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DNA methylation acts as a major epigenetic modification in mammals, characterized by the transfer of a methyl group to a cytosine. DNA methylation plays a pivotal role in regulating normal development, and misregulation in cells leads to an abnormal phenotype as is seen in several cancers. Any mutations or expression anomalies of genes encoding regulators of DNA methylation may lead to abnormal expression of critical molecules. A comprehensive genomic study encompassing all the genes related to DNA methylation regulation in relation to breast cancer is lacking. We used genomic and transcriptomic datasets from the Cancer Genome Atlas (TGCA) Pan-Cancer Atlas, Genotype-Tissue Expression (GTEx) and microarray platforms and conducted in silico analysis of all the genes related to DNA methylation with respect to writing, reading and erasing this epigenetic mark. Analysis of mutations was conducted using cBioportal, while Xena and KMPlot were utilized for expression changes and patient survival, respectively. Our study identified multiple mutations in the genes encoding regulators of DNA methylation. The expression profiling of these showed significant differences between normal and disease tissues. Moreover, deregulated expression of some of the genes, namely DNMT3B, MBD1, MBD6, BAZ2B, ZBTB38, KLF4, TET2 and TDG, was correlated with patient prognosis. The current study, to our best knowledge, is the first to provide a comprehensive molecular and genetic profile of DNA methylation machinery genes in breast cancer and identifies DNA methylation machinery as an important determinant of the disease progression. The findings of this study will advance our understanding of the etiology of the disease and may serve to identify alternative targets for novel therapeutic strategies in cancer.
Spontaneous brain activity builds the foundation for human cognitive processing during external demands. Neuroimaging studies based on functional magnetic resonance imaging (fMRI) identified specific characteristics of spontaneous (intrinsic) brain dynamics to be associated with individual differences in general cognitive ability, i.e., intelligence. However, fMRI research is inherently limited by low temporal resolution, thus, preventing conclusions about neural fluctuations within the range of milliseconds. Here, we used resting-state electroencephalographical (EEG) recordings from 144 healthy adults to test whether individual differences in intelligence (Raven’s Advanced Progressive Matrices scores) can be predicted from the complexity of temporally highly resolved intrinsic brain signals. We compared different operationalizations of brain signal complexity (multiscale entropy, Shannon entropy, Fuzzy entropy, and specific characteristics of microstates) regarding their relation to intelligence. The results indicate that associations between brain signal complexity measures and intelligence are of small effect sizes (r ∼ 0.20) and vary across different spatial and temporal scales. Specifically, higher intelligence scores were associated with lower complexity in local aspects of neural processing, and less activity in task-negative brain regions belonging to the default-mode network. Finally, we combined multiple measures of brain signal complexity to show that individual intelligence scores can be significantly predicted with a multimodal model within the sample (10-fold cross-validation) as well as in an independent sample (external replication, N = 57). In sum, our results highlight the temporal and spatial dependency of associations between intelligence and intrinsic brain dynamics, proposing multimodal approaches as promising means for future neuroscientific research on complex human traits.
Mammalian embryonic development is subject to complex biological relationships that need to be understood. However, before the whole structure of development can be put together, the individual building blocks must first be understood in more detail. One of these building blocks is the second cell fate decision and describes the differentiation of cells of the inner cell mass of the embryo into epiblast and primitive endoderm cells. These cells then spatially segregate and form the subsequent bases for the embryo and yolk sac, respectively. In organoids of the inner cell mass, these two types of progenitor cells are also observed to form, and to some extent to spatially separate. This work has been devoted to these phenomena over the past three years. Plenty of studies already provide some insights into the basic mechanics of this cell differentiation, such that the first signs of epiblast and primitive endoderm differentiation, are the expression levels of transcription factors NANOG and GATA6. Here, cells with low expression of GATA6 and high expression of NANOG adopt the epiblast fate. If the expressions are reversed, a primitive endoderm cell is formed. Regarding the spatial segregation of the two cell types, it is not yet clear what mechanism leads to this. A common hypothesis suggests the differential adhesion of cell as the cause for the spatial rearrangement of cells. In this thesis however, the possibility of a global cell-cell communication is investigated. The approach chosen to study these phenomena follows the motto "mathematics is biology's next microscope". Mathematical modeling is used to transform the central gene regulatory network at the heart of this work into a system of equations that allows us to describe the temporal evolution of NANOG and GATA6 under the influence of an external signal. Special attention is paid to the derivation of new models using methods of statistical mechanics, as well as the comparison with existing models. After a detailed stability analysis the advantages of the derived model become clear by the fact that an exact relationship of the model parameters and the formation of heterogeneous mixtures of two cell types was found. Thus, the model can be easily controlled and the proportions of the resulting cell types can be estimated in advance. This mathematical model is also combined with a mechanism for global cell-cell communication, as well as a model for the growth of an organoid. It is shown that the global cell-cell communication is able to unify the formation of checkerboard patterns as well as engulfing patterns based on differently propagating signals. In addition, the influence of cell division and thus organoid growth on pattern formation is studied in detail. It is shown that this is able to contribute to the formation of clusters and, as a consequence, to breathe some randomness into otherwise perfectly sorted patterns.
