@phdthesis{Grimbs2009, author = {Grimbs, Sergio}, title = {Towards structure and dynamics of metabolic networks}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-32397}, school = {Universit{\"a}t Potsdam}, year = {2009}, abstract = {This work presents mathematical and computational approaches to cover various aspects of metabolic network modelling, especially regarding the limited availability of detailed kinetic knowledge on reaction rates. It is shown that precise mathematical formulations of problems are needed i) to find appropriate and, if possible, efficient algorithms to solve them, and ii) to determine the quality of the found approximate solutions. Furthermore, some means are introduced to gain insights on dynamic properties of metabolic networks either directly from the network structure or by additionally incorporating steady-state information. Finally, an approach to identify key reactions in a metabolic networks is introduced, which helps to develop simple yet useful kinetic models. The rise of novel techniques renders genome sequencing increasingly fast and cheap. In the near future, this will allow to analyze biological networks not only for species but also for individuals. Hence, automatic reconstruction of metabolic networks provides itself as a means for evaluating this huge amount of experimental data. A mathematical formulation as an optimization problem is presented, taking into account existing knowledge and experimental data as well as the probabilistic predictions of various bioinformatical methods. The reconstructed networks are optimized for having large connected components of high accuracy, hence avoiding fragmentation into small isolated subnetworks. The usefulness of this formalism is exemplified on the reconstruction of the sucrose biosynthesis pathway in Chlamydomonas reinhardtii. The problem is shown to be computationally demanding and therefore necessitates efficient approximation algorithms. The problem of minimal nutrient requirements for genome-scale metabolic networks is analyzed. Given a metabolic network and a set of target metabolites, the inverse scope problem has as it objective determining a minimal set of metabolites that have to be provided in order to produce the target metabolites. These target metabolites might stem from experimental measurements and therefore are known to be produced by the metabolic network under study, or are given as the desired end-products of a biotechological application. The inverse scope problem is shown to be computationally hard to solve. However, I assume that the complexity strongly depends on the number of directed cycles within the metabolic network. This might guide the development of efficient approximation algorithms. Assuming mass-action kinetics, chemical reaction network theory (CRNT) allows for eliciting conclusions about multistability directly from the structure of metabolic networks. Although CRNT is based on mass-action kinetics originally, it is shown how to incorporate further reaction schemes by emulating molecular enzyme mechanisms. CRNT is used to compare several models of the Calvin cycle, which differ in size and level of abstraction. Definite results are obtained for small models, but the available set of theorems and algorithms provided by CRNT can not be applied to larger models due to the computational limitations of the currently available implementations of the provided algorithms. Given the stoichiometry of a metabolic network together with steady-state fluxes and concentrations, structural kinetic modelling allows to analyze the dynamic behavior of the metabolic network, even if the explicit rate equations are not known. In particular, this sampling approach is used to study the stabilizing effects of allosteric regulation in a model of human erythrocytes. Furthermore, the reactions of that model can be ranked according to their impact on stability of the steady state. The most important reactions in that respect are identified as hexokinase, phosphofructokinase and pyruvate kinase, which are known to be highly regulated and almost irreversible. Kinetic modelling approaches using standard rate equations are compared and evaluated against reference models for erythrocytes and hepatocytes. The results from this simplified kinetic models can simulate acceptably the temporal behavior for small changes around a given steady state, but fail to capture important characteristics for larger changes. The aforementioned approach to rank reactions according to their influence on stability is used to identify a small number of key reactions. These reactions are modelled in detail, including knowledge about allosteric regulation, while all other reactions were still described by simplified reaction rates. These so-called hybrid models can capture the characteristics of the reference models significantly better than the simplified models alone. The resulting hybrid models might serve as a good starting point for kinetic modelling of genome-scale metabolic networks, as they provide reasonable results in the absence of experimental data, regarding, for instance, allosteric regulations, for a vast majority of enzymatic reactions.}, language = {en} } @phdthesis{GomezPorras2005, author = {G{\´o}mez-Porras, Judith Lucia}, title = {In silico identification of genes regulated by abscisic acid in Arabidopsis thaliana (L.) Heynh.}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-7401}, school = {Universit{\"a}t Potsdam}, year = {2005}, abstract = {Abscisic acid (ABA) is a major plant hormone that plays an important role during plant growth and development. During vegetative growth ABA mediates (in part) responses to various environmental stresses such as cold, drought and high salinity. The response triggered by ABA includes changes in the transcript level of genes involved in stress tolerance. The aim of this project was the In silico identification of genes putatively regulated by ABA in A. thaliana. In silico predictions were combined with experimental data in order to evaluate the reliability of computational predictions. Taking advantage of the genome sequence of A. thaliana publicly available since 2000, 1 kb upstream sequences were screened for combinations of cis-elements known to be involved in the regulation of ABA-responsive genes. It was found that around 10 to 20 percent of the genes of A. thaliana might be regulated by ABA. Further analyses of the predictions revealed that certain combinations of cis-elements that confer ABA-responsiveness were significantly over-represented compared with results in random sequences and with random expectations. In addition, it was observed that other combinations that confer ABA-responsiveness in monocotyledonous species might not be functional in A. thaliana. It is proposed that ABA-responsive genes in A. thaliana show pairs of ABRE (abscisic acid responsive element) with MYB binding sites, DRE (dehydration responsive element) or with itself. The analysis of the distances between pairs of cis-elements suggested that pairs of ABREs are bound by homodimers of ABRE binding proteins. In contrast, pairs between MYB binding sites and ABRE, or DRE and ABRE showed a distance between cis-elements that suggested that the binding proteins interact