Nicotinamide adenine dinucleotide (NAD+) is the substrate used for the introduction of the ubiquitous and highly dynamic PTM in which either one or multiple adenosine diphosphate ribose (ADPr)... Show moreNicotinamide adenine dinucleotide (NAD+) is the substrate used for the introduction of the ubiquitous and highly dynamic PTM in which either one or multiple adenosine diphosphate ribose (ADPr) moieties are covalently attached to a nucleophilic side chain of an specific amino acid in the target protein to regulate cellular pathways including adipogenesis, DNA damage repair and gene expression. A significant fraction of the nucleophilic amino acid functionalities, most recently histidine and tyrosine, have been identified as ADPr-acceptor sites. In this thesis, new methodologies have been developed to synthesize peptide fragments carrying an ADPr modification to investigate ADP-ribosylation on histidine. Show less
Diacylglycerol lipases (DAGLα and DAGLβ) are responsible for the biosynthesis of the endocannabinoid 2-arachidonoylglycerol (2-AG) in the brain and peripheral tissues. Selective DAGLβ inhibitors... Show moreDiacylglycerol lipases (DAGLα and DAGLβ) are responsible for the biosynthesis of the endocannabinoid 2-arachidonoylglycerol (2-AG) in the brain and peripheral tissues. Selective DAGLβ inhibitors have been proposed as a potential treatment for inflammatory diseases with reduced potential for central nervous system (CNS) mediated side effects, but they are currently lacking. To develop DAGLβ selective inhibitors, a fluorescent biochemical assay was optimized and applied in a high-throughput screening (HTS) for DAGLβ. During the HTS, eight hits classified into four distinct chemotypes were identified. Subsequent structure-activity relationship (SAR) studies, focusing on hit 1 and its modifications, revealed a specific group as the modification hotspot crucial for achieving selectivity towards DAGLβ. Through an extensive SAR investigation, focusing on modifying this group, the first-in-class DAGLβ selective inhibitors, LEI-130 and LEI-131, were discovered. Following their discovery, LEI-130 and LEI-131 underwent comprehensive in vitro and in situ profiling studies. These investigations confirmed that LEI-130 and LEI-131 are selective and noncompetitive inhibitors of DAGLβ, effectively reducing inflammation. Show less
The endocannabinoid receptors CB1R and CB2R are involved in a plethora of processes, and consequently are involved in many pathological conditions. Their wide distribution makes the CBRs both an... Show moreThe endocannabinoid receptors CB1R and CB2R are involved in a plethora of processes, and consequently are involved in many pathological conditions. Their wide distribution makes the CBRs both an interesting therapeutic target and hard to study. Additional chemical tools are required to study and understand the function and mechanism of CB1R and CB2R. This thesis describes the development of several such tools to improve our insight in the (pathological) roles of the receptors in order to develop novel and improved therapeutics. First evaluation of three dimensional ligand-CB2R complexes made and analysed with Cryo-EM are described. Hotspots that potentially generate selectivity between CB1R and CB2R are evaluated with point-mutations in vitro. Consequently describes the development of the first tools, two-step bifunctional probes based on LEI-121 and LEI 102, is described. As two-step probes are not compatible with every assay, the toolbox is expanded with a one-step fluorescent probe. Briefly touching upon CB1R, ligands were designed with negatively charged phosphonium groups that are potentially selective for mtCB1R. Show less
In this thesis, I focused on studying the above- and belowground interactions of J. vulgaris from a plant-soil feedback (hereafter, PSF) perspective. I investigated the temporal variation of... Show moreIn this thesis, I focused on studying the above- and belowground interactions of J. vulgaris from a plant-soil feedback (hereafter, PSF) perspective. I investigated the temporal variation of negative PSF and examined the effects of root-associated bacteria on plant performance and aboveground herbivores. Additionally, I tested the role of PSF in relation to plant population structure and the significance of soil legacy effects in natural conditions. The findings reveal that temporal dynamics in PSF are driven by changes in plant sensitivity and in the soil microbiome. Although bacteria isolated from J. vulgaris roots can negatively affect plant performance, they can also affect aboveground herbivores and other plant species. Consequently, these bacteria may not be suitable for biological control of J. vulgaris. Moreover, I discovered that soil nematodes can mediate plant-plant interactions, but often favoring J. vulgaris. In my field work, I detected soil legacy effects, but seedling recruitment spatial patterns of J. vulgaris were not soil-mediated. The insights gained from studying PSF and above- and belowground interactions have the potential to reshape traditional approaches employed in controlling invasive plants. This thesis emphasizes the importance of transitioning PSF experiments from indoor to outdoor settings considering various influencing factors simultaneously. Show less
