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Die Regulation der Genexpression steht am Anfang vieler zellbiologischer Prozesse wie beispielsweise dem Zellwachstum oder der Differenzierung. Gene werden an Promotoren transkribiert, wobei ein Promotor selbst aus vielen logischen Einheiten aufgebaut ist, den Transkriptionsfaktorbindestellen (TFBSs). Diese können sehr nah beieinander liegen, aber auch weit entfernt voneinander sein. Sie werden spezifisch von Transkriptionsfaktoren (TFs) gebunden, die die Transkritptionsrate z.B. verstärken (Enhancer) oder schwächen (Silencer) können. Zwei oder mehr dieser TFBSs mit bestimmtem Abstand werden als "Module" zusammengefasst, die über Spezies hinweg konserviert sein können. Typischerweise findet man Module in Zellen mit einem Zellkern. Spezies mit gemeinsamen Modulen können ein Hinweis auf die gemeinsame phylogenetische Abstammung darstellen, aber auch gemeinsame Funktionsmechanismen von TFs über Gene hinweg aufdecken. Heutzutage sind verschiedene Anwendungen verfügbar, mit denen nach TFBSs in DNA gesucht werden kann. Zum Zeitpunkt des Verfassens dieser Arbeit sind aber nur zwei kommerzielle Produkte bekannt, die nicht nur TFBSs, sondern auch Module erkennen. Deshalb stellen wir hier die freie und quelloffene Lösung "AIModules" vor, die diese Lücke füllt und einen Webservice zur Verfügung stellt, der es erlaubt nach TFBSs sowie nach Modulen auf DNA- und auf RNA-Abschnitten zu suchen. Für die Motivesuche werden entweder Matrizen aus der Jaspar Datenbank oder Matrizen vom Anwender verwendet. Darüberhinaus zeigen wir, dass unser Tool für die TF Suche nur Sekunden benötigt, wohingegen conTraV3 mindestens eine Stunde für dieselbe Analyse braucht. Zusätzlich kann der Anwender bei unserem Tool den Grad der Konserviertheit für TFs mit angeben und wir zeigen, dass wir mit unserer Lösung, die die Jaspar Datenbank heranzieht, mehr Module finden, als ein kommerziell verfügbares Produkt. Weiterhin kann mit unserer Lösung auch auf RNA-Sequenzen nach regulatorischen Motiven gesucht werden, wenn der Anwender die dafür nötigen Matrizen liefert. Wir zeigen dies am Beispiel von Polyadenylierungsstellen. Zusammenfassend stellen wir ein Werkzeug vor, das erstens frei und quelloffen ist und zweitens entweder auf Servern veröffentlicht werden kann oder On-Site auf einem Notebook läuft. Unser Tool erlaubt es Promotoren zu analysieren und nach konservierten Modulen sowie TFBSs in Genfamilien sowie nach regulatorischen Elementen in mRNA wie z.B. Polyadenylierungsstellen oder andere regulatorische Elemente wie beispielsweise Enhancern oder Silencern in genomischer DNA zu suchen.
Die Identifikation der Bindungsspezifitäten von Proteininteraktionsdomänen und damit letztlich auch die Fähigkeit potentielle Bindungspartner dieser in vivo vorherzusagen bildet ein grundlegendes Element für das Verständnis der biologischen Funktionen dieser Domänen. In dieser Arbeit wurde untersucht, inwieweit solche Vorhersagen bezüglich der SH3-Domäne – als Beispiel für eine Proteininteraktionsdomäne – mithilfe von Support-Vector-Machines (SVMs) möglich sind, wenn diesen als Informationsquelle ausschließlich die innerhalb der Aminosäuresequenz der Domäne konservierten Informationen zur Verfügung stehen. Um den SVM-basierten Klassifikator zu trainieren und zu validieren, wurde ein Satz aus 51 SH3-Domänen verwendet, die zuvor entsprechend ihrer Ligandenpräferenz in ein System aus acht verschiedenen Klassen eingeteilt worden waren. Da die innerhalb der Aminosäuresequenzen konservierten Informationen in abstrakte Zahlenwerte konvertiert werden mussten (Voraussetzung für mathematisch basierte Klassifikatoren wie SVMs), wurde jede Aminosäuresequenz durch ihren jeweiligen Fisher-Score-Vektor ausgedrückt. Die Ergebnisse erbrachten einen Klassifikationserror, welcher weit unterhalb des Zufallsniveaus lag, was darauf hindeutet, dass sich die Bindungsspezifität (Klasse) einer SH3-Domäne in der Tat von seiner Aminosäuresequenz ableiten lassen dürfte. Mithilfe klassenspezifisch emittierter, artifizieller Sequenzen, implementiert in den Trainingsprozess des Klassifikators, um etwaigen nachteiligen Auswirkungen von Overfitting zu entgegenzuwirken, sowie durch Berücksichtigung taxonomischer Informationen des Klassensystems während Training und Validierung, ließ sich der Klassifikationserror sogar noch weiter senken und lag schließlich bei lediglich 35,29% (vergleiche Zufall: 7/8 = 87.50%). Auch die Nutzung von Feature Selections zur Abmilderung Overfitting-bedingter, negativer Effekte lieferte recht vielversprechende Ergebnisse, wenngleich ihr volles Potential aufgrund von Software-Beschränkungen nicht ausgenutzt werden konnte.
