Systematic characterization of intracellular metabolic states through Flux Directionality Profile Analysis A.Kiparissides, J. Pinto Vieira, V. Hatzimanikatis

Laboratory of Computational Systems Biotechnology EPFL, CH-­�1015, Lausanne, Switzerland

Swiss Institute of Bioinformatics CH-­�1015, Lausanne, Switzerland

Abstract

Metabolic modeling has proven to be a valuable tool for the investigation of cellular physiology in metabolic engineering studies. However, the sheer complexity of even the simplest metabolic networks obstructs the exact determination of intracellular states, despite the ample supply of â??omics data. Identifying the gamut of possible feasible states allows us to query for factors that are crucial in interpreting the observed physiology or in developing metabolic engineering strategies. Towards this end, we developed a framework called Flux Directionality Profile Analysis (FDPA) that enables both the complete enumeration and the characterization of all possible intracellular flux states. The proposed methodology allows for the seamless incorporation of available experimental data, when available, such as intracellular reaction fluxes, uptake rates, and intra-­â? and extra-­â?cellular metabolite concentration measurements. Additionally, FDPA employs a set of metabolic objectives in order to rank the thermodynamically feasible intracellular flux states based on their performance against one (or more) of these objectives. We are therefore able to isolate internal flux states that are both thermodynamically consistent and consistent with the observed physiology. We demonstrate the utility of this framework in studying central carbon metabolism of mammalian cells and we characterize the physiological differences between two distinct growth conditions.