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Regulation of potassium channels in plants : biophysical mechanisms and physiological implacations
(2011)
Eumelanin ist ein Fluorophor mit teilweise recht ungewöhnlichen spektralen Eigenschaften. Unter anderem konnten in früheren Veröffentlichungen Unterschiede zwischen dem 1- und 2-photonen-angeregtem Fluoreszenzspektrum beobachtet werden, weshalb im nichtlinearen Anregungsfall ein schrittweiser Anregungsprozess vermutet wurde. Um diese und weitere optische Eigenschaften des Eumelanins besser zu verstehen, wurden in der vorliegenden Arbeit vielfältige messmethodische Ansätze der linearen und nichtlinearen Optik an synthetischem Eumelanin in 0,1M NaOH verfolgt. Aus den Ergebnissen wurde ein Modell abgeleitet, welches die beobachteten photonischen Eigenschaften konsistent beschreibt. In diesem kaskadierten Zustandsmodell (Kaskaden-Modell) wird die aufgenommene Photonenenergie schrittweise von Anregungszuständen hoher Übergangsenergien zu Anregungszuständen niedrigerer Übergangsenergien transferiert. Messungen der transienten Absorption ergaben dominante Anteile mit kurzen Lebensdauern im ps-Bereich und ließen damit auf eine hohe Relaxationsgeschwindigkeit entlang der Kaskade schließen. Durch Untersuchung der nichtlinear angeregten Fluoreszenz von verschieden großen Eumelanin-Aggregaten konnte gezeigt werden, dass Unterschiede zwischen dem linear und nichtlinear angeregten Fluoreszenzspektrum nicht nur durch einen schrittweisen Anregungsprozess bei nichtlinearer Anregung sondern auch durch Unterschiede in den Verhältnissen der Quantenausbeuten zwischen kleinen und großen Aggregaten beim Wechsel von linearer zu nichtlinearer Anregung begründet sein können. Durch Bestimmung des Anregungswirkungsquerschnitts und der Anregungspulsdauer-Abhängigkeit der nichtlinear angeregten Fluoreszenz von Eumelanin konnte jedoch ein schrittweiser 2-Photonen-Anregungsprozess über einen Zwischenzustand mit Lebendsdauern im ps-Bereich nachgewiesen werden.
Mathematical modeling of biological phenomena has experienced increasing interest since new high-throughput technologies give access to growing amounts of molecular data. These modeling approaches are especially able to test hypotheses which are not yet experimentally accessible or guide an experimental setup. One particular attempt investigates the evolutionary dynamics responsible for today's composition of organisms. Computer simulations either propose an evolutionary mechanism and thus reproduce a recent finding or rebuild an evolutionary process in order to learn about its mechanism. The quest for evolutionary fingerprints in metabolic and gene-coexpression networks is the central topic of this cumulative thesis based on four published articles. An understanding of the actual origin of life will probably remain an insoluble problem. However, one can argue that after a first simple metabolism has evolved, the further evolution of metabolism occurred in parallel with the evolution of the sequences of the catalyzing enzymes. Indications of such a coevolution can be found when correlating the change in sequence between two enzymes with their distance on the metabolic network which is obtained from the KEGG database. We observe that there exists a small but significant correlation primarily on nearest neighbors. This indicates that enzymes catalyzing subsequent reactions tend to be descended from the same precursor. Since this correlation is relatively small one can at least assume that, if new enzymes are no "genetic children" of the previous enzymes, they certainly be descended from any of the already existing ones. Following this hypothesis, we introduce a model of enzyme-pathway coevolution. By iteratively adding enzymes, this model explores the metabolic network in a manner similar to diffusion. With implementation of an Gillespie-like algorithm we are able to introduce a tunable parameter that controls the weight of sequence similarity when choosing a new enzyme. Furthermore, this method also defines a time difference between successive evolutionary innovations in terms of a new enzyme. Overall, these simulations generate putative time-courses of the evolutionary walk on the metabolic network. By a time-series analysis, we find that the acquisition of new enzymes appears in bursts which are pronounced when the influence of the sequence similarity is higher. This behavior strongly resembles punctuated equilibrium which denotes the observation that new species tend to appear in bursts as well rather than in a gradual manner. Thus, our