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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)
- Lehrstuhl für Physiologische Chemie (1)
- Zentrale Abteilung für Mikroskopie, Universität Würzburg (1)
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.
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.
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.
Since the advent of high-throughput sequencing technologies in the mid-2010s, RNA se-
quencing (RNA-seq) has been established as the method of choice for studying gene
expression. In comparison to microarray-based methods, which have mainly been used to
study gene expression before the rise of RNA-seq, RNA-seq is able to profile the entire
transcriptome of an organism without the need to predefine genes of interest. Today,
a wide variety of RNA-seq methods and protocols exist, including dual RNA sequenc-
ing (dual RNA-seq) and multi RNA sequencing (multi RNA-seq). Dual RNA-seq and
multi RNA-seq simultaneously investigate the transcriptomes of two or more species, re-
spectively. Therefore, the total RNA of all interacting species is sequenced together and
only separated in silico. Compared to conventional RNA-seq, which can only investi-
gate one species at a time, dual RNA-seq and multi RNA-seq analyses can connect the
transcriptome changes of the species being investigated and thus give a clearer picture of
the interspecies interactions. Dual RNA-seq and multi RNA-seq have been applied to a
variety of host-pathogen, mutualistic and commensal interaction systems.
We applied dual RNA-seq to a host-pathogen system of human mast cells and Staphylo-
coccus aureus (S. aureus). S. aureus, a commensal gram-positive bacterium, can become
an opportunistic pathogen and infect skin lesions of atopic dermatitis (AD) patients.
Among the first immune cells S. aureus encounters are mast cells, which have previously
been shown to be able to kill the bacteria by discharging antimicrobial products and re-
leasing extracellular traps made of protein and deoxyribonucleic acid (DNA). However,
S. aureus is known to evade the host’s immune response by internalizing within mast
cells. Our dual RNA-seq analysis of different infection settings revealed that mast cells
and S. aureus need physical contact to influence each other’s gene expression. We could
show that S. aureus cells internalizing within mast cells undergo profound transcriptome
changes to adjust their metabolism to survive in the intracellular niche. On the host side,
we found out that infected mast cells elicit a type-I interferon (IFN-I) response in an
autocrine manner and in a paracrine manner to non-infected bystander-cells. Our study
provides the first evidence that mast cells are capable to produce IFN-I upon infection
with a bacterial pathogen.
T-Zell-aktivierende Formate, wie BiTE (bispecific T-cell engagers) Antikörper und CAR T Zellen haben in den vergangen Jahren die Therapiemöglichkeiten für Tumorpatienten erweitert. Diese Therapeutika verknüpfen T-Zellen mit malignen Zellen über je ein spezifisches Oberflächenmolekül und initiieren, über eine T-Zell-vermittelte Immunantwort, die Lyse der Tumorzelle. Tumorspezifische Antigene sind jedoch selten. Häufig werden Proteine adressiert, die neben den Tumorzellen auch auf gesunden Zellen exprimiert werden. Die Folgen sind toxische Effekte abseits der Tumorzellen auf Antigen-positiven gesunden Zellen (on target/off tumor), welche nicht nur die Dosis des Therapeutikums und dessen Effektivität limitieren, sondern zu geringen bis letalen Begleiterscheinungen führen können. Der Bedarf an effektiven Therapieformen mit geringen Nebenwirkungen ist folglich immer noch sehr hoch. Diese Lücke soll durch ein neues Antikörperformat, sogenannten Hemibodies, geschlossen werden. Hemibodies sind eine neue Klasse von T-Zell-aktivierenden Antikörpern, die sich gegen eine Antigenkombination und nicht einzelne Antigene auf Tumorzellen richten. Sie bestehen aus zwei komplementären Molekülen mit je einer Antigen-bindenden Sequenz, die entweder mit der leichten (VL) oder der schweren (VH) Kette eines T-Zell-aktivierenden anti CD3 Antikörpers fusioniert ist. Nur wenn beide Hemibody-Fragmente gleichzeitig in unmittelbarer Nähe an ihr jeweiliges Antigenepitop auf der Tumorzelle binden, komplementieren die beiden Antikörperkonstrukte über das geteilte anti-CD3 und bilden einen trivalenten T Zell aktivierenden Komplex aus. Diese funktionale Einheit rekrutiert T-Zellen zur Tumorzelle und induzierte die T-Zell-vermittelte Lyse der malignen Zelle.
