Figure 2From: Hybrid metabolic flux analysis: combining stoichiometric and statistical constraints to model the formation of complex recombinant productsData-driven framework for predictive metabolic flux analysis. (A) Schematic representation of a metabolic network with an unknown or ill-defined portion corresponding to the synthesis of a complex recombinant product. These poorly defined pathways are substituted by a statistical sub-model bridging the known well-defined stoichiometry with the target product formation rate. (B) Given a set of measured fluxes (V m - usually exchange fluxes of metabolic consumption and production), metabolic flux analysis is used to estimate the entire flux distribution (V e ) in a predefined metabolic network. Then, PLS is performed to find a linear regression model between the estimated fluxome and the vector of a measured target such as productivity, V t . As a result, a list of regression coefficients representing how strongly each flux correlates with the target is obtained (B), making it possible to predict the productivity of independent cultures after metabolic manipulation.Back to article page