model helps to establish a better understanding of punctuated equilibrium giving a potential description at molecular level. From the time-courses we also extract a tentative order of new enzymes, metabolites, and even organisms. The consistence of this order with previous findings provides evidence for the validity of our approach. While the sequence of a gene is actually subject to mutations, its expression profile might also indirectly change through the evolutionary events in the cellular interplay. Gene coexpression data is simply accessible by microarray experiments and commonly illustrated using coexpression networks where genes are nodes and get linked once they show a significant coexpression. Since the large number of genes makes an illustration of the entire coexpression network difficult, clustering helps to show the network on a metalevel. Various clustering techniques already exist. However, we introduce a novel one which maintains control of the cluster sizes and thus assures proper visual inspection. An application of the method on Arabidopsis thaliana reveals that genes causing a severe phenotype often show a functional uniqueness in their network vicinity. This leads to 20 genes of so far unknown phenotype which are however suggested to be essential for plant growth. Of these, six indeed provoke such a severe phenotype, shown by mutant analysis. By an inspection of the degree distribution of the A.thaliana coexpression network, we identified two characteristics. The distribution deviates from the frequently observed power-law by a sharp truncation which follows after an over-representation of highly connected nodes. For a better understanding, we developed an evolutionary model which mimics the growth of a coexpression network by gene duplication which underlies a strong selection criterion, and slight mutational changes in the expression profile. Despite the simplicity of our assumption, we can reproduce the observed properties in A.thaliana as well as in E.coli and S.cerevisiae. The over-representation of high-degree nodes could be identified with mutually well connected genes of similar functional families: zinc fingers (PF00096), flagella, and ribosomes respectively. In conclusion, these four manuscripts demonstrate the usefulness of mathematical models and statistical tools as a source of new biological insight. While the clustering approach of gene coexpression data leads to the phenotypic characterization of so far unknown genes and thus supports genome annotation, our model approaches offer explanations for observed properties of the coexpression network and furthermore substantiate punctuated equilibrium as an evolutionary process by a deeper understanding of an underlying molecular mechanism.
A phagocyte-specific Irf8 gene enhancer establishes early conventional dendritic cell commitment
(2011)
Haematopoietic development is a complex process that is strictly hierarchically organized. Here, the phagocyte lineages are a very heterogeneous cell compartment with specialized functions in innate immunity and induction of adaptive immune responses. Their generation from a common precursor must be tightly controlled. Interference within lineage formation programs for example by mutation or change in expression levels of transcription factors (TF) is causative to leukaemia. However, the molecular mechanisms driving specification into distinct phagocytes remain poorly understood. In the present study I identify the transcription factor Interferon Regulatory Factor 8 (IRF8) as the specification factor of dendritic cell (DC) commitment in early phagocyte precursors. Employing an IRF8 reporter mouse, I showed the distinct Irf8 expression in haematopoietic lineage diversification and isolated a novel bone marrow resident progenitor which selectively differentiates into CD8α+ conventional dendritic cells (cDCs) in vivo. This progenitor strictly depends on Irf8 expression to properly establish its transcriptional DC program while suppressing a lineage-inappropriate neutrophile program. Moreover, I demonstrated that Irf8 expression during this cDC commitment-step depends on a newly discovered myeloid-specific cis-enhancer which is controlled by the haematopoietic transcription factors PU.1 and RUNX1. Interference with their binding leads to abrogation of Irf8 expression, subsequently to disturbed cell fate decisions, demonstrating the importance of these factors for proper phagocyte cell development. Collectively, these data delineate a transcriptional program establishing cDC fate choice with IRF8 in its center.
