Center for Magnetic Resonance Research, University of Minnesota, 2021 6th St SE, Minneapolis, MN 55455, USA.
Neurochem Res. 2012 Nov;37(11):2388-401. doi: 10.1007/s11064-012-0782-5. Epub 2012 Apr 24.
Metabolic modeling of dynamic (13)C labeling curves during infusion of (13)C-labeled substrates allows quantitative measurements of metabolic rates in vivo. However metabolic modeling studies performed in the brain to date have only modeled time courses of total isotopic enrichment at individual carbon positions (positional enrichments), not taking advantage of the additional dynamic (13)C isotopomer information available from fine-structure multiplets in (13)C spectra. Here we introduce a new (13)C metabolic modeling approach using the concept of bonded cumulative isotopomers, or bonded cumomers. The direct relationship between bonded cumomers and (13)C multiplets enables fitting of the dynamic multiplet data. The potential of this new approach is demonstrated using Monte-Carlo simulations with a brain two-compartment neuronal-glial model. The precision of positional and cumomer approaches are compared for two different metabolic models (with and without glutamine dilution) and for different infusion protocols ([1,6-(13)C(2)]glucose, [1,2-(13)C(2)]acetate, and double infusion [1,6-(13)C(2)]glucose + [1,2-(13)C(2)]acetate). In all cases, the bonded cumomer approach gives better precision than the positional approach. In addition, of the three different infusion protocols considered here, the double infusion protocol combined with dynamic bonded cumomer modeling appears the most robust for precise determination of all fluxes in the model. The concepts and simulations introduced in the present study set the foundation for taking full advantage of the available dynamic (13)C multiplet data in metabolic modeling.
在输注 13C 标记的底物期间对动态 13C 标记曲线进行代谢建模可以实现体内代谢率的定量测量。然而，迄今为止在大脑中进行的代谢建模研究仅对单个碳原子位置（位置丰度）的总同位素丰度时间过程进行了建模，而没有利用来自 13C 光谱中精细结构多重峰的额外动态 13C 同位素质谱信息。在这里，我们引入了一种新的 13C 代谢建模方法，使用键合累积同位素体或键合 cumomer 的概念。键合 cumomer 与 13C 多重峰之间的直接关系使得可以对动态多重峰数据进行拟合。使用具有脑两室神经元-神经胶质模型的蒙特卡罗模拟证明了这种新方法的潜力。对于两种不同的代谢模型（带有和不带有谷氨酰胺稀释）以及不同的输注方案（[1,6-（13）C2]葡萄糖、[1,2-（13）C2]乙酸盐和双输注 [1,6-（13）C2]葡萄糖 + [1,2-（13）C2]乙酸盐），比较了位置和 cumomer 方法的精度。在所有情况下，键合 cumomer 方法的精度都优于位置方法。此外，在所考虑的三种不同的输注方案中，双输注方案与动态键合 cumomer 建模相结合，对于精确确定模型中的所有通量似乎是最稳健的。本研究中引入的概念和模拟为充分利用代谢建模中可用的动态 13C 多重峰数据奠定了基础。