Human vocal communication and music perception represent advanced cognitive skills, seemingly innate and universal. These faculties encompass a range of perceptual and cognitive abilities. Cross... Show moreHuman vocal communication and music perception represent advanced cognitive skills, seemingly innate and universal. These faculties encompass a range of perceptual and cognitive abilities. Cross-species research sheds light on the origins of musicality by investigating whether these traits are shared by nonhuman species. Songbirds, notably zebra finches, serve as valuable models due to their complex vocalizations and similarities to humans in auditory perception. My thesis explored zebra finches' sensitivity to spectral and temporal sound features. Chapter 2 examines the influence of song duration and spectral characteristics on song discrimination, while Chapter 3 tests song preferences. Chapter 4 investigates sequential and spectral feature recognition. Chapter 5 focuses on melody recognition. Zebra finches demonstrate perceptual flexibility, adapting focus based on stimulus characteristics. These findings underscore the importance of training conditions and stimulus nature in shaping auditory perception. Overall, my thesis enhances understanding of auditory cognition and cognitive flexibility among songbirds. Show less
This thesis introduces the concept of "physics-based inverse design", working on the notion that the physical driving forces governing functionality are inherently encoded in independently... Show moreThis thesis introduces the concept of "physics-based inverse design", working on the notion that the physical driving forces governing functionality are inherently encoded in independently parameterized energy functions, which can be resolved through the use of inverse design strategies.The thesis describes the development of EVO-MD, a Python-based implementation of the physics-based inverse design concept. EVO-MD is capable of automatically setting-up, performing, and analyzing molecular dynamics simulations, allowing for the evolutionary optimization of complex and dynamic features in peptides. Examples of such applications include the optimization of lipid composition and curvature sensors, and the development of peptides with antiviral properties. Show less
This thesis aims to investigate the effect of tripartite interaction between microbial inoculants, the plant, and herbivore insects on the rhizosphere microbiome and volatilome. We investigated the... Show moreThis thesis aims to investigate the effect of tripartite interaction between microbial inoculants, the plant, and herbivore insects on the rhizosphere microbiome and volatilome. We investigated the rhizosphere microbiome and volatilome of tomato plants exposed to insect herbivory and/or inoculated with beneficial microbes known to trigger ISR. First, we reviewed the abiotic and biotic factors that impact the success of ISR microbial inoculants (Chapter 2). Then, we tested microbial inoculants against different stresses and experimental conditions to compare interactions in variable contexts (Chapter 3). Next, we explored the impact of insect herbivory aboveground, on the volatile and microbial belowground compartment. In Chapter 4 we explored root volatiles under stress in two tomato species to evaluate the genotype impact on the stress-induced root volatilome. In Chapter 5, we studied the impact of endosymbiotic fungi arbuscular mycorrhizal fungi (AMF) on root volatiles in an in vitro bioassay and in a greenhouse setup with herbivory-stressed plants. In Chapter 6, we compared the effect of four phylogenetically diverse bacteria and fungi, inoculated as single-species and as a synthetic community, on the rhizosphere microbiome assembly and volatilome in herbivory-stressed plants. Overall, this thesis delves into overlooked interactions providing novel data on belowground plant-microbe interactions. Show less
Metabolomics has the potential to play a pivotal role in understanding disease onset and progression, and ultimately personalized treatments. One of its major challenges is its large-scale... Show moreMetabolomics has the potential to play a pivotal role in understanding disease onset and progression, and ultimately personalized treatments. One of its major challenges is its large-scale implementation, which is necessary to deal with the high variability of the metabolome. In this work we have developed tools for automated sample handling and preparation for metabolomics analysis, and bioanalysis in general. The tools are versatile, suitable for high-throughput, and able to deal with sensitive and biomass-limited samples. Sample transfer through segmented-flow can accommodate a wide range of samples and volumes, and can work seamlessly with many downstream processing or analysis. Two sample preparation tools based on droplets; one universal preconcentration tools using controlled evaporation, and one based on simultaneous extraction and enrichment, also provide a versatile interface and can be used to bridge gaps between processing steps. The working principles of these sample handling and preparation tools are universal and can be adapted for specific applications. Show less
