92-XX BIOLOGY AND OTHER NATURAL SCIENCES
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The complex hierarchical structure of bone undergoes a lifelong remodeling process, where it adapts to mechanical needs. Hereby, bone resorption by osteoclasts and bone formation by osteoblasts have to be balanced to sustain a healthy and stable organ. Osteocytes orchestrate this interplay by sensing mechanical strains and translating them into biochemical signals. The osteocytes are located in lacunae and are connected to one another and other bone cells via cell processes through small channels, the canaliculi. Lacunae and canaliculi form a network (LCN) of extracellular spaces that is able to transport ions and enables cell-to-cell communication. Osteocytes might also contribute to mineral homeostasis by direct interactions with the surrounding matrix. If the LCN is acting as a transport system, this should be reflected in the mineralization pattern. The central hypothesis of this thesis is that osteocytes are actively changing their material environment. Characterization methods of material science are used to achieve the aim of detecting traces of this interaction between osteocytes and the extracellular matrix. First, healthy murine bones were characterized. The properties analyzed were then compared with three murine model systems: 1) a loading model, where a bone of the mouse was loaded during its life time; 2) a healing model, where a bone of the mouse was cut to induce a healing response; and 3) a disease model, where the Fbn1 gene is dysfunctional causing defects in the formation of the extracellular tissue.
The measurement strategy included routines that make it possible to analyze the organization of the LCN and the material components (i.e., the organic collagen matrix and the mineral particles) in the same bone volumes and compare the spatial distribution of different data sets. The three-dimensional network architecture of the LCN is visualized by confocal laser scanning microscopy (CLSM) after rhodamine staining and is then subsequently quantified. The calcium content is determined via quantitative backscattered electron imaging (qBEI), while small- and wide-angle X-ray scattering (SAXS and WAXS) are employed to determine the thickness and length of local mineral particles.
First, tibiae cortices of healthy mice were characterized to investigate how changes in LCN architecture can be attributed to interactions of osteocytes with the surrounding bone matrix. The tibial mid-shaft cross-sections showed two main regions, consisting of a band with unordered LCN surrounded by a region with ordered LCN. The unordered region is a remnant of early bone formation and exhibited short and thin mineral particles. The surrounding, more aligned bone showed ordered and dense LCN as well as thicker and longer mineral particles. The calcium content was unchanged between the two regions.
In the mouse loading model, the left tibia underwent two weeks of mechanical stimulation, which results in increased bone formation and decreased resorption in skeletally mature mice. Here the specific research question addressed was how do bone material characteristics change at (re)modeling sites? The new bone formed in response to mechanical stimulation showed similar properties in terms of the mineral particles, like the ordered calcium region but lower calcium content compared to the right, non-loaded control bone of the same mice. There was a clear, recognizable border between mature and newly formed bone. Nevertheless, some canaliculi went through this border connecting the LCN of mature and newly formed bone.
Additionally, the question should be answered whether the LCN topology and the bone matrix material properties adapt to loading. Although, mechanically stimulated bones did not show differences in calcium content compared to controls, different correlations were found between the local LCN density and the local Ca content depending on whether the bone was loaded or not. These results suggest that the LCN may serve as a mineral reservoir.
For the healing model, the femurs of mice underwent an osteotomy, stabilized with an external fixator and were allowed to heal for 21 days. Thus, the spatial variations in the LCN topology with mineral properties within different tissue types and their interfaces, namely calcified cartilage, bony callus and cortex, could be simultaneously visualized and compared in this model. All tissue types showed structural differences across multiple length scales. Calcium content increased and became more homogeneous from calcified cartilage to bony callus to lamellar cortical bone. The degree of LCN organization increased as well, while the lacunae became smaller, as did the lacunar density between these different tissue types that make up the callus. In the calcified cartilage, the mineral particles were short and thin. The newly formed callus exhibited thicker mineral particles, which still had a low degree of orientation. While most of the callus had a woven-like structure, it also served as a scaffold for more lamellar tissue at the edges. The lamelar bone callus showed thinner mineral particles, but a higher degree of alignment in both, mineral particles and the LCN. The cortex showed the highest values for mineral length, thickness and degree of orientation. At the same time, the lacunae number density was 34% lower and the lacunar volume 40% smaller compared to bony callus. The transition zone between cortical and callus regions showed a continuous convergence of bone mineral properties and lacunae shape. Although only a few canaliculi connected callus and the cortical region, this indicates that communication between osteocytes of both tissues should be possible. The presented correlations between LCN architecture and mineral properties across tissue types may suggest that osteocytes have an active role in mineralization processes of healing.
