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The thesis entitled „Investigations on the significance of nucleo-cytoplasmic transport for the biological function of cellular proteins" aimed to unreveal molecular mechanisms in order to improve our understanding of the impact of nucleo-cytoplasmic transport on cellular functions. Within the scope of this work, it could be shown that regulated nucleo-cytoplasmic transport of a subfamily of homeobox transcription factors controlled their intra- and intercellular transport, and thereby influencing also their transcriptional activity. This study describes a novel regulatory mechanism, which could in general play an important role for the ordered differentiation of complex organisms. Besides cis-active transport Signals, also post-translational modifications can influence the localization and biological activity of proteins in trans. In addition to the known impact of phosphorylation on the transport and activity of STAT1, experimental evidence was provided demonstrating that acetylation affected the interaction of STAT1 with NF-kB p65, and subsequently modulated the expression of apoptosis-inducing NF-kB target genes. The impact of nucleo-cytoplasmic transport on the regulation of apoptosis was underlined by showing that the evolutionary conservation of a NES within the anti-apoptotic protein survivin plays an essential role for its dual function in the inhibition of apoptosis and ordered cell division. Since survivin is considered a bona fide cancer therapy target, these results strongly encourage future work to identify molecular decoys that specifically inhibit the nuclear export of survivin as novel therapeutics. In order to further dissect the regulation of nuclear transport and to efficiently identify transport inhibitors, cell-based assays are urgently required. Therefore, the cellular assay Systems developed in this work may not only serve to identify synthetic nuclear export and Import inhibitors but may also be applied in systematic RNAi-screening approaches to identify novel components of the transport machinery. In addition, the translocation based protease- and protein-interaction biosensors can be applied in various biological Systems, in particular to identify protein-protein interaction inhibitors of cancer relevant proteins. In summary, this work does not only underline the general significance of nucleo-cytoplasmic transport for cell biology, but also demonstrates its potential for the development of novel therapies against diseases like cancer and viral infections.
Mitogen activated protein kinases (MAPKs) are found in all eukaryotic cells and represent crucial elements in the signal transduction from the plasma membrane to the nucleus. Although a broad variety of extracellular stimuli activate MAPKs, they evoke very distinct cellular responses. The amplitude and duration of MAPK activation determine signal identity and ultimately cell fate. A tight and finely tuned regulation is therefore critical for a specific cellular response. The role and the regulation of extracellular signal-regulated kinase 5 (ERK5), a MAPK with a large and unique C-terminal tail, were studied in different cellular systems. The study highlights two aspects of ERK5 regulation: control of the phosphorylation state and regulated protein stability. In analogy to other MAPKs ERK5 is activated by dual phosphorylation of threonine and tyrosine residues in its activation motif. A first part of the study concentrates on whether and how the protein tyrosine phosphatase PTP-SL is involved in the downregulation of the ERK5 signal. The direct interaction of both proteins is shown to result in mutual modulation of their enzymatic activities. PTP-SL is a substrate of ERK5 and, independent of its phosphorylation, binding to the kinase enhances its catalytic phosphatase activity. On the other hand, interaction with PTP-SL does not only downregulate enzymatic ERK5 activity but also effectively impedes its translocation to the nucleus. The second part of this study focuses on the interaction of ERK5 with c-Abl and its oncogenic variants Bcr/Abl and v-Abl. In this study these tyrosine kinases are demonstrated to regulate ERK5 by two mechanisms: first, by induction of kinase activity and secondly, by stabilisation of the ERK5 protein. Stabilisation involves the direct interaction of unique ERK5 domains with Abl kinases and is independent of MAPK cascade activation. The level of ERK5 and its intrinsic basal activity – rather than its activation – are essential for v-Abl-induced transformation as well as for survival of Bcr/Abl-positive leukaemia cells. Stabilisation of ERK5 thus contributes to cell survival and should therefore be considered as an additional aspect in therapy of chronic myeloid leukaemia. Taken together, the results obtained in this study demonstrate that diverse pathways regulate ERK5 signalling by affecting kinase activity, localisation and protein stability. While the phosphatase PTP-SL is involved in negative regulation of ERK5, Abl kinases potently activate ERK5 and increase its half-life. Protein stabilisation thus is presented as a novel mechanism in the regulation of MAPKs.
