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- Graduate School of Life Sciences (29) (entfernen)
Sonstige beteiligte Institutionen
- Biomedical Center Munich, Department of Physiological Chemistry, Ludwig-Maximilians-Universität München (1)
- Chair of Experimental Biomedicine I (1)
- Department of Veterinary Sciences, Experimental Parasitology, Ludwig-Maximilians-Universität München (1)
- GEOMAR Helmholtz-Zentrum für Ozeanforschung Kiel (1)
- Research Center for Infectious Diseases, University of Würzburg (1)
- University of Stellenbosch, Division of Medical Virology (1)
Introduction.
Mobile health (mHealth) integrates mobile devices into healthcare, enabling remote monitoring, data collection, and personalized interventions. Machine Learning (ML), a subfield of Artificial Intelligence (AI), can use mHealth data to confirm or extend domain knowledge by finding associations within the data, i.e., with the goal of improving healthcare decisions. In this work, two data collection techniques were used for mHealth data fed into ML systems: Mobile Crowdsensing (MCS), which is a collaborative data gathering approach, and Ecological Momentary Assessments (EMA), which capture real-time individual experiences within the individual’s common environments using questionnaires and sensors. We collected EMA and MCS data on tinnitus and COVID-19. About 15 % of the world’s population suffers from tinnitus.
Materials & Methods.
This thesis investigates the challenges of ML systems when using MCS and EMA data. It asks: How can ML confirm or broad domain knowledge? Domain knowledge refers to expertise and understanding in a specific field, gained through experience and education. Are ML systems always superior to simple heuristics and if yes, how can one reach explainable AI (XAI) in the presence of mHealth data? An XAI method enables a human to understand why a model makes certain predictions. Finally, which guidelines can be beneficial for the use of ML within the mHealth domain? In tinnitus research, ML discerns gender, temperature, and season-related variations among patients. In the realm of COVID-19, we collaboratively designed a COVID-19 check app for public education, incorporating EMA data to offer informative feedback on COVID-19-related matters. This thesis uses seven EMA datasets with more than 250,000 assessments. Our analyses revealed a set of challenges: App user over-representation, time gaps, identity ambiguity, and operating system specific rounding errors, among others. Our systematic review of 450 medical studies assessed prior utilization of XAI methods.
Results.
ML models predict gender and tinnitus perception, validating gender-linked tinnitus disparities. Using season and temperature to predict tinnitus shows the association of these variables with tinnitus. Multiple assessments of one app user can constitute a group. Neglecting these groups in data sets leads to model overfitting. In select instances, heuristics outperform ML models, highlighting the need for domain expert consultation to unveil hidden groups or find simple heuristics.
Conclusion.
This thesis suggests guidelines for mHealth related data analyses and improves estimates for ML performance. Close communication with medical domain experts to identify latent user subsets and incremental benefits of ML is essential.
LIM and SH3 protein 1 (LASP1) is a nucleocytoplasmic scaffolding protein. LASP1 interacts with various cytoskeletal proteins via its domain structure and is known to participate in physiological processes of cells. In the present study, a detailed investigation of the expression pattern of LASP1 protein in normal skin, melanocytic nevi and melanoma was carried out and the melanocyte–specific function of LASP1 was analyzed. LASP1 protein was identified in stratum basale of skin epidermis and a very high level was detected in nevi, the benign tumor of melanocyte. In the highly proliferative basal cells, an additional distinct nuclear localization of the protein was noted. In different tumor entities, an elevated LASP1 expression and nuclear localization, correlated positively with malignancy and tumor grade. However, LASP1 level was determined to be very low in melanoma and even reduced in metastases. Melanoma is distinguished as the first tumor tested to date – that displayed an absence of elevated LASP1 expression. In addition no significant relation was observed between LASP1 protein expression and clinicopathological parameters in melanoma.