Im Rahmen der vorliegenden Arbeit wurden geeignete Antigenkombinationen identifiziert und die erste effektive und spezifische Hemibody-basierte Immuntherapie gegen das Multiple Myelom (MM), ohne Nebenwirkungen auf Antigen-einfach-positiven gesunden Zellen, entwickelt. Basierend auf einer umfangreichen Analyse von Kandidaten-Antigenen wurden Kombinationen aus bekannten MM Zielmolekülen, wie BCMA, CD38, CD138, CD229 und SLAMF7, und für das MM unbekannte Oberflächenmolekülen, wie CHRM5 und LAX1, untersucht. Gegen die vielversprechendsten Antigene wurden Hemibodies entwickelt und produziert. Im Zusammenhang mit Analysen zur Produzierbarkeit sowie biochemischen und funktionalen Charakterisierungen, konnte aus 75 initialen Hemibody-Kombinationen drei Kombinationen mit geeigneten Eigenschaften identifiziert werden. Die Bindung von zwei Hemibody-Partnern auf der Oberfläche der MM Zelle führte zur Ausbildung eines trivalenten T-Zell-rekrutierenden Komplexes. Dieser initiierte nachfolgend über eine T-Zell-vermittelte Immunantwort die spezifische Lyse der malignen Zellen, ohne die Viabilität von Antigen-einfach-positiven gesunden Körper- oder Effektor-Zellen zu beeinflussen. Zusätzlich führte eine Hemibody-Therapie in vivo in einem NOD SCID MM-Mausmodel innerhalb von 7 Tagen zur kompletten Remission der MM Zellen. Diese Daten zeigten Hemibodies als ein neues, sehr vielversprechendes Antikörperformat für eine effektive und tumorspezifische Immuntherapie mit potentiell geringen Nebenwirkungen.
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.
Cellular growth and proliferation are among the most important processes for cells and
organisms. One of the major determinants of these processes is the amount of proteins
and consequently also the amount of ribosomes. Their synthesis involves several hundred
proteins and four different ribosomal RNA species, is highly coordinated and very
energy-demanding. However, the molecular mechanims of transcriptional regulation of
the protein-coding genes involved, is only poorly understood in mammals.
In this thesis, unbiased genome-wide knockout reporter screens were performed, aiming
to identify previously unknown transcriptional regulators of ribosome biogenesis
factors (RiBis), which are important for the assembly and maturation of ribosomes,
and ribosomal proteins (RPs), which are ribosomal components themself. With that
approach and follow-up (validation) experiments, ALDOA and RBM8A among others,
could be identified as regulators of ribosome biogenesis.
Depletion of the glycolytic enzyme ALDOA led to a downregulation of RiBi- and RPpromoter
driven reporters on protein and transcript level, as well as to a downregulation
of ribosome biogenesis gene transcripts and of mRNAs of other genes important for
proliferation.
Reducing the amount of the exon junction complex protein RBM8A, led to a more prominent
downregulation of one of the fluorescent reporters, but this regulation was independent
of the promoter driving the expression of the reporter. However, acute protein
depletion experiments in combination with nascent RNA sequencing (4sU-Seq)
revealed, that mainly cytosolic ribosomal proteins (CRPs) were downregulated upon
acute RBM8A withdrawal. ChIP experiments showed RBM8A binding to promoters of
RP genes, but also to other chromatin regions. Total POL II or elongating and initiating
POL II levels were not altered upon acute RBM8A depletion.
These data provide a starting point for further research on the mechanisms of transcriptional
regulation of RP and RiBi genes in mammals.
Einflüsse der Photophysik und Photochemie von Cyaninfarbstoffen auf die Lokalisationsmikroskopie
(2023)
In den letzten Jahren haben sich hochauflösende Fluoreszenzmikroskopiemethoden, basierend auf der Lokalisation einzelner Fluorophore, zu einem leistungsstarken Werkzeug etabliert, um Fluoreszenzbilder weit unterhalb der Auflösungsgrenze zu generieren. Hiermit können räumliche Auflösungen von ~ 20 nm erzielt werden, was weit unterhalb der Beugungsgrenze liegt. Dabei haben zahlreiche Optimierungen und Entwicklungen neuer Methoden in der Einzelmolekül-Lokalisationsmikroskopie die Genauigkeit der orstspezifischen Bestimmung einzelner Fluorophore auf bis zu ~ 1 – 3 nm erhöht. Eine Auflösung im molekularen Bereich, weit unterhalb von ~ 10 nm bleibt allerdings herausfordernd, da die Lokalisationsgenauigkeit nur ein Kriterium hierfür ist. Allerdings wurde sich in den letzten Jahren überwiegend auf die Verbesserung dieses Parameters konzentriert. Weitere Kriterien für die fluoreszenzmikroskopische Auflösung sind dabei unter anderem die Markierungsdichte und die Kopplungseffizienz der Zielstruktur, sowie der Kopplungsfehler (Abstand zur