In this thesis entitled “Saccharide Recognition - Boronic acids as Receptors in Polymeric Networks” different aspects of boronic acid synthesis, their analysis and incorporation or attachment to different polymeric networks and characterisation thereof were investigated. The following key aspects were considered: • Provision of a variety of different characterised arylboronic acids and benzoboroxoles • Attachment of certain derivatives to nanoparticles and the characterisation of saccharide binding by means of isothermal titration calorimetry and displacement assay (ARS) to enhance the association constant to saccharides at pH 7.4 • Enhancement of selectivity in polymeric systems by means of molecular imprinting using fructose as template and a polymerisable benzoboroxole as functional monomer for the recognition at pH 7.4 (Joined by a diploma thesis of F. Grüneberger) • Development of biomimetic saccharide structures and the development of saccharide (especially glucose and fructose) binding MIPs by using these structures as template molecules. In the first part of the thesis different arylboronic acid derivatives were synthesised and their binding to glucose or fructose was investigated by means of isothermal titration calorimetry (ITC). It could be derived, which is in parallel to the literature, that derivatives bearing a methylhydroxyl-group in ortho-position to the boron (benzoboroxole) exhibit in most cases a two-fold higher association constant compared to the corresponding phenylboronic acid derivative. To gain a deeper understanding NMR spectroscopy and mass spectrometry with the benzoboroxole and glucose or fructose was performed. It could be shown that the exchange rate in terms of NMR time scale is quite slow since in titration experiments new peaks appeared. Via mass spectrometry of a mixture between benzoboroxole and glucose or fructose, different binding stoichiometries could be detected showing that the binding of saccharides is comparable with their binding to phenylboronic acid. In addition, the use of Alizarin Red S as an electrochemical reporter was described for the first time to monitor the saccharide binding to arylboronic acids not only with spectroscopy. Here, the redox behaviour and the displacement were recorded by cyclic voltammograms. In the second part different applications of boronic acids in polymeric networks were investigated. The attachment of benzoboroxoles to nanoparticles was investigated and monitored by means of isothermal titration calorimetry and a colourimetric assay with Alizarin Red S as the report dye. The investigations by isothermal titration calorimetry compared the fructose binding of arylboronic acids and benzoboroxoles coupled to these nanoparticles and “free” in solution. It could be shown that the attached derivatives showed a higher binding constant due to an increasing entropy term. This states for possible multivalent binding combined with a higher water release. Since ITC could not characterise the binding of glucose to these nanoparticles due to experimental restrictions the glucose binding at pH 7.4 was shown with ARS. Here, the displacement of ARS by fructose and also glucose could be followed and consequently these nanoparticles can be used for saccharide determination. Within this investigation also the temperature stability of these nanoparticles was examined and after normal sterilisation procedures (121°C, 20 min.) the binding behaviour was still unchanged. To target the selectivity of the used polymeric networks, molecular imprinting was used as a technique for creating artificial binding pockets on a molecular scale. As functional monomer 3-methacrylamidobenzoboroxole was introduced for the recognition of fructose. In comparison to polymers prepared with vinylphenylboronic acid the benzoboroxole containing polymer had a stronger binding at pH 7.4 which was shown for the first time. In addition, another imprinted polymer was synthesised especially for the recognition of glucose and fructose employing biomimetic saccharide analogues as template molecule. The advantage to use the saccharide analogues is the defined template-functional monomer complex during the polymerisation which is not the case, for example, for glucose-boronic acid interaction. The biomimetic character was proven through structural superimposition of crystal structures of the analogues with already described crystal structures of boronic acid esters of glucose and fructose. A molecularly imprinted polymer was synthesised with vinylphenylboronic acid as the functional monomer to show that both glucose and fructose are able to bind to the polymer which was predicted by the structural similarity of the analogues. The major scientific contributions of this thesis are • the determination of binding constants for some, not yet reported saccharide – boronic acid / benzoboroxole pairs, • the use of ARS as electrochemical reporter for saccharide detection, • the thermodynamic characterisation of a saccharide binding nanoparticle system containing benzoboroxole and functioning at pH 7.4, • the use of a polymerisable benzoboroxole as functional monomer for saccharide recognition in neutral, aqueous environments • and the synthesis and utilisation of biomimetic saccharide analogues as template molecules especially for the development of a glucose binding MIP.
