Metabolic flux analysis (MFA) is an important analytical technique to quantify intracellular metabolic fluxes as a consequence of all catalytic and transcriptional interactions. In systems metabolic engineering, MFA has played important role to understand cellular physiology under particular conditions and predict its metabolic capability after genetic or environmental perturbations. Two methods using optimization procedure, ¹³C-based flux analysis and constraints-based flux analysis, have been used generally on the basis of stoichiometry of metabolic reactions and mass balances around intracellular metabolites under pseudo-steady state assumption. Practically, MFA has been applied to generate new knowledge on the biological system, analyze cellular physiology system-wide, and consequently design metabolic engineering strategies at a systems-level. In this chapter, we study the basic principle of MFA (more particularly constraints-based flux analysis), inspect the characteristics of several in silico algorithms developed for system-wide analysis of cellular metabolic fluxes, and discuss their applications.
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