Refine
Has Fulltext
- yes (83)
Is part of the Bibliography
- yes (83)
Year of publication
Document Type
- Doctoral Thesis (82)
- Master Thesis (1)
Keywords
- Bioinformatik (9)
- Tissue Engineering (5)
- Thrombozyt (4)
- Genom (3)
- Genregulation (3)
- High throughput screening (3)
- In vitro (3)
- Knochenmark (3)
- Metagenom (3)
- Signaltransduktion (3)
Institute
- Theodor-Boveri-Institut für Biowissenschaften (40)
- Graduate School of Life Sciences (29)
- Fakultät für Biologie (10)
- Institut für Humangenetik (5)
- Institut für Virologie und Immunbiologie (3)
- Lehrstuhl für Tissue Engineering und Regenerative Medizin (3)
- Abteilung für Forensische Psychiatrie (2)
- Institut für Experimentelle Biomedizin (2)
- Institut für Klinische Epidemiologie und Biometrie (2)
- Medizinische Fakultät (2)
Sonstige beteiligte Institutionen
- EMBL Heidelberg (2)
- 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)
- European Molecular Biology Laboratory, Heidelberg, Germany (1)
- Fraunhofer IGB - Institutsteil Würzburg Translationszentrum Regenerative Therapien für Krebs- und Muskuloskelettale Erkrankungen (1)
- GEOMAR Helmholtz-Zentrum für Ozeanforschung Kiel (1)
- Institut für Medizinische Mikrobiologie und Hygiene der Eberhard-Karls-Universität Tübingen (1)
- Lehrstuhl für Bioinformatik (1)
- Lehrstuhl für Translationale Onkologie (1)
ResearcherID
- J-8841-2015 (1)
Microbial species (bacteria and archaea) in the gut are important for human health in various ways. Not only does the species composition vary considerably within the human population, but each individual also appears to have its own strains of a given species. While it is known from studies of bacterial pan-genomes, that genetic variation between strains can differ considerably, such as in Escherichia coli, the extent of genetic variation of strains for abundant gut species has not been surveyed in a natural habitat. This is mainly due to the fact that most of these species cannot be cultured in the laboratory. Genetic variation can range from microscale genomic rearrangements such as small nucleotide polymorphism (SNP) to macroscale large genomic rearrangements like structural variations. Metagenomics offers an alternative solution to study genetic variation in prokaryotes, as it involves DNA sequencing of the whole community directly from the environment. However, most metagenomic studies to date only focus on variation in gene abundance and hence are not able to characterize genetic variation (in terms of presence or absence of SNPs and genes) of gut microbial strains of individuals.
The aim of my doctorate studies was therefore to study the extent of genetic variation in the genomic sequence of gut prokaryotic species and its phenotypic effects based on: (1) the impact of SNP variation in gut bacterial species, by focusing on genes under selective pressure and (2) the gene content variation (as a proxy for structural variation) and their effect on microbial species and the phenotypic traits of their human host.
In the first part of my doctorate studies, I was involved in a project in which we created a catalogue of 10.3 million SNPs in gut prokaryotic species, based on metagenomes. I used this to perform the first SNP-based comparative study of prokaryotic species evolution in a natural habitat. Here, I found that strains of gut microbial species in different individuals evolve at more similar rates than the strains within an individual. In addition, I found that gene evolution can be uncoupled from the evolution of its originating species, and that this could be related to selective pressure such as diet, exemplified by galactokinase gene (galK). Despite the individuality (i.e. uniqueness of each individual within the studied metagenomic dataset) in the SNP profile of the gut microbiota that we found, for most cases it is not possible to link SNPs with phenotypic differences. For this reason I also used gene content as a proxy to study structural variation in metagenomes.