The epidermal melanin unit of skin comprises of melanocytes and keratinocytes. Melanocytes are specialized cells that synthesize the photo protective coloring pigment, melanin inside unique organelles called melanosomes. The presence of LASP1 in melanocytes is reported for the first time through this study and the existence was confirmed by immunoblotting analysis in cultured normal human epidermal melanocyte (NHEM) and in melanoma cell lines, along with the immunohistostaining imaging in normal skin and in melanocytic nevi. LASP1 depletion in MaMel2 cells revealed a moderate increase in the intracellular melanin level independently of de novo melanogenesis, pointing to a partial hindrance in melanin release. Immunofluorescence images of NHEM and MaMel2 cells visualized co-localization of LASP1 with dynamin and tyrosinase concomitant with melanosomes at the dendrite tips of the cells. Melanosome isolation experiments by sucrose density gradient centrifugation clearly demonstrated the presence of LASP1 and the melanosome specific markers tyrosinase and TRP1 in late stage melanosomes.
The study identified LASP1 and dynamin as novel binding partners in melanocytes and provides first evidence for the existence of LASP1 and dynamin (a protein well–known for its involvement in vesicle formation and budding) in melanosomes. Co-localization of LASP1 and dynamin along the dendrites and at the tips of the melanocytes indicates a potential participation of the two proteins in the membrane vesicle fission at the plasma membrane.
In summary, a possible involvement of LASP1 in the actin–dynamin mediated membrane fission and exocytosis of melanin laden melanosome vesicles into the extracellular matrix is suggested.
The platelet cytoskeleton ensures normal size and discoid shape under resting conditions and undergoes immediate reorganization in response to changes in the extracellular environment through integrin-based adhesion sites, resulting in actomyosin-mediated contractile forces. Mutations in the contractile protein non-muscle myosin heavy chain IIA display, among others, macrothrombocytopenia and a mild to moderate bleeding tendency in human patients. It is insufficiently understood which factors contribute to the hemostatic defect found in MYH9-related disease patients. Therefore, a better understanding of the underlying biophysical mechanisms in thrombus formation and stabilization is warranted.
This thesis demonstrates that an amino acid exchange at the positions 702, 1424 and 1841 in the heavy chain of the contractile protein non-muscle myosin IIA, caused by heterozygous point mutations in the gene, resulted in macrothrombocytopenia and increased bleeding in mice, reflecting the clinical hallmark of the MYH9-related disease in human patients. Basic characterization of biological functions of Myh9 mutant platelets revealed overall normal surface glycoprotein expression and agonist-induced activation when compared to wildtype platelets. However, myosin light chain phosphorylation after thrombin-activation was reduced in mutant platelets, resulting in less contractile forces and a defect in clot retraction. Altered biophysical characteristics with lower adhesion and interaction forces of Myh9 mutant platelets led to reduced thrombus formation and stability. Platelets from patients with the respective mutations recapitulated the findings obtained with murine platelets, such as impaired thrombus formation and stiffness.
Besides biological and biophysical characterization of mutant platelets from mice and men, treatment options were investigated to prevent increased bleeding caused by reduced platelet forces. The antifibrinolytic agent tranexamic acid was applied to stabilize less compact thrombi, which are presumably more vulnerable to fibrinolysis. The hemostatic function in Myh9 mutant mice was improved by interfering with the fibrinolytic system. These results show the beneficial effect of fibrin stabilization to reduce bleeding in MYH9-related disease.
Background: Integrase strand transfer inhibitors (INSTIs) are the latest addition to the array of antiretroviral compounds used to treat an infection with Human Immunodeficiency Virus (HIV). Due to their high efficacy and increased tolerability, INSTIs have become an integral part of first-line therapy in most high-income countries over the past years. However, little is known about HIV-1’s genetic inter- and intra-subtype diversity on the Integrase (IN)-gene and its impact on the emergence of INSTI-resistance. In the absence of a functional cure, long-term efficacy of first-line compounds remains paramount for reducing virological failure and curbing on-going HIV transmissions. South Africa, harbouring more than 20% of the global HIV burden (7.7 / 37.9 million people), requires international attention in order to globally pursue UNAIDS’ (Joint United Nations Programme on HIV/AIDS) 90-90-90 goals and the road to ending the HIV/AIDS (Acquired immunodeficiency syndrome) pandemic by 2030.
