Cardiovascular Medicine Unit, Department of Medicine, Karolinska Institutet, Karolinska University Hospital, SE-17176 Stockholm, Sweden; Center for Molecular Medicine, Karolinska Institutet, Karolinska University Hospital, SE-17176 Stockholm, Sweden.
Departments of Medicine & Pharmacology, University of California, San Diego, USA.
Metab Eng. 2017 Sep;43(Pt B):137-146. doi: 10.1016/j.ymben.2017.02.005. Epub 2017 Feb 20.
Model-based metabolic flux analysis (MFA) using isotope-labeled substrates has provided great insight into intracellular metabolic activities across a host of organisms. One challenge with applying MFA in mammalian systems, however, is the need for absolute quantification of nutrient uptake, biomass composition, and byproduct release fluxes. Such measurements are often not feasible in complex culture systems or in vivo. One way to address this issue is to estimate flux ratios, the fractional contribution of a flux to a metabolite pool, which are independent of absolute measurements and yet informative for cellular metabolism. Prior work has focused on "local" estimation of a handful of flux ratios for specific metabolites and reactions. Here, we perform systematic, model-based estimation of all flux ratios in a metabolic network using isotope labeling data, in the absence of uptake/release data. In a series of examples, we investigate what flux ratios can be well estimated with reasonably tight confidence intervals, and contrast this with confidence intervals on normalized fluxes. We find that flux ratios can provide useful information on the metabolic state, and is complementary to normalized fluxes: for certain metabolic reactions, only flux ratios can be well estimated, while for others normalized fluxes can be obtained. Simulation studies of a large human metabolic network model suggest that estimation of flux ratios is technically feasible for complex networks, but additional studies on data from actual isotopomer labeling experiments are needed to validate these results. Finally, we experimentally study serine and methionine metabolism in cancer cells using flux ratios. We find that, in these cells, the methionine cycle is truncated with little remethylation from homocysteine, and polyamine synthesis in the absence of methionine salvage leads to loss of 5-methylthioadenosine, suggesting a new mode of overflow metabolism in cancer cells. This work highlights the potential for flux ratio analysis in the absence of absolute quantification, which we anticipate will be important for both in vitro and in vivo studies of cancer metabolism.
基于模型的代谢通量分析（MFA）使用同位素标记的底物为研究各种生物体的细胞内代谢活动提供了重要的见解。然而，在哺乳动物系统中应用 MFA 的一个挑战是需要对营养物质摄取、生物量组成和副产物释放通量进行绝对定量。在复杂的培养系统或体内，这些测量通常是不可行的。解决这个问题的一种方法是估计通量比，即通量对代谢物池的分数贡献，它不依赖于绝对测量，但对细胞代谢具有信息性。先前的工作主要集中在对特定代谢物和反应的少数通量比进行“局部”估计。在这里，我们使用同位素标记数据对代谢网络中的所有通量比进行系统的、基于模型的估计，而无需摄取/释放数据。在一系列示例中，我们研究了哪些通量比可以用相当紧的置信区间很好地估计，并将其与归一化通量的置信区间进行对比。我们发现，通量比可以提供有关代谢状态的有用信息，并且与归一化通量互补：对于某些代谢反应，只有通量比可以很好地估计，而对于其他反应，则可以获得归一化通量。对大型人类代谢网络模型的模拟研究表明，对于复杂网络，估计通量比在技术上是可行的，但需要对实际同位素标记实验的数据进行进一步研究，以验证这些结果。最后，我们使用通量比实验研究了癌细胞中的丝氨酸和蛋氨酸代谢。我们发现，在这些细胞中，蛋氨酸循环被截断，很少有来自同型半胱氨酸的再甲基化，并且在没有蛋氨酸回收的情况下多胺合成会导致 5-甲基硫腺苷的丢失，这表明癌细胞中存在新的溢出代谢模式。这项工作强调了在缺乏绝对定量的情况下进行通量比分析的潜力，我们预计这对于癌症代谢的体外和体内研究都将非常重要。
