MODELING COMPARTMENTATION IN THE BRAIN

这个子项目是利用由NIH/NCRR资助的中心拨款提供的资源的许多研究子项目之一。子项目和调查员(PI)可能从另一个NIH来源获得了主要资金，因此可能会出现在其他CRISE条目中。列出的机构是针对中心的，而不一定是针对调查员的机构。在体内，~(13)C核磁共振波谱已成为研究脑代谢区划的独特工具。例如，在输注13C标记底物(例如，[1-13C]葡萄糖或[2-13C]醋酸酯)过程中测量13C标记掺入脑氨基酸，以及随后使用代谢模型分析13C核磁共振时间进程，使得能够非侵入性地测量大脑中TCA循环率和谷氨酸-谷氨酰胺循环率。由于不同类型的细胞(如神经元和星形胶质细胞)之间的代谢区隔，代谢建模在大脑中尤其具有挑战性。30多年前，使用14C标记的底物证明了这种区隔，并导致了现在被广泛接受的谷氨酸-谷氨酰胺循环的概念，即突触前神经元释放的谷氨酸被星形胶质细胞摄取，转化为谷氨酰胺，然后送回神经元重新合成谷氨酸。在过去的十年里，在建立分区代谢的代谢模型方面取得了很大的进展。然而，这些复杂的模型需要足够的实验数据来确保拟合过程的稳定性，例如，不仅包括13C标记掺入谷氨酸和谷氨酰胺的C4位，而且还包括C3和C2位。这些额外的数据有助于稳定拟合过程并减少拟合参数的不确定性。虽然现在可以在活体中分辨检测对应于单个同位素异构体的多重态，但传统上代谢建模是使用每个碳位置的总13C标记的时间历程来执行的，忽略了来自多标记分子的额外信息。这些独立的同位素异构体在13C谱中被检测为不同的多重态，提供了可用于提高代谢模型研究的稳健性的有价值的信息。这一点已经在心脏上得到了证实，但还没有被用于大脑研究。这项合作的目标是通过开发一种可以使用这些信息的模型来充分利用来自多个标记的同位素异构体的信息。我们预计，这项工作将导致新的代谢建模方法，从而优化利用13C核磁共振获得的高度特异性信息，最近也可以在体内获得这些信息，最终提高大脑代谢建模研究的稳健性和精确度。这一点意义重大，因为对大脑代谢通量的13C核磁共振测量将提供一种直接和非侵入性地测量各种神经和精神疾病中人类大脑中葡萄糖代谢和谷氨酸神经传递的手段。

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. In vivo 13C NMR spectroscopy has emerged as a unique tool to study compartmentalized brain metabolism. For example, measurements of 13C label incorporation into brain amino acids during infusion of a 13C labeled-substrate (e.g. [1-13C]glucose or [2-13C]acetate and subsequent analysis of 13C NMR time courses with a metabolic model has permitted non-invasive measurements of the TCA cycle rate and the rate of glutamate-glutamine cycle in the brain. Metabolic modeling is particularly challenging in the brain due to compartmentation of metabolism between different cell types such as neurons and astrocytes. This compartmentation has been demonstrated over 30 years ago using 14C labeled substrates and has led to the now widely accepted concept of glutamate-glutamine cycle, whereby glutamate released by presynaptic neurons is taken up by astrocytes, converted to glutamine, and sent back to neurons to resynthesize glutamate. Much progress has been done in the past ten years to develop metabolic models of compartmentalized metabolism. However, these complex models require sufficient experimental data to ensure the stability of the fitting procedure, e.g. including time courses of 13C label incorporation not only into the C4 position of glutamate and glutamine, but also the C3 and C2 positions. This additional data helps stabilize the fitting procedure and reduce uncertainty on fitted parameters. Although resolved detection of multiplets corresponding to individual isotopomers is now feasible in vivo, metabolic modeling has been traditionally performed using time courses of total 13C label at each carbon position, ignoring the additional information from multiply labeled molecules. These individual isotopomers, detected as distinct multiplets in 13C spectra, provide valuable information that could be used to improve the robustness of metabolic modeling studies. This has been demonstrated in the heart, but has not been exploited for brain studies. The goal of this collaboration is to take full advantage of the information from multiply labeled isotopomers by developing a model that can use this information. We expect that this work will lead to new metabolic modeling approaches that make optimal use of the highly specific information that can be obtained with 13C NMR and has recently become available also in vivo, ultimately increasing the robustness and precision of metabolic modeling studies in the brain. This is significant because 13C NMR measurements of brain metabolic fluxes would provide a means to directly and non-invasively measure glucose metabolism and glutamate neurotransmission in the human brain in a variety of neurological and psychiatric disorders.