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Extra- and intracellular time-series data from stimulus-response experiments are gaining in importance in the identification of <jats:italic>in vivo<\/jats:italic> metabolite dynamics, while dynamic network models are excellent tools for analyzing complex metabolic control patterns. This is the first study that has been undertaken on the data-driven identification of a dynamic liver central carbon metabolism model and its application in the analysis of the distribution of metabolic control in hepatoma cells.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Results<\/jats:title>\n            <jats:p>Dynamic metabolite data were collected from HepG2 cells after they had been deprived of extracellular glucose. The concentration of 25 extra- and intracellular intermediates was quantified using HPLC, LC-MS-MS, and GC-MS. The <jats:italic>in silico<\/jats:italic> metabolite dynamics were in accordance with the experimental data. The central carbon metabolism of hepatomas was further analyzed with a particular focus on the control of metabolite concentrations and metabolic fluxes. It was observed that the enzyme glucose-6-phosphate dehydrogenase exerted substantial negative control over the glycolytic flux, whereas oxidative phosphorylation had a significant positive control. The control over the rate of NADPH consumption was found to be shared between the NADPH-demand itself (0.65) and the NADPH supply (0.38).<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Conclusions<\/jats:title>\n            <jats:p>Based on time-series data, a dynamic central carbon metabolism model was developed for the investigation of new and complex metabolic control patterns in hepatoma cells. The control patterns found support the hypotheses that the glucose-6-phosphate dehydrogenase and the Warburg effect are promising targets for tumor treatment. The systems-oriented identification of metabolite dynamics is a first step towards the genome-based assessment of potential risks posed by nutrients and drugs.<\/jats:p>\n          <\/jats:sec>","DOI":"10.1186\/1752-0509-4-54","type":"journal-article","created":{"date-parts":[[2010,4,29]],"date-time":"2010-04-29T06:13:49Z","timestamp":1272521629000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":40,"title":["Dynamics and Control of the Central Carbon Metabolism in Hepatoma Cells"],"prefix":"10.1186","volume":"4","author":[{"given":"Klaus","family":"Maier","sequence":"first","affiliation":[]},{"given":"Ute","family":"Hofmann","sequence":"additional","affiliation":[]},{"given":"Matthias","family":"Reuss","sequence":"additional","affiliation":[]},{"given":"Klaus","family":"Mauch","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2010,4,28]]},"reference":[{"key":"443_CR1","doi-asserted-by":"publisher","first-page":"171","DOI":"10.1038\/msb.2008.8","volume":"4","author":"N Jamshidi","year":"2008","unstructured":"Jamshidi N, Palsson BO: Formulating genome-scale kinetic models in the post-genome era. 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