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Sonstige beteiligte Institutionen
- Center for Computational and Theoretical Biology (CCTB), Universität Würzburg (1)
- Chemical Biology Laboratory, National Cancer Institue, Frederick (USA) (1)
- Fachgebiet für Populationsgenomik bei Nutztieren, Universität Hohenheim (1)
- Lehrstuhl für Chemie, Brooklyn College, City University of New York, Brooklyn (1)
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- Zentrale Abteilung für Mikroskopie, Universität Würzburg (1)
The signal modelling framework JimenaE simulates dynamically Boolean networks. In contrast to SQUAD, there is systematic and not just heuristic calculation of all system states. These specific features are not present in CellNetAnalyzer and BoolNet. JimenaE is an expert extension of Jimena, with new optimized code, network conversion into different formats, rapid convergence both for system state calculation as well as for all three network centralities. It allows higher accuracy in determining network states and allows to dissect networks and identification of network control type and amount for each protein with high accuracy. Biological examples demonstrate this: (i) High plasticity of mesenchymal stromal cells for differentiation into chondrocytes, osteoblasts and adipocytes and differentiation-specific network control focusses on wnt-, TGF-beta and PPAR-gamma signaling. JimenaE allows to study individual proteins, removal or adding interactions (or autocrine loops) and accurately quantifies effects as well as number of system states. (ii) Dynamical modelling of cell–cell interactions of plant Arapidopsis thaliana against Pseudomonas syringae DC3000: We analyze for the first time the pathogen perspective and its interaction with the host. We next provide a detailed analysis on how plant hormonal regulation stimulates specific proteins and who and which protein has which type and amount of network control including a detailed heatmap of the A.thaliana response distinguishing between two states of the immune response. (iii) In an immune response network of dendritic cells confronted with Aspergillus fumigatus, JimenaE calculates now accurately the specific values for centralities and protein-specific network control including chemokine and pattern recognition receptors.
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.
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.
Monarch butterflies are famous for their annual long-distance migration. Decreasing temperatures and reduced daylight induce the migratory state in the autumn generation of monarch butterflies. Not only are they in a reproductive diapause, they also produce fat deposits to be prepared for the upcoming journey: Driven by their instinct to migrate, they depart from their eclosion grounds in the northern regions of the North American continent and start their southern journey to their hibernation spots in Central Mexico. The butterflies cover a distance of up to 4000 km across the United States. In the next spring, the same butterflies invert their preferred heading direction due to seasonal changes and start their northward spring migration. The spring migration is continued by three consecutive butterfly generations, until the animals repopulate the northern regions in North America as non-migratory monarch butterflies. The monarch butterflies’ migratory state is genetically and epigenetically regulated, including the directed flight behavior. Therefore, the insect’s internal compass system does not only have to encode the butterflies preferred, but also its current heading direction. However, the butterfly’s internal heading representation has to be matched to external cues, to avoid departing from its initial flight path and increasing its risk of missing its desired destination. During the migratory flight, visual cues provide the butterflies with reliable orientation information. The butterflies refer to the sun as their main orientation cue. In addition to the sun, the butterflies likely use the polarization pattern of the sky for orientation. The sky compass signals are processed within a region in the brain, termed the central complex (CX). Previous research on the CX neural circuitry of the monarch butterflies demonstrated that tangential central complex neurons (TL) carry the visual input information into the CX and respond to a simulated sun and polarized light. However, whether these cells process additional visual cues like the panoramic skyline is still unknown. Furthermore, little is known about how the migratory state affects visual cue processing. In addition to this, most experiments studying the monarch butterfly CX focused on how neurons process single visual cues. However, how combined visual stimuli are processed in the CX is still unknown.
This thesis is investigating the following questions:
1) How does the migratory state affect visual cue processing in the TL cells within the monarch butterfly brain?
2) How are multiple visual cues integrated in the TL cells?
3) How is compass information modulated in the CX?
To study these questions, TL neurons from both animal groups (migratory and non-migratory) were electrophysiologically characterized using intracellular recordings while presenting different simulated celestial cues and visual sceneries. I showed that the TL neurons of migratory butterflies are more narrowly tuned to the sun, possibly helping them in keeping a directed flight course during migration. Furthermore, I found that TL cells encode a panoramic skyline, suggesting that the CX network combines celestial and terrestrial information. Experiments with combined celestial stimuli revealed that the TL cells combine both cue information linearly. However, if exposing the animals to a simulated visual scenery containing a panoramic skyline and a simulated sun, the single visual cues are weighted differently. These results indicate that the CX’s input region can flexibly adapt to different visual cue conditions. Furthermore, I characterize a previously unknown neuron in the monarch butterfly CX which responds to celestial stimuli and connects the CX with other brain neuropiles. How this cell type affects heading direction encoding has yet to be determined.