through protein complexes and not directly. The comparison of computational predictions with experimental data confirmed that the regulatory mechanisms leading to the induction or repression of genes by ABA is very incompletely understood. It became evident that besides the cis-elements proposed in this study to be present in ABA-responsive genes, other known and unknown cis-elements might play an important role in the transcriptional regulation of ABA-responsive genes. For example, auxin-related cis elements, or the cis-elements recognized by the NAM-family of transcription factors (Non-Apical meristem). This work documents the use of computational and experimental approaches to analyse possible interactions between cis-elements involved in the regulation of ABA-responsive genes. The computational predictions allowed the distinction between putatively relevant combinations of cis-elements from irrelevant combinations of cis-elements in ABA-responsive genes. The comparison with experimental data allowed to identify certain cis-elements that have not been previously associated to the ABA-mediated transcriptional regulation, but that might be present in ABA-responsive genes (e.g. auxin responsive elements). Moreover, the efforts to unravel the gene regulatory network associated with the ABA-signalling pathway revealed that NAM-transcription factors and their corresponding binding sequences are important components of this network.}, subject = {Bioinformatik}, language = {en} } @misc{GebserSchaubThieleetal.2011, author = {Gebser, Martin and Schaub, Torsten H. and Thiele, Sven and Veber, Philippe}, title = {Detecting inconsistencies in large biological networks with answer set programming}, series = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, journal = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, number = {561}, issn = {1866-8372}, doi = {10.25932/publishup-41246}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-412467}, pages = {38}, year = {2011}, abstract = {We introduce an approach to detecting inconsistencies in large biological networks by using answer set programming. To this end, we build upon a recently proposed notion of consistency between biochemical/genetic reactions and high-throughput profiles of cell activity. We then present an approach based on answer set programming to check the consistency of large-scale data sets. Moreover, we extend this methodology to provide explanations for inconsistencies by determining minimal representations of conflicts. In practice, this can be used to identify unreliable data or to indicate missing reactions.}, language = {en} } @phdthesis{RobainaEstevez2017, author = {Robaina Estevez, Semidan}, title = {Context-specific metabolic predictions}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-401365}, school = {Universit{\"a}t Potsdam}, pages = {vi, 158}, year = {2017}, abstract = {All life-sustaining processes are ultimately driven by thousands of biochemical reactions occurring in the cells: the metabolism. These reactions form an intricate network which produces all required chemical compounds, i.e., metabolites, from a set of input molecules. Cells regulate the activity through metabolic reactions in a context-specific way; only reactions that are required in a cellular context, e.g., cell type, developmental stage or environmental condition, are usually active, while the rest remain inactive. The context-specificity of metabolism can be captured by several kinds of experimental data, such as by gene and protein expression or metabolite profiles. In addition, these context-specific data can be assimilated into computational models of metabolism, which then provide context-specific metabolic predictions. This thesis is composed of three individual studies focussing on context-specific experimental data integration into computational models of metabolism. The first study presents an optimization-based method to obtain context-specific metabolic predictions, and offers the advantage of being fully automated, i.e., free of user defined parameters. The second study explores the effects of alternative optimal solutions arising during the generation of context-specific metabolic predictions. These alternative optimal solutions are metabolic model predictions that represent equally well the integrated data, but that can markedly differ. This study proposes algorithms to analyze the space of alternative solutions, as well as some ways to cope with their impact in the predictions. Finally, the third study investigates the metabolic specialization of the guard cells of the plant Arabidopsis thaliana, and compares it with that of a different cell type, the mesophyll cells. To this end, the computational methods developed in this thesis are applied to obtain metabolic predictions specific to guard cell and mesophyll cells. These cell-specific predictions are then compared to explore the differences in metabolic activity between the two cell types. In addition, the effects of alternative optima are taken into consideration when comparing the two cell types. The computational results indicate a major reorganization of the primary metabolism in guard cells. These results are supported by an independent 13C labelling experiment.}, language = {en} } @misc{BarlowHartmannGonzalezetal.2020, author = {Barlow, Axel and Hartmann, Stefanie and Gonzalez, Javier and Hofreiter, Michael and Paijmans, Johanna L. A.}, title = {Consensify}, series = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, journal = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, number = {1033}, issn = {1866-8372}, doi = {10.25932/publishup-47252}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-472521}, pages = {24}, year = {2020}, abstract = {A standard practise in palaeogenome analysis is the conversion of mapped short read data into pseudohaploid sequences, frequently by selecting a single high-quality nucleotide at random from the stack of mapped reads. This controls for biases due to differential sequencing coverage, but it does not control for differential rates and types of sequencing error, which are frequently large and variable in datasets obtained from ancient samples. These errors have the potential to distort phylogenetic and population clustering analyses, and to mislead tests of admixture using D statistics. We introduce Consensify, a method for generating pseudohaploid sequences, which controls for biases resulting from differential sequencing coverage while greatly reducing error rates. The error correction is derived directly from the data itself, without the requirement for additional genomic resources or simplifying assumptions such as contemporaneous sampling. For phylogenetic and population clustering analysis, we find that Consensify is less affected by artefacts than methods based on single read sampling. For D statistics, Consensify is more resistant to false positives and appears to be less affected by biases resulting from different laboratory protocols than other frequently used methods. Although Consensify is developed with palaeogenomic data in mind, it is applicable for any low to medium coverage short read datasets. We predict that Consensify will be a useful tool for future studies of palaeogenomes.}, language = {en} }