Methods: In this study, the prevalence of INSTI-resistance associated mutations (RAM) was investigated in a cohort of 169 archived drug-naïve blood samples from multiple collection sites around Cape Town, South Africa. Viral RNA was isolated from plasma samples, the integrase fragment amplified by RT-PCR and subsequently sequenced by Sanger-sequencing. Additionally, all publicly available drug-naïve, South African IN sequences, isolated before the availability of the first INSTIs in 2007, were retrieved from the Los Alamos HIV sequence database (n=284). All sequences were analysed for RAMs using the Stanford HIV Drug resistance database. The identification of polymorphism in the South African subtype C IN consensus sequence allowed for comparative analyses with global subtype B, as well as subtype C sequences, from countries other than South Africa.
Results: The IN gene could be amplified and sequenced in 95/169 samples (56%). Phylogenetic inference revealed close homology between three sequence-pairs, warranting the exclusion of 3/95 sequences from further analyses. Of the 92 samples used for mutational analyses, 86/92 (93.5%) belonged to subtype C, 5/92 (5.4%) to subtype B and 1/92 (1.1%) to subtype A. The prevalence of major and accessory INSTI RAMs was 0/92 (0%) and 1/91 (1.1%), respectively, similar to the observed rates of 8/284 (2.8%) and 8/284 (2.8%) in the database sequences (p = 0.2076 and p = 0.6944, Fisher’s exact test). Compared to subtype B IN sequences, 15 polymorphisms were significantly enriched in South African subtype C sequences (corrected p<0.0015. Fisher’s exact test, Bonferroni post-hoc procedure).
Compared to subtype C IN sequences isolated outside South Africa, four polymorphisms were significantly enriched in this study cohort (corrected p<0.0014, Fisher’s exact test, Bonferroni post-hoc procedure). The highest prevalence margin was observed for the polymorphism Met50Ile being present in 60.1% of South African subtype C sequences, compared to 37% in non-South African subtype C sequences.
Conclusions: The low prevalence of major and minor RAMs in all South African Integrase sequences predicts a high susceptibility to INSTIs, however, the presence of natural polymorphisms, in particular Met50Ile, in the majority of sequences warrants further monitoring under therapeutic pressure, as their role in mutational pathways leading to INSTI- resistance is yet to be determined. Additionally, this study revealed the presence of substantial inter- and intra-subtype diversity within the HIV-1 Subtype C IN-gene. These results implicate the need for more research on a regional, potentially patient-specific level, as mutational insights from other diverse backgrounds may not accurately represent the South African context. The implementation of a national pre-treatment INSTI-resistance screening program may provide necessary insights into the development of mutational pathways leading to INSTI-resistance under therapeutic pressure for the South African context and thereby bring South Africa one step closer to achieving UNAIDS 90-90-90 goals and ending the AIDS epidemic by 2030.
Kritische Knochendefekte stellen heutzutage ein ungelöstes Problem in der klinischen Praxis dar, da die verfügbaren prothetischen Optionen oft die mechanische Anpassung an das Gewebe nicht gewährleisten oder zu wichtigen immunologischen und Implantat-bedingten Komplikationen führen.
In diesem Kontext ermöglichen Tissue Engineering-Ansätze neue Strategien, um in vitro Zell-Material Interaktionen zu untersuchen und so die Implantatmaterialien zu optimieren.
In dieser Arbeit habe ich Zell-Material Interaktionen eines neuen Kollagen-basierten Scaffolds untersucht, das langfristig als Trägerstruktur für eine zellbasierte Therapie für kritische Knochendefekte entwickelt werden soll. Im Rahmen der Dissertation konnte ich belegen, dass die Kollagen-basierten makroporöse Mikrocarrier für die Zellvermehrung humaner mesenchymaler Stammzellen (MSC) und deren osteogene Differenzierung unter GMP Bedingungen verwendet werden können. Außerdem habe ich die die Kokultur von hämatopoietischen Stammzellen des Knochenmarks und multiplen Myelomzellen funktionell charakterisiert. Ich konnte erstmals Kulturbedingungen etablieren, die die Langzeitkultur ohne die Verwendung von Zytokinen ermöglicht. Mittels dieser Kokultur konnte ich ein Knochenmarknischen-Modell etablieren und die Untersuchung der Expression von zentralen Signalkaskaden der Homöostase dieser Nische untersuchen. Ich konnte die Expression von zwei verschiedenen Isoformen von Osteopontin nachweisen, die in Tiermodellen nicht gefunden werden. Diese Isoformen des Osteopontins habe ich kloniert und die rekombinanten Isoformen exprimiert und ihre Rollen in der Homöostase der Knochenmarknische untersucht.