A mouse model for the disease marfan syndrome, which includes a genetic defect in the fibrillin-1 gene, was investigated. In humans, Marfan syndrome is characterized by a range of clinical symptoms such as long bone overgrowth, loose joints, reduced bone mineral density, compromised bone microarchitecture, and increased fracture rates. Thus, fibrillin-1 seems to play a role in the skeletal homeostasis. Therefore, the present work studied how marfan syndrome alters LCN architecture and the surrounding bone matrix. The mice with marfan syndrome showed longer tibiae than their healthy littermates from an age of seven weeks onwards. In contrast, the cortical development appeared retarded, which was observed across all measured characteristics, i. e. lower endocortical bone formation, looser and less organized lacuno-canalicular network, less collagen orientation, thinner and shorter mineral particles.
In each of the three model systems, this study found that changes in the LCN architecture spatially correlated with bone matrix material parameters. While not knowing the exact mechanism, these results provide indications that osteocytes can actively manipulate a mineral reservoir located around the canaliculi to make a quickly accessible contribution to mineral homeostasis. However, this interaction is most likely not one-sided, but could be understood as an interplay between osteocytes and extra-cellular matrix, since the bone matrix contains biochemical signaling molecules (e.g. non-collagenous proteins) that can change osteocyte behavior. Bone (re)modeling can therefore not only be understood as a method for removing defects or adapting to external mechanical stimuli, but also for increasing the efficiency of possible osteocyte-mineral interactions during bone homeostasis. With these findings, it seems reasonable to consider osteocytes as a target for drug development related to bone diseases that cause changes in bone composition and mechanical properties. It will most likely require the combined effort of materials scientists, cell biologists, and molecular biologists to gain a deeper understanding of how bone cells respond to their material environment.
Proteine sind an praktisch allen Prozessen in lebenden Zellen maßgeblich beteiligt. Auch in der Biotechnologie werden Proteine in vielfältiger Weise eingesetzt.
Ein Protein besteht aus einer Kette von Aminosäuren. Häufig lagern sich mehrere dieser Ketten zu größeren Strukturen und Funktionseinheiten, sogenannten Proteinkomplexen,
zusammen. Kürzlich wurde gezeigt, dass eine Proteinkomplexbildung bereits während der Biosynthese der Proteine (co-translational) stattfinden kann
und nicht stets erst danach (post-translational) erfolgt. Da Fehlassemblierungen von Proteinen zu Funktionsverlusten und adversen Effekten führen, ist eine präzise und verlässliche Proteinkomplexbildung sowohl für zelluläre Prozesse als auch für biotechnologische Anwendungen essenziell. Mit experimentellen Methoden lassen sich zwar u.a. die Stöchiometrie und die Struktur von Proteinkomplexen bestimmen,
jedoch bisher nicht die Dynamik der Komplexbildung auf unterschiedlichen Zeitskalen. Daher sind grundlegende Mechanismen der Proteinkomplexbildung noch nicht vollständig verstanden. Die hier vorgestellte, auf experimentellen Erkenntnissen aufbauende, computergestützte Modellierung der Proteinkomplexbildung erlaubt eine umfassende Analyse des Einflusses physikalisch-chemischer Parameter
