Application of systems biology methods to the study of the regulatory mechanisms of organisms with biotechnological interest

The scope of the present thesis is the study of regulatory mechanisms of two organisms of great biotechnological interest, the plant rapeseed and the bacterium Escherichia coli, by applying Systems Biology methodologies. In order to understand a biological mechanism as a system, it is necessary to examine the biological structures and their dynamic properties in a holistic manner and in different levels of organization (genomic, cellular, tissue etc.), instead of investigating the properties of isolated components. Firstly, the development of a large-scale computational model is presented, which describes the central metabolism of the rapeseed embryo (Brassica napus) that is considered as a cellular factory of production of oil with high added value. The computational modeling permits the simulation of the systematic application of perturbations and the subsequent investigation of their effect. The developed computational model was subjected to mathematical methods for complexity reduction in order to reduce the metabolic network properties to a small number of important regulatory reactions. Therefore, the quantification of the regulatory role of the enzymatic activities was achieved, resulting to the highlight of the most important potential enzymatic targets for the regulation of metabolism, with emphasis to lipid biosynthesis. The computational simulations of seed development were consistent with experimental measurements from the literature and they hence confirmed the model functionality as well as its usefulness to the study of the regulatory role of transcription factors. Further, potential enzymatic targets for lipid biosynthesis regulation were investigated by applying computational simulations of genetic modifications. In the second part, a computational procedure is presented, which performs automatic detection of transcription factor binding sites in the level of the whole genome of the bacterium Escherichia coli. The transcription factors are the main mechanism of gene expression regulation and signal transduction in the cell. A particular category of transcription factors, the response regulators, control the transcriptional response of the bacterial cells to external environmental stimuli, as parts of Two-Component Systems. The study of these systems is important to Biotechnology as they are behind the molecular basis of main bacterial properties (chemiotaxis, resistance to antibiotics, biosynthesis of high added-value products etc). The developed computational procedure permits the automatic detection of multiple transcription factor binding sites and the subsequent statistical analysis of Gene Ontology Terms, in order to correlate the binding sites with biochemical pathways. The procedure was applied to the study of the Two-Component System AtoSC and detected many potential gene targets, 21 of which were experimentally confirmed. Thus, the presented computational procedure not only revealed the molecular basis of AtoSC functions, but it also represents an important contribution to the examination of networks of bacterial signal transduction regulatory mechanisms, by statistically correlating biological functions with weakly conserved regulatory DNA sequence