TY - THES A1 - Schwarz, Roland T1 - Modellierung von Metabolismus, Transkriptom und Zellentwicklung bei Arabidopsis, Listerien und anderen Organismen T1 - Modeling of metabolism, transcriptome and cell development in Arabidopsis, Listeria and other organisms N2 - Im gleichen Maße wie informatisches Wissen mehr und mehr in den wissenschaftlichen Alltag aller Lebenswissenschaften Einzug gehalten hat, hat sich der Schwerpunkt bioinformatischer Forschung in stärker mathematisch und informatisch-orientierte Themengebiete verschoben. Bioinformatik heute ist mehr als die computergestützte Verarbeitung großer Mengen an biologischen Daten, sondern hat einen entscheidenden Fokus auf der Modellierung komplexer biologischer Systeme. Zur Anwendung kommen hierbei insbesondere Theorien aus dem Bereich der Stochastik und Statistik, des maschinellen Lernens und der theoretischen Informatik. In der vorliegenden Dissertation beschreibe ich in Fallstudien die systematische Modellierung biologischer Systeme aus einem informatisch - mathematischen Standpunkt unter Anwendung von Verfahren aus den genannten Teilbereichen und auf unterschiedlichen Ebenen biologischer Abstraktion. Ausgehend von der Sequenzinformation über Transkriptom, Metabolom und deren regulatorischer Interaktion hin zur Modellierung von Populationseffekten werden hierbei aktuelle biologische Fragestellungen mit mathematisch - informatischen Modellen und einer Vielzahl experimenteller Daten kombiniert. Ein besonderer Augenmerk liegt dabei auf dem Vorgang der Modellierung und des Modellbegriffs als solchem im Rahmen moderner bioinformatischer Forschung. Im Detail umfassen die Projekte (mehrere Publikationen) die Entwicklung eines neuen Ansatzes zur Einbettung und Visualisierung von Multiplen Sequenz- und Sequenz-Strukturalignments, illustriert am Beispiel eines Hemagglutininalignments unterschiedlicher H5N1 Varianten, sowie die Modellierung des Transkriptoms von A. thaliana, bei welchem mit Hilfe einer kernelisierten nicht-parametrischen Metaanalyse neue, an der Infektionsabwehr beteiligten, Gene ausfindig gemacht werden konnten. Desweiteren ist uns mit Hilfe unserer Software YANAsquare eine detaillierte Untersuchung des Metabolismus von L. monocytogenes unter Aktivierung des Transkriptionsfaktors prfA gelungen, dessen Vorhersagen durch experimentelle 13C Isotopologstudien belegt werden konnten. In einem Anschlußprojekt war der Zusammenhang zwischen Regulation des Metabolismus durch Regulation der Genexpression und der Fluxverteilung des metabolischen Steady- State-Netzwerks das Ziel. Die Modellierung eines komplexen organismischen Phänotyps, der Zellgrößenentwicklung der Diatomee Pseudo-nitzschia delicatissima, schließt die Untersuchungen ab. N2 - In the same way that informatical knowledge has made its way into almost all areas of research in the Life Sciences, the focus of bioinformatical research has shifted towards topics originating more in the fields of mathematics and theoretical computer science. Bioinformatics today is more than the computer-driven processing of huge amounts of biological data, but it has a special focus on the emphmodelling of complex biological systems. Of special importance hereby are theories from stochastics and statistics, from the field of machine learning and theoretical computer science. In the following dissertation, I describe the systematic modelling of biological systems from an informatical-mathematical point of view in a case studies approach, applying methods from the aforementioned areas of research and on different levels of biological abstraction. Beginning with the sequence information itself, followed by the transcriptome, metabolome and the interaction of both and finally population effects I show how current biological questions can be tackled with mathematical models and combined with a variety of different experimental datasets. A special focus lies hereby on the procedure of modelling and the concept and notion of a model as such in the framework of bioinformatical research. In more detail, the projects contained the development of a new approach for embedding and visualizing Multiple Sequence and Structure Alignments, which was illustrated using a hemagglutinin alignment from different H5N1 variants as an example. Furthermore we investigated the A. thaliana transcriptome by means of a kernelized non-parametric meta-analysis, thus being able to annotate several new genes as pathogen-defense related. Another major part of this work was the modelling of the metabolic network of L. monocytogenes under activation of the transcription factor prfA, establishing predictions which were later verified by experimental 13C isotopologue studies. Following this project we investigated the