auf den Assemblierungsprozess. Die Modelle bilden möglichst realistisch die experimentellen Systeme der Kooperationspartner (Bar-Ziv, Weizmann-Institut, Israel; Bukau und Kramer, Universität Heidelberg) ab, um damit die Assemblierung von Proteinkomplexen einerseits in einem quasi-zweidimensionalen synthetischen Expressionssystem (in vitro) und andererseits im Bakterium Escherichia coli (in vivo) untersuchen zu können. Mit Hilfe eines vereinfachten Expressionssystems, in dem die Proteine nur an die Chip-Oberfläche, aber nicht aneinander binden können, wird das theoretische Modell parametrisiert. In diesem vereinfachten in-vitro-System durchläuft die Effizienz der Komplexbildung drei Regime – ein bindedominiertes Regime, ein Mischregime und ein produktionsdominiertes Regime. Ihr Maximum erreicht die Effizienz dabei kurz nach dem Übergang vom bindedominierten ins Mischregime und fällt anschließend monoton ab. Sowohl im nicht-vereinfachten in-vitro- als auch im in-vivo-System koexistieren je zwei konkurrierende Assemblierungspfade: Im in-vitro-System erfolgt die Komplexbildung entweder spontan in wässriger Lösung (Lösungsassemblierung) oder aber in einer definierten Schrittfolge an der Chip-Oberfläche (Oberflächenassemblierung); Im in-vivo-System konkurrieren hingegen die co- und die post-translationale Komplexbildung. Es zeigt sich, dass die Dominanz der Assemblierungspfade im in-vitro-System zeitabhängig ist und u.a. durch die Limitierung und Stärke der Bindestellen auf der Chip-Oberfläche beeinflusst werden kann. Im in-vivo-System hat der räumliche Abstand zwischen den Syntheseorten der beiden Proteinkomponenten nur dann einen Einfluss auf die Komplexbildung, wenn die Untereinheiten schnell degradieren. In diesem Fall dominiert die co-translationale Assemblierung auch auf kurzen Zeitskalen deutlich, wohingegen es bei stabilen Untereinheiten zu einem Wechsel von der Dominanz der post- hin zu einer geringen Dominanz der co-translationalen Assemblierung kommt. Mit den in-silico-Modellen lässt sich neben der Dynamik u.a. auch die Lokalisierung der Komplexbildung und -bindung darstellen, was einen Vergleich der theoretischen Vorhersagen mit experimentellen Daten und somit eine Validierung der Modelle ermöglicht. Der hier präsentierte in-silico Ansatz ergänzt die experimentellen Methoden, und erlaubt so, deren Ergebnisse zu interpretieren und neue Erkenntnisse davon abzuleiten.
The cell interior is a highly packed environment in which biological macromolecules evolve and function. This crowded media has effects in many biological processes such as protein-protein binding, gene regulation, and protein folding. Thus, biochemical reactions that take place in such crowded conditions differ from diluted test tube conditions, and a considerable effort has been invested in order to understand such differences.
In this work, we combine different computationally tools to disentangle the effects of molecular crowding on biochemical processes. First, we propose a lattice model to study the implications of molecular crowding on enzymatic reactions. We provide a detailed picture of how crowding affects binding and unbinding events and how the separate effects of crowding on binding equilibrium act together. Then, we implement a lattice model to study the effects of molecular crowding on facilitated diffusion. We find that obstacles on the DNA impair facilitated diffusion. However, the extent of this effect depends on how dynamic obstacles are on the DNA. For the scenario in which crowders are only present in the bulk solution, we find that at some conditions presence of crowding agents can enhance specific-DNA binding. Finally, we make use of structure-based techniques to look at the impact of the presence of crowders on the folding a protein. We find that polymeric crowders have stronger effects on protein stability than spherical crowders. The strength of this effect increases as the polymeric crowders become longer. The methods we propose here are general and can also be applied to more complicated systems.