Abstract:
The aim of this study is to understand the effect of caffeine and rapamycin on the growth of yeast cells and identify flux changes in the presence of these chemicals in yeast. The repression effect of different concentrations of caffeine and rapamycin on the growth of the yeast cells in both F1 and YPD media was observed. The higher the concentration of the chemicals, the more growth of the yeast cells was repressed. However the repression effects of caffeine and rapamycin were found to have different characteristics. Yeast cells treated with rapamycin or lower amount of caffeine for a longer time of period reached higher optical density values compared to the untreated cells, which may indicate extending life span effect of the chemicals. Well-controlled batch cultivations of Saccharomyces cerevisiae BY4743 were carried out inYPD media and samples were collected to obtain biomass and extracellular metabolite profiles in the absence or presence of chemicals. This data was used in flux balance analysis (FBA) to determine the distribution of metabolic fluxes under these conditions by using whole genome models. Ethanol production was successfully predicted by using FBA when the objective function was chosen as the maximization of ethanol production. The fluxes successfully predicted by FBA in the absence and presence of caffeine were analyzed by clustering via self-organizing maps methodology. A decrease in the magnitude of fluxes in glucose fermentation and glycerol biosynthesis pathways was observed, which may indicate that caffeine represses respiration and fermentation. Additionally, since it was reported that both caffeine and rapamycin affect the the TOR signalling pathway, a system based modular approach based on literature curated protein-protein interactions was developed within the framework for this thesis. TOR signalling network was found to have a scale-free property. Functional modules were identified using Bron-Kerbosch algorithm. Ras1p and Tor1p were the most common proteins among more than 3 member modules, indicating a possible interaction between TOR and RAS signalling. Tor1p and Gln3p were found to have a central role in TOR signalling network. The proteins in modules are significantly annotated to gene ontology terms, indicating the organized structure of the TOR signalling network.
