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- Bone (1)
- Extracellular matrix proteins (1)
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Institut
- Graduate School of Life Sciences (3) (entfernen)
Platelets, small anucleated blood cells responsible for hemostasis, interact at sights of injury with several exposed extracellular matrix (ECM) proteins through specific receptors. Ligand binding leads to activation, adhesion and aggregation of platelets. Already megakaryocytes (MKs), the immediate precursor cells in bone marrow (BM), are in constant contact to these ECM proteins (ECMP). The interaction of ECMP with MKs is, in contrast to platelets, less well understood. It is therefore important to study how MKs interact with sinusoids via the underlying ECMP. This thesis addresses three major topics to elucidate these interactions and their role in platelet biogenesis.
First, we studied the topology of ECMP within BM and their impact on proplatelet formation (PPF) in vitro. By establishing a four-color immunofluorescence microscopy we localized collagens and other ECMP and determined their degree of contact towards vessels and megakaryocytes (MKs). In in vitro assays we could demonstrate that Col I mediates increased MK adhesion, but inhibits PPF by collagen receptor GPVI. By immunoblot analyses we identified that the signaling events underyling this inhibition are different from those in platelet activation at the Src family kinase level.
Second, we determined the degree of MK-ECM interaction in situ using confocal laser scanning microscopy of four-color IF-stained femora and spleen sections. In transgenic mouse models lacking either of the two major collagen receptors we could show that these mice have an impaired association of MKs to collagens in the BM, while the MK count in spleen increased threefold. This might contribute to the overall unaltered platelet counts in collagen receptor-deficient mice.
In a third approach, we studied how the equilibrium of ECMP within BM is altered after irradiation. Collagen type IV and laminin-α5 subunits were selectively degraded at the sinusoids, while the matrix degrading protease MMP9 was upregulated in MKs. Platelet numbers decreased and platelets became hyporesponsive towards agonists, especially those for GPVI activation.
Taken together, the results indicate that MK-ECM interaction differs substantially from the well-known platelet-ECM signaling. Future work should further elucidate how ECMP can be targeted to ameliorate the platelet production and function defects, especially in patients after BM irradiation.
Neurobiology is widely supported by bioinformatics. Due to the big amount of data generated from the biological side a computational approach is required. This thesis presents four different cases of bioinformatic tools applied to the service of Neurobiology.
The first two tools presented belong to the field of image processing. In the first case, we make use of an algorithm based on the wavelet transformation to assess calcium activity events in cultured neurons. We designed an open source tool to assist neurobiology researchers in the analysis of calcium imaging videos. Such analysis is usually done manually which is time consuming and highly subjective. Our tool speeds up the work and offers the possibility of an unbiased detection of the calcium events. Even more important is that our algorithm not only detects the neuron spiking activity but also local spontaneous activity which is normally discarded because it is considered irrelevant. We showed that this activity is determinant in the calcium dynamics in neurons and it is involved in important functions like signal modulation and memory and learning.
The second project is a segmentation task. In our case we are interested in segmenting the neuron nuclei in electron microscopy images of c.elegans. Marking these structures is necessary in order to reconstruct the connectome of the organism. C.elegans is a great study case due to the simplicity of its nervous system (only 502 neurons). This worm, despite its simplicity has taught us a lot about neuronal mechanisms. There is still a lot of information we can extract from the c.elegans, therein lies the importance of reconstructing its connectome. There is a current version of the c.elegans connectome but it was done by hand and on a single subject which leaves a big room for errors. By automatizing the segmentation of the electron microscopy images we guarantee an unbiased approach and we will be able to verify the connectome on several subjects.
For the third project we moved from image processing applications to biological modeling. Because of the high complexity of even small biological systems it is necessary to analyze them with the help of computational tools. The term in silico was coined to refer to such computational models of biological systems. We designed an in silico model of the TNF (Tumor necrosis factor) ligand and its two principal receptors. This biological system is of high relevance because it is involved in the inflammation process. Inflammation is of most importance as protection mechanism but it can also lead to complicated diseases (e.g. cancer). Chronic inflammation processes can be particularly dangerous in the brain. In order to better understand the dynamics that govern the TNF system we created a model using the BioNetGen language. This is a rule based language that allows one to simulate systems where multiple agents are governed by a single rule. Using our model we characterized the TNF system and hypothesized about the relation of the ligand with each of the two receptors. Our hypotheses can be later used to define drug targets in the system or possible treatments for chronic inflammation or lack of the inflammatory response.
The final project deals with the protein folding problem. In our organism proteins are folded all the time, because only in their folded conformation are proteins capable of doing their job (with some very few exceptions). This folding process presents a great challenge for science because it has been shown to be an NP problem. NP means non deterministic Polynomial time problem. This basically means that this kind of problems cannot be efficiently solved. Nevertheless, somehow the body is capable of folding a protein in just milliseconds. This phenomenon puzzles not only biologists but also mathematicians. In mathematics NP problems have been studied for a long time and it is known that given the solution to one NP problem we could solve many of them (i.e. NP-complete problems). If we manage to understand how nature solves the protein folding problem then we might be able to apply this solution to many other problems. Our research intends to contribute to this discussion. Unfortunately, not to explain how nature solves the protein folding problem, but to explain that it does not solve the problem at all. This seems contradictory since I just mentioned that the body folds proteins all the time, but our hypothesis is that the organisms have learned to solve a simplified version of the NP problem. Nature does not solve the protein folding problem in its full complexity. It simply solves a small instance of the problem. An instance which is as simple as a convex optimization problem. We formulate the protein folding problem as an optimization problem to illustrate our claim and present some toy examples to illustrate the formulation. If our hypothesis is true, it means that protein folding is a simple problem. So we just need to understand and model the conditions of the vicinity inside the cell at the moment the folding process occurs. Once we understand this starting conformation and its influence in the folding process we will be able to design treatments for amyloid diseases such as Alzheimer's and Parkinson's.
In summary this thesis project contributes to the neurobiology research field from four different fronts. Two are practical contributions with immediate benefits, such as the calcium imaging video analysis tool and the TNF in silico model. The neuron nuclei segmentation is a contribution for the near future. A step towards the full annotation of the c.elegans connectome and later for the reconstruction of the connectome of other species. And finally, the protein folding project is a first impulse to change the way we conceive the protein folding process in nature. We try to point future research in a novel direction, where the amino code is not the most relevant characteristic of the process but the conditions within the cell.
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.