@phdthesis{Schuette2011,
  author    = {Sch{\"u}tte, Moritz},
  title     = {Evolutionary fingerprints in genome-scale networks},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-57483},
  school      = {Universit{\"a}t Potsdam},
  year      = {2011},
  abstract  = {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.},
  language  = {en}
}
@phdthesis{CastroMarin2007,
  author    = {Castro Marin, Inmaculada},
  title     = {Nitrate: metabolism and development},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-18827},
  school      = {Universit{\"a}t Potsdam},
  year      = {2007},
  abstract  = {The major aim of this thesis was to study the effect of nitrate on primary metabolism and in development of the model plant Arabidopsis thaliana. The present work has two separate topics. First, to investigate the GDH family, a small gene family at the interface between nitrogen and carbon metabolisms. Second, to investigate the mechanisms whereby nitrogen is regulating the transition to flowering time in Arabidopsis thaliana. To gain more insights into the regulation of primary metabolism by the functional characterization of the glutamate dehydrogenase (GDH) family, an enzyme putatively involved in the metabolism of amino acids and thus suggested to play different and essential roles in carbon and nitrogen metabolism in plants, knock out mutants and transgenic plants carrying RNA interference construct were generated and characterized. The effect of silencing GDH on carbon and nitrogen metabolisms was investigated, especially the level of carbohydrates and the amino acid pool were further analysed. It has been shown that GDH expression is regulated by light and/or sugar status therefore, phenotypic and metabolic analysis were developed in plants grown at different points of the diurnal rhythm and in response to an extended night period. In addition, we are interested in the effect of nutrient availability in the transition from vegetative growth to flowering and especially in nitrate as a metabolite that triggers widespread and coordinated changes in metabolism and development. Nutrient availability has a dramatic effect on flowering time, with a marked delay of flowering when nitrate is supplied (Stitt, 1999). The use of different mutants and transgenic plants impaired in flowering signalling pathways was crucial to evaluate the impact of different nitrate concentrations on flowering time and to better understand the interaction of nitrate-dependent signals with other main flowering signalling pathways. Plants were grown on glutamine as a constitutive source of nitrogen, and the nitrate supply varied. Low nitrate led to earlier flowering. The response to nitrate is accentuated in short days and in the CONSTANS deficient co2 mutant, whereas long days or overexpression of CONSTANS overrides the nitrate response. These results indicate that nitrates acts downstream of the known flowering signalling pathways for photoperiod, autonomy, vernalization and gibberellic acid. Global analyses of gene expression of two independent flowering systems, a light impaired mutant (co2tt4) and a constitutive over-expresser of the potent repressor of flowering (35S::FLC), were to be investigated under two different concentrations of nitrate in order to identify candidate genes that may be involved in the regulation of flowering time by nitrate.},
  language  = {en}
}