Die Analyse der Positionen im Sequence-Alignment, welche für den SVM- basierten Klassifikator am relevantesten waren, zeigte, dass diese häufig mit Positionen korrelierten, von denen angenommen wird auch in vivo eine Schlüsselrolle bei der Determination der Bindungsspezifität (Klasse) zu spielen. Dies unterstreicht nicht nur die Reliabilität des präsentierten Klassifikators, es gibt auch Grund zur Annahme, dass das Verfahren möglicherweise auch als Supplement anderer Ansätze genutzt werden könnte, welche zum Ziel haben die Positionen zu identifizieren, die die Ligandenpräferenz in vivo determinieren. Informationen, die nicht nur für ein besseres Verständnis der SH3-Domäne (und möglicherweise auch anderer Proteininteraktionsdomänen) von grundlegender Bedeutung sind, sondern auch aus pharmakologischer Sicht von großem Interesse sein dürften.
Copy number variations (CNVs) of the KITLG gene seem to be involved in the oncogenesis of digital squamous cell carcinoma (dSCC). The aims of this study were (1) to investigate KITLG CNV in giant (GS), standard (SS), and miniature (MS) schnauzers and (2) to compare KITLG CNV between black GS with and without dSCC. Blood samples from black GS (22 with and 17 without dSCC), black SS (18 with and 4 without dSSC; 5 unknown), and 50 MS (unknown dSSC status and coat colour) were analysed by digital droplet PCR. The results are that (1) most dogs had a copy number (CN) value > 4 (range 2.5–7.6) with no significant differences between GS, SS, and MS, and (2) the CN value in black GS with dSCC was significantly higher than in those without dSCC (p = 0.02). CN values > 5.8 indicate a significantly increased risk for dSCC, while CN values < 4.7 suggest a reduced risk for dSCC (grey area: 4.7–5.8). Diagnostic testing for KITLG CNV may sensitise owners to the individual risk of their black GS for dSCC. Further studies should investigate the relevance of KITLG CNV in SS and the protective effects in MS, who rarely suffer from dSCC.
The interaction of synaptic proteins orchestrate the function of one of the most complex organs, the brain. The multitude of molecular elements influencing neurological correlations makes imaging processes complicated since conventional fluorescence microscopy methods are unable to resolve structures beyond the diffraction-limit.
The implementation of super-resolution fluorescence microscopy into the field of neuroscience allows the visualisation of the fine details of neural connectivity. The key element of my thesis is the super-resolution technique dSTORM (direct Stochastic Optical Reconstruction Microscopy) and its optimisation as a multi-colour approach. Capturing more than one target, I aim to unravel the distribution of synaptic proteins with nanometer precision and set them into a structural and quantitative context with one another. Therefore dSTORM specific protocols are optimized to serve the peculiarities of particular neural samples.
In one project the brain derived neurotrophic factor (BDNF) is investigated in primary, hippocampal neurons. With a precision beyond 15 nm, preand post-synaptic sites can be identified by staining the active zone proteins bassoon and homer. As a result, hallmarks of mature synapses can be exhibited. The single molecule sensitivity of dSTORM enables the measurement of endogenous BDNF and locates BDNF granules aligned with glutamatergic pre-synapses. This data proofs that hippocampal neurons are capable of enriching BDNF within the mature glutamatergic pre-synapse, possibly influencing synaptic plasticity.