Critical size bone defects represent nowadays an unresolved problem in the clinical practice, where the available prosthetic options often lack adequate mechanical matching to the host tissue or lead to important immunological and implant-related complications.
In this context, Tissue Engineering approaches promise more effective strategies to study cell-material interactions in vitro and consequently optimize implant materials.
In this work, I investigated the cell-scaffold interactions of a new collagen-based scaffold for a putative cell-based therapy for critical size defects to be developed. In the context of this thesis, I could demonstrate that the collagen-based macroporous microcarriers could be employed for the expansion and osteogenic differentiation of human mesenchymal stromal cells (MSCs) under GMP-compliant conditions. Moreover, I functionally characterized the co-culture of bone marrow hematopoietic stem cells and multiple myeloma cells. I was for the first time able to establish culture conditions allowing their long-term culture in absence of externally supplemented cytokines. Using this co-culture, I was able to establish a bone marrow niche model to investigate the expression of key signaling pathways involved in the niche´s homeostasis. I was able to demonstrate the expression of two different isoforms of Osteopontin, that could not previously be detected in animal models. Finally, I cloned these Osteopontin isoforms, expressed recombinant versions of the isoforms, and investigated their roles in the homeostasis of the bone marrow niche.
The microbial communities that live inside the human gastrointestinal tract -the human gut
microbiome- are important for host health and wellbeing. Characterizing this new “organ”,
made up of as many cells as the human body itself, has recently become possible through
technological advances. Metagenomics, the high-throughput sequencing of DNA directly from
microbial communities, enables us to take genomic snapshots of thousands of microbes living
together in this complex ecosystem, without the need for isolating and growing them.
Quantifying the composition of the human gut microbiome allows us to investigate its
properties and connect it to host physiology and disease. The wealth of such connections was
unexpected and is probably still underestimated. Due to the fact that most of our dietary as well
as medicinal intake affects the microbiome and that the microbiome itself interacts with our
immune system through a multitude of pathways, many mechanisms have been proposed to
explain the observed correlations, though most have yet to be understood in depth.
An obvious prerequisite to characterizing the microbiome and its interactions with the host is
the accurate quantification of its composition, i.e. determining which microbes are present and
in what numbers they occur. Historically, standard practices have existed for sample handling,
DNA extraction and data analysis for many years. However, these were generally developed for
single microbe cultures and it is not always feasible to implement them in large scale
metagenomic studies. Partly because of this and partly because of the excitement that new
technology brings about, the first metagenomic studies each took the liberty to define their own
approach and protocols. From early meta-analysis of these studies it became clear that the
differences in sample handling, as well as differences in computational approaches, made
comparisons across studies very difficult. This restricts our ability to cross-validate findings of
individual studies and to pool samples from larger cohorts. To address the pressing need for
standardization, we undertook an extensive comparison of 21 different DNA extraction methods
as well as a series of other sample manipulations that affect quantification. We developed a
number of criteria for determining the measurement quality in the absence of a mock
community and used these to propose best practices for sampling, DNA extraction and library
preparation. If these were to be accepted as standards in the field, it would greatly improve
comparability across studies, which would dramatically increase the power of our inferences
and our ability to draw general conclusions about the microbiome.
Most metagenomics studies involve comparisons between microbial communities, for example
between fecal samples from cases and controls. A multitude of approaches have been proposed
to calculate community dissimilarities (beta diversity) and they are often combined with
various preprocessing techniques. Direct metagenomics quantification usually counts
sequencing reads mapped to specific taxonomic units, which can be species, genera, etc. Due to
technology-inherent differences in sampling depth, normalizing counts is necessary, for
instance by dividing each count by the sum of all counts in a sample (i.e. total sum scaling), or by
subsampling. To derive a single value for community (dis-)similarity, multiple distance
measures have been proposed. Although it is theoretically difficult to benchmark these
approaches, we developed a biologically motivated framework in which distance measures can
be evaluated. This highlights the importance of data transformations and their impact on the
measured distances.