In the second part of my doctorate studies, I developed a methodology to characterize the variability of gene content in gut bacterial species, using metagenomes. My approach is based on gene deletions, and was applied to abundant species (demonstrated using a set of 11 species). The method is sufficiently robust as it captures a similar range of gene content variability as has been detected in completely sequenced genomes. Using this procedure I found individuals differ by an average of 13% in their gene content of gut bacterial strains within the same species. Interestingly no two individuals shared the same gene content across bacterial species. However, this variation corresponds to a lower limit, as it is only accounts for gene deletion and not insertions. This large variation in the gene content of gut strain was found to affect important functions, such as polysaccharide utilization loci (PULs) and capsular polysaccharide synthesis (CPS), which are related with digestion of dietary fibers.
In summary, I have shown that metagenomics based approaches can be robust in characterizing genetic variation in gut bacterial species. I also illustrated, using examples both for SNPs and gene content (galK, PULs and CPS), that this genetic variation can be used to predict the phenotypic characteristics of the microbial species, as well as predicting the phenotype of their human host (for example, their capacity to digest different food components). Overall, the results of my thesis highlight the importance of characterizing the strains in the gut microbiome analogous to the emerging variability and importance of human genomics.
Dynamic interactions and their changes are at the forefront of current research in bioinformatics and systems biology. This thesis focusses on two particular dynamic aspects of cellular adaptation: miRNA and metabolites.
miRNAs have an established role in hematopoiesis and megakaryocytopoiesis, and platelet miRNAs have potential as tools for understanding basic mechanisms of platelet function. The thesis highlights the possible role of miRNAs in regulating protein translation in platelet lifespan with relevance to platelet apoptosis and identifying involved pathways and potential key regulatory molecules. Furthermore, corresponding miRNA/target mRNAs in murine platelets are identified. Moreover, key miRNAs involved in aortic aneurysm are predicted by similar techniques. The clinical relevance of miRNAs as biomarkers, targets, resulting later translational therapeutics, and tissue specific restrictors of genes expression in cardiovascular diseases is also discussed.
In a second part of thesis we highlight the importance of scientific software solution development in metabolic modelling and how it can be helpful in bioinformatics tool development along with software feature analysis such as performed on metabolic flux analysis applications. We proposed the “Butterfly” approach to implement efficiently scientific software programming. Using this approach, software applications were developed for quantitative Metabolic Flux Analysis and efficient Mass Isotopomer Distribution Analysis (MIDA) in metabolic modelling as well as for data management. “LS-MIDA” allows easy and efficient MIDA analysis and, with a more powerful algorithm and database, the software “Isotopo” allows efficient analysis of metabolic flows, for instance in pathogenic bacteria (Salmonella, Listeria). All three approaches have been published (see Appendices).
Erweiterte Diagnostik bei neuromuskulären Erkrankungen: vom Genpanel zum Whole Genome Sequencing
(2019)
Muskeln und Nerven bilden eine essentielle funktionelle Einheit für den Bewegungsapparat. Neuromuskuläre Erkrankungen lassen sich unterteilen in Krankheiten, denen ein muskuläres Problem zu Grunde liegt, wie zum Beispiel Muskeldystrophien (Muskeldystrophie Duchenne, DMD) und Myopathien (Myofibrilläre Myopathie, MFM), und in Erkrankungen aufgrund von Nervenschädigungen, wie zum Beispiel Neuropathien und spastische Paraplegien (SPG).
In den vier Teilen der vorliegenden Arbeit konnte sowohl das genetische wie auch das phänotypische Spektrum von neuromuskulären Krankheiten erweitert werden. Die dafür verwendeten Methoden reichen von der Sanger-Sequenzierung einzelner Gene über Next-Generation Sequencing (NGS)-Panel-Diagnostik, zu Whole Exome Sequencing (WES) und schließlich zu Whole Genome Sequencing (WGS). Zusätzlich wurde cDNA zur Detektion von Veränderungen im Transkriptom sequenziert.
