Theodor-Boveri-Institut für Biowissenschaften
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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.
A cascade of histone acetylation events with subsequent incorporation of a histone H2A variant plays an essential part in transcription regulation in various model organisms. A key player in this cascade is the chromatin remodelling complex SWR1, which replaces the canonical histone H2A with its variant H2A.Z. Transcriptional regulation of polycistronic transcription units in the unicellular parasite Trypanosoma brucei has been shown to be highly dependent on acetylation of H2A.Z, which is mediated by the histone-acetyltransferase HAT2. The chromatin remodelling complex which mediates H2A.Z incorporation is not known and an SWR1 orthologue in trypanosomes has not yet been reported. In this study, we identified and characterised an SWR1-like remodeller complex in T. brucei that is responsible for Pol II-dependent transcriptional regulation. Bioinformatic analysis of potential SNF2 DEAD/Box helicases, the key component of SWR1 complexes, identified a 1211 amino acids-long protein that exhibits key structural characteristics of the SWR1 subfamily. Systematic protein-protein interaction analysis revealed the existence of a novel complex exhibiting key features of an SWR1-like chromatin remodeller. RNAi-mediated depletion of the ATPase subunit of this complex resulted in a significant reduction of H2A.Z incorporation at transcription start sites and a subsequent decrease of steady-state mRNA levels. Furthermore, depletion of SWR1 and RNA-polymerase II (Pol II) caused massive chromatin condensation. The potential function of several proteins associated with the SWR1-like complex and with HAT2, the key factor of H2A.Z incorporation, is discussed.
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.
Chlamydia trachomatis (Ctr) can persist over extended times within their host cell and thereby establish chronic infections. One of the major inducers of chlamydial persistence is interferon-gamma (IFN-γ) released by immune cells as a mechanism of immune defence. IFN-γ activates the catabolic depletion of L-tryptophan (Trp) via indoleamine-2,3-dioxygenase (IDO), resulting in persistent Ctr. Here, we show that IFN-γ induces the downregulation of c-Myc, the key regulator of host cell metabolism, in a STAT1-dependent manner. Expression of c-Myc rescued Ctr from IFN-γ-induced persistence in cell lines and human fallopian tube organoids. Trp concentrations control c-Myc levels most likely via the PI3K-GSK3β axis. Unbiased metabolic analysis revealed that Ctr infection reprograms the host cell tricarboxylic acid (TCA) cycle to support pyrimidine biosynthesis. Addition of TCA cycle intermediates or pyrimidine/purine nucleosides to infected cells rescued Ctr from IFN-γ-induced persistence. Thus, our results challenge the longstanding hypothesis of Trp depletion through IDO as the major mechanism of IFN-γ-induced metabolic immune defence and significantly extends the understanding of the role of IFN-γ as a broad modulator of host cell metabolism.
Ultrastructural analysis of wild-type and RIM1α knockout active zones in a large cortical synapse
(2022)
Rab3A-interacting molecule (RIM) is crucial for fast Ca\(^{2+}\)-triggered synaptic vesicle (SV) release in presynaptic active zones (AZs). We investigated hippocampal giant mossy fiber bouton (MFB) AZ architecture in 3D using electron tomography of rapid cryo-immobilized acute brain slices in RIM1α\(^{−/−}\) and wild-type mice. In RIM1α\(^{−/−}\), AZs are larger with increased synaptic cleft widths and a 3-fold reduced number of tightly docked SVs (0–2 nm). The distance of tightly docked SVs to the AZ center is increased from 110 to 195 nm, and the width of their electron-dense material between outer SV membrane and AZ membrane is reduced. Furthermore, the SV pool in RIM1α\(^{−/−}\) is more heterogeneous. Thus, RIM1α, besides its role in tight SV docking, is crucial for synaptic architecture and vesicle pool organization in MFBs.
Background
Despite advances in treatment of patients with non-small cell lung cancer, carriers of certain genetic alterations are prone to failure. One such factor frequently mutated, is the tumor suppressor PTEN. These tumors are supposed to be more resistant to radiation, chemo- and immunotherapy.
Results
We demonstrate that loss of PTEN led to altered expression of transcriptional programs which directly regulate therapy resistance, resulting in establishment of radiation resistance. While PTEN-deficient tumor cells were not dependent on DNA-PK for IR resistance nor activated ATR during IR, they showed a significant dependence for the DNA damage kinase ATM. Pharmacologic inhibition of ATM, via KU-60019 and AZD1390 at non-toxic doses, restored and even synergized with IR in PTEN-deficient human and murine NSCLC cells as well in a multicellular organotypic ex vivo tumor model.
Conclusion
PTEN tumors are addicted to ATM to detect and repair radiation induced DNA damage. This creates an exploitable bottleneck. At least in cellulo and ex vivo we show that low concentration of ATM inhibitor is able to synergise with IR to treat PTEN-deficient tumors in genetically well-defined IR resistant lung cancer models.
To counteract insect decline, it is essential to understand the underlying causes, especially for key pollinators such as nocturnal moths whose ability to orientate can easily be influenced by ambient light conditions. These comprise natural light sources as well as artificial light, but their specific relevance for moth orientation is still unknown. We investigated the influence of moonlight on the reproductive behavior of privet hawkmoths (Sphinx ligustri) at a relatively dark site where the Milky Way was visible while the horizon was illuminated by distant light sources and skyglow. We show that male moths use the moon for orientation and reach females significantly faster with increasing moon elevation. Furthermore, the choice of flight direction depended on the cardinal position of the moon but not on the illumination of the horizon caused by artificial light, indicating that the moon plays a key role in the orientation of male moths.
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.