多约束代谢网络模型的研究进展

基于约束的基因组尺度代谢网络模型(genome-scale metabolic models,GEMs)分析已被广泛应用于代谢表型的预测.而实际细胞中代谢速率除计量学约束外,还受到酶资源可用性和反应热力学可行性等其他因素影响,在GEMs中整合酶资源约束或者热力学约束构建多约束代谢网络模型可以进一步缩小优化解空间,提升细...

Development of metabolic models with multiple constraints: a review

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.