relationship between the regulation of metabolism by changes in the cellular genexpression patterns and the flux distributions of the metabolic steady-state network. Modelling of a complex organismal property, the cell size development of the planktonic diatom Pseudo-nitzschia delicatissima concludes this work. KW - Bioinformatik KW - Würzburg / Universität / Lehrstuhl für Bioinformatik KW - Modellierung KW - Metabolismus KW - Stoffwechsel KW - Transkriptom KW - Transkriptomanalyse KW - bioinformatics KW - metabolome KW - transcriptome KW - modeling KW - steady-state Y1 - 2008 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-27622 ER - TY - JOUR A1 - Koetschan, Christian A1 - Foerster, Frank A1 - Keller, Alexander A1 - Schleicher, Tina A1 - Ruderisch, Benjamin A1 - Schwarz, Roland A1 - Mueller, Tobias A1 - Wolf, Matthias A1 - Schultz, Joerg T1 - The ITS2 Database III-sequences and structures for phylogeny N2 - The internal transcribed spacer 2 (ITS2) is a widely used phylogenetic marker. In the past, it has mainly been used for species level classifications. Nowadays, a wider applicability becomes apparent. Here, the conserved structure of the RNA molecule plays a vital role. We have developed the ITS2 Database (http://its2.bioapps .biozentrum.uni-wuerzburg.de) which holds information about sequence, structure and taxonomic classification of all ITS2 in GenBank. In the new version, we use Hidden Markov models (HMMs) for the identification and delineation of the ITS2 resulting in a major redesign of the annotation pipeline. This allowed the identification of more than 160 000 correct full ength and more than 50 000 partial structures. In the web interface, these can now be searched with a modified BLAST considering both sequence and structure, enabling rapid taxon sampling. Novel sequences can be annotated using the HMM based approach and modelled according to multiple template structures. Sequences can be searched for known and newly identified motifs. Together, the database and the web server build an exhaustive resource for ITS2 based phylogenetic analyses. KW - Biologie Y1 - 2010 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-68390 ER - TY - JOUR A1 - Biju, Joseph A1 - Schwarz, Roland A1 - Linke, Burkhard A1 - Blom, Jochen A1 - Becker, Anke A1 - Claus, Heike A1 - Goesmann, Alexander A1 - Frosch, Matthias A1 - Müller, Tobias A1 - Vogel, Ulrich A1 - Schoen, Christoph T1 - Virulence Evolution of the Human Pathogen Neisseria meningitidis by Recombination in the Core and Accessory Genome JF - PLoS One N2 - Background Neisseria meningitidis is a naturally transformable, facultative pathogen colonizing the human nasopharynx. Here, we analyze on a genome-wide level the impact of recombination on gene-complement diversity and virulence evolution in N. meningitidis. We combined comparative genome hybridization using microarrays (mCGH) and multilocus sequence typing (MLST) of 29 meningococcal isolates with computational comparison of a subset of seven meningococcal genome sequences. Principal Findings We found that lateral gene transfer of minimal mobile elements as well as prophages are major forces shaping meningococcal population structure. Extensive gene content comparison revealed novel associations of virulence with genetic elements besides the recently discovered meningococcal disease associated (MDA) island. In particular, we identified an association of virulence with a recently described canonical genomic island termed IHT-E and a differential distribution of genes encoding RTX toxin- and two-partner secretion systems among hyperinvasive and non-hyperinvasive lineages. By computationally screening also the core genome for signs of recombination, we provided evidence that about 40% of the meningococcal core genes are affected by recombination primarily within metabolic genes as well as genes involved in DNA replication and repair. By comparison with the results of previous mCGH studies, our data indicated that genetic structuring as revealed by mCGH is stable over time and highly similar for isolates from different geographic origins. Conclusions Recombination comprising lateral transfer of entire genes as well as homologous intragenic recombination has a profound impact on meningococcal population structure and genome composition. Our data support the hypothesis that meningococcal virulence is polygenic in nature and that differences in metabolism might contribute to virulence. KW - population genetics KW - DNA recombination KW - meningococcal disease KW - recombinant proteins KW - genomic databases KW - comparative genomics KW - neisseria meningitidis KW - homologous recombination Y1 - 2011 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-137960 VL - 6 IS - 4 ER -