This thesis combines behavioral and cognitive approaches regarding the Web for analyzing users' behavior and supposed interests.
The work is placed in a new field of research called Web Science, which includes, but is not restricted to, the analysis of the World Wide Web. The term Web Science is affected by Tim Berners-Lee et al., who invited the researchers to "create a science of the web" [BLHH+06a]. The thesis is structured in two parts, reflecting the intersection of disciplines that is required for Web Science.
The first part is related to computer science and information systems. This part defines the Gugubarra concepts and algorithms for web user profiling and builds upon the results by Mushtaq et al. [MWTZ04]. This profiling aims at understanding the behavior and supposed interests of users. Based on these concepts, a framework was implemented to support the needs of web site owners. The core technologies used are Java, Spring, Hibernate, and content management systems. The design principles, architecture, implementation, and tests of the prototype are reported.
The second part is directly related to behavioral economics and is connected to the areas of economics, mathematics, and psychology. This part contributes to behavior models, as was claimed by Tim Berners-Lee et al.: "Though individual users may or may not be rational, it has long been noted that en masse people behave as utility maximisers. In that case, understanding the incentives that are available to web users should provide methods for generating models of behaviour..."[BLHH+06b]. The focus here is on studies that investigate the user's choice of online information services in a multi-attribute context. The introduced research framework takes into account background and local context effects and builds upon theoretical foundations by Tversky and Kahneman [TK86]. The findings provide useful insights to behavioral scientists and to practitioners on how to use framing strategies to alter the user's choice.
The aim of this work was to establish a new way of predicting novel dual active compounds by combining classical fingerprint representation with state-of-the-art machine learning algorithms. Advantages and disadvantages of the applied 2D- and 3D-fingerprints were investigated. Further, the impact of various machine learning algorithms was analyzed. The new method developed in this work was used to predict compounds, which inhibit two different targets (LTA4H and sEH) involved in the same disease pattern (inflammation). The development of multitarget drugs has become more important in recent years. Many widespread diseases like metabolic syndrome, or cancer are of a multifactorial nature, which makes them hard to be treated effectively with a single drug. The new in silico method presented in this work can help to accelerate the design and development of multitarget drugs, saving time and efforts.
The nowadays readily available access to a large number of 3D-structures of biological targets and published activity data of millions of synthesized compounds enabled this study and was used as a starting point for this work. Four different data sets were compiled (crystalized ligands from the PDB, active and inactive compounds from ChEMBL23, newly designed compounds using a combinatorial library). Those data sets were collected and processed using an automated KNIME workflow. This automation has the advantage of allowing easy change and update of compound sources and adapted processing ways.
In a next step, the compounds from the compiled data sets were represented using a variety of well-established 2D- and 3D-fingerprints (PLIF, AtomPair, Morgan, FeatMorgan, MACCS). All those fingerprints share the same underlying bit string scheme but vary in the way they describe the molecular structure. Especially the difference between 2D- and 3D-fingerprints was investigated. 2D-fingerprints are solely based on ligand information. 3D-fingerprints, on the other hand, are based on X-ray structure information of protein-ligand complexes. One major difference between 2D- and 3D-fingerprints usage is the need for a 3D-conformation (pose) of the compound in the targets of interest when using 3D-fingerprints. This additional step is time-consuming and brings further uncertainties to the method.
Based on the calculated fingerprints state-of-the-art machine learning algorithms (SVC, RF, XGB and ADA) were used to predict novel dual active compounds. The models were evaluated by 10-fold cross validation and accuracy as the primary measure of model performance was maximized. Second, individual parameters of the four machine learning algorithms were optimized in a grid search to achieve maximal accuracy using the optimized partitioning scheme. Overall accuracies, regardless of fingerprint and machine learning algorithm, are slightly better for LTA4H than for sEH.