Building on our experience with accurate abundance estimation and data preprocessing
techniques, we can now try and understand some of the basic properties of microbial
communities. In 2011, it was proposed that the space of genus level variation of the human gut
microbial community is structured into three basic types, termed enterotypes. These were
described in a multi-country cohort, so as to be independent of geography, age and other host
properties. Operationally defined through a clustering approach, they are “densely populated
areas in a multidimensional space of community composition”(source) and were proposed as a
general stratifier for the human population. Later studies that applied this concept to other
datasets raised concerns about the optimum number of clusters and robustness of the
clustering approach. This heralded a long standing debate about the existence of structure and
the best ways to determine and capture it. Here, we reconsider the concept of enterotypes, in
the context of the vastly increased amounts of available data. We propose a refined framework
in which the different types should be thought of as weak attractors in compositional space and
we try to implement an approach to determining which attractor a sample is closest to. To this
end, we train a classifier on a reference dataset to assign membership to new samples. This way,
enterotypes assignment is no longer dataset dependent and effects due to biased sampling are
minimized. Using a model in which we assume the existence of three enterotypes characterized
by the same driver genera, as originally postulated, we show the relevance of this stratification
and propose it to be used in a clinical setting as a potential marker for disease development.
Moreover, we believe that these attractors underline different rules of community assembly and
we recommend they be accounted for when analyzing gut microbiome samples.
While enterotypes describe structure in the community at genus level, metagenomic sequencing
can in principle achieve single-nucleotide resolution, allowing us to identify single nucleotide
polymorphisms (SNPs) and other genomic variants in the gut microbiome. Analysis
methodology for this level of resolution has only recently been developed and little exploration
has been done to date. Assessing SNPs in a large, multinational cohort, we discovered that the
landscape of genomic variation seems highly structured even beyond species resolution,
indicating that clearly distinguishable subspecies are prevalent among gut microbes. In several
cases, these subspecies exhibit geo-stratification, with some subspecies only found in the
Chinese population. Generally however, they present only minor dispersion limitations and are
seen across most of our study populations. Within one individual, one subspecies is commonly
found to dominate and only rarely are several subspecies observed to co-occur in the same
ecosystem. Analysis of longitudinal data indicates that the dominant subspecies remains stable
over periods of more than three years. When interrogating their functional properties we find
many differences, with specific ones appearing relevant to the host. For example, we identify a
subspecies of E. rectale that is lacking the flagellum operon and find its presence to be
significantly associated with lower body mass index and lower insulin resistance of their hosts;
it also correlates with higher microbial community diversity. These associations could not be
seen at the species level (where multiple subspecies are convoluted), which illustrates the
importance of this increased resolution for a more comprehensive understanding of microbial
interactions within the microbiome and with the host.
Taken together, our results provide a rigorous basis for performing comparative metagenomics
of the human gut, encompassing recommendations for both experimental sample processing
and computational analysis. We furthermore refine the concept of community stratification into
enterotypes, develop a reference-based approach for enterotype assignment and provide
compelling evidence for their relevance. Lastly, by harnessing the full resolution of
metagenomics, we discover a highly structured genomic variation landscape below the
microbial species level and identify common subspecies of the human gut microbiome. By
developing these high-precision metagenomics analysis tools, we thus hope to contribute to a
greatly improved understanding of the properties and dynamics of the human gut microbiome.
Additive manufacturing processes such as 3D printing are booming in the industry due to their high degree of freedom in terms of geometric shapes and available materials. Focusing on patient-specific medicine, 3D printing has also proven useful in the Life Sciences, where it exploits the shape fidelity for individualized tissues in the field of bioprinting. In parallel, the current systems of bioreactor technology have adapted to the new manufacturing technology as well and 3D-printed bioreactors are increasingly being developed. For the first time, this work combines the manufacturing of the tissue and a tailored bioreactor, significantly streamlining the overall process and optimally merging the two processes. This way the production of the tissues can be individualized by customizing the reactor to the tissue and the patient-specific wound geometry. For this reason, a common basis and guideline for the cross-device and cross-material use of 3D printers was created initially. Their applicability was demonstrated by the iterative development of a perfusable bioreactor system, made from polydimethylsiloxane (PDMS) and a lignin-based filament, into which a biological tissue of flexible shape can be bioprinted. Cost-effective bioink-replacements and in silico computational fluid dynamics simulations were used for material sustainability and shape development. Also, nutrient distribution and shear stress could be predicted in this way pre-experimentally.