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.
Aim
Global warming is assumed to restructure mountain insect communities in space and time. Theory and observations along climate gradients predict that insect abundance and richness, especially of small‐bodied species, will increase with increasing temperature. However, the specific responses of single species to rising temperatures, such as spatial range shifts, also alter communities, calling for intensive monitoring of real‐world communities over time.
Location
German Alps and pre‐alpine forests in south‐east Germany.
Methods
We empirically examined the temporal and spatial change in wild bee communities and its drivers along two largely well‐protected elevational gradients (alpine grassland vs. pre‐alpine forest), each sampled twice within the last decade.
Results
We detected clear abundance‐based upward shifts in bee communities, particularly in cold‐adapted bumble bee species, demonstrating the speed with which mobile organisms can respond to climatic changes. Mean annual temperature was identified as the main driver of species richness in both regions. Accordingly, and in large overlap with expectations under climate warming, we detected an increase in bee richness and abundance, and an increase in small‐bodied species in low‐ and mid‐elevations along the grassland gradient. Community responses in the pre‐alpine forest gradient were only partly consistent with community responses in alpine grasslands.
Main Conclusion
In well‐protected temperate mountain regions, small‐bodied bees may initially profit from warming temperatures, by getting more abundant and diverse. Less severe warming, and differences in habitat openness along the forested gradient, however, might moderate species responses. Our study further highlights the utility of standardized abundance data for revealing rapid changes in bee communities over only one decade.
Cancer is one of the leading causes of death worldwide, with currently assessed chances to develop at least one cancer in a lifetime for about 20%. High cases rates and mortality require the development of new anticancer therapies and treatment strategies. Another important concern is toxicity normally associated with conventional therapy methods, such as chemo- and radiotherapy. Among many proposed antitumoral agents, oncolytic viruses are still one of the promising and fast-developing fields of research with almost a hundred studies published data on over 3000 patients since the beginning of the new millennia.
Among all oncolytic viruses, the Vaccinia virus is arguably one of the safest, with an extremely long and prominent history of use, since it was the one and only vaccine used in the Smallpox Eradication Program in the 1970s. Interestingly enough, it was the first oncolytic virus proven to have tumor tropism in vitro and in vivo in laboratory settings, and this year we can celebrate an unofficial 100th anniversary since the publication of the fact. While being highly immunogenic, Vaccinia virus DNA replication takes place in the cytoplasm of the infected cell, and virus genes never integrate into the host genome. Another advantage of using Vaccinia as an oncolytic agent is its high genome capacity, which allows inserting up to 25 kbps of exogenous genes, thus allowing to additionally arm the virus against the tumor.
Oncolytic virus action consists of two major parts: direct oncolysis and immune activation against the tumor, with the latter being the key to successful treatment. To this moment, preclinical research data are mostly generated in immunocompromised xenograft models, which have hurdles to be properly translated for clinical use. In the first part of the current study, fourteen different recombinant Vaccinia virus strains were tested in two different murine tumor cell lines and corresponding immunocompetent animal models. We found, that Copenhagen backbone Vaccinia viruses while being extremely effective in cell culture, do not show significant oncolytic efficacy in animals. In contrast, several of the LIVP backbone viruses tested (specifically, IL-2 expressing ones) have little replication ability when compared to the Copenhagen strain, but are able to significantly delay tumor growth and prolong survival of the treated animals. We have also noted cytokine related toxicity of the animals to be mouse strain specific.
We have also tested the virus with the highest therapeutic benefit in combination with romidepsin and cyclophosphamide. While the combination with histone deacetylase inhibitor romidepsin did not result in therapeutic benefit in our settings, the addition of cyclophosphamide significantly improved the efficacy of the treatment, at the same time reducing cytokine-associated toxicity of the IL-2 expressing virus.
