Maier Klaus, Hofmann Ute, Reuss Matthias, Mauch Klaus
Institute of Biochemical Engineering, University of Stuttgart, Allmandring 31, 70569 Stuttgart, Germany.
Biotechnol Bioeng. 2008 Jun 1;100(2):355-70. doi: 10.1002/bit.21746.
This contribution addresses the identification of metabolic fluxes and metabolite concentrations in mammalian cells from transient (13)C-labeling experiments. Whilst part I describes experimental set-up and acquisition of required metabolite and (13)C-labeling data, part II focuses on setting up network models and the estimation of intracellular fluxes. Metabolic fluxes were determined in glycolysis, pentose-phosphate pathway (PPP), and citric acid cycle (TCA) in a hepatoma cell line grown in aerobic batch cultures. In glycolytic and PPP metabolite pools isotopic stationarity was observed within 30 min, whereas in the TCA cycle the labeling redistribution did not reach isotopic steady state even within 180 min. In silico labeling dynamics were in accordance with in vivo (13)C-labeling data. Split ratio between glycolysis and PPP was 57%:43%; intracellular glucose concentration was estimated at 101.6 nmol per 10(6) cells. In contrast to isotopic stationary (13)C-flux analysis, transient (13)C-flux analysis can also be applied to industrially relevant mammalian cell fed-batch and batch cultures.
本论文探讨了通过瞬态（13）C标记实验来识别哺乳动物细胞中的代谢通量和代谢物浓度。第一部分描述了实验设置以及所需代谢物和（13）C标记数据的获取，第二部分则着重于建立网络模型和细胞内通量的估计。在需氧分批培养的肝癌细胞系中，测定了糖酵解、磷酸戊糖途径（PPP）和柠檬酸循环（TCA）中的代谢通量。在糖酵解和PPP代谢物池中，30分钟内观察到同位素平稳状态，而在TCA循环中，即使在长达180分钟内，标记物的重新分布也未达到同位素稳态。计算机模拟的标记动力学与体内（13）C标记数据一致。糖酵解和PPP之间的分流比为57%:43%；估计每10^6个细胞内葡萄糖浓度为101.6纳摩尔。与同位素稳态（13）C通量分析不同，瞬态（13）C通量分析也可应用于工业相关的哺乳动物细胞补料分批培养和分批培养。
