A graph-theory-based method for processing of currency metabolites in metabolic networks / 生物工程学报

Graph-theory-based pathway analysis is a commonly used method for pathway searching in genome-scale metabolic networks. However, such searching often results in many pathways biologically infeasible due to the presence of currency metabolites (e.g. H+, H2O, CO2, ATP etc.). Several methods have been proposed to address the problem but up to now there is no well-recognized methods for processing the currency metabolites. In this study, we proposed a new method based on the function of currency metabolites for transferring of functional groups such as phosphate. We processed most currency metabolites as pairs rather than individual metabolites, and ranked the pairs based on their importance in transferring functional groups, in order to make sure at least one main metabolite link exists for any reaction. The whole process can be done automatically by programming. Comparison with existing approaches indicates that more biologically infeasible pathways were removed by our method and the calculated pathways were more reliable, which may facilitate the graph-theory-based pathway design and visualization.

Development of metabolic models with multiple constraints: a review / 生物工程学报

Constraint-based genome-scale metabolic network models (genome-scale metabolic models, GEMs) have been widely used to predict metabolic phenotypes. In addition to stoichiometric constraints, other constraints such as enzyme availability and thermodynamic feasibility may also limit the cellular phenotype solution space. Recently, extended GEM models considering either enzymatic or thermodynamic constraints have been developed to improve model prediction accuracy. This review summarizes the recent progresses on metabolic models with multiple constraints (MCGEMs). We presented the construction methods and various applications of MCGEMs including the simulation of gene knockout, prediction of biologically feasible pathways and identification of bottleneck steps. By integrating multiple constraints in a consistent modeling framework, MCGEMs can predict the metabolic bottlenecks and key controlling and modification targets for pathway optimization more precisely, and thus may provide more reliable design results to guide metabolic engineering of industrially important microorganisms.

Progress and application of metabolic network model based on enzyme constraints / 生物工程学报

Genome-scale metabolic network models have been successfully applied to guide metabolic engineering. However, the conventional flux balance analysis only considers stoichiometry and reaction direction constraints, and the simulation results cannot accurately describe certain phenomena such as overflow metabolism and diauxie growth on two substrates. Recently, researchers proposed new constraint-based methods to simulate the cellular behavior under different conditions more precisely by introducing new constraints such as limited enzyme content and thermodynamics feasibility. Here we review several enzyme-constrained models, giving a comprehensive introduction on the biological basis and mathematical representation for the enzyme constraint, the optimization function, the impact on the calculated flux distribution and their application in identification of metabolic engineering targets. The main problems in these existing methods and the perspectives on this emerging research field are also discussed. By introducing new constraints, metabolic network models can simulate and predict cellular behavior under various environmental and genetic perturbations more accurately, and thus can provide more reliable guidance to strain engineering.