Most current brain metabolic models are not capable of taking into account the dynamic isotopomer information available from fine structure multiplets in 13C spectra, due to the difficulty of implementing such models. Here we present a new approach that allows automatic implementation of multi-compartment metabolic models capable of fitting any number of 13C isotopomer curves in the brain. The new automated approach also makes it possible to quickly modify and test new models to best describe the experimental data. We demonstrate the power of the new approach by testing the effect of adding separate pyruvate pools in astrocytes and neurons, and adding a vesicular neuronal glutamate pool. Including both changes reduced the global fit residual by half and pointed to dilution of label prior to entry into the astrocytic TCA cycle as the main source of glutamine dilution. The glutamate–glutamine cycle rate was particularly sensitive to changes in the model.
Bibliographical noteFunding Information:
This work was supported by NIH Grants P41EB015894, P30NS076408 and R01NS038672 and École des Neurosciences de Paris Ile-de-France (P.G.H.).
© 2015, Springer Science+Business Media New York.
- Metabolic modeling
- Neuronal-glial metabolism