Im ersten Teil wurde der klinische Phänotyp der Seipinopathien erweitert, der jetzt auch amyotrophe Lateralsklerose (ALS) und multifokale motorische Neuropathie (MMN) beinhaltet. Dafür wurde eine Panel-Analyse durchgeführt, die eine bekannte Mutation in BSCL2 aufdeckte. Aufgrund des hiermit erweiterten Phänotyps der Seipinopathien sollten Mutationen in BSCL2 auch bei anderen Verdachtsdiagnosen, wie ALS oder MMN, berücksichtigt werden. Außerdem wurde gezeigt, dass in der Diagnostik SPGs und Charcot-Marie-Tooth Erkrankungen (CMTs) eine Überlappung zeigen und bei der Diagnose von Verdachtsfällen Gene aus beiden Krankheitsbereichen berücksichtigt werden sollten. Die Suche mit Hilfe eines Phänotyp-Filters hat sich dabei als erfolgreich erwiesen. Ungelöste Fälle sollten aber in regelmäßigen Abständen neu analysiert werden, da immer neue Gene mit den Phänotypen assoziiert werden.
Der zweite Teil befasst sich mit der Untersuchung von DMD-Patienten mit bisher ungeklärtem Genotyp. Durch eine RNA-Analyse des gesamten DMD-Transkripts wurden tief-intronische Mutationen aufgedeckt, die Einfluss auf das Spleißen haben. Durch diese Mutationen wurden intronische Sequenzen als Pseudoexons in die mRNA eingefügt. Diese Mutationsart scheint häufig unter ungeklärten DMD-Fällen zu sein, in unserer Kohorte von 5 DMD-Patienten wurden in zwei Fällen Pseudoexons entdeckt. Eine Besonderheit besteht darin, dass in der RNA-Analyse immer noch ein Rest Wildtyp-Transkript vorhanden war, wodurch die Patienten vermutlich einen milderen Becker-Phänotyp aufweisen. Ein weiterer ungeklärter DMD-Fall konnte durch die Sequenzierung der gesamten genomischen Sequenz aufgeklärt werden. Es wurde eine perizentrische Inversion entdeckt (46,Y,inv(X)(p21.1q13.3). Dies zeigt, dass WGS auch zur Detektion von großen Strukturvariationen geeignet ist.
Im dritten Teil wurden Spleißmutationen untersucht. Spleißmutationen wurden bisher nicht in TMEM5-assoziierter alpha-Dystroglykanopathie beschrieben und somit als neue Mutationsart für diese Erkrankung nachgewiesen. Dabei wurde auch die funktionelle Exostosin-Domäne in TMEM5 bestätigt. Eine RNA-Untersuchung verschiedener Spleißmutationen zeigte, dass Spleißmutationen häufig zu einem veränderten Transkript führen, auch wenn diese Mutationen weiter von der Konsensussequenz entfernt sind. Spleißmutation sollten daher häufiger in der Diagnostik berücksichtig und überprüft werden.
Im letzten Teil wurde eine strukturierte Diagnostik von MFM-Patienten beschrieben und neue Kandidaten-Gene für MFM vorgestellt. Es ist zu vermuten, dass auch Mutationen in Genen, die bisher für Kardiomyopathien, Kollagen Typ VI-Myopathien und Neuropathien beschrieben sind, einen MFM-Phänotyp verursachen können. Diese Ergebnisse erweitern das genetische Spektrum der MFM, was sich auf die Diagnostik dieser Erkrankungen auswirken sollte.
Im Laufe dieser Arbeit konnten damit die neuromuskulären Erkrankungen vieler Patienten genetisch geklärt werden. Neue Phänotypen und genetische Ursachen wurden beschrieben und es wurde gezeigt, dass sich WGS technisch für die Diagnostik, auch zur Detektion von großen Strukturvarianten, eignet.
