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.
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