Various types of cancer involve aberrant cell cycle regulation. Among the pathways responsible for tumor growth, the YAP oncogene, a key downstream effector of the Hippo pathway, is responsible for oncogenic processes including cell proliferation, and metastasis by controlling the expression of cell cycle genes. In turn, the MMB multiprotein complex (which is formed when B-MYB binds to the MuvB core) is a master regulator of mitotic gene expression, which has also been associated with cancer. Previously, our laboratory identified a novel crosstalk between the MMB-complex and YAP. By binding to enhancers of MMB target genes and promoting B-MYB binding to promoters, YAP and MMB co-regulate a set of mitotic and cytokinetic target genes which promote cell proliferation. This doctoral thesis addresses the mechanisms of YAP and MMB mediated transcription, and it characterizes the role of YAP regulated enhancers in transcription of cell cycle genes.
The results reported in this thesis indicate that expression of constitutively active, oncogenic YAP5SA leads to widespread changes in chromatin accessibility in untransformed human MCF10A cells. ATAC-seq identified that newly accessible and active regions include YAP-bound enhancers, while the MMB-bound promoters were found to be already accessible and remain open during YAP induction. By means of CRISPR-interference (CRISPRi) and chromatin immuniprecipitation (ChIP), we identified a role of YAP-bound enhancers in recruitment of CDK7 to MMB-regulated promoters and in RNA Pol II driven transcriptional initiation and elongation of G2/M genes. Moreover, by interfering with the YAP-B-MYB protein interaction, we can show that binding of YAP to B-MYB is also critical for the initiation of transcription at MMB-regulated genes. Unexpectedly, overexpression of YAP5SA also leads to less accessible chromatin regions or chromatin closing. Motif analysis revealed that the newly closed regions contain binding motifs for the p53 family of transcription factors. Interestingly, chromatin closing by YAP is linked to the reduced expression and loss of chromatin-binding of the p53 family member Np63. Furthermore, I demonstrate that downregulation of Np63 following expression of YAP is a key step in driving cellular migration.
Together, the findings of this thesis provide insights into the role of YAP in the chromatin changes that contribute to the oncogenic activities of YAP. The overexpression of YAP5SA not only leads to the opening of chromatin at YAP-bound enhancers which together with the MMB complex stimulate the expression of G2/M genes, but also promotes the closing of chromatin at ∆Np63 -bound regions in order to lead to cell migration.
Coxiella burnetii, a Gram negative obligate intracellular bacterium, is the causative
agent of Q fever. It has a world wide distribution and has been documented to
be capable of causing infections in several domestic animals, livestock species,
and human beings. Outbreaks of Q fever are still being observed in livestock
across animal farms in Europe, and primary transmission to humans still oc-
curs especially in animal handlers. Public health authorities in some countries
like Germany are required by law to report human acute cases denoting the
significance of the challenge posed by C. burnetii to public health.