Development and application of computational tools for RNA-Seq based transcriptome annotations
(2019)
In order to understand the regulation of gene expression in organisms, precise genome annotation is essential. In recent years, RNA-Seq has become a potent method for generating and improving genome annotations. However, this Approach is time consuming and often inconsistently performed when done manually. In particular, the discovery of non-coding RNAs benefits strongly from the application of RNA-Seq data but requires significant amounts of expert knowledge and is labor-intensive. As a part of my doctoral study, I developed a modular tool called ANNOgesic that can detect numerous transcribed genomic features, including non-coding RNAs, based on RNA-Seq data in a precise and automatic fashion with a focus on bacterial and achaeal species. The software performs numerous analyses and generates several visualizations. It can generate annotations of high-Resolution that are hard to produce using traditional annotation tools that are based only on genome sequences. ANNOgesic can detect numerous novel genomic Features like UTR-derived small non-coding RNAs for which no other tool has been developed before. ANNOgesic is available under an open source license (ISCL) at https://github.com/Sung-Huan/ANNOgesic.
My doctoral work not only includes the development of ANNOgesic but also its application to annotate the transcriptome of Staphylococcus aureus HG003 - a strain which has been a insightful model in infection biology. Despite its potential as a model, a complete genome sequence and annotations have been lacking for HG003. In order to fill this gap, the annotations of this strain, including sRNAs and their functions, were generated using ANNOgesic by analyzing differential RNA-Seq data from 14 different samples (two media conditions with seven time points), as well as RNA-Seq data generated after transcript fragmentation. ANNOgesic was
also applied to annotate several bacterial and archaeal genomes, and as part of this its high performance was demonstrated. In summary, ANNOgesic is a powerful computational tool for RNA-Seq based annotations and has been successfully applied to several species.
Interleukin 2 (IL-2) was the first cytokine applied for cancer treatment in human history. It has been approved as monotherapy for renal cell carcinoma and melanoma by the FDA and does mediate the regression of the tumors in patients. One of the possible mechanisms is that the administration of IL-2 led to T lymphocytes expansion, including CD4+ and CD8+ T cells. In addition, a recent study demonstrated that antigen-specific T cells could also be expanded through the induction of IL-2, which plays a crucial role in mediating tumor regression. However, despite the long-term and extensive use of IL-2 in the clinic, the ratio of patients who get a complete response was still low, and only about one-fifth of patients showed objective tumor regression. Therefore, the function of IL-2 in cancer treatment should continue to be optimized and investigated. A study by Franz O. Smith et al. has shown that the combination treatment of IL-2 and tumor-associated antigen vaccine has a strong trend to increased objective responses compared to patients with melanoma receiving IL-2 alone. Peptide vaccines are anti-cancer vaccines able to induce a powerful tumor antigenspecific immune response capable of eradicating the tumors. According to the type of antigens, peptide vaccines can be classified into two distinct categories: Tumor-associated antigens (TAA) vaccine and tumor-specific neoantigens (TSA) vaccine. Currently, Peptide vaccines are mainly investigated in phase I and phase II clinical trials of human cancer patients with various advanced cancers such as lung cancer, gastrointestinal tumors, and breast cancers. Vaccinia virus (VACV) is one of the safest viral vectors, which has been wildly used in cancer treatment and pathogen prevention. As an oncolytic vector, VACV can carry multiple large foreign genes, which enable the virus to introduce diagnostic and therapeutic agents without dramatically reducing the viral replication. Meanwhile, the recombinant vaccinia virus (rVACV) can be easily generated by homologous recombination. Here, we used the vaccinia virus as the therapeutic cancer vector, expressing mouse Interleukin 2 (IL-2) and tumor-associated antigens simultaneously to investigate the combined effect of anti-tumor immune response in the 4T1 mouse tumor model. As expected, the VACV driven mIL-2 expression remarkably increased both CD4+ and CD8+ populations in vivo, and the virus-expressed tumor-associated peptides successfully elicited theantigen-specific T cell response to inhibit the growth of tumors. Furthermore, the experiments with tumor-bearing animals showed that the mIL-2 plus tumor antigens expressing VACV vector gave a better anti-cancer response than the mIL-2 alone expressing vector. The combinations did significantly more inhibit tumor growth than mIL-2 treatment alone. Moreover, the results confirmed our previous unpublished data that the mIL-2 expression driven by synthetic early/late promoter in the Lister strain VACV could enhance the tumor regression in the 4T1 mouse model.
