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- Institut für Biochemie und Biologie (61) (entfernen)
Dispersal behavior plays an important role for the geographical distribution and population structure of any given species. Individual’s fitness, reproductive and competitive ability, and dispersal behavior can be determined by the age of the individual. Age-dependent as well as density-dependent dispersal patterns are common in many bird species. In this thesis, I first present age-dependent breeding ability and natal site fidelity in white storks (Ciconia ciconia); migratory birds breeding in large parts of Europe. I predicted that both the proportion of breeding birds and natal site fidelity increase with the age. After the seventies of the last century, following a steep population decline, a recovery of the white stork population has been observed in many regions in Europe. Increasing population density in the white stork population in Eastern Germany especially after 1983 allowed examining density- as well as age-dependent breeding dispersal patterns. Therefore second, I present whether: young birds show more often and longer breeding dispersal than old birds, and frequency of dispersal events increase with the population density increase, especially in the young storks. Third, I present age- and density-dependent dispersal direction preferences in the give population. I asked whether and how the major spring migration direction interacts with dispersal directions of white storks: in different age, and under different population densities. The proportion of breeding individuals increased in the first 22 years of life and then decreased suggesting, the senescent decay in aging storks. Young storks were more faithful to their natal sites than old storks probably due to their innate migratory direction and distance. Young storks dispersed more frequently than old storks in general, but not for longer distance. Proportion of dispersing individuals increased significantly with increasing population densities indicating, density- dependent dispersal behavior in white storks. Moreover, the finding of a significant interaction effects between the age of dispersing birds and year (1980–2006) suggesting, older birds dispersed more from their previous nest sites over time due to increased competition. Both young and old storks dispersed along their spring migration direction; however, directional preferences were different in young storks and old storks. Young storks tended to settle down before reaching their previous nest sites (leading to the south-eastward dispersal) while old birds tended to keep migrating along the migration direction after reaching their previous nest sites (leading to the north-westward dispersal). Cues triggering dispersal events may be age-dependent. Changes in the dispersal direction over time were observed. Dispersal direction became obscured during the second half of the observation period (1993–2006). Increase in competition may affect dispersal behavior in storks. I discuss the potential role of: age for the observed age-dependent dispersal behavior, and competition for the density dependent dispersal behavior. This Ph.D. thesis contributes significantly to the understanding of population structure and geographical distribution of white storks. Moreover, presented age- and density (competition)-dependent dispersal behavior helps understanding underpinning mechanisms of dispersal behavior in bird species.
Untersuchung und Veränderung der Genexpression und Proteinstabilität in Plastiden höherer Pflanzen
(2009)
Transcription factor networks in the initial ohase of drouht stress in rice (Oryza sativa L.)
(2009)
This work presents mathematical and computational approaches to cover various aspects of metabolic network modelling, especially regarding the limited availability of detailed kinetic knowledge on reaction rates. It is shown that precise mathematical formulations of problems are needed i) to find appropriate and, if possible, efficient algorithms to solve them, and ii) to determine the quality of the found approximate solutions. Furthermore, some means are introduced to gain insights on dynamic properties of metabolic networks either directly from the network structure or by additionally incorporating steady-state information. Finally, an approach to identify key reactions in a metabolic networks is introduced, which helps to develop simple yet useful kinetic models. The rise of novel techniques renders genome sequencing increasingly fast and cheap. In the near future, this will allow to analyze biological networks not only for species but also for individuals. Hence, automatic reconstruction of metabolic networks provides itself as a means for evaluating this huge amount of experimental data. A mathematical formulation as an optimization problem is presented, taking into account existing knowledge and experimental data as well as the probabilistic predictions of various bioinformatical methods. The reconstructed networks are optimized for having large connected components of high accuracy, hence avoiding fragmentation into small isolated subnetworks. The usefulness of this formalism is exemplified on the reconstruction of the sucrose biosynthesis pathway in Chlamydomonas reinhardtii. The problem is shown to be computationally demanding and therefore necessitates efficient approximation algorithms. The problem of minimal nutrient requirements for genome-scale metabolic networks is analyzed. Given a metabolic network and a set of target metabolites, the inverse scope problem has as it objective determining a minimal set of metabolites that have to be provided in order to produce the target metabolites. These target metabolites might stem from experimental measurements and therefore are known to be produced by the metabolic network under study, or are given as the desired end-products of a biotechological application. The inverse scope problem is shown to be computationally hard to solve. However, I assume that the complexity strongly depends on the number of directed cycles within the metabolic network. This might guide the development of efficient approximation algorithms. Assuming mass-action kinetics, chemical reaction network theory (CRNT) allows for eliciting conclusions about multistability directly from the structure of metabolic networks. Although CRNT is based on mass-action kinetics originally, it is shown how to incorporate further reaction schemes by emulating molecular enzyme mechanisms. CRNT is used to compare several models of the Calvin cycle, which differ in size and level of abstraction. Definite results are obtained for small models, but the available set of theorems and algorithms provided by CRNT can not be applied to larger models due to the computational limitations of the currently available implementations of the provided algorithms. Given the stoichiometry of a metabolic network together with steady-state fluxes and concentrations, structural kinetic modelling allows to analyze the dynamic behavior of the metabolic network, even if the explicit rate equations are not known. In particular, this sampling approach is used to study the stabilizing effects of allosteric regulation in a model of human erythrocytes. Furthermore, the reactions of that model can be ranked according to their impact on stability of the steady state. The most important reactions in that respect are identified as hexokinase, phosphofructokinase and pyruvate kinase, which are known to be highly regulated and almost irreversible. Kinetic modelling approaches using standard rate equations are compared and evaluated against reference models for erythrocytes and hepatocytes. The results from this simplified kinetic models can simulate acceptably the temporal behavior for small changes around a given steady state, but fail to capture important characteristics for larger changes. The aforementioned approach to rank reactions according to their influence on stability is used to identify a small number of key reactions. These reactions are modelled in detail, including knowledge about allosteric regulation, while all other reactions were still described by simplified reaction rates. These so-called hybrid models can capture the characteristics of the reference models significantly better than the simplified models alone. The resulting hybrid models might serve as a good starting point for kinetic modelling of genome-scale metabolic networks, as they provide reasonable results in the absence of experimental data, regarding, for instance, allosteric regulations, for a vast majority of enzymatic reactions.