Utilizing the polymeric platform of polypept(o)ides, this thesis describes synthesis and investigation of novel triblock copolymers to obtain carrier systems with multiple compartments for... Show moreUtilizing the polymeric platform of polypept(o)ides, this thesis describes synthesis and investigation of novel triblock copolymers to obtain carrier systems with multiple compartments for efficient siRNA delivery. Although the individual microstructure of nanoparticles differs depending on the polymeric building blocks, desired application and cargo, the final nanoparticles always combine a polysarcosine (pSar) shell with a polypeptide core, providing the ability of siRNA complexation by a polycationic segment. In addition, a third block enabled either covalent cross-linking, hydrophobic / π- π-stacking mediated stabilization or co-encapsulation of small hydrophobic drugs. Broadening the structural variety of such polypept(o)ides, a novel synthetic procedure was introduced to access AA'B- and ABC-type miktoarm star polymers.Investigations have been dedicated to the design of novel polymeric structures based on polypept(o)ides, to improve the delivery of siRNA by Polyion Complex Micelles (PICMs), provide access to different polymeric architectures, and to establish novel synthetic methods for the synthesis of these materials. Covering aspects from the synthesis of novel polymeric species up to advanced drug delivery strategies for siRNA in vivo, developments throughout this thesis extent the accessibility of the polypept(o)ide platform for nucleic acid delivery, highlight their potential in nanomedicine and further elaborate delivery strategies for next-generation nanomedical applications. Show less
The outbreaks of AIDS and COVID-19 showed clearly how infectious viruses can influence people’s lives. Investigating the changes in the host metabolism may provide a paradigm shift to consider... Show moreThe outbreaks of AIDS and COVID-19 showed clearly how infectious viruses can influence people’s lives. Investigating the changes in the host metabolism may provide a paradigm shift to consider immune-metabolic interactions as therapeutic targets. The aim of this thesis is to examine the interplay between the immune system and metabolism during viral infections, such as HIV and coronavirus. These investigations will utilize metabolomic and lipidomic mass spectrometry techniques to gain a comprehensive understanding of the metabolic changes that occur during viral infections. To enhance the coverage of the lipidome, a new method will be developed. Show less
In the current global context, there is a pressing need to address sustainable energy supplies to safeguard our Planet and its ecosystems. The choices made by human society have a significant... Show moreIn the current global context, there is a pressing need to address sustainable energy supplies to safeguard our Planet and its ecosystems. The choices made by human society have a significant impact on genetic evolution and climate. To ensure a better future for all, it is crucial to exercise foresight, foster collaboration across various sectors, and reach agreements based on fair and ethical principles. Science plays a pivotal role in advancing energy conversion, offering the potential for significant scientific breakthroughs that contribute to the protection and respect of our World. Specifically, the development of solar-to-fuel devices holds promise for achieving this transition to green energy. This Ph.D. dissertation centers on the development and functionalization of 2D membranes and materials, which constitute integral components of these conversion devices. The optimization of functionalized 2D materials necessitates a comprehensive computational design approach. This involves the adoption of a multiscale computational framework for the thorough design of these materials and the precise prediction and understanding of molecular processes, encompassing molecular self-assembly, ion transport, and catalytic surface reactions. Show less
We show that Kirchhoff ’s law of conservation holds for non-commutative graph flows if and only if the graph is planar. We generalize the theory of (Euclidean) lattices to infinite dimension and... Show moreWe show that Kirchhoff ’s law of conservation holds for non-commutative graph flows if and only if the graph is planar. We generalize the theory of (Euclidean) lattices to infinite dimension and consider the ring of algebraic integers as such a lattice. We compute some invariants using capacity theory and obtain a partial solution to the (algorithmic) closest vector problem. We generalize the results on (universally) graded rings by Lenstra and Silverberg. We study the special case of group rings, and show that under similar assumptions rings can be uniquely decomposed into a group ring in a maximal way. We give a functorial algorithm to compute roots of fractional ideals of orders in number rings. Show less
Polymyxins are clinically used antibiotics, discovered in mid-20th century. Once abandoned due to excessive nephrotoxicity, they are now used increasingly to address infections caused by multi-drug... Show morePolymyxins are clinically used antibiotics, discovered in mid-20th century. Once abandoned due to excessive nephrotoxicity, they are now used increasingly to address infections caused by multi-drug resistant Gram-negative bacteria.In this thesis, we describe the development and synthesis of analogues of polymyxin, aimed at reducing its associated nephrotoxicity. Analogues were made by semisynthesis, with modifications introduced mostly in the exocyclic portion of the molecule. Especially the introduction of a disulfide bond within the linked lipid helped in reducing the toxicity of the molecules, as evidenced by testing on proximal tubule epithelial cells. For most potent analogues, the antimicrobial activity was completely retained.In addition, this thesis describes studies on the mechanism of action of polymyxin, mostly based on the full stereoisomer of polymyxin B4. This analogue lacks antimicrobial activity, indicating its original stereochemistry to be of utmost importance for its use as an antibiotic.Hybrids based on polymyxin B derivatives are described, addressing non-conventional targets. A hybrid with vancomycin (typically active on Gram-positive bacteria only) shows activity on Gram-negative bacteria. A polymyxin-based hybrid coupled to a peptide with a beta-hairpin motif addresses Gram-negative bacteria, presumably by binding to outer membrane protein BamA. Show less