Chlamydia trachomatis (Ct) is an obligate intracellular human pathogen. It causes blinding trachoma and sexually transmitted disease such as chlamydia, pelvic inflammatory disease and lymphogranuloma venereum. Ct has a unique biphasic development cycle and replicates in an intracellular vacuole called inclusion. Normally it has two forms: the infectious form, elementary body (EB); and the non-infectious form, reticulate body (RB). Ct is not easily amenable to genetic manipulation. Hence, to understand the infection process, it is crucial to study how the metabolic activity of Ct exactly evolves in the host cell and what roles of EB and RB play differentially in Ct metabolism during infection. In addition, Ct was found regularly coinfected with other pathogens in patients who got sexually transmitted diseases (STDs). A lack of powerful methods to culture Ct outside of the host cell makes the detailed molecular mechanisms of coinfection difficult to study.
In this work, a genome-scale metabolic model with 321 metabolites and 277 reactions was first reconstructed by me to study Ct metabolic adaptation in the host cell during infection. This model was calculated to yield 84 extreme pathways, and metabolic flux strength was then modelled regarding 20hpi, 40hpi and later based on a published proteomics dataset. Activities of key enzymes involved in target pathways were further validated by RT-qPCR in both HeLa229 and HUVEC cell lines. This study suggests that Ct's major active pathways involve glycolysis, gluconeogenesis, glycerolphospholipid biosynthesis and pentose phosphate pathway, while Ct's incomplete tricarboxylic acid cycle and fatty acid biosynthesis are less active. EB is more activated in almost all these carbohydrate pathways than RB. Result suggests the survival of Ct generally requires a lot of acetyl-CoA from the host. Besides, both EB and RB can utilize folate biosynthesis to generate NAD(P)H but may use different pathways depending on the demands of ATP. When more ATP is available from both host cell and Ct itself, RB is more activated by utilizing energy providing chemicals generated by enzymes associated in the nucleic acid metabolism. The forming of folate also suggests large glutamate consumption, which is supposed to be converted from glutamine by the glutamine-fructose-6-phosphate transaminase (glmS) and CTP synthase (pyrG).
Then, RNA sequencing (RNA-seq) data analysis was performed by me in a coinfection study. Metatranscriptome from patient RNA-seq data provides a realistic overview. Thirteen patient samples were collected and sequenced by our collaborators. Six male samples were obtained by urethral swab, and seven female samples were collected by cervicovaginal lavage. All the samples were Neisseria gonorrhoeae (GC) positive, and half of them had coinfection with Ct. HISAT2 and Stringtie were used for transcriptomic mapping and assembly respectively, and differential expression analysis by DESeq2, Ballgown and Cuffdiff2 are parallelly processed for comparison. Although the measured transcripts were not sufficient to assemble Ct's transcriptome, the differential expression of genes in both the host and GC were analyzed by comparing Ct positive group (Ct+) against Ct-uninfected group. The results show that in the Ct+ group, the host MHC class II immune response was highly induced. Ct infection is associated with the regulation of DNA methylation, DNA double-strand damage and ubiquitination. The analysis also shows Ct infection enhances host fatty acid beta oxidation, thereby inducing mROS, and the host responds to reduce ceramide production and glycolysis. The coinfection upregulates GC's own ion transporters and amino acid uptake, while it downregulates GC's restriction and modification systems. Meanwhile, GC has the nitrosative and oxidative stress response and also increases the ability for ferric uptake especially in the Ct+ group compared to Ct-uninfected group.
In conclusion, methods in bioinformatics were used here in analyzing the metabolism of Ct itself, and the responses of the host and GC respectively in a coinfection study with and without Ct. These methods provide metabolic and metatranscriptomic details to study Ct metabolism during infection and Ct associated coinfection in the human microbiota.
The field of genetics faces a lot of challenges and opportunities in both research and diagnostics due to the rise of next generation sequencing (NGS), a technology that allows to sequence DNA increasingly fast and cheap.
