Improving the accuracy of flux balance analysis through the implementation of carbon availability constraints for intracellular reactions.

Constraint based modelling methods, such as Flux Balance Analysis (FBA), have been extensively used to decipher complex, information rich -omics datasets in order to elicit system-wide behavioral patterns of cellular metabolism. FBA has been successfully used to gain insight in a wide range of applications, such as range of substrate utilization, product yields and to design metabolic engineering strategies to improve bioprocess performance. A well-known challenge associated with large genome-scale metabolic networks (GEMs) is that they result in underdetermined problem formulations. Consequently, rather than unique solutions, FBA and related methods examine ranges of reaction flux values that are consistent with the studied physiological conditions. The wider the reported flux ranges, the higher the uncertainty in the determination of basic reaction properties, limiting interpretability of and confidence in the results. Herein we propose a new, computationally efficient approach that refines flux range predictions by constraining reaction fluxes based on the elemental balance of carbon. We compared carbon constraint FBA (ccFBA) against experimentally measured intracellular fluxes using the latest CHO GEM (iCHO1766) and were able to substantially improve the accuracy of predicted flux values compared to FBA. ccFBA can be used as a stand-alone method but is also compatible with and complimentary to other constraint-based approaches. This article is protected by copyright. All rights reserved.