DNA methylation in Dictyostelium discoideum

DNA methyltransferases of type Dnmt2 are a highly conserved protein family with enigmatic function. The aim of this work was to characterize DnmA, the Dnmt2 methyltransferase in Dictyostelium discoideum, and further to investigate its implication in DNA methylation and transcriptional gene silencing. The genome of the social amoeba Dictyostelium encodes DnmA as the sole DNA methyltransferase. The enzyme bears all ten characteristic DNA methyltransferase motifs in its catalytic domain. The DnmA mRNA was found by RT-PCR to be expressed during vegetative growth and down regulated during development. Investigations using fluorescence microscopy showed that both DnmA-myc and DnmA-GFP fusions predominantly localised to the nucleus. The function of DnmA remained initially unclear, but later experiment revealed that the enzyme is an active DNA methyltransferase responsible for all DNA (cytosine) methylation in Dictyostelium. Neither in gel retardation assays, nor by the yeast two hybrid system, clues on the functionality of DnmA could be obtained. However, immunological detection of the methylation mark with an α - 5mC antibody gave initial evidence that the DNA of Dictyostelium was methylated. Furthermore, addition of 5-aza-cytidine as demethylating agent to the Dictyostelium medium and subsequent in vitro incubation of the DNA isolated from these cells with recombinant DnmA showed that the enzyme binds slightly better to this target DNA. In order to investigate further the function of the protein, a gene knock-out for dnmA was generated. The gene was successfully disrupted by homologous recombination, the knock-out strain, however, did not show any obvious phenotype under normal laboratory conditions. To identify specific target sequences for DNA methylation, a microarray analysis was carried out. Setting a threshold of at least 1.5 fold for differences in the strength of gene expression, several such genes in the knock-out strain were chosen for further investigation. Among the up-regulated genes were the ESTs representing the gag and the RT genes respectively of the retrotransposon skipper. In addition Northern blot analysis confirmed the up-regulation of skipper in the DnmA knock-out strain. Bisufite treatment and sequencing of specific DNA stretches from skipper revealed that DnmA is responsible for methylation of mostly asymmetric cytosines. Together with skipper, DIRS-1 retrotransposon was found later also to be methylated but was not present on the microarray. Furthermore, skipper transcription was also up-regulated in strains that had genes disrupted encoding components of the RNA interference pathway. In contrast, DIRS 1 expression was not affected by a loss of DnmA but was strongly increased in the strain that had the RNA directed RNA polymerase gene rrpC disrupted. Strains generated by propagating the usual wild type Ax2 and the DnmA knock-out cells over 16 rounds in development were analyzed for transposon activity. Northern blot analysis revealed activation for skipper expression, but not for DIRS-1. A large number of siRNAs were found to be correspondent to the DIRS-1 sequence, suggesting concerted regulation of DIRS-1 expression by RNAi and DNA methylation. In contrast, no siRNAs corresponding to the standard skipper element were found. The data show that DNA methylation plays a crucial role in epigenetic gene regulation in Dictyostelium and that different, partially overlapping mechanisms control transposon silencing for skipper and DIRS-1. To elucidate the mechanism of targeting the protein to particular genes in the Dictyostelium genome, some more genes which were up-regulated in the DnmA knock-out strain were analyzed by bisulfite sequencing. The chosen genes are involved in the multidrug response in other species, but their function in Dictyostelium is uncertain. Bisulfite data showed that two of these genes were methylated at asymmetrical C-residues in the wild type, but not in DnmA knock-out cells. This suggested that DNA methylation in Dictyostelium is involved not only in transposon regulation but also in transcriptional silencing of specific genes.

Information Exchange and Fusion in Dynamic and Heterogeneous Distributed Environments

Context awareness, dynamic reconfiguration at runtime and heterogeneity are key characteristics of future distributed systems, particularly in ubiquitous and mobile computing scenarios. The main contributions of this dissertation are theoretical as well as architectural concepts facilitating information exchange and fusion in heterogeneous and dynamic distributed environments. Our main focus is on bridging the heterogeneity issues and, at the same time, considering uncertain, imprecise and unreliable sensor information in information fusion and reasoning approaches. A domain ontology is used to establish a common vocabulary for the exchanged information. We thereby explicitly support different representations for the same kind of information and provide Inter-Representation Operations that convert between them. Special account is taken of the conversion of associated meta-data that express uncertainty and impreciseness. The Unscented Transformation, for example, is applied to propagate Gaussian normal distributions across highly non-linear Inter-Representation Operations. Uncertain sensor information is fused using the Dempster-Shafer Theory of Evidence as it allows explicit modelling of partial and complete ignorance. We also show how to incorporate the Dempster-Shafer Theory of Evidence into probabilistic reasoning schemes such as Hidden Markov Models in order to be able to consider the uncertainty of sensor information when deriving high-level information from low-level data. For all these concepts we provide architectural support as a guideline for developers of innovative information exchange and fusion infrastructures that are particularly targeted at heterogeneous dynamic environments. Two case studies serve as proof of concept. The first case study focuses on heterogeneous autonomous robots that have to spontaneously form a cooperative team in order to achieve a common goal. The second case study is concerned with an approach for user activity recognition which serves as baseline for a context-aware adaptive application. Both case studies demonstrate the viability and strengths of the proposed solution and emphasize that the Dempster-Shafer Theory of Evidence should be preferred to pure probability theory in applications involving non-linear Inter-Representation Operations.

Parameter identification of structural dynamic models by inverse statistical analysis

Auf dem Gebiet der Strukturdynamik sind computergestützte Modellvalidierungstechniken inzwischen weit verbreitet. Dabei werden experimentelle Modaldaten, um ein numerisches Modell für weitere Analysen zu korrigieren. Gleichwohl repräsentiert das validierte Modell nur das dynamische Verhalten der getesteten Struktur. In der Realität gibt es wiederum viele Faktoren, die zwangsläufig zu variierenden Ergebnissen von Modaltests führen werden: Sich verändernde Umgebungsbedingungen während eines Tests, leicht unterschiedliche Testaufbauten, ein Test an einer nominell gleichen aber anderen Struktur (z.B. aus der Serienfertigung), etc. Damit eine stochastische Simulation durchgeführt werden kann, muss eine Reihe von Annahmen für die verwendeten Zufallsvariablengetroffen werden. Folglich bedarf es einer inversen Methode, die es ermöglicht ein stochastisches Modell aus experimentellen Modaldaten zu identifizieren. Die Arbeit beschreibt die Entwicklung eines parameter-basierten Ansatzes, um stochastische Simulationsmodelle auf dem Gebiet der Strukturdynamik zu identifizieren. Die entwickelte Methode beruht auf Sensitivitäten erster Ordnung, mit denen Parametermittelwerte und Kovarianzen des numerischen Modells aus stochastischen experimentellen Modaldaten bestimmt werden können.