The goal to predict dual active compounds was realized by comparing the set of predicted to be active compounds for LTA4H and sEH. For the 3D-fingerprint PLIF the machine learning algorithm Random Forest was chosen, from which compounds for synthesis and testing were selected. Of 115 predicted to be active compounds, six compounds were cherry picked. Two compounds showed very good/moderate dual inhibitory activity. Of the 2D-fingerprints, the AtomPair fingerprint in combination with the machine learning algorithm Random Forest was chosen from which compounds were selected for synthesis and testing. 116 compounds were predicted to be dual active against LTA4H and sEH. One of those compounds showed good dual inhibitory activity.
In this work it was possible to show advantages and disadvantages of using 2D- and 3D-fingerprints in combination with machine learning algorithms. Both strategies (2D: ligand-based, 3D: structure-based) lead to the prediction of novel dual active compounds with moderate to very good inhibitory activity. The method developed in this work is able to predict dual active compounds with very good inhibitory activity and novel (previously unknown) scaffolds inhibiting the targets LTA4H and sEH. This contribution to in silico drug design is promising and can be used for the prediction of novel dual active compounds. Those compounds can further be optimized regarding binding affinity, solubility and further pharmacological and physicochemical properties.
Guanosine triphosphate (GTP) cyclohydrolase I (GCH1) catalyzes the conversion of GTP to dihydroneopterin triphosphate (H2NTP), the initiating step in the biosynthesis of tetrahydrobiopterin (BH4). Besides other roles, BH4 functions as cofactor in neurotransmitter biosynthesis. The BH4 biosynthetic pathway and GCH1 have been identified as promising targets to treat pain disorders in patients. The function of mammalian GCH1s is regulated by a metabolic sensing mechanism involving a regulator protein, GCH1 feedback regulatory protein (GFRP). GFRP binds to GCH1 to form inhibited or activated complexes dependent on availability of cofactor ligands, BH4 and phenylalanine, respectively. We determined high-resolution structures of human GCH1−GFRP complexes by cryoelectron microscopy (cryo-EM). Cryo-EM revealed structural flexibility of specific and relevant surface lining loops, which previously was not detected by X-ray crystallography due to crystal packing effects. Further, we studied allosteric regulation of isolated GCH1 by X-ray crystallography. Using the combined structural information, we are able to obtain a comprehensive picture of the mechanism of allosteric regulation. Local rearrangements in the allosteric pocket upon BH4 binding result in drastic changes in the quaternary structure of the enzyme, leading to a more compact, tense form of the inhibited protein, and translocate to the active site, leading to an open, more flexible structure of its surroundings. Inhibition of the enzymatic activity is not a result of hindrance of substrate binding, but rather a consequence of accelerated substrate binding kinetics as shown by saturation transfer difference NMR (STD-NMR) and site-directed mutagenesis. We propose a dissociation rate controlled mechanism of allosteric, noncompetitive inhibition.
Anthropogenic activities have a major impact on our planet and rapidly drive biodiversity loss in ecosystems at a global scale. Particularly over the last century, rising CO2 emissions significantly raised global temperatures and increased the intensity and frequency of droughts and heatwaves. Additionally, agricultural land use and fossil fuel combustion contribute to the continuous release of nitrogen (N) and phosphorus (P) into ecosystems worldwide through extensive fertilization and deposition from the atmosphere. It is important to understand how these rapid changes affect the evolution of plant populations and their adaptive potential. Adaptation by natural selection (i.e., adaptive evolution) within a few generations is an essential process as a response to rapid environmental changes. Rapid evolution of plant populations can be detected by using the so-called resurrection approach. Here, diaspores (i.e., seeds) from a population are collected before (ancestors) and after (descendants) a potential selection pressure (e.g., consecutive years of drought or changes in nutrient supply). Comparing phenotypes of ancestors and descendants in a common environment such as an outside garden, greenhouse, or climate chamber, may then reveal evolutionary changes. Ideally, plants are first grown in a common environment for an intermediate refresher generation to reduce parental and storage effects.