The distribution of the metabotropic glutamate receptor mGlu4 is investigated in physiological brain slices enabling the analysis of the receptor in its natural environment. With dual-colour dSTORM, the spatial arrangement of the mGlu4 receptor in the pre-synaptic sites of parallel fibres in the molecular layer of the mouse cerebellum is visualized, as well as a four to six-fold increase in the density of the receptor in the active zone compared to the nearby environment. Prior functional measurements show that metabotropic glutamate receptors influence voltage-gated calcium channels and proteins that are involved in synaptic vesicle priming. Corresponding dSTORM data indeed suggests that a subset of the mGlu4 receptor is correlated with the voltage-gated calcium channel Cav2.1 on distances around 60 nm.
These results are based on the improvement of the direct analysis of localisation data. Tools like coordinated based correlation analysis and nearest neighbour analysis of clusters centroids are used complementary to map protein connections of the synapse. Limits and possible improvements of these tools are discussed to foster the quantitative analysis of single molecule localisation microscopy data.
Performing super-resolution microscopy on complex samples like brain slices benefits from a maximised field of view in combination with the visualisation of more than two targets to set the protein of interest in a cellular context. This challenge served as a motivation to establish a workflow for correlated structured illumination microscopy (SIM) and dSTORM. The development of the visualisation software coSIdSTORM promotes the combination of these powerful super-resolution techniques even on separated setups. As an example, synapses in the cerebellum that are affiliated to the parallel fibres and the dendrites of the Purkinje cells are identified by SIM and the protein bassoon of those pre-synapses is visualised threedimensionally with nanoscopic precision by dSTORM.
In this work I placed emphasis on the improvement of multi-colour super-resolution imaging and its analysing tools to enable the investigation of synaptic proteins. The unravelling of the structural arrangement of investigated proteins supports the building of a synapse model and therefore helps to understand the relation between structure and function in neural transmission processes.
Chlamydia trachomatis is the main cause of sexually transmitted diseases worldwide. As obligate intracellular bacteria Chlamydia replicate in a membrane bound vacuole called inclusion and acquire nutrients for growth and replication from their host cells. However, like all intracellular bacteria, Chlamydia have to prevent eradication by the host's cell autonomous system. The chlamydial deubiquitinase Cdu1 is secreted into the inclusion membrane, facing the host cell cytosol where it deubiquitinates cellular proteins. Here we show that inactivation of Cdu1 causes a growth defect of C. trachomatis in primary cells. Moreover, ubiquitin and several autophagy receptors are recruited to the inclusion membrane of Cdu1‐deficient Chlamydia . Interestingly, the growth defect of cdu1 mutants is not rescued when autophagy is prevented. We find reduced recruitment of Golgi vesicles to the inclusion of Cdu1 mutants indicating that vesicular trafficking is altered in bacteria without active deubiquitinase (DUB). Our work elucidates an important role of Cdu1 in the functional preservation of the chlamydial inclusion surface.
The human pathogen Chlamydia trachomatis is the main cause of sexually transmitted infections worldwide. The obligate intracellular bacteria are the causative agent of several diseases that reach from conjunctivitis causing trachoma and blindness as well as salpingitis and urethritis which can lead to infertility if left untreated.
In order to gain genetically engineered Chlamydia that inducible knock down specific gene expression, the CRISPRi system was established in C. trachomatis. In a proof of principle experiment it was shown that C. trachomatis pCRISPRi:gCdu1III target ChlaDUB1 expression and reduce the protein amount up to 50 %. Knock-down of the DUB did not influence protein levels of anti-apoptotic Mcl-1 and did not make cells susceptible for apoptosis. However, reduced dCas9 protein size, bacterial growth impairment and off target effects interfering with the GFP signal, form obstacles in CRISPRi system in Chlamydia. For routinely use of the CRISPRi method in C. trachomatis further investigation is needed.
