Estimation of Intracellular Flux Distribution under Underdetermined and Uncertain Conditions by Maximum Entropy Principle

This is the authors' abstract. We don't add key points for this paper.

In silico simulation is much more powerful and reliable than before for the bioprocess analysis and optimization in the fields of metabolic engineering and systems biology. The intracellular flux distribution could be estimated by Metabolic Flux Analysis (MFA) and Elementary Mode Analysis (EMA). It is always difficult to obtain an accurate flux distribution due to the insufficiencies, the measurement errors of the experimental data and the redundancy of EMs. An algorithm has been proposed to determine the Elementary Mode Coefficients (EMCs) by the maximum entropy principle (MEP). The intracellular flux distribution is calculated from the extracellular fluxes under underdetermined and uncertain conditions. To demonstrate the feasibility of this algorithm, it is used to estimate of the intracellular flux distribution for hybridoma, Escherichia coli and Bacillus subtilis. The MEP algorithm avoids any physiological hypotheses for the cellular states. It is reliable and feasible for the estimation of the intracellular flux distribution compared with other objective functions.