In this thesis, I have developed a platform alongside methods to address the
challenges of genomic analyses of C. burnetii for typing purposes. Identification
of C. burnetii isolates is an important task in the laboratory as well as in the
clinics and genotyping is a reliable method to identify and characterize known
and novel isolates. Therefore, I designed and implemented several methods
to facilitate the genotyping analyses of C. burnetii genomes in silico via a web
platform. As genotyping is a data intensive process, I also included additional
features such as visualization methods and databases for interpretation and
storage of obtained results. I also developed a method to profile the resistome
of C. burnetii isolates using a machine learning approach. Data about antibiotic
resistance in C. burnetii are scarce majorly due to its lifestyle and the difficulty
of cultivation in laboratory media. Alternative methods that rely on homology
identification of resistance genes are also inefficient in C. burnetii, hence, I
opted for a novel approach that has been shown to be promising in other
bacteria species. The applied method relied on an artificial neural network as
well as amino acid composition of position specific scoring matrix profile for
feature extraction. The resulting model achieved an accuracy of ≈ 0.96 on test
data and the overall performance was significantly higher in comparison to
existing models. Finally, I analyzed two new C. burnetii isolates obtained from
an outbreak in Germany, I compared the genome to the RSA 493 reference
isolate and found extensive deletions across the genome landscape.
This work has provided a new digital infrastructure to analyze and character-
ize C. burnetii genomes that was not in existence before and it has also made a
significant contribution to the existing information about antibiotic resistance
genes in C. burnetii.
The original habitat of native European honey bees (\(Apis\) \(mellifera\)) is forest, but currently there is a lack of data about the occurrence of wild honey bee populations in Europe. Prior to being kept by humans in hives, honey bees nested as wild species in hollow trees in temperate forests. However, in the 20th century, intensification of silviculture and agriculture with accompanying losses of nesting sites and depletion of food resources caused population declines in Europe. When the varroa mite (Varroa destructor), an invasive ectoparasite from Asia, was introduced in the late 1970s, wild honey bees were thought to be eradicated in Europe. Nevertheless, sporadic, mostly anecdotal, reports from ornithologists or forest ecologists indicated that honey bee colonies still occupy European forest areas. In my thesis I hypothesize that near-natural deciduous forests may provide sufficient large networks of nesting sites representing refugia for wild-living honey bees. Using two special search techniques, i.e. the tracking of flight routes of honey bee foragers (the “beelining” method) and the inspection of known cavity trees, I collected for the first time data on the occurrence and density of wild-living honey bees in forest areas in Germany (CHAPTER 3). I found wild-living honey bee colonies in the Hainich national park at low densities in two succeeding years. In another forest region, I checked known habitat trees containing black woodpecker cavities for occupation by wild-living honey bee colonies. It turned out that honey bees regularly use these cavities and occur in similar densities in both studied forest regions, independent of the applied detection method. Extrapolating these densities to all German forest areas, I estimate several thousand wild-living colonies in Germany that potentially interact in different ways with the forest environment. I conclude that honey bees regularly colonize forest areas in Germany and that networks of mapped woodpecker cavities offer unique possibilities to study the ecology of wild-living honey bees over several years.
While their population status is ambiguous and the density of colonies low, the fact that honey bees can still be found in forests poses questions about food supply in forest environments. Consequently, I investigated the suitability of woodlands as a honey bee foraging habitat (CHAPTER 4). As their native habitat, forests are assumed to provide important pollen and nectar sources for honey bee colonies. However, resource supply might be spatially and temporally restricted and landscape-scale studies in European forest regions are lacking. Therefore, I set up twelve honey bee colonies in observation hives at locations with varying degree of forest cover. Capitalizing on the unique communication behaviour, the waggle dance, I examined the foraging distances and habitat preferences of honey bees over almost an entire foraging season. Moreover, by connecting this decoded dance information with colony weight recordings, I could draw conclusions about the contribution of the different habitat types to honey yield. Foraging distances generally increased with the amount of forest in the surrounding landscape. Yet, forest cover did not have an effect on colony weight. Compared to expectations based on the proportions of different habitats in the surroundings, colonies foraged more frequently in cropland and grasslands than in deciduous and coniferous forests, especially in late summer when pollen foraging in the forest is most difficult. In contrast, colonies used forests for nectar/honeydew foraging in early summer during times of colony weight gain emphasizing forests as a temporarily significant source of carbohydrates. Importantly, my study shows that the ecological and economic value of managed forest as habitat for honey bees and other wild pollinators can be significantly increased by the continuous provision of floral resources, especially for pollen foraging.