Supermassive black holes are a fundamental component of the universe in general and of galaxies in particular. Almost every massive galaxy harbours a supermassive black hole (SMBH) in its center. Furthermore, there is a close connection between the growth of the SMBH and the evolution of its host galaxy, manifested in the relationship between the mass of the black hole and various properties of the galaxy's spheroid component, like its stellar velocity dispersion, luminosity or mass. Understanding this relationship and the growth of SMBHs is essential for our picture of galaxy formation and evolution. In this thesis, I make several contributions to improve our knowledge on the census of SMBHs and on the coevolution of black holes and galaxies. The first route I follow on this road is to obtain a complete census of the black hole population and its properties. Here, I focus particularly on active black holes, observable as Active Galactic Nuclei (AGN) or quasars. These are found in large surveys of the sky. In this thesis, I use one of these surveys, the Hamburg/ESO survey (HES), to study the AGN population in the local volume (z~0). The demographics of AGN are traditionally represented by the AGN luminosity function, the distribution function of AGN at a given luminosity. I determined the local (z<0.3) optical luminosity function of so-called type 1 AGN, based on the broad band B_J magnitudes and AGN broad Halpha emission line luminosities, free of contamination from the host galaxy. I combined this result with fainter data from the Sloan Digital Sky Survey (SDSS) and constructed the best current optical AGN luminosity function at z~0. The comparison of the luminosity function with higher redshifts supports the current notion of 'AGN downsizing', i.e. the space density of the most luminous AGN peaks at higher redshifts and the space density of less luminous AGN peaks at lower redshifts. However, the AGN luminosity function does not reveal the full picture of active black hole demographics. This requires knowledge of the physical quantities, foremost the black hole mass and the accretion rate of the black hole, and the respective distribution functions, the active black hole mass function and the Eddington ratio distribution function. I developed a method for an unbiased estimate of these two distribution functions, employing a maximum likelihood technique and fully account for the selection function. I used this method to determine the active black hole mass function and the Eddington ratio distribution function for the local universe from the HES. I found a wide intrinsic distribution of black hole accretion rates and black hole masses. The comparison of the local active black hole mass function with the local total black hole mass function reveals evidence for 'AGN downsizing', in the sense that in the local universe the most massive black holes are in a less active stage then lower mass black holes. The second route I follow is a study of redshift evolution in the black hole-galaxy relations. While theoretical models can in general explain the existence of these relations, their redshift evolution puts strong constraints on these models. Observational studies on the black hole-galaxy relations naturally suffer from selection effects. These can potentially bias the conclusions inferred from the observations, if they are not taken into account. I investigated the issue of selection effects on type 1 AGN samples in detail and discuss various sources of bias, e.g. an AGN luminosity bias, an active fraction bias and an AGN evolution bias. If the selection function of the observational sample and the underlying distribution functions are known, it is possible to correct for this bias. I present a fitting method to obtain an unbiased estimate of the intrinsic black hole-galaxy relations from samples that are affected by selection effects. Third, I try to improve our census of dormant black holes and the determination of their masses. One of the most important techniques to determine the black hole mass in quiescent galaxies is via stellar dynamical modeling. This method employs photometric and kinematic observations of the galaxy and infers the gravitational potential from the stellar orbits. This method can reveal the presence of the black hole and give its mass, if the sphere of the black hole's gravitational influence is spatially resolved. However, usually the presence of a dark matter halo is ignored in the dynamical modeling, potentially causing a bias on the determined black hole mass. I ran dynamical models for a sample of 12 galaxies, including a dark matter halo. For galaxies for which the black hole's sphere of influence is not well resolved, I found that the black hole mass is systematically underestimated when the dark matter halo is ignored, while there is almost no effect for galaxies with well resolved sphere of influence.