Abstract
Metabolic flux estimation using 13C isotopic tracers (13C-MFA) provides a greater resolution of intracellular fluxes than using only cell growth and consumption/production rates. However, 13C-MFA is computationally more demanding. A nonlinear least-square optimization process is employed to constrain metabolic fluxes using atom balance models and experimentally measured 13C labelling pattern of intracellular or proteinogenic metabolites. OpenFLUX was therefore developed for the purpose of streamlining the computational workflow. Here, we describe in detail the computational procedure for performing 13C-MFA using OpenFLUX. We also provide some helpful information on model reconstruction and GC-MS data treatment.
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Quek, LE., Nielsen, L.K. (2014). Steady-State 13C Fluxomics Using OpenFLUX. In: Krömer, J., Nielsen, L., Blank, L. (eds) Metabolic Flux Analysis. Methods in Molecular Biology, vol 1191. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-1170-7_13
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DOI: https://doi.org/10.1007/978-1-4939-1170-7_13
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