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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

It is among the goals in metabolic engineering to construct microbial cell factories producing high-yield and high value-added target products, and an important solution is to design efficient synthetic pathway for the target products. However, due to the difference in metabolic capacity among microbial chassises, the available substrate and the yielded products are limited. Therefore, it is urgent to design related metabolic pathways to improve the production capacity. Existing metabolic engineering approaches to designing heterologous pathways are mainly based on biological experience, which are inefficient. Moreover, the yielded results are in no way comprehensive. However, systems biology provides new methods for heterologous pathway design, particularly the graph-based and constraint-based methods. Based on the databases containing rich metabolism information, they search for and uncover possible metabolic pathways with designated strategy (graph-based method) or algorithm (constraint-based method) and then screen out the optimal pathway to guide the modification of strains. In this paper, we reviewed the databases and algorithms for pathway design, and the applications in metabolic engineering and discussed the strengths and weaknesses of existing algorithms in practical application, hoping to provide a reference for the selection of optimal methods for the design of product synthesis pathway.

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.

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.基因组尺度代谢网络模型已经成功地应用于指导代谢工程改造，但由于传统通量平衡分析法仅考虑化学计量学和反应方向约束，模拟得到的是理论最优结果，对一些现象如代谢溢流、底物层级利用等无法准确描述。近年来人们通过在代谢网络模型中引入新的蛋白量、热力学等约束发展了新的约束优化计算方法，可以更准确真实地模拟细胞在不同条件下的代谢行为。文中主要对近年来提出的多种酶约束模型进行评述，对酶约束引入的基本思路、酶约束的数学方程表示及优化目标设定、引入酶约束后对代谢通量计算结果的影响及酶约束模型在代谢工程菌种改造中的应用等进行了全面深入的介绍，并提出了已有各种方法存在的主要问题，展望了相关方法的未来发展方向。通过引入新的约束，代谢网络模型能够更精确模拟和预测细胞在环境和基因扰动下的代谢行为，为代谢工程菌种改造提供更准确可靠的指导。.

Kinetic model analysis is a useful tool for understanding the regulation and control of cellular metabolism and thus offering a guideline for rational design of high efficiency cell factory. Based on previously published models and experimental measurement of enzyme kinetics data, we developed a kinetic model for the threonine biosynthesis pathway in Escherichia coli. This model integrates the central pathways that produce precursors, ATP and reducing power with the threonine biosynthesis pathway from aspartate. In contrast to the previous models, we considered the energy and reducing power balance rather than artificially set their concentrations. Metabolic control analysis of the model showed that enzymes PTS, G6PDH, HDH etc. have great flux control coefficients on the threonine biosynthesis flux. This indicates higher threonine synthesis flux could be achieved by overexpressing these enzymes.

High-throughput data supply a basis for the reconstruction of genome-scale metabolic networks, and meanwhile bring challenges to the reconstruction and analysis methods. With the increasