| Autor: |
Weglarz-Tomczak E; Swammerdam Institute for Life Sciences, Faculty of Science, University of Amsterdam, 1098 XH Amsterdam, The Netherlands., Mondeel TDGA; Swammerdam Institute for Life Sciences, Faculty of Science, University of Amsterdam, 1098 XH Amsterdam, The Netherlands., Piebes DGE; Swammerdam Institute for Life Sciences, Faculty of Science, University of Amsterdam, 1098 XH Amsterdam, The Netherlands., Westerhoff HV; Swammerdam Institute for Life Sciences, Faculty of Science, University of Amsterdam, 1098 XH Amsterdam, The Netherlands.; Molecular Cell Physiology, Amsterdam Institute for Molecules, Medicines and Systems, Faculty of Science, Vrije Universiteit Amsterdam, 1081 HZ Amsterdam, The Netherlands.; Manchester Centre for Integrative Systems Biology, School for Chemical Engineering and Analytical Sciences, University of Manchester, Manchester M1 7DN, UK. |
| Abstrakt: |
How cancer cells utilize nutrients to support their growth and proliferation in complex nutritional systems is still an open question. However, it is certainly determined by both genetics and an environmental-specific context. The interactions between them lead to profound metabolic specialization, such as consuming glucose and glutamine and producing lactate at prodigious rates. To investigate whether and how glucose and glutamine availability impact metabolic specialization, we integrated computational modeling on the genome-scale metabolic reconstruction with an experimental study on cell lines. We used the most comprehensive human metabolic network model to date, Recon3D, to build cell line-specific models. RNA-Seq data was used to specify the activity of genes in each cell line and the uptake rates were quantitatively constrained according to nutrient availability. To integrated both constraints we applied a novel method, named Gene Expression and Nutrients Simultaneous Integration (GENSI), that translates the relative importance of gene expression and nutrient availability data into the metabolic fluxes based on an observed experimental feature(s). We applied GENSI to study hepatocellular carcinoma addiction to glucose/glutamine. We were able to identify that proliferation, and lactate production is associated with the presence of glucose but does not necessarily increase with its concentration when the latter exceeds the physiological concentration. There was no such association with glutamine. We show that the integration of gene expression and nutrient availability data into genome-wide models improves the prediction of metabolic phenotypes. |
