Improving pathway prediction accuracy of constraints-based metabolic network models by treating enzymes as microcompartments  

作　　者：Xue Yang Zhitao Mao Jianfeng Huang Ruoyu Wang Huaming Dong Yanfei Zhang Hongwu Ma 

机构地区：[1]Tianjin Institute of Industrial Biotechnology,Chinese Academy of Sciences,Tianjin,300308,China [2]National Technology Innovation Center of Synthetic Biology,Tianjin,300308,China [3]School of Environmental Ecology and Biological Engineering,Wuhan Institute of Technology,Wuhan,430205,China

出　　处：《Synthetic and Systems Biotechnology》2023年第4期597-605,共9页合成和系统生物技术（英文）

基　　金：funded by the National Key Research and Development Program of China(2018YFA0900300,2020YFA0908301);the National Natural Science Foundation of China(32201188);the Tianjin Synthetic Biotechnology Innovation Capacity Improvement Project(TSBICIP-CXRC-060,TSBICIP-PTJS-001,and TSBICIP-PTJS-013);the China Postdoctoral Science Foundation(2022M723341).

摘　　要：Metabolic network models have become increasingly precise and accurate as the most widespread and practical digital representations of living cells.The prediction functions were significantly expanded by integrating cellular resources and abiotic constraints in recent years.However,if unreasonable modeling methods were adopted due to a lack of consideration of biological knowledge,the conflicts between stoichiometric and other constraints,such as thermodynamic feasibility and enzyme resource availability,would lead to distorted predictions.In this work,we investigated a prediction anomaly of EcoETM,a constraints-based metabolic network model,and introduced the idea of enzyme compartmentalization into the analysis process.Through rational combination of reactions,we avoid the false prediction of pathway feasibility caused by the unrealistic assumption of free intermediate metabolites.This allowed us to correct the pathway structures of L-serine and L-tryptophan.A specific analysis explains the application method of the EcoETM-like model and demonstrates its potential and value in correcting the prediction results in pathway structure by resolving the conflict between different constraints and incorporating the evolved roles of enzymes as reaction compartments.Notably,this work also reveals the trade-off between product yield and thermodynamic feasibility.Our work is of great value for the structural improvement of constraints-based models.

关 键 词：Genome-scale metabolic network models (GEMs) Enzymatic and thermodynamic constraints Thermodynamic driving force(MDF) COMPARTMENTALIZATION Multifunctional enzymes Enzyme complexes 

分 类 号：Q81[生物学—生物工程]