As a proof of functionality and adaptability of the reactor, tissues made from a nanocellulose-based Cellink® Bioink, as well as an alginate-based ink mixed with Me-PMeOx100-b-PnPrOzi100-EIP (POx) (Alginate-POx bioink) were successfully cultured dynamically in the bioreactor together with C2C12 cell line. Tissue maturation was further demonstrated using hMSC which were successfully induced to adipocyte differentiation. For further standardization, a mobile electrical device for automated media exchange was developed, improving handling in the laboratory and thus reduces the probability of contamination.
Lungenkrebs ist weltweit für die meisten krebsassoziierten Tode verantwortlich. Ursache dafür ist unter anderem, dass viele Medikamente in der klinischen Anwendung, aufgrund nicht übertragbarer Ergebnisse aus der Präklinik, scheitern. Zur Entwicklung neuer Therapiestrategien werden deshalb Modelle benötigt, welche die in vivo Situation besser widerspiegeln. Besonders wichtig ist es dabei, zu zeigen, für welche Fragestellungen ein neues Testsystem valide Ergebnisse liefert.
In dieser Arbeit ist es mit Hilfe des Tissue Engineering gelungen, ein humanes 3D in vitro Lungentumor-Testsystem weiter zu entwickeln und für verschiedene Fragestellungen zu validieren. Zudem konnten sowohl für die Herstellung als auch für die Behandlung der Tumormodelle SOPs etabliert werden. Hier wurde zunächst beobachtet, dass die Auswerteparameter für die Beurteilung von Behandlungseffekten eine geringe Varianz aufweisen und das 3D Modell deshalb als Testsystem geeignet ist.
Ein Vergleich der Morphologie, des EMT-Status und der Differenzierung der Tumorzelllinien im 3D Modell mit Tumorbiopsaten von Adenokarzinompatienten verdeutlichte, dass die 3D Modelle tumorrelevante Merkmale besitzen. So sind die Zelllinien auf der biologischen Matrix, verglichen mit der jeweiligen 2D Kultur, durch eine reduzierte Proliferationsrate gekennzeichnet, welche eher der in vivo Situation entspricht. Für die Etablierung und Validierung des 3D Modells als Testsystem war es notwendig, klinisch relevante Therapien in dem Modell anzuwenden und die Ergebnisse der Behandlung in vitro mit denen im Patienten zu vergleichen. Dabei konnte zunächst bestätigt werden, dass eine zielgerichtete Therapie gegen den EGFR in dem 3D System zu einer verstärkten Induktion der Apoptose im Vergleich zu 2D führt. Dies entspricht klinischen Beobachtungen, bei denen EGFR-mutierte Patienten gut auf eine Therapie mit Tyrosin-Kinase-Inhibitoren (TKI) ansprechen. Anschließend wurde in dieser Arbeit erstmals in vitro gezeigt, dass die Behandlung mit einem HSP90-Inhibitor bei KRAS-Mutation wie in behandelten Patienten keine eindeutigen Vorteile bringt, diese jedoch in Experimenten der 2D Zellkultur mit den entsprechenden Zelllinien vorhergesagt werden. Die Ergebnisse aus dem in vitro Modell spiegeln damit verschiedene klinische Studien wider und unterstreichen das Potenzial des 3D Lungentumor-Testsystems die Wirkung zielgerichteter Therapien vorherzusagen. Durch die Messung von Signalwegsaktivierungen über Phospho-Arrays und Western Blot konnten in dieser Arbeit Unterschiede zwischen 2D und 3D nach Behandlung gezeigt werden. Diese lieferten die Grundlage für bioinformatische Vorhersagen für Medikamente.