Although the basic structure of biological membranes is provided by the lipid bilayer, most of the specific functions are carried out by membrane proteins (MPs) such as channels, ion-pumps and receptors. Additionally, it is known, that mutations in MPs are directly or indirectly involved in many diseases. Thus, structure determination of MPs is of major interest not only in structural biology but also in pharmacology, especially for drug development. Advances in structural biology of membrane proteins (MPs) have been strongly supported by the success of three leading techniques: X-ray crystallography, electron microscopy and solution NMR spectroscopy. However, X-ray crystallography and electron microscopy, require highly diffracting 3D or 2D crystals, respectively. Today, structure determination of non-crystalline solid protein preparations has been made possible through rapid progress of solid-state MAS NMR methodology for biological systems. Castellani et. al. solved and refined the first structure of a microcrystalline protein using only solid-state MAS NMR spectroscopy. These successful application open up perspectives to access systems that are difficult to crystallise or that form large heterogeneous complexes and insoluble aggregates, for example ligands bound to a MP-receptor, protein fibrils and heterogeneous proteins aggregates. Solid-state MAS NMR spectroscopy is in principle well suited to study MP at atomic resolution. In this thesis, different types of MP preparations were tested for their suitability to be studied by solid-state MAS NMR. Proteoliposomes, poorly diffracting 2D crystals and a PEG precipitate of the outer membrane protein G (OmpG) were prepared as a model system for large MPs. Results from this work, combined with data found in the literature, show that highly diffracting crystalline material is not a prerequirement for structural analysis of MPs by solid-state MAS NMR. Instead, it is possible to use non-diffracting 3D crystals, MP precipitates, poorly diffracting 2D crystals and proteoliposomes. For the latter two types of preparations, the MP is reconstituted into a lipid bilayer, which thus allows the structural investigation in a quasi-native environment. In addition, to prepare a MP sample for solid-state MAS NMR it is possible to use screening methods, that are well established for 3D and 2D crystallisation of MPs. Hopefully, these findings will open a fourth method for structural investigation of MP. The prerequisite for structural studies by NMR in general, and the most time consuming step, is always the assignment of resonances to specific nuclei within the protein. Since the last few years an ever-increasing number of assignments from solid-state MAS NMR of uniformly carbon and nitrogen labelled samples is being reported, mostly for small proteins of up to around 150 amino acids in length. However, the complexity of the spectra increases with increasing molecular weight of the protein. Thus the conventional assignment strategies developed for small proteins do not yield a sufficiently high degree of assignment for the large MP OmpG (281 amino acids). Therefore, a new assignment strategy to find starting points for large MPs was devised. The assignment procedure is based on a sample with [2,3-13C, 15N]-labelled Tyr and Phe and uniformly labelled alanine and glycine. This labelling pattern reduces the spectral overlap as well as the number of assignment possibilities. In order to extend the assignment, four other specifically labelled OmpG samples were used. The assignment procedure starts with the identification of the spin systems of each labelled amino acid using 2D 13C-13C and 3D NCACX correlation experiments. In a second step, 2D and 3D NCOCX type experiments are used for the sequential assignment of the observed resonances to specific nuclei in the OmpG amino acid sequence. Additionally, it was shown in this work, that biosynthetically site directed labelled samples, which are normally used to observe long-range correlations, were helpful to confirm the assignment. Another approach to find assignment starting points in large protein systems, is the use of spectroscopic filtering techniques. A filtering block that selects methyl resonances was used to find further assignment starting points for OmpG. Combining all these techniques, it was possible to assign nearly 50 % of the observed signals to the OmpG sequence. Using this information, a prediction of the secondary structure elements of OmpG was possible. Most of the calculated motifs were in good aggreement with the crystal structures of OmpG. The approaches presented here should be applicable to a wide variety of MPs and MP-complexes and should thus open a new avenue for the structural biology of MPs.