The density of these wild-living honey bee colonies and their survival is driven by several factors that vary locally, making it crucial to compare results in different regions. Therefore, I investigated a wild-living honey bee population in Galicia in north-western Spain, where colonies were observed to reside in hollow electric poles (CHAPTER 5). The observed colony density only in these poles was almost twice as high as in German forest areas, suggesting generally more suitable resource conditions for the bees in Galicia. Based on morphometric analyses of their wing venation patterns, I assigned the colonies to the native evolutionary lineage (M-lineage) where the particularly threatened subspecies \(Apis\) \(mellifera\) \(iberiensis\) also belongs to. Averaged over two consecutive years, almost half of the colonies survived winter (23 out of 52). Interestingly, semi-natural areas both increased abundance and subsequent colony survival. Colonies surrounded by more semi-natural habitat (and therefore less intensive cropland) had an elevated overwintering probability, indicating that colonies need a certain amount of semi-natural habitat in the landscape to survive. Due to their ease of access these power poles in Galicia are, ideally suited to assess the population demography of wild-living Galician honey bee colonies through a long-term monitoring.
In a nutshell, my thesis indicates that honey bees in Europe always existed in the wild. I performed the first survey of wild-living bee density yet done in Germany and Spain. My thesis identifies the landscape as a major factor that compromises winter survival and reports the first data on overwintering rates of wild-living honey bees in Europe. Besides, I established methods to efficiently detect wild-living honey bees in different habitat. While colonies can be found all over Europe, their survival and viability depend on unpolluted, flower rich habitats. The protection of near-natural habitat and of nesting sites is of paramount importance for the conservation of wild-living honey bees in Europe.
The monarch butterfly (Danaus plexippus) performs one of the most astonishing behaviors in the animal kingdom: every fall millions of these butterflies leave their breeding grounds in North Amerika and migrate more than 4.000 km southwards until they reach their overwintering habitat in Central Mexico. To maintain their migratory direction over this enormous distance, the butterflies use a time-compensated sun compass. Beside this, skylight polarization, the Earth’s magnetic field and specific mountain ranges seem to guide the butterflies as well the south. In contrast to this fascinating orientation ability, the behavior of the butterflies in their non-migratory state received less attention. Although they do not travel long distances, they still need to orient themselves to find food, mating partners or get away from competitors. The aim of the present doctoral thesis was to investigate use of visual cues for orientation in migrating as well as non-migrating monarch butterflies. For this, field experiments investigating the migration of the butterflies in Texas (USA) were combined with experiments testing the orientation performance of non-migratory butterflies in Germany.
In the first project, I recorded the heading directions of tethered butterflies during their annual fall migration. In an outdoor flight simulator, the butterflies maintained a southwards direction as long as they had a view of the sun’s position. Relocating the position of the sun by 180° using a mirror, revealed that the sun is the animals’ main orientation reference. Furthermore, I demonstrated that when the sun is blocked and a green light stimulus (simulated sun) is introduced, the animals interpreted this stimulus as the ‘real’ sun. However, this cue was not sufficient to set the migratory direction when simulated as the only visual cue in indoor experiments. When I presented the butterflies a linear polarization pattern additionally to the simulated sun, the animals headed in the correct southerly direction showing that multiple skylight cues are required to guide the butterflies during their migration.
In the second project, I, furthermore, demonstrated that non-migrating butterflies are able to maintain a constant direction with respect to a simulated sun. Interestingly, they ignored the spectral component of the stimulus and relied on the intensity instead. When a panoramic skyline was presented as the only orientation reference, the butterflies maintained their direction only for short time windows probably trying to stabilize their flight based on optic-flow information. Next, I investigated whether the butterflies combine celestial with local cues by simulating a sun stimulus together with a panoramic skyline. Under this conditions, the animals’ directedness was increased demonstrating that they combine multiple visual cues for spatial orientation.
Following up on the observation that a sun stimulus resulted in a different behavior than the panoramic skyline, I investigated in my third project which orientation strategies the butterflies use by presenting different simulated cues to them. While a bright stripe on a dark background elicited a strong attraction of the butterflies steering in the direction of the stimulus, the inverted version of the stimulus was used for flight stabilization. In contrast to this, the butterflies maintained arbitrary directions with a high directedness with respect to a simulated sun. In an ambiguous scenery with two identical stimuli (two bright stripes, two dark stripes, or two sun stimuli) set 180° apart, a constant flight course was only achieved when two sun stimuli were displayed suggesting an involvement of the animals’ internal compass. In contrast, the butterflies used two dark stripes for flight stabilization and were alternatingly attracted by two bright stripes. This shows that monarch butterflies use stimulus-dependent orientation strategies and gives the first evidence for different neuronal pathways controlling the output behavior.