Mit fortschreitender Erkrankung und dem Entstehen invasiver Tumore, die möglicherweise Metastasen bilden, verschlechtert sich die Prognose von Krebspatienten. Zudem entwickeln Patienten, die zunächst auf eine Therapie mit TKI ansprechen, bereits nach kurzer Zeit Resistenzen, die ebenfalls zur Progression des Tumorwachstums führen. Zur Wirkungsuntersuchung von Substanzen in solchen fortgeschrittenen Erkrankungsstadien wurde das bestehende Testsystem erweitert. Zum einen wurde mit Hilfe des Wachstumsfaktors TGF-β1 eine EMT ausgelöst. Hier konnte beobachtet werden, dass sich die Expression verschiedener EMT- und invasionsassoziierter Gene und Proteine veränderte und die Zellen vor allem in dynamischer Kultur verstärkt die Basalmembran der Matrix überquerten. Zum anderen wurde die Ausbildung von Resistenzen gegenüber TKI durch die Generierung von resistenten Subpopulationen aus einer ursprünglich sensitiven Zelllinie und anschließender Kultivierung auf der Matrix abgebildet. Dabei zeigte sich keine der klinisch bekannten Mutationen als ursächlich für die Resistenz, sodass weitere Mechanismen untersucht wurden. Hier konnten Veränderungen in der Signaltransduktion sowie der Expression EMT-assoziierter Proteine festgestellt werden.
Im letzten Teil der Arbeit wurde eine neuartige Behandlung im Bereich der Immuntherapie erfolgreich in dem 3D Modell angewendet. Dafür wurden T-Zellen, die einen chimären Antigen-Rezeptor (CAR) gegen ROR1 tragen, in statischer und dynamischer Kultur zu den Tumorzellen gegeben und der Therapieeffekt mittels histologischer Färbung und der Bestimmung der Apoptose evaluiert. Zusätzlich konnten Eigenschaften der T-Zellen, wie deren Proliferation sowie Zytokinausschüttung quantifiziert und damit eine spezifische Wirkung der CAR transduzierten T-Zellen gegenüber Kontroll-T-Zellen nachgewiesen werden.
Zusammenfassend ist es in dieser Arbeit gelungen, ein humanes 3D Lungentumor-Testsystem für die Anwendung in der präklinischen Entwicklung von Krebsmedikamenten sowie der Grundlagenforschung im Bereich der Tumorbiologie zu etablieren. Dieses Testsystem ist in der Lage relevante Daten zu Biomarker-geleiteten Therapien, zur Behandlung fortgeschrittener Tumorstadien und zur Verbesserung neuartiger Therapiestrategien zu liefern.
Traditionally, ischemic stroke has been regarded as the mere consequence of cessation of cerebral blood flow, e.g. due to the thromboembolic occlusion of a major brain supplying vessel. However, the simple restoration of blood flow via thrombolysis and/or mechanical recanalization alone often does not guarantee a good functional outcome. It appears that secondary detrimental processes are triggered by hypoxia and reoxygenation, which are referred to as ischemia/reperfusion (I/R) injury. During recent years it became evident that, beside thrombosis inflammation and edema formation are key players in the pathophysiology of cerebral ischemia. The contact-kinin system represents an interface between thrombotic, inflammatory and edematous circuits. It connects the intrinsic coagulation pathway with the plasma kallikrein-kinin system (KKS) via coagulation factor FXII.
The serine protease inhibitor C1-inhibitor (C1-INH) has a wide spectrum of inhibitory activities and counteracts activation of the contact-kinin system at multiple levels. The first part of the thesis aimed to multimodally interfere with infarct development by C1-INH and to analyze modes of actions of human plasma derived C1-INH Berinert® P in a murine model of focal cerebral ischemia. It was shown that C57BL/6 mice following early application of 15.0 units (U) C1-INH, but not 7.5 U developed reduced brain infarctions by ~60% and less neurological deficits in the model of transient occlusion of the middle cerebral artery (tMCAO). This protective effect was preserved at more advanced stages of infarction (day 7), without increasing the risk of intracerebral bleeding or affecting normal hemostasis. Less neurological deficits could also be observed with delayed C1-INH treatment, whereas no improvement was achieved in the model of permanent MCAO (pMCAO). Blood-brain-barrier (BBB) damage, inflammation and thrombosis were significantly improved following 15.0 U C1-INH application early after onset of ischemia. Based on its strong antiedematous, antiinflammatory and antithrombotic properties C1-INH constitutes a multifaceted therapeutic compound that protects from ischemic neurodegeneration in ‘clinically meaningful’ settings.
