For MFA, we established a combined model for glycolysis, the PPP and TCA cycle, which has been previously described and utilized in Stifel et al. (43 (link)). It predicts 13C mass distributions on metabolites based on flow rates of the metabolic system by utilizing the EMU concept (40 (link), 55 (link)–57 (link)) and was implemented in RStan [R interface to Stan, a tool for Bayesian analysis (58 )]. Comparing predictions for 13C mass distributions with the corresponding GC/MS measurements (section 2.6) using sampling-based Bayesian statistics allowed for identifying suitable fluxes within the network. It further estimated how the precision in measurements affects the precision of estimated fluxes, including standard deviations and confidence intervals. Conveniently, unidentifiable fluxes can be recognized by wide confidence ranges.
Our PPP estimation is built on the same method as the one used by Lee, Katz, and Rognstad (59 (link), 60 (link)) that is based on the assumption that PPP utilization can be represented as a shift in the label (‘carbon scrambling’) of the top carbon atoms of PPP metabolites. For this approach, usually only the m+1/m+2 ratio on lactate would be used as a proxy for triose labeling using a 1,2-13C2-labeled glucose input, but we expanded the method so that the complete CMD of the full metabolite as well as the CMD of the lactate fragment across carbon 2 and 3 were taken into account. The model firstly estimated relative fluxes from GC/MS measurements and subsequently utilized 13CO2 production and the secretion of lactate into the medium to transform these relative fluxes into absolute values. The parallel tracer setup of 1,2-13C2-labeled glucose, 13C6-labeled glucose, and 13C5-labeled glutamine enabled improved flux determination, as the estimated fluxes must apply to sets of measurements obtained from each tracer. The details of the metabolic model are available in the Supplements.
Our PPP estimation is built on the same method as the one used by Lee, Katz, and Rognstad (59 (link), 60 (link)) that is based on the assumption that PPP utilization can be represented as a shift in the label (‘carbon scrambling’) of the top carbon atoms of PPP metabolites. For this approach, usually only the m+1/m+2 ratio on lactate would be used as a proxy for triose labeling using a 1,2-13C2-labeled glucose input, but we expanded the method so that the complete CMD of the full metabolite as well as the CMD of the lactate fragment across carbon 2 and 3 were taken into account. The model firstly estimated relative fluxes from GC/MS measurements and subsequently utilized 13CO2 production and the secretion of lactate into the medium to transform these relative fluxes into absolute values. The parallel tracer setup of 1,2-13C2-labeled glucose, 13C6-labeled glucose, and 13C5-labeled glutamine enabled improved flux determination, as the estimated fluxes must apply to sets of measurements obtained from each tracer. The details of the metabolic model are available in the Supplements.
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