Translationsregulation des Myelin basischen Proteins in Gliazellen

Im zentralen Nervensystem (ZNS) myelinisieren Oligodendrozyten neuronale Axone, indem sie ihre Zellfortsätze mehrfach um axonale Segmente wickeln. Die Ausbildung dieser multilamellaren Membranstapel ermöglicht eine saltatorische und damit rasche und energie-effiziente Erregungsleitung (Nave, 2010). Eine Schädigung des Myelins beeinträchtigt die Reizweiterleitung und führt zur Degeneration der Axone, wie es zum Beispiel bei der Multiplen Sklerose der Fall ist. Das Myelin basische Protein (MBP) ist ein Hauptbestandteil des Myelin und ist essentiell für die Kompaktierung der Myelinmembran (Wood et al., 1984). Die MBP mRNA wird in hnRNP A2 enthaltenen RNA Granulen in einem translations-inaktiven Zustand zu den distalen Fortsätzen transportiert. Vermittelt durch axonale Signale wird nach axo-glialem Kontakt die Translation von MBP ermöglicht (White et al., 2008). Der genaue Mechanismus der differentiellen Genregulation des MBP Proteins ist bisher nur unzureichend aufgeklärt. In der vorliegenden Arbeit konnte eine kleine regulatorische RNA (sncRNA) identifiziert werden, welche über die seed Region mit der MBP mRNA interagieren und die Translation regulieren kann. In primären Oligodendrozyten führt die Überexpression der sncRNA-715 zu reduzierten MBP Protein Mengen und die Blockierung der endogenen sncRNA-715 führt zu einer gesteigerten MBP Synthese. Interessanterweise korreliert während der Differenzierung der Oligodendrozyten in vitro und in vivo die Synthese des MBP Proteins invers mit der Expression der sncRNA-715. In Oligodendrozyten beeinflusst eine experimentell erhöhte sncRNA-715 Menge die Zellmorphologie und induziert Apoptose. Weiterhin ist sncRNA-715 in zytoplasmatischen granulären Strukturen lokalisiert und assoziiert mit MBP mRNA in hnRNP A2 Transport- Granula. Diese Ergebnisse lassen vermuten, dass sncRNA-715 ein Bestandteil der hnRNP A2 Granula sein könnte und dort spezifisch die Translation der MBP mRNA während des Lokalisationsprozesses inhibiert. In chronischen MS Läsionen sind Olig2+-Zellen zu finden. Obwohl die MBP mRNA in diesen Läsionen nachzuweisen ist, kann kein Protein synthetisiert werden. In dieser Arbeit konnte gezeigt werden, dass in diesen Läsionen die Expression der sncRNA-715 erhöht ist. SncRNA-715 könnte die Translation von MBP verhindern und folglich als Inhibitor der Remyelinisierung während des Krankheitsverlaufs fungieren. Schwann-Zellen sind die myelinisierenden Zellen im peripheren Nervensystem (PNS). Im Zuge der Myelinisierung wird die MBP mRNA in diesen Gliazellen ebenfalls in die distalen Fortsätze transportiert und dort lokal translatiert und in die Myelinmembran eingebaut (Trapp et al., 1987). Im Gegensatz zum ZNS ist im PNS nur wenig über den Transportmechanismus der mRNA bekannt (Masaki, 2012). Es ist es sehr wahrscheinlich, dass in Schwann-Zellen und Oligodendrozyten die Lokalisation und die translationale Hemmung der MBP mRNA ähnlichen Mechanismen unterliegen. In der vorliegenden Arbeit konnte gezeigt werden, dass hnRNP A2 und sncRNA-715 in Schwann-Zellen exprimiert werden und in zytoplasmatischen Granula-ähnlichen Strukturen lokalisiert sind. Während der Differenzierung dieser Gliazellen in vivo und in vitro korreliert die Expression der sncRNA-715 invers mit der Synthese des MBP Proteins. HnRNP A2 und sncRNA-715 scheinen in Schwann-Zellen assoziiert zu sein und könnten wie in Oligodendrozyten den Transport der MBP mRNA vermitteln.