The aim of this thesis was to investigate the occurrence of adaptive evolution in natural plant populations in response to rapidly changing environments over the past three decades. I conducted three experiments using the resurrection approach to generate comprehensive data on the adaptive processes that acted on three plant populations from three different species over the last three decades. Furthermore, I filled knowledge gaps in plant evolutionary ecology and conceptually developed the resurrection approach further.
In Chapter I, I performed a novel approach by testing for adaptive evolution in natural plant populations using the resurrection approach in combination with in-situ transplantations. I cultivated seedlings from ancestors (23 – 26 years old) and contemporary descendants of three perennial species (Melica ciliata, Leontodon hispidus and Clinopodium vulgare) from calcareous grasslands in the greenhouse and In Chapter III, I assessed the reproducibility of phenotypic differences between genotypes among three different growth facilities (climate chamber, greenhouse, and outdoor garden). I also evaluated differences in phenotypic expression between plants grown after one vs. two intermediate generations (i.e., refresher generations). I performed this experiment within the framework of the resurrection approach and compared ancestors and descendants of the same population of Leontodon hispidus.
I observed very strong differences among plants growing in the different growth facilities. I found a significant interaction between the growth facility and the temporal origin (ancestors vs. descendants): descendants had significantly larger rosettes than ancestors only in the greenhouse and they flowered significantly later than ancestors exclusively in the climate chamber. I did not find significant differences between intermediate generations within the growth facilities. Overall, Chapter III shows that the use of a particular experimental system can dictate the presence and magnitude of phenotypic differences. This implies that absence of evidence is not evidence of absence when it comes to investigating genetically based trait differentiation among plant origins (in space or time). Experimental systems should be carefully designed to provide meaningful conditions, ideally mimicking the environmental conditions of the population’s origins. Finally, growing a second intermediate generation did not impact the genetic differences of ancestors and descendants within the environments, supporting the idea that only one intermediate generation may be sufficient to reduce detectable parental and storage effects.
The resurrection approach allows a better understanding of rapid plant adaptation, but some limitations deserve to be highlighted. I only studied one population per species, and Chapters II and III only focus on one population of L. hispidus, which is also hampering generalizations, as adaptive potential can vary greatly among populations of the same species. I only compared the ancestral genotypes to one descendant sample with a long time span in between (26 – 28 years), which makes it hard to pinpoint the selection agents that caused the genetic differentiation among the sampling years. Hence, closely monitoring biotic and abiotic factors of the studied populations between the ancestral and descendant sampling in future studies, would make identifying the responsible selection pressures more precise. I also recommend sampling multiple populations over consecutive years to improve the robustness of results and make generalizations more approachable.Furthermore, combining the resurrection approach with other methods such as in-situ transplantations will be valuable to offset the limitation that adaptations cannot be proven under artificial conditions (e.g., in the greenhouse).
Using walls to navigate the room: egocentric representations of borders for spatial navigation
(2021)
Spatial navigation forms one of the core components of an animal’s behavioural repertoire. Good navigational skills boost survival by allowing one to avoid predators, to search successfully for food in an unpredictable world, and to be able to find a mating partner. As a consequence, the brain has dedicated many of its resources to the processing of spatial information. Decades of seminal work has revealed how the brain is able to form detailed representations of one’s current position, and use an internal cognitive map of the environment to traverse the local space. However, what is much less understood is how neural computations of position depend on distance information of salient external locations such as landmarks, and how these distal places are encoded in the brain.
The work in this thesis explores the role of one brain region in particular, the retrosplenial cortex (RSC), as a key area to implement distance computations in relation to distal landmarks. Previous research has shown that damage to the RSC results in losses of spatial memory and navigation ability, but its exact role in spatial cognition remains unclear. Initial electrophysiological recordings of single cells in the RSC during free exploration behaviour of the animal resulted in the discovery of a new population of neurons that robustly encode distance information towards nearby walls throughout the environment. Activity of these border cells was characterized by high firing rates near all boundaries of the arena that were available to the animal, and sensory manipulation experiments revealed that this activity persisted in the absence of direct visual or somatosensory detection of the wall.