The second part of the thesis addresses the still elusive functional role of macrophages in the early phase of stroke, especially the role of the macrophage-specific adhesion molecule sialoadhesin (Sn). For the first time, sialoadhesin null (Sn-/-) mice, homozygous deficient for Sn on macrophages were subjected to tMCAO to assess the clinical outcome. Neurological and motor function was significantly improved in Sn-/- mice on day 1 after ischemic stroke compared with wildtype (Sn+/+) animals. These clinical improvements were clearly detectable even on day 3 following tMCAO. Infarctions on day 1 were roughly the same size as in Sn+/+ mice and did not grow until day 3. No intracerebral bleeding could be detected at any time point of data acquisition. Twenty four hours after ischemia a strong induction of Sn was detectable in Sn+/+ mice, which was previously observed only on perivascular macrophages in the normal brain. Deletion of Sn on macrophages resulted in less disturbance of the BBB and a reduced number of CD11b+ (specific marker for macrophages/microglia) cells, which, however, was not associated with altered expression levels of inflammatory cytokines. To further analyze the function of macrophages following stroke this thesis took advantage of LysM-Cre+/-/IKK2-/- mice bearing a nuclear factor (NF)-ϰB activation defect in the myeloid lineage, including macrophages. Consequently, macrophages were not able to synthesize inflammatory cytokines under the control of NF-ϰB. Surprisingly, infarct sizes and neurological deficits upon tMCAO were roughly the same in conditional knockout mice and respective wildtype littermates. These findings provide evidence that macrophages do not contribute to tissue damage and neurological deficits, at least, not by release of inflammatory cytokines in the early phase of cerebral ischemia. In contrast, Sn which is initially expressed on perivascular macrophages and upregulated on macrophages/microglia within the parenchyma following stroke, influenced functional outcome.
Transcription describes the process of converting the information contained in DNA into RNA. Although, tremendous progress has been made in recent decades to uncover this complex mechanism, it is still not fully understood. Given the advances and reduction in cost of high-throughput sequencing experiments, more and more data have been generated to help elucidating this complex process. Importantly, these sequencing experiments produce massive amounts of data that are incomprehensible in their raw form for humans. Further, sequencing techniques are not always 100% accurate and are subject to a certain degree of variability and, in special cases, they might introduce technical artifacts. Thus, computational and statistical methods are indispensable to uncover the information buried in these datasets.
In this thesis, I worked with multiple high throughput datasets from herpes simplex virus 1 (HSV-1) and human cytomegalovirus (HCMV) infections. During the last decade, it has became clear that a gene might not have a single, but multiple sites at which transcription initiates. These multiple transcription start sites (TiSS) demonstrated to have regulatory effects on the gene itself depending on which TiSS is used. Specialized experimental approaches were developed to help identify TiSS (TiSS-profiling). In order to facilitate the identification of all potential TiSS that are used for cell type- and condition-specific transcription, I developed the tool iTiSS. By using a new general enrichment-based approach to predict TiSS, iTiSS proved to be applicable in integrated studies and made it less prone to false positives compared to other TiSS-calling tools. Another improvement in recent years was made in metabolic labeling experiments such as SLAM-seq. Here, they removed the time consuming and laborious step of physically separating new from old RNA in the samples. This was achieved by inducing specific nucleotide conversions in newly synthesized RNA that are later visible in the data. Consequently, the separation of new and old RNA is now done computationally and, hence, tools are needed that accurately quantify these fold-changes. My second tool that I developed, called GRAND-SLAM proved to be capable to accomplish this task and outperform competing programs. As both of my tools, iTiSS and GRAND-SLAM are not specifically tailored to my own goals, but could also facilitate the research of other groups in this field, I made them publicly available on GitHub.
I applied my tools to datasets generated in our lab as well as to publicly available data sets from HSV-1 and HCMV, respectively. For HSV-1, I was able to predict and validate TiSS with nucleotide precision using iTiSS. This has lead to the most comprehensive annotation for HSV-1 to date, which now serves as the fundamental basis of any future transcriptomic research on HSV-1. By combining both my tools, I was further able to uncover parts of the highly complex gene kinetics in HCMV and to resolve the limitations caused by the densely packed genome of HCMV.
With the ever-increasing advances in sequencing techniques and their decrease in cost, the amounts of data produced will continue to rise massively in the future. Additionally, more and more specialized omics approaches are appearing, calling for new tools to leverage their full information potential. Consequently, it has become apparent that specialized computational tools such as iTiSS and GRAND-SLAM are needed and will become an essential and indispensable part of the analysis.