Early steps in ventral nerve cord development in chelicerates and myriapods and formation of brain compartments in spiders

The central point of this work is the investigation of neurogenesis in chelicerates and myriapods. By comparing decisive mechanisms in neurogenesis in the four arthropod groups (Chelicerata, Crustacea, Insecta, Myriapoda) I was able to show which of these mechanisms are conserved and which developmental modules have diverged. Thereby two processes of embryonic development of the central nervous system were brought into focus. On the one hand I studied early neurogenesis in the ventral nerve cord of the spiders Cupiennius salei and Achaearanea tepidariorum and the millipede Glomeris marginata and on the other hand the development of the brain in Cupiennius salei.rnWhile the nervous system of insects and crustaceans is formed by the progeny of single neural stem cells (neuroblasts), in chelicerates and myriapods whole groups of cells adopt the neural cell fate and give rise to the ventral nerve cord after their invagination. The detailed comparison of the positions and the number of the neural precursor groups within the neuromeres in chelicerates and myriapods showed that the pattern is almost identical which suggests that the neural precursors groups in these arthropod groups are homologous. This pattern is also very similar to the neuroblast pattern in insects. This raises the question if the mechanisms that confer regional identity to the neural precursors is conserved in arthropods although the mode of neural precursor formation is different. The analysis of the functions and expression patterns of genes which are known to be involved in this mechanism in Drosophila melanogaster showed that neural patterning is highly conserved in arthropods. But I also discovered differences in early neurogenesis which reflect modifications and adaptations in the development of the nervous systems in the different arthropod groups.rnThe embryonic development of the brain in chelicerates which was investigated for the first time in this work shows similarities but also some modifications to insects. In vertebrates and arthropods the adult brain is composed of distinct centres with different functions. Investigating how these centres, which are organised in smaller compartments, develop during embryogenesis was part of this work. By tracing the morphogenetic movements and analysing marker gene expressions I could show the formation of the visual brain centres from the single-layered precheliceral neuroectoderm. The optic ganglia, the mushroom bodies and the arcuate body (central body) are formed by large invaginations in the peripheral precheliceral neuroectoderm. This epithelium itself contains neural precursor groups which are assigned to the respective centres and thereby build the three-dimensional optical centres. The single neural precursor groups are distinguishable during this process leading to the assumption that they carry positional information which might subdivide the individual brain centres into smaller functional compartments.rn

Ab-initio study of hydrogen technology materials for hydrogen storage and proton conduction

This dissertation deals with two specific aspects of a potential hydrogen-based energy economy, namely the problems of energy storage and energy conversion. In order to contribute to the solution of these problems, the structural and dynamical properties of two promising materials for hydrogen storage (lithium imide/amide) and proton conduction (poly[vinyl phosphonic acid]) are modeled on an atomistic scale by means of first principles molecular dynamics simulation methods.rnrnrnIn the case of the hydrogen storage system lithium amide/imide (LiNH_2/Li_2NH), the focus was on the interplay of structural features and nuclear quantum effects. For these calculations, Path-Integral Molecular Dynamics (PIMD) simulations were used. The structures of these materials at room temperature were elucidated; in collaboration with an experimental group, a very good agreement between calculated and experimental solid-state 1H-NMR chemical shifts was observed. Specifically, the structure of Li_2NH features a disordered arrangement of the Li lattice, which was not reported in previous studies. In addition, a persistent precession of the NH bonds was observed in our simulations. We provide evidence that this precession is the consequence of a toroid-shaped effective potential, in which the protons in the material are immersed. This potential is essentially flat along the torus azimuthal angle, which might lead to important quantum delocalization effects of the protons over the torus.rnrnOn the energy conversion side, the dynamics of protons in a proton conducting polymer (poly[vinyl phosphonic acid], PVPA) was studied by means of a steered ab-initio Molecular Dynamics approach applied on a simplified polymer model. The focus was put on understanding the microscopic proton transport mechanism in polymer membranes, and on characterizing the relevance of the local environment. This covers particularly the effect of water molecules, which participate in the hydrogen bonding network in the material. The results indicate that these water molecules are essential for the effectiveness of proton conduction. A water-mediated Grotthuss mechanism is identified as the main contributor to proton conduction, which agrees with the experimentally observed decay on conductivity for the same material in the absence of water molecules.rnrnThe gain in understanding the microscopic processes and structures present in this materials can help the development of new materials with improved properties, thus contributing to the solution of problems in the implementation of fuel cells.