The fusion of methods from several disciplines is a crucial component of scientific development. Artificial Neural Networks, based on the principle of biological neuronal networks, demonstrate how nature provides the best templates for technological advancement. These innovations can then be employed to solve the remaining mysteries of biology, including, in particular, processes that take place on microscopic scales and can only be studied with sophisticated techniques. For instance, direct Stochastic Optical Reconstruction Microscopy combines tools from chemistry, physics, and computer science to visualize biological processes at the molecular level. One of the key components is the computer-aided reconstruction of super-resolved images. Improving the corresponding algorithms increases the quality of the generated data, providing further insights into our biology. It is important, however, to ensure that the heavily processed images are still a reflection of reality and do not originate in random artefacts.
Expansion microscopy is expanding the sample by embedding it in a swellable hydrogel. The method can be combined with other super-resolution techniques to gain additional resolution. We tested this approach on microtubules, a well-known filamentous reference structure, to evaluate the performance of different protocols and labelling techniques.
We developed LineProfiler an objective tool for data collection. Instead of collecting perpendicular profiles in small areas, the software gathers line profiles from filamentous structures of the entire image. This improves data quantity, quality and prevents a biased choice of the evaluated regions. On the basis of the collected data, we deployed theoretical models of the expected intensity distribution across the filaments. This led to the conclusion that post-expansion labelling significantly reduces the labelling error and thus, improves the data quality. The software was further used to determine the expansion factor and arrangement of synaptonemal complex data.
Automated Simple Elastix uses state-of-the-art image alignment to compare pre- and post-expansion images. It corrects linear distortions occurring under isotropic expansion, calculates a structural expansion factor and highlights structural mismatches in a distortion map. We used the software to evaluate expanded fungi and NK cells. We found that the expansion factor differs for the two structures and is lower than the overall expansion of the hydrogel.
Assessing the fluorescence lifetime of emitters used for direct Stochastic Optical Reconstruction Microscopy can reveal additional information about the molecular environment or distinguish dyes emitting with a similar wavelength. The corresponding measurements require a confocal scanning of the sample in combination with the fluorescent switching of the underlying emitters. This leads to non-linear, interrupted Point Spread Functions. The software ReCSAI targets this problem by combining the classical algorithm of compressed sensing with modern methods of artificial intelligence. We evaluated several different approaches to combine these components and found, that unrolling compressed sensing into the network architecture yields the best performance in terms of reconstruction speed and accuracy.
In addition to a deep insight into the functioning and learning of artificial intelligence in combination with classical algorithms, we were able to reconstruct the described non-linearities with significantly improved resolution, in comparison to other state-of-the-art architectures.
The variant surface glycoprotein (VSG) of African trypanosomes plays an essential role in protecting the parasites from host immune factors. These trypanosomes undergo antigenic variation resulting in the expression of a single VSG isoform out of a repertoire of around 2000 genes. The molecular mechanism central to the expression and regulation of the VSG is however not fully understood.
Gene expression in trypanosomes is unusual due to the absence of typical RNA polymerase II promoters and the polycistronic transcription of genes. The regulation of gene expression is therefore mainly post-transcriptional. Regulatory sequences, mostly present in the 3´ UTRs, often serve as key elements in the modulation of the levels of individual mRNAs. In T. brucei VSG genes, a 100 % conserved 16mer motif within the 3´ UTR has been shown to modulate the stability of VSG transcripts and hence their expression. As a stability-associated sequence element, the absence of nucleotide substitutions in the motif is however unusual. It was therefore hypothesised that the motif is involved in other essential roles/processes besides stability of the VSG transcripts.
