@phdthesis{Usadel2004,
  author    = {Usadel, Bj{\"o}rn},
  title     = {Untersuchungen zur Biosynthese der pflanzlichen Zellwand = [Identification and characterization of genes involved in plant cell wall synthesis]},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-2947},
  school      = {Universit{\"a}t Potsdam},
  year      = {2004},
  abstract  = {Even though the structure of the plant cell wall is by and large quite well characterized, its synthesis and regulation remains largely obscure. However, it is accepted that the building blocks of the polysaccharidic part of the plant cell wall are nucleotide sugars. Thus to gain more insight into the cell wall biosynthesis, in the first part of this thesis, plant genes possibly involved in the nucleotide sugar interconversion pathway were identified using a bioinformatics approach and characterized in plants, mainly in Arabidopsis. For the computational identification profile hidden markov models were extracted from the Pfam and TIGR databases. Mainly with these, plant genes were identified facilitating the "hmmer" program. Several gene families were identified and three were further characterized, the UDP-rhamnose synthase (RHM), UDP-glucuronic acid epimerase (GAE) and the myo-inositol oxygenase (MIOX) families. For the three-membered RHM family relative ubiquitous expression was shown using variuos methods. For one of these genes, RHM2, T-DNA lines could be obtained. Moreover, the transcription of the whole family was downregulated facilitating an RNAi approach. In both cases a alteration of cell wall typic polysaccharides and developmental changes could be shown. In the case of the rhm2 mutant these were restricted to the seed or the seed mucilage, whereas the RNAi plants showed profound changes in the whole plant. In the case of the six-membered GAE family, the gene expressed to the highest level (GAE6) was cloned, expressed heterologously and its function was characterized. Thus, it could be shown that GAE6 encodes for an enzyme responsible for the conversion of UDP-glucuronic acid to UDP-galacturonic acid. However, a change in transcript level of variuos GAE family members achieved by T-DNA insertions (gae2, gae5, gae6), overexpression (GAE6) or an RNAi approach, targeting the whole family, did not reveal any robust changes in the cell wall. Contrary to the other two families the MIOX gene family had to be identified using a BLAST based approach due to the lack of enough suitable candidate genes for building a hidden markov model. An initial bioinformatic characterization was performed which will lead to further insights into this pathway. In total it was possible to identify the two gene families which are involved in the synthesis of the two pectin backbone sugars galacturonic acid and rhamnose. Moreover with the identification of the MIOX genes a genefamily, important for the supply of nucleotide sugar precursors was identified. In a second part of this thesis publicly available microarray datasets were analyzed with respect to co-responsive behavior of transcripts on a global basis using nearly 10,000 genes. The data has been made available to the community in form of a database providing additional statistical and visualization tools (http://csbdb.mpimp-golm.mpg.de). Using the framework of the database to identify nucleotide sugar converting genes indicated that co-response might be used for identification of novel genes involved in cell wall synthesis based on already known genes.},
  subject      = {Zellwand},
  language  = {en}
}
@phdthesis{Steinhauser2004,
  author    = {Steinhauser, Dirk},
  title     = {Inferring hypotheses from complex profile data - by means of CSB.DB, a comprehensive systems-biology database},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-2467},
  school      = {Universit{\"a}t Potsdam},
  year      = {2004},
  abstract  = {The past decades are characterized by various efforts to provide complete sequence information of genomes regarding various organisms. The availability of full genome data triggered the development of multiplex high-throughput assays allowing simultaneous measurement of transcripts, proteins and metabolites. With genome information and profiling technologies now in hand a highly parallel experimental biology is offering opportunities to explore and discover novel principles governing biological systems. Understanding biological complexity through modelling cellular systems represents the driving force which today allows shifting from a component-centric focus to integrative and systems level investigations. The emerging field of systems biology integrates discovery and hypothesis-driven science to provide comprehensive knowledge via computational models of biological systems. Within the context of evolving systems biology, investigations were made in large-scale computational analyses on transcript co-response data through selected prokaryotic and plant model organisms. CSB.DB - a comprehensive systems-biology database - (http://csbdb.mpimp-golm.mpg.de/) was initiated to provide public and open access to the results of biostatistical analyses in conjunction with additional biological knowledge. The database tool CSB.DB enables potential users to infer hypothesis about functional interrelation of genes of interest and may serve as future basis for more sophisticated means of elucidating gene function. The co-response concept and the CSB.DB database tool were successfully applied to predict operons in Escherichia coli by using the chromosomal distance and transcriptional co-responses. Moreover, examples were shown which indicate that transcriptional co-response analysis allows identification of differential promoter activities under different experimental conditions. The co-response concept was successfully transferred to complex organisms with the focus on the eukaryotic plant model organism Arabidopsis thaliana. The investigations made enabled the discovery of novel genes regarding particular physiological processes and beyond, allowed annotation of gene functions which cannot be accessed by sequence homology. GMD - the Golm Metabolome Database - was initiated and implemented in CSB.DB to integrated metabolite information and metabolite profiles. This novel module will allow addressing complex biological questions towards transcriptional interrelation and extent the recent systems level quest towards phenotyping.},
  subject      = {Datenbank},
  language  = {en}
}