It quickly became apparent that border cell activity was not only modulated by the distance to walls, but was contingent on the direction the animal was facing relative to the boundary. Approximately 40% of neurons displayed significant selectivity to the direction of walls, mostly in the hemifield contra-lateral to the recorded hemisphere, such that a neuron in left RSC is active whenever a wall occupies proximal space on the right side of the animal. Using a cue-rotation paradigm, experiments initially showed that this egocentric direction information was invariant to the physical rotation of the arena. Yet this rotation elicited a corresponding shift in the preferred direction of local head-direction cells, as well as a rotation in the firing fields of spatially-tuned cells in RSC. As a consequence, position and direction encoding in RSC must be bound together, rotating in unison during the environmental manipulations, as information about allocentric boundary locations is integrated with head-direction signals to form egocentric border representations.
It is known that the RSC forms many anatomical connections with other parts of the brain that encode spatial information, like the hippocampus and para-hippocampal areas. The next step was to establish the circuit mechanisms in place for RSC neurons to generate their activity in respect to the distance and direction of walls. A series of inactivation experiments revealed how RSC activity is inter-dependent with one of its communication partners, the medial entorhinal cortex (MEC). Together they form a wider functional network that encodes precise spatial information of borders, with information flowing from the MEC to RSC but not vice versa. While the conjunction between distance and heading direction relative to the outer walls was the main driver of neural activity in RSC, border cells displayed further behavioural correlates related to movement trajectories. Spiking activity in either hemisphere tended to precede turning behaviour on a short time-scale in a way that border cells in the right RSC anticipated right-way turns ~300 ms into the future.
The interpretation of these results is that the RSC’s primary role in spatial cognition is not necessarily on the early sensory processing stage as suggested by previous studies. Instead, it is involved in computations related to the generation of motion plans, using spatial information that is processed in other brain areas to plan and execute future actions. One potential function of the RSC’s role in this process could be to act correctly in relation to the nearby perimeter, such that border cells in one hemisphere are involved in the encoding of walls in the contralateral hemifield, after which the animal makes an ipsilateral turn to avoid collision. Together this supports the idea that the MEC→RSC pathway links the encoding of space and position in the hippocampal system with the brain’s motor action systems, allowing animals to use walls as prominent landmarks to navigate the room.
Post-translational modifications (PTMs) of cell fate regulating proteins determine their stability, localization and function and control the activation of cell protective signaling pathways. Particularly in aberrantly dividing cancer cells the surveillance of cell cycle progression is essential to control tumorigenicity. In a variety of carcinomas, lymphomas and leukemias, the tumor-suppressive functions of the apoptosis- and senescence-regulating promyelocytic leukemia protein (PML) is controlled by numerous PTMs. PML poly-ubiquitylation and polySUMOylation at several lysine (K) residues induce PML degradation that is correlated to a progressive and invasive cancer phenotype. Besides several known E3 ubiquitin protein ligases that are involved in PML degradation, less is known about PML-specific deubiquitylases (DUBs), the respective DUB-controlled ubiquitin conjugation sites and the functional consequences of PML (de)ubiquitylation. Here, we show that the pro-tumorigenic DUB USP22 critically regulates PML protein stability by modifying PML residue K394 in advanced colon carcinoma cells in vitro and that this modification also impacts the homeostasis and function of the leukemia-associated mutant variant PML-RARα. We found that ablation of USP22 decreases PML mono-ubiquitylation and correlates with a prolonged protein half-live in colon carcinoma and acute promyelocytic leukemia (APL) cell lines. Additionally, silencing of USP22 enhances interferon and interferon-stimulated gene (ISG) expression in APL cells in vitro, which together with prolonged PML-RARα stability increases the APL cell sensitivity towards differentiation treatment. In accordance with the novel roles of USP22 as suppressor of the interferon response in human intestinal epithelial cells (hIECs), our findings imply USP22-dependent surveillance of PML-RARα stability and interferon signaling in human leukemia cells, revealing USP22 as central regulator of leukemia pathogenesis.