NGS is not only used to analyze DNA, but also RNA, which is a very similar molecule also present in the cell, in both cases producing large amounts of data.
The big amount of data raises both infrastructure and usability problems, as powerful computing infrastructures are required and there are many manual steps in the data analysis which are complicated to execute.
Both of those problems limit the use of NGS in the clinic and research, by producing a bottleneck both computationally and in terms of manpower, as for many analyses geneticists lack the required computing skills.
Over the course of this thesis we investigated how computer science can help to improve this situation to reduce the complexity of this type of analysis.
We looked at how to make the analysis more accessible to increase the number of people that can perform OMICS data analysis (OMICS groups various genomics data-sources).
To approach this problem, we developed a graphical NGS data analysis pipeline aimed at a diagnostics environment while still being useful in research in close collaboration with the Human Genetics Department at the University of Würzburg.
The pipeline has been used in various research papers on covering subjects, including works with direct author participation in genomics, transcriptomics as well as epigenomics.
To further validate the graphical pipeline, a user survey was carried out which confirmed that it lowers the complexity of OMICS data analysis.
We also studied how the data analysis can be improved in terms of computing infrastructure by improving the performance of certain analysis steps.
We did this both in terms of speed improvements on a single computer (with notably variant calling being faster by up to 18 times), as well as with distributed computing to better use an existing infrastructure.
The improvements were integrated into the previously described graphical pipeline, which itself also was focused on low resource usage.
As a major contribution and to help with future development of parallel and distributed applications, for the usage in genetics or otherwise, we also looked at how to make it easier to develop such applications.
Based on the parallel object programming model (POP), we created a Java language extension called POP-Java, which allows for easy and transparent distribution of objects.
Through this development, we brought the POP model to the cloud, Hadoop clusters and present a new collaborative distributed computing model called FriendComputing.
The advances made in the different domains of this thesis have been published in various works specified in this document.
Der Meniskus, ein scheibenförmiger Faserknorpel, spielt im Kniegelenk eine bedeutende Rolle, weil er Kräfte und Druck im Kniegelenk gleichmäßig verteilt, Stöße dämpft sowie der Kraftübertragung und Stabilisierung dient. Durch die Entfernung des Gewebes, der sogenannten Totalmeniskektomie, nach einer Meniskusverletzung oder einem Riss, verändern sich die mechanischen Eigenschaften des Gelenks stark und verursachen durch die erhöhte Belastung der Gelenkflächen Arthrose. Arthrose ist weltweit die Häufigste aller Gelenkerkrankungen. Der Erhalt der körperlichen Leistungsfähigkeit und Mobilität bis ins hohe Alter sowie die Bewahrung der Gesundheit von Herz-Kreislauf- und Stoffwechselorganen zählen aufgrund des demografischen Wandels zu den großen medizinischen Herausforderungen. Die Erkrankung des muskuloskelettalen Systems stellte 2010 im Bundesgebiet die am häufigsten vorkommende Krankheitsart dar.
Während Risse in den äußeren Teilen des Meniskus aufgrund des Anschlusses an das Blutgefäßsystem spontan heilen können, können sie dies in tieferen Zonen nicht. Durch die begrenzte Heilungsfähigkeit des Knorpels bleibt langfristig der Einsatz eines Ersatzgewebes die einzige therapeutische Alternative.