Since the bacterial life cycle includes two morphological and functional distinct forms, it is essential for chlamydial spread to complete the development cycle and form infectious progeny. Therefore, Chlamydia has evolved strategies to evade the host immune system in order to stay undetected throughout the developmental cycle. The bacteria prevent host cell apoptosis via stabilization of anti-apoptotic proteins like Mcl-1, Survivin and HIF-1α and activate pro-survival pathways, inhibiting invasion of immune cells to the site of infection. The host cell itself can destroy intruders via cell specific defense systems that involve autophagy and recruitment of professional immune cells. In this thesis the role of the chlamydial deubiuqitinase ChlaDUB1 upon immune evasion was elucidated. With the mutant strain Ctr Tn-cdu1 that encodes for a truncated DUB due to transposon insertion, it was possible to identify ChlaDUB1 as a potent opponent of the autophagic system. Mutant inclusions were targeted by K48 and K63 chain ubiquitination. Subsequently the inclusion was recognized by autophagic receptors like p62, NBR1 and NDP52 that was reversed again by complementation with the active DUB. Xenophagy was promoted so far as LC3 positive phagosomes formed around the inclusion of Ctr Tn-cdu1, which did not fuse with the lysosome. The detected growth defect in human primary cells of Chlamydia missing the active DUB was not traced back to autophagy, but was due to impaired development and replication. It was possible to identify Ankib1, the E3 ligase, that ubiquitinates the chlamydial inclusion in a siRNA based screen. The activating enzyme Ube1 and the conjugating enzyme Ube2L3 are also essential in this process. Chlamydia have a reduced genome and depend on lipids and nutrients that are translocated from the host cell to the inclusion to proliferate. Recruitment of fragmented Golgi stacks to the inclusion surface was prevented when ChlaDUB1 was inactive, probably causing diminished bacterial growth. Additionally, the modification of the inclusion by Ankib1 and subsequent decoration by autophagic markers was not only present in human but also murine cells. Comparison of other Chlamydia strains and species revealed Ankib1 to be located at the proximity of the inclusion in C. trachomatis strains only but not in C. muridarum or C. pneumoniae, indicating that Ankib1 is specifically the E3 ligase of C. trachomatis. Moreover, the role of ChlaDUB1 in infected tissue was of interest, since ChlaDUB1 protein was also found in early EB stage and so might get in contact with invading immune cells after cell lysis. While bacteria spread and infect new host cells, Chlamydia can also infect immune cells. Infection of human neutrophils with Ctr Tn-cdu1 shows less bacterial survival and affirms the importance of the DUB for bacterial fitness in these cells.
Stapylococcus aureus colonises the nose of healthy individuals but can also cause a wide range of infections. Amino acid (AA) synthesis and their availability is crucial to adapt to conditions encountered in vivo. Most S. aureus genomes comprise all genes required for AA biosynthesis. Nevertheless, different strains require specific sets of AAs for growth. In this study we show that regulation inactivates pathways under certain conditions which result in these observed auxotrophies. We analyzed in vitro and modeled in silico in a Boolean semiquantitative model (195 nodes, 320 edges) the regulatory impact of stringent response (SR) on AA requirement in S. aureus HG001 (wild-type) and in mutant strains lacking the metabolic regulators RSH, CodY and CcpA, respectively. Growth in medium lacking single AAs was analyzed. Results correlated qualitatively to the in silico predictions of the final model in 92% and quantitatively in 81%. Remaining gaps in our knowledge are evaluated and discussed. This in silico model is made fully available and explains how integration of different inputs is achieved in SR and AA metabolism of S. aureus. The in vitro data and in silico modeling stress the role of SR and central regulators such as CodY for AA metabolisms in S. aureus.
Animals acquire predictive values of sensory stimuli through reinforcement. In the brain of Drosophila melanogaster, activation of two types of dopamine neurons in the PAM and PPL1 clusters has been shown to induce aversive odor memory. Here, we identified the third cell type and characterized aversive memories induced by these dopamine neurons. These three dopamine pathways all project to the mushroom body but terminate in the spatially segregated subdomains. To understand the functional difference of these dopamine pathways in electric shock reinforcement, we blocked each one of them during memory acquisition. We found that all three pathways partially contribute to electric shock memory. Notably, the memories mediated by these neurons differed in temporal stability. Furthermore, combinatorial activation of two of these pathways revealed significant interaction of individual memory components rather than their simple summation. These results cast light on a cellular mechanism by which a noxious event induces different dopamine signals to a single brain structure to synthesize an aversive memory.
This thesis consists of three major chapters, each of which has been separately published or under the process for publication. The first chapter is about anatomical characterization of the mushroom body of adult Drosophila melanogaster. The mushroom body is the center for olfactory learning and many other functions in the insect brains. The functions of the mushroom body have been studied by utilizing the GAL4/UAS gene expression system. The present study characterized the expression patterns of the commonly used GAL4 drivers for the mushroom body intrinsic neurons, Kenyon cells. Thereby, we revealed the numerical composition of the different types of Kenyon cells and found one subtype of the Kenyon cells that have not been described. The second and third chapters together demonstrate that the multiple types of dopaminergic neurons mediate the aversive reinforcement signals to the mushroom body. They induce the parallel memory traces that constitute the different temporal domains of the aversive odor memory. In prior to these chapters, “General introduction and discussion” section reviews and discuss about the current understanding of neuronal circuit for olfactory learning in Drosophila.