Developments in genome scale metabolic modeling techniques and omics technologies have enabled the reconstruction of context-specific metabolic models. In this study, glioblastoma multiforme (GBM), one of the most common and aggressive malignant brain tumors, is investigated by mapping GBM gene expression data on the growth-implemented brain specific genome-scale metabolic network, and GBM-specific models are generated. The models are used to calculate metabolic flux distributions in the tumor cells. Metabolic phenotypes predicted by the GBM-specific metabolic models reconstructed in this work reflect the general metabolic reprogramming of GBM, reported both in in-vitro and in-vivo experiments. The computed flux profiles quantitatively predict that major sources of the acetyl-CoA and oxaloacetic acid pool used in TCA cycle are pyruvate dehydrogenase from glycolysis and anaplerotic flux from glutaminolysis, respectively. Also, our results, in accordance with recent studies, predict a contribution of oxidative phosphorylation to ATP pool via a slightly active TCA cycle in addition to the major contributor aerobic glycolysis. We verified our results by using different computational methods that incorporate transcriptome data with genome-scale models and by using different transcriptome datasets. Correct predictions of flux distributions in glycolysis, glutaminolysis, TCA cycle and lipid precursor metabolism validate the reconstructed models for further use in future to simulate more specific metabolic patterns for GBM.

Leuconostoc mesenteroides subsp. cremoris is an obligate heterolactic fermentative lactic acid bacterium that is mostly used in industrial dairy fermentations. The phosphoketolase pathway (PKP) is a unique feature of the obligate heterolactic fermentation, which leads to the production of lactate, ethanol, and/or acetate, and the final product profile of PKP highly depends on the energetics and redox state of the organism. Another characteristic of the L. mesenteroides subsp. cremoris is the production of aroma compounds in dairy fermentation, such as in cheese production, through the utilization of citrate. Considering its importance in dairy fermentation, a detailed metabolic characterization of the organism is necessary for its more efficient use in the industry. To this aim, a genome-scale metabolic model of dairy-origin L. mesenteroides subsp. cremoris ATCC 19254 (iLM.c559) was reconstructed to explain the energetics and redox state mechanisms of the organism in full detail. The model includes 559 genes governing 1088 reactions between 1129 metabolites, and the reactions cover citrate utilization and citraterelated flavor metabolism. The model was validated by simulating co-metabolism of glucose and citrate and comparing the in silico results to our experimental results. Model simulations further showed that, in co-metabolism of citrate and glucose, no flavor compounds were produced when citrate could stimulate the formation of biomass. Significant amounts of flavor metabolites (e.g., diacetyl and acetoin) were only produced when citrate could not enhance growth, which suggests that flavor formation only occurs under carbon and ATP excess. The effects of aerobic conditions and different carbon sources on product profiles and growth were also investigated using the reconstructed model. The analyses provided further insights for the growth stimulation and flavor formation mechanisms of the organism.

No abstract