In der vorliegenden Arbeit wurde als therapeutische Alternative erfolgreich ein vaskularisiertes Meniskusersatzgewebe mit Methoden des Tissue Engineering entwickelt. Es soll in Zukunft als Implantat Verwendung finden. Tissue Engineering ist ein interdisziplinäres Forschungsfeld, in dem Gewebe außerhalb des Körpers generiert werden. Schlüsselkomponenten sind Zellen, die aus einem Organismus isoliert werden, und Trägerstrukturen, die mit Zellen besiedelt werden. Die Biomaterialien geben den Zellen eine geeignete Umgebung, die die Extrazelluläre Matrix (EZM) ersetzen soll, um die Funktion der Zellen beizubehalten, eigene Matrix zu bilden. Zum Erhalt eines funktionelles Gewebes werden oftmals dynamische Kultursysteme, sogenannte Bioreaktoren, verwendet, die natürliche Stimuli wie beispielsweise den Blutfluss oder mechanische Kompressionskräfte während der in vitro Reifungsphase des Gewebes, zur Verfügung stellen. Das Gewebekonstrukt wurde auf Basis natürlicher Biomaterialien aufgebaut, unter Verwendung ausschließlich primärer Zellen, die später direkt vom Patienten gewonnen werden können und damit Abstoßungsreaktionen auszuschließen sind. Da der Meniskus teilvaskularisiert ist und die in vivo Situation des Gewebes bestmöglich nachgebaut werden sollte, wurden Konstrukte mit mehreren Zelltypen, sogenannte Ko-Kulturen aufgebaut. Neben mikrovaskulären Endothelzellen (mvEZ) und Meniskuszellen (MZ) erfolgten Versuche mit mesenchymalen Stammzellen (MSZ).
Zur Bereitstellung einer zelltypspezifischen Matrixumgebung, diente den mvEZ ein Stück Schweinedarm mit azellularisierten Gefäßstrukturen (BioVaSc®) und den MZ diente eine geeig- nete Kollagenmatrix (Kollagen Typ I Hydrogel). Die Validierung und Charakterisierung des aufgebauten 3D Meniskuskonstrukts, welches in einem dynamischen Perfusions-Bioreaktorsystem kultiviert wurde, erfolgte mit knorpeltypischen Matrixmarkern wie Aggrekan, Kollagen Typ I, II und X sowie mit den Transkriptionsfaktoren RunX2 und Sox9, die in der Knorpelentstehung von großer Bedeutung sind. Zusätzlich erfolgten Auswertungen mit endothelzellspezifischen Markern wie vWF, CD31 und VEGF, um die Vaskularisierung im Konstrukt nachzuweisen. Analysiert wurden auch die Zellvitalitäten in den Konstrukten.
Aufgrund einer nur geringen Verfügbarkeit von MZ wurden Kulturansätze mit alternativen Zellquellen, den MSZ, durchgeführt. Dafür erfolgte zunächst deren Isolation und Charakterisierung und die Auswahl einer geeigneten 3D Kollagenmatrix. Die beste Zellintegration der MSZ konnte auf einer eigens hergestellten elektrogesponnenen Matrix beobachtet werden. Die Matrix besteht aus zwei unterschiedlichen Kollagentypen, die auf insgesamt fünf Schichten verteilt sind. Die Fasern besitzen weiter unterschiedliche Ausrichtungen. Während die Kollagen Typ I Fasern in den äußeren Schichten keiner Ausrichtung zugehören, liegen die Kollagen Typ II Fasern in der mittleren Schicht parallel zueinander. Der native Meniskus war für den Aufbau einer solchen Kollagen-Trägerstruktur das natürliche Vorbild, das imitiert werden sollte. Nach der Besiedelung der Matrix mit MSZ, konnte eine Integration der Zellen bereits nach vier Tagen bis in die Mittelschicht sowie eine spontane chondrogene Differenzierung nach einer insgesamt dreiwöchigen Kultivierung gezeigt werden. Das Biomaterial stellt in Hinblick auf die Differenzierung der Zellen ohne die Zugabe von Wachstumsfaktoren eine relevante Bedeutung für klinische Studien dar.
Zur Kultivierung des 3D Meniskuskonstrukts wurde ein Bioreaktor entwickelt. Mit diesem können neben Perfusion der Gefäßsysteme zusätzlich Kompressionskräfte sowie Scherspannungen auf das Ersatzgewebe appliziert und die Differenzierung von MZ bzw. MSZ während der in vitro Kultur über mechanische Reize stimuliert werden. Ein anderes Anwendungsfeld für den neuartigen Bioreaktor ist seine Verwendung als Prüftestsystem für die Optimierung und Qualitätssicherung von Gewebekonstrukten.