Understanding how galaxies form, interact, and evolve comes largely from comparing theory predictions with observational data. Numerical simulations of galaxies provide the most accurate approach... Show moreUnderstanding how galaxies form, interact, and evolve comes largely from comparing theory predictions with observational data. Numerical simulations of galaxies provide the most accurate approach to testing the theory, as they follow the non-linear evolution of gas and dark matter in great detail and incorporate numerous baryonic processes, among which are energy feedback from supernovae (SNe) and Active Galactic Nuclei (AGN). In this thesis, we show the results of the development of the new model COLIBRE for cosmological simulations of galaxy formation that include a cold interstellar medium. First, we present a new SN feedback recipe developed for COLIBRE, whereby SN energy is injected into the gas in thermal and kinetic forms, and the total energy and momentum of the system of gas and stars are exactly conserved. Second, we conduct a detailed comparison of different ways in which SN energy is distributed in the gas environment around young stellar populations. Third, by using our simulation setup originally developed to test COLIBRE’s SN feedback, we show that the radioactive isotope Fe60 that has been detected on Earth is likely of SN origin. Finally, we present the calibration of the SN and AGN feedback of the COLIBRE model using machine learning. Show less
The research presented in this thesis explores the chemotherapeutic potential of metal-based compounds as chemotherapy agents, with an initial focus on the synthesis and DNA interaction studies of... Show moreThe research presented in this thesis explores the chemotherapeutic potential of metal-based compounds as chemotherapy agents, with an initial focus on the synthesis and DNA interaction studies of platinum and palladium compounds utilizing the [Pt(bapbpy)]2+ scaffold. The study identifies intercalation as the primary mechanism of action for these complexes. Furthermore, it provides a detailed structure-activity relationship analysis, highlighting the critical role of the complex's protonation state in influencing its biological activity and efficacy. Subsequently, the study delves into photoactivated chemotherapy (PACT) using ruthenium (II) complexes, where light activation of ruthenium complexes enables targeted drug delivery to tumor cells, thereby reducing adverse effects. This research emphasizes the development of ruthenium-based compounds that can photorelease a DNA repair inhibitor, specifically targeting the RAD51 protein, essential for Homologous Recombination (HR). By disrupting the DNA repair mechanisms in cancer cells, this approach seeks to enhance the cytotoxicity of the therapy and address drug resistance. Show less
Quantum computing is an emerging technology, which holds the potential to simulate complex quantum systems beyond the reach of classical numerical methods.Despite recent formidable advancements in... Show moreQuantum computing is an emerging technology, which holds the potential to simulate complex quantum systems beyond the reach of classical numerical methods.Despite recent formidable advancements in quantum hardware, constructing a quantum computer capable of performing useful calculations remains challenging.In the absence of a reliable quantum computer, the study of potential applications relies on mathematical methods, ingenious approximations, and heuristics derived from the fields of application. This thesis focuses on developing new quantum algorithms, targeting some of the key challenges in the simulation of complex quantum systems.The techniques introduced in this thesis span from quantum state preparation to mitigation of hardware and algorithmic noise, from efficient expectation value measurement to noise-resilient applications in quantum chemistry. A common thread connecting all these algorithms is the introduction of a single auxiliary qubit – a fundamental unit of quantum information – which has an active and distinctive role in the task at hand. Show less
Learning from small data sets in machine learning is a crucial challenge, especially when dealing with data imbalances and anomaly detection. This thesis delves into the challenges and... Show moreLearning from small data sets in machine learning is a crucial challenge, especially when dealing with data imbalances and anomaly detection. This thesis delves into the challenges and methodologies of learning from small datasets in machine learning, with a particular focus on addressing data imbalances and anomaly detec- tion. It thoroughly explores various strategies for effective small dataset learning in ML, examining both existing approaches and introducing novel techniques. The research pivots around two key questions: firstly, it investigates current methods employed for learning from small datasets in machine learning, and secondly, it assesses the efficacy of batch normalization in enhancing model performance and utilizing salient image segmentation as an augmentation policy in self-supervised learning.The thesis comprehensively reviews techniques for managing small datasets, in- cluding data selection and preprocessing, ensemble methods, transfer learning, regularization techniques, and synthetic data generation. A critical examination of batch normalization reveals its significant role in improving training time and testing errors for minority classes in highly imbalanced datasets. The study also