Aim: To study the changes in leiomyoma volume following uterine artery embolization (UAE) and to correlate these changes with the initial leiomyoma volume and location within the uterus and to evaluate the impact of preprocedural prediction of the best tube angle obliquity for visualization of the uterine artery origin using 3D-reconstructed contrast-enhanced MR angiography (CE-MRA) on the radiation dose, fluoroscopy time and contrast medium volume used during UAE. Materials and Methods: The study was performed in two parts. The first part was retrospectively done on 28 patients (age range: 37-57 years, mean: 48 years, SD: 4.81) in whom UAE was performed. All leiomyomas in all patients were evaluated. In total, 84 leiomyomas were evaluated. MRI studies were performed before, 3 months and 1 year after UAE. The volumes and location of each leiomyoma in each patient were evaluated in consensus by two radiologists. The second part included 40 consecutive patients (age range: 37-56 years, mean: 46 years, SD: 4.49) and was done in a controlled prospective/retrospective manner. In 20 sample patients (prospective part) pre-procedural prediction of the best tube angle obliquity was predicted using 3D-reconstructed CE-MRA and provided to the interventionalist. 3D-reconstruction was done using Inspace application. The radiation dose, fluoroscopy time and contrast medium volume for those patients were compared with the data of the last 20 procedures (control) performed by the same interventionalist (retrospective part). Results: For the first part the mean pre-embolization volume was 51.6 cm3 range:0.72-371.1cm3, SD=79.3). At 3-month follow-up 83 (98.8%) leiomyomas showed a mean volume reduction of 52.62% (range: 12.79–96.67%, SD=21.85) and 1 leiomyoma (1.2%) increased in volume. At 1-year follow-up 5 (6%) leiomyomas were not detectable, 72 (85.7%) showed a further mean of 20.5% (range: 2.52–58.72%, SD=11.92) volume reduction compared to the 3-month follow-up volume and 7 (8.3%) leiomyomas increased in volume. A statistically significant (p=0.026 at 3-month, p=0.0046 at 1-year) difference in percentage of volume change was observed based on leiomyoma location; submucous leiomyomas showed the largest volume reduction. The initial leiomyoma volume showed a weak negative correlation (Spearman's correlation-coefficient =-0.35 at 3m and -0.36 at 1y) with the leiomyoma volume change. For the second part the tube angle prediction resulted in a significant reduction of the radiation dose utilized (p<0.001), fluoroscopy time (p=0.002) and contrast medium volume (p<0.001) for the sample patients when compared with the control patients. The overall radiation dose was reduced from a mean of 11044 μGym2 to a mean of 4172.5 μGym2, fluoroscopy time was reduced from a mean of 15.45 minutes to 8.81 minutes and contrast medium volume was reduced from a mean of 135 ml to 75 ml. Conclusion: UAE results in significant leiomyoma volume reduction at 3-month and 1- year follow-up. The leiomyoma location plays an important role in volume changes while the initial leiomyoma volume plays a minor role. Pre-procedural prediction of the best tube angle obliquity for visualization of the origin of the uterine artery using 3D-reconstructed CE-MRA results in a significant reduction of the radiation dose, fluoroscopy time and contrast medium volume used during UAE.
This dissertation consists of three essays, which study the relation between stock prices and the macroeconomy using vector autoregressions (VARs). The first essay focuses on the link between stock prices and the current account. I find that stock markets provide a channel, in addition to the traditional exchange rate channel, through which external balance for a country with a current account imbalance can be restored. The second essay explores the transmission of U.S. stock price shocks to real activity and prices in G-7 countries. I achieve identification by imposing a small number of sign restrictions on impulse responses, while controlling for monetary policy, business cycle and government spending shocks. The results suggest that stock price movements are important for fluctuations in G-7 real activity and prices, but do not qualify as demand side business cycle shocks. The third essay investigates the impact of monetary and technology shocks on the stock market. I find an important role for technology shocks, but not monetary shocks, in explaining variations in real stock prices. The identification method is flexible enough to study the effects of technology news shocks. The responses are consistent with the idea that news on technology improvements have an immediate impact on stock prices.