Chlamydia trachomatis, an obligate intracellular human pathogen, is the world’s leading cause of infection related blindness and the most common, bacterial sexually transmitted disease. In order to establish an optimal replicative niche, the pathogen extensively interferes with the physiology of the host cell. Chlamydia switches in its complex developmental cycle between the infectious non-replicative elementary bodies (EBs) and the non-infectious replicative reticulate bodies (RBs). The transformation to RBs, shortly after entering a host cell, is a crucial process in infection to start chlamydial replication. Currently it is unknown how the transition from EBs to RBs is initiated. In this thesis, we could show that, in an axenic media approach, L glutamine uptake by the pathogen is crucial to initiate the EB to RB transition. L-glutamine is converted to amino acids which are used by the bacteria to synthesize peptidoglycan. Peptidoglycan inturn is believed to function in separating dividing Chlamydia. The glutamine metabolism is reprogrammed in infected cells in a c-Myc-dependent manner, in order to accomplish the increased requirement for L-glutamine. Upon a chlamydial infection, the proto-oncogene c-Myc gets upregulated to promote host cell glutaminolysis via glutaminase GLS1 and the L-glutamine transporter SLC1A5/ASCT2. Interference with this metabolic reprogramming leads to limited growth of C. trachomatis. Besides the active infection, Chlamydia can persist over a long period of time within the host cell whereby chronic and recurrent infections establish. C. trachomatis acquire a persistent state during an immune attack in response to elevated interferon-γ (IFN-γ) levels. It has been shown that IFN-γ activates the catabolic depletion of L-tryptophan via indoleamine 2,3-dioxygenase (IDO), resulting in the formation of non-infectious atypical chlamydial forms. In this thesis, we could show that IFN-γ depletes the key metabolic regulator c-Myc, which has been demonstrated to be a prerequisite for chlamydial development and growth, in a STAT1-dependent manner. Moreover, metabolic analyses revealed that the pathogen de routs the host cell TCA cycle to enrich pyrimidine biosynthesis. Supplementing pyrimidines or a-ketoglutarate helps the bacteria to partially overcome the persistent state. Together, the results indicate a central role of c-Myc induced host glutamine metabolism reprogramming and L-glutamine for the development of C. trachomatis, which may provide a basis for anti-infectious strategies. Furthermore, they challenge the longstanding hypothesis of L-tryptophan shortage as the sole reason for IFN-γ induced persistence and suggest a pivotal role of c-Myc in the control of the C. trachomatis dormancy.
Erstellung eines genregulatorischen Netzwerkes zur Simulation der Entstehung von Zahnhartsubstanz
(2020)
In dieser Dissertation beschreibt der Autor die Erstellung eines grundlegenden bioinformatischen Modelles der menschlichen Zahnschmelzreifung. Mithilfe der KEGG Pathway-Datenbank wurde ein genregulatorisches Netzwerk (GRN) erstellt, welches maßgeblich auf den Signaltransduktionswegen Apoptose, Zellzyklus, Hedgehog-Signalweg, MAP-Kinase-Weg, mTOR-Signalweg Notch-Signalweg Signalweg, TGF-β-Signalweg und Wnt-Signalweg basiert. Im Weiteren wurde dieses Netzwerk durch zahlreiche verifizierte Wechselwirkungen erweitert und die zahnspezifischen Gene AMELX, AMELY, AMBN, ENAM und DSPP implementiert. In der anschließenden Simulation des Netzwerks mit dem Simulations-Tool Jimena konnten sechs stabile Zustände identifiziert werden. Diese wurden genauer untersucht und den Erkenntnissen eines GEO-Datensatzes gegenübergestellt. Langfristiges Ziel ist es, durch konsequente Optimierung des bioinformatischen Netzwerks Rückschlüsse auf die Odontogenese des Menschen zu ziehen.