Metabolic flux distribution analysis by ¹³C-tracer experiments using the Markov chain–Monte Carlo method

Metabolic flux analysis using ¹³C-tracer experiments is an important tool in metabolic engineering since intracellular fluxes are non-measurable quantities in vivo. Current metabolic flux analysis approaches are fully based on stoichiometric constraints and carbon atom balances, where the over-determined system is iteratively solved by a parameter estimation approach. However, the unavoidable measurement noises involved in the fractional enrichment data obtained by ¹³C-enrichment experiment and the possible existence of unknown pathways prevent a simple parameter estimation method for intracellular flux quantification. The MCMC (Markov chain–Monte Carlo) method, which obtains intracellular flux distributions through delicately constructed Markov chains, is shown to be an effective approach for deep understanding of the intracellular metabolic network. Its application is illustrated through the simulation of an example metabolic network.