Zielstruktur nach Farbstoffkopplung), die sich herausfordernd für eine molekulare Auflösung darstellen. Auch wenn die Kopplungseffizienz und -dichte hoch und der Kopplungsfehler gering ist, steigt bei Interfluorophordistanzen < 5nm, abhängig von den Farbstoffen, die Wahrscheinlichkeit von starken und schwachen Farbstoffwechselwirkungen und damit von Energieübertragungsprozessen zwischen den Farbstoffen, stark an. Daneben sollten Farbstoffe, abhänging von der Lokalisationsmikroskopiemethode, spezifische Kriterien, wie beispielsweise die Photoschaltbarkeit bei dSTORM, erfüllen, was dazu führt, dass diese Methoden häufig nur auf einzelne Farbstoffe beschränkt sind. In dieser Arbeit konnte mithilfe von definierten DNA-Origami Konstrukten gezeigt werden, dass das Blinkverhalten von Cyaninfarbstoffen unter dSTORM-Bedingungen einer Abstandsabhängigkeit aufgrund von spezifischen Energieübertragungsprozessen folgt, womit Farbstoffabstände im sub-10 nm Bereich charakterisiert werden konnten. Darüber hinaus konnte diese Abstandsabhängigkeit an biologischen Proben gezeigt werden. Hierbei konnten verschiedene zelluläre Rezeptoren effizient und mit geringem Abstandsfehler zur Zielstruktur mit Cyaninfarbstoffen gekoppelt werden. Diese abstandsabhänigen Prozesse und damit Charakterisierungen könnten dabei nicht nur spezifisch für die häufig unter dSTORM-Bedingungen verwendeten Cyaninfarbstoffen gültig sein, sondern auch auf andere Farbstoffklassen, die einen Auszustand zeigen, übertragbar sein. Darüber hinaus konnte gezeigt werden, dass hochauflösende dSTORM Aufnahmen unabhängig vom Farbstoffkopplungsgrad der Antikörpern sind, welche häufig für Standardfärbungen von zellulären Strukturen verwendet werden. Dabei konnte durch Photonenkoinzidenzmessungen dargelegt werden, dass aufgrund komplexer Farbstoffwechselwirkungen im Mittel nur ein Farbstoff aktiv ist, wobei höhere Kopplungsgrade ein komplexes Blinkverhalten zu Beginn der Messung zeigen. Durch die undefinierten Farbstoffabstände an Antikörpern konnte hier kein eindeutiger Energieübertragungsmechanismus entschlüsselt werden. Dennoch konnte gezeigt werden, dass Farbstoffaggregate bzw. H-Dimere unter dSTORM-Bedingungen destabilisiert werden. Durch die zuvor erwähnten DNA-Origami Konstrukte definierter Interfluorophordistanzen konnten Energieübertragungsmechanismen entschlüsselt werden, die auch für die Antikörper diverser Kopplungsgrade gültig sind. Des Weiteren konnten, ausgelöst durch komplexe Energieübertragungsprozesse höherer Kopplungsgrade am Antikörper, Mehrfarbenaufnahmen zellulärer Strukturen generiert werden, die über die spezifische Fluoreszenzlebenszeit separiert werden konnten. Dies stellt hier eine weitere Möglichkeit dar, unter einfachen Bedingungen, schnelle Mehrfarbenaufnahmen zellulärer Strukturen zu generieren. Durch die Verwendung des selben Farbstoffes unterschiedlicher Kopplungsgrade kann hier nur mit einer Anregungswellenlänge und frei von chromatischer Aberration gearbeitet werden. Neben den photophysikalischen Untersuchungen der Cyaninfarbstoffe Cy5 und Alexa Fluor 647 wurden diese ebenso photochemisch näher betrachtet. Dabei konnte ein neuartiger chemischer Mechanismus entschlüsselt werden. Dieser Mechanismus führt, ausgelöst durch Singulett-Sauerstoff (1O2), zu einer Photozerschneidung des konjugierten Doppelbindungssystems um zwei Kohlenstoffatome, was zu strukturellen und spektroskopischen Veränderungen dieser Farbstoffe führt. Auf Grundlage dieses Mechanismus konnte eine neue DNA-PAINT Methode entwickelt werden, die zu einer Beschleunigung der Aufnahmezeit führt.
Die Rolle transposabler Elemente in der Genese des malignen Melanom im Fischmodell Xiphophorus
(2023)
Der Name der transposablen Elemente beruht auf ihrer Fähigkeit, ihre genomische Position verändern zu können. Durch Chromosomenaberrationen, Insertionen oder Deletionen können ihre genomischen Transpositionen genetische Instabilität verursachen. Inwieweit sie darüber hinaus regulatorischen Einfluss auf Zellfunktionen besitzen, ist Gegenstand aktueller Forschung ebenso wie die daraus resultierende Frage nach der Gesamtheit ihrer biologischen Signifikanz. Die Weiterführung experimenteller Forschung ist unabdingbar, um weiterhin offenen Fragen nachzugehen. Das Xiphophorus-Melanom-Modell stellt hierbei eines der ältesten Tiermodelle zur Erforschung des malignen Melanoms dar. Durch den klar definierten genetischen Hintergrund eignet es sich hervorragend zur Erforschung des bösartigen schwarzen Hautkrebses, welcher nach wie vor die tödlichste aller bekannten Hautkrebsformen darstellt. Die hier vorliegende Arbeit beschäftigt sich mit der Rolle transposabler Elemente in der malignen Melanomgenese von Xiphophorus.