demonstrates that utilizing salient image segmentation as an augmentation policy in self-supervised learning substantially improves representation learning. This improvement is particularly evident in the context of downstream tasks such as image segmentation, highlighting the effectiveness of this technique in enhancing model performance.In summary, this study contributes to the field of machine learning by exploring strategies for learning from small datasets. It offers a detailed analysis of batch normalization, highlighting its potential in improving performance for minority classes in imbalanced datasets. Additionally, the study introduces salient image segmentation as an augmentation policy in self-supervised learning, showing its effectiveness in tasks like image segmentation. These findings provide a solid foundation for further research in small sample learning and present practical insights for machine learning practitioners working with limited data. Show less
The research aims to explore the evolutionary adaptability of enzymes and the impact of temperature on protein evolution pathways, using M. tuberculosis β-lactamase BlaC as the object of study.... Show moreThe research aims to explore the evolutionary adaptability of enzymes and the impact of temperature on protein evolution pathways, using M. tuberculosis β-lactamase BlaC as the object of study. Enzymes inherently embody a delicate balance between activity and stability, and the acquisition of new enzymatic functions is often accompanied by trade-offs, such as decreased stability or reduction of the original activity. Probing evolutionary adaptability of BlaC with laboratory evolution in combination with structural characterization can provide information about the mechanisms of rapid adaptations observed for β-lactamases in the clinic. The role of temperature as a conventional selection pressure in such evolutionary adaptation is unclear. The cooperative nature of enzyme unfolding over a narrow temperature trajectory raises the question whether evolution at temperatures well below the melting point is influenced by temperature. The approach used in this work to answer these questions is by simulating evolution under different selection pressures and characterize the variant enzymes in terms of activity, structure, dynamics and melting temperature. The research makes clear how enzyme kinetics and dynamics vary with different selection pressures and maps the evolutionary path that enzymes may take. The underlying structural mechanisms are established to provide a rationale for the observed effects. Show less
The research in this dissertation aims to optimise blood donation processes in the framework of the Dutch national blood bank Sanquin. The primary health risk for blood donors is iron deficiency,... Show moreThe research in this dissertation aims to optimise blood donation processes in the framework of the Dutch national blood bank Sanquin. The primary health risk for blood donors is iron deficiency, which is evaluated based on donors' hemoglobin and ferritin levels. If either of these levels are inadequate, donors are deferred from donation. Deferral due to low hemoglobin levels occurs on-site, meaning that donors have already traveled to the blood bank and then have to return home without donating, which is demotivating for the donor and inefficient for the blood bank. A large part of this dissertation therefore has the objective to develop a prediction model for donors' hemoglobin levels, based on historical measurements and donor characteristics.The prediction model that was developed reduces the deferral rate by approximately 60\% (from 3\% to 1\% for women, and from 1\% to 0.4\% for men), showing the potential of using data to enhance blood bank policy efficiency. Additionally, the model predictions were made explainable, providing the blood bank with insights into why specific predictions are made. These insights increase our understanding of the relationships between donor characteristics and hemoglobin levels. If this prediction model would be implemented in practice, the explanations could also be shared with the donor to help them understand why they are (not) invited to donate, which could also contribute to donor satisfaction and retention.In a collaborative effort with blood banks in Australia, Belgium, Finland and South Africa, the same prediction model was applied on data from each blood bank. Despite differences in blood bank policies and donor demographics, the models found similar associations with the predictor variables in all countries. Differences in performance could mostly be attributed to differences in deferral rates, with blood banks with higher deferral rates obtaining higher model accuracy.Beyond hemoglobin prediction models, additional research questions are explored. One study aims to identify determinants of ferritin levels in donors through repeated measurements, and linking these to environmental variables. Another study involves modeling the pharmacokinetics of antibodies in COVID-19 recovered donors, and finding relationships between patient characteristics, symptoms, and antibody levels over time.In summary, the research in this dissertation shows the potential within the wealth of data collected by blood banks. The proposed data-driven donation strategies not only decrease deferral rates but also increase donor retention and understanding. This comprehensive approach allows Sanquin to provide more personalised feedback to donors regarding their iron status, ultimately optimising the blood donation process and contributing to the overall efficacy of blood banking systems. Show less