In this study, it was demonstrated that the 100 % conservation of the 16mer motif is not essential for cell viability or for the maintenance of functional VSG protein levels. It was further shown that the intact motif in the active VSG 3´ UTR is neither required to promote VSG silencing during switching nor is it needed during differentiation from bloodstream forms to procyclic forms. Crosstalk between the VSG and procyclin genes during differentiation to the insect vector stage is also unaffected in cells with a mutated 16mer motif. Ectopic overexpression of a second VSG however requires the intact motif to trigger silencing and exchange of the active VSG, suggesting a role for the motif in transcriptional VSG switching. The 16mer motif therefore plays a dual role in VSG in situ switching and stability of VSG transcripts. The additional role of the 16mer in the essential process of antigenic variation appears to be the driving force for the 100 % conservation of this RNA motif.
A screen aimed at identifying candidate RNA-binding proteins interacting with the 16mer motif, led to the identification of a DExD/H box protein, Hel66. Although the protein did not appear to have a direct link to the 16mer regulation of VSG expression, the DExD/H family of proteins are important players in the process of ribosome biogenesis. This process is relatively understudied in trypanosomes and so this candidate was singled out for detailed characterisation, given that the 16mer story had reached a natural end point. Ribosome biogenesis is a major cellular process in eukaryotes involving ribosomal RNA, ribosomal proteins and several non-ribosomal trans-acting protein factors. The DExD/H box proteins are the most important trans-acting protein factors involved in the biosynthesis of ribosomes. Several DExD/H box proteins have been directly implicated in this process in yeast. In trypanosomes, very few of this family of proteins have been characterised and therefore little is known about the specific roles they play in RNA metabolism. Here, it was shown that Hel66 is involved in rRNA processing during ribosome biogenesis. Hel66 localises to the nucleolus and depleting the protein led to a severe growth defect. Loss of the protein also resulted in a reduced rate of global translation and accumulation of rRNA processing intermediates of both the small and large ribosomal subunits. Hel66 is therefore an essential nucleolar DExD/H protein involved in rRNA processing during ribosome biogenesis. As very few protein factors involved in the processing of rRNAs have been described in trypanosomes, this finding represents an important platform for future investigation of this topic.
The reprogramming of metabolic pathways is a hallmark of cancer: Tumour cells are dependent on the supply with metabolites and building blocks to fulfil their increased need as highly proliferating cells. Especially de novo synthesis pathways are upregulated when the cells of the growing tumours are not able to satisfy the required metabolic levels by uptake from the environment.
De novo synthesis pathways are often under the control of master transcription factors which regulate the gene expression of enzymes involved in the synthesis process. The master regulators for de novo fatty acid synthesis and cholesterogenesis are sterol regulatory element-binding proteins (SREBPs). While SREBP1 preferably controls the expression of enzymes involved in fatty acid synthesis, SREBP2 regulates the transcription of the enzymes of the mevalonate pathway and downstream processes namely cholesterol, isoprenoids and building blocks for ubiquinone synthesis.
SREBP activity is tightly regulated at different levels: The post-translational modification by ubiquitination decreases the stability of active SREBPs. The attachment of K48-linked ubiquitin chains marks the transcription factors for the proteasomal degradation. In tumour cells, high levels of active SREBPs are essential for the upregulation of the respective metabolic pathways. The increased stability and activity of SREBPs were investigated in this thesis.
SREBPs are ubiquitinated by the E3 ligase Fbw7 which leads to the subsequential proteolysis of the transcription factors. The work conducted in this thesis identified the counteracting deubiquitination enzyme USP28 which removes the ubiquitin chains from SREBPs and prevents their proteasomal degradation.
It further revealed that the stabilization of SREBP2 by USP28 plays an important role in the context of squamous cancers. Increased USP28 levels are associated with a poor survival in patients with squamous tumour subtypes. It was shown that reduced USP28 levels in cell lines and in vivo result in a decrease of SREBP2 activity and downregulation of the mevalonate pathway. This manipulation led to reduced proliferation and tumour growth.
A direct comparison of adenocarcinomas and squamous cell carcinomas in lung cancer patients revealed an upregulation of USP28 as well as SREBP2 and its target genes. Targeting the USP28-SREBP2 regulatory axis in squamous cell lines by inhibitors also reduced cell viability and proliferation.
In conclusion, this study reports evidence for the importance of the mevalonate pathway regulated by the USP28-SREBP2 axis in tumour initiation and progression of squamous cancer. The combinatorial inhibitor treatment of USP28 and HMGCR, the rate limiting enzyme of the mevalonate pathway, by statins opens the possibility for a targeted therapeutic treatment of squamous cancer patients.