Fyn kinase targets in oligodendroglial physiology and myelination

In the central nervous system (CNS), oligodendrocytes form the multilamellar and compacted myelin sheath by spirally wrapping around defined axons with their specialised plasma membrane. Myelin is crucial for the rapid saltatory conduction of nerve impulses and for the preservation of axonal integrity. The absence of the major myelin component Myelin Basic Protein (MBP) results in an almost complete failure to form compact myelin in the CNS. The mRNA of MBP is sorted to cytoplasmic RNA granules and transported to the distal processes of oligodendrocytes in a translationally silent state. A main mediator of MBP mRNA localisation is the trans-acting factor heterogeneous nuclear ribonucleoprotein (hnRNP) A2 which binds to the cis-acting A2 response element (A2RE) in the 3’UTR of MBP mRNA. A signalling cascade had been identified that triggers local translation of MBP at the axon-glial contact site, involving the neuronal cell adhesion molecule (CAM) L1, the oligodendroglial plasma membrane-tethered Fyn kinase and Fyn-dependent phosphorylation of hnRNP A2. This model was confirmed here, showing that L1 stimulates Fyn-dependent phosphorylation of hnRNP A2 and a remodelling of A2-dependent RNA granule structures. Furthermore, the RNA helicase DDX5 was confirmed here acting together with hnRNP A2 in cytoplasmic RNA granules and is possibly involved in MBP mRNA granule dynamics.rnLack of non-receptor tyrosine kinase Fyn activity leads to reduced levels of MBP and hypomyelination in the forebrain. The multiadaptor protein p130Cas and the RNA-binding protein hnRNP F were verified here as additional targets of Fyn in oligodendrocytes. The findings point at roles of p130Cas in the regulation of Fyn-dependent process outgrowth and signalling cascades ensuring cell survival. HnRNP F was identified here as a novel constituent of oligodendroglial cytoplasmic RNA granules containing hnRNP A2 and MBP mRNA. Moreover, it was found that hnRNP F plays a role in the post-transcriptional regulation of MBP mRNA and that defined levels of hnRNP F are required to facilitate efficient synthesis of MBP. HnRNP F appears to be directly phosphorylated by Fyn kinase what presumably contributes to the initiation of translation of MBP mRNA at the plasma membrane.rnFyn kinase signalling thus affects many aspects of oligodendroglial physiology contributing to myelination. Post-transcriptional control of the synthesis of the essential myelin protein MBP by Fyn targets is particularly important. Deregulation of these Fyn-dependent pathways could thus negatively influence disorders involving the white matter of the nervous system.rnrn

Periodicities in the Hodgkin-Huxley model and versions of this model with stochastic input

A field of computational neuroscience develops mathematical models to describe neuronal systems. The aim is to better understand the nervous system. Historically, the integrate-and-fire model, developed by Lapique in 1907, was the first model describing a neuron. In 1952 Hodgkin and Huxley [8] described the so called Hodgkin-Huxley model in the article “A Quantitative Description of Membrane Current and Its Application to Conduction and Excitation in Nerve”. The Hodgkin-Huxley model is one of the most successful and widely-used biological neuron models. Based on experimental data from the squid giant axon, Hodgkin and Huxley developed their mathematical model as a four-dimensional system of first-order ordinary differential equations. One of these equations characterizes the membrane potential as a process in time, whereas the other three equations depict the opening and closing state of sodium and potassium ion channels. The membrane potential is proportional to the sum of ionic current flowing across the membrane and an externally applied current. For various types of external input the membrane potential behaves differently. This thesis considers the following three types of input: (i) Rinzel and Miller [15] calculated an interval of amplitudes for a constant applied current, where the membrane potential is repetitively spiking; (ii) Aihara, Matsumoto and Ikegaya [1] said that dependent on the amplitude and the frequency of a periodic applied current the membrane potential responds periodically; (iii) Izhikevich [12] stated that brief pulses of positive and negative current with different amplitudes and frequencies can lead to a periodic response of the membrane potential. In chapter 1 the Hodgkin-Huxley model is introduced according to Izhikevich [12]. Besides the definition of the model, several biological and physiological notes are made, and further concepts are described by examples. Moreover, the numerical methods to solve the equations of the Hodgkin-Huxley model are presented which were used for the computer simulations in chapter 2 and chapter 3. In chapter 2 the statements for the three different inputs (i), (ii) and (iii) will be verified, and periodic behavior for the inputs (ii) and (iii) will be investigated. In chapter 3 the inputs are embedded in an Ornstein-Uhlenbeck process to see the influence of noise on the results of chapter 2.