In the second part of the work, we analyzed the ability of adipose-derived mesenchymal stem cells to serve as a carrier for the oncolytic Vaccinia virus. We showed for the first time that the cells can be infected with the virus and can generate virus progeny. They are also able to survive for a substantially long time and, when injected into the bloodstream of tumor-bearing animals, produce the virus that is colonizing the tumor. Analysis of the systemic distribution of the cells after injection revealed that infected and uninfected cells are not distributed in the same manner, possibly suggesting that infected cells are getting recognized and cleared by an impaired immune system of athymic mice faster than non-infected cells. Despite this, injection of virus-loaded adipose-derived mesenchymal stem cells to human A549 tumor-bearing xenograft mice resulted in rapid tumor regression and reduced virus-related side effects of the treatment when compared to injection of the naked virus.
In conclusion, we have tested two different approaches to augmenting oncolytic Vaccinia virus therapy. First, the combination of recombinant Vaccinia virus expressing IL-2 and cyclophosphamide showed promising results in a syngeneic mouse model, despite the low permissivity of murine cells to the virus. Second, we loaded the oncolytic Vaccinia virus into mesenchymal stem cells and have proven that they can potentially serve as a vehicle for the virus.
Honeybees (Apis mellifera) need their fine sense of taste to evaluate nectar and pollen sources. Gustatory receptors (Grs) translate taste signals into electrical responses. In vivo experiments have demonstrated collective responses of the whole Gr-set. We here disentangle the contributions of all three honeybee sugar receptors (AmGr1-3), combining CRISPR/Cas9 mediated genetic knock-out, electrophysiology and behaviour. We show an expanded sugar spectrum of the AmGr1 receptor. Mutants lacking AmGr1 have a reduced response to sucrose and glucose but not to fructose. AmGr2 solely acts as co-receptor of AmGr1 but not of AmGr3, as we show by electrophysiology and using bimolecular fluorescence complementation. Our results show for the first time that AmGr2 is indeed a functional receptor on its own. Intriguingly, AmGr2 mutants still display a wildtype-like sugar taste. AmGr3 is a specific fructose receptor and is not modulated by a co-receptor. Eliminating AmGr3 while preserving AmGr1 and AmGr2 abolishes the perception of fructose but not of sucrose. Our comprehensive study on the functions of AmGr1, AmGr2 and AmGr3 in honeybees is the first to combine investigations on sugar perception at the receptor level and simultaneously in vivo. We show that honeybees rely on two gustatory receptors to sense all relevant sugars.
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.
Cancer is one of the leading causes of death worldwide. The underlying tumorigenesis is driven by the accumulation of alterations in the genome, eventually disabling tumor suppressors and activating proto-oncogenes.
The MYC family of proto-oncogenes shows a strong deregulation in the majority of tumor entities. However, the exact mechanisms that contribute to MYC-driven oncogenesis remain largely unknown. Over the past decades, the influence of the MYC protein on transcription became increasingly apparent and was thoroughly investigated. Additionally, in recent years several publications provided evidence for so far unreported functions of MYC that are independent of a mere regulation of target genes. These findings suggest an additional role of MYC in the maintenance of genomic stability and this role is strengthened by key findings presented in this thesis.
In the first part, I present data revealing a pathway that allows MYC to couple transcription elongation and DNA double-strand break repair, preventing genomic instability of MYC-driven tumor cells. This pathway is driven by a rapid transfer of the PAF1 complex from MYC onto RNAPII, a process that is mediated by HUWE1. The transfer controls MYC-dependent transcription elongation and, simultaneously, the remodeling of chromatin structure by ubiquitylation of histone H2B. These regions of open chromatin favor not only elongation but also DNA double-strand break repair.
In the second part, I analyze the ability of MYC proteins to form multimeric structures in response to perturbation of transcription and replication. The process of multimerization is also referred to as phase transition. The observed multimeric structures are located proximal to stalled replication forks and recruit factors of the DNA-damage response and transcription termination machinery. Further, I identified the HUWE1-dependent ubiquitylation of MYC as an essential step in this phase transition. Cells lacking the ability to form multimers display genomic instability and ultimately undergo apoptosis in response to replication stress.
Both mechanisms present MYC as a stress resilience factor under conditions that are characterized by a high level of transcriptional and replicational stress. This increased resilience ensures oncogenic proliferation.
Therefore, targeting MYC’s ability to limit genomic instability by uncoupling transcription elongation and DNA repair or disrupting its ability to multimerize presents a therapeutic window in MYC-dependent tumors.