 to 5, radio-labeled ligands were used to quantify ligand binding to the receptor, and Chapter 6 describes an alternative approach towards ligand binding assays. Instead of using a radio-label, mass spectrometry was used to quantify binding of an unlabeled ligand to adenosine A1 and A2A receptors. Show less
Identifying and elucidating the functions and activation of GPCRs will provide opportunities for novel drug discovery. We confirmed that a yeast system with an extended library of G... Show more Identifying and elucidating the functions and activation of GPCRs will provide opportunities for novel drug discovery. We confirmed that a yeast system with an extended library of G proteins is very well suited for the study of GPCR activation, G protein coupling profiles, receptor-G protein binding and G protein selectivity. For example, we used a scanning mutagenesis approach of the NPxxY(x)5,6F motif and of helix 8 of the adenosine A2B receptor (A2BR), and learned among others that amino acid residues in these motifs are crucial for receptor function, since alanine mutants of these amino acid residues led to a complete loss of function. Hopefully, such findings can contribute to further drug development. We also focused on structure-kinetics relationship (SKR) studies next to the more traditional Structure-affinity relationship (SAR) studies. We found two compounds showing longer residence times than nicotinic acid, which may provide clues for further drug discovery efforts on this receptor. All in all, the variety of methods described in this thesis provided us a detailed understanding of receptor function, suggesting that novel avenues for further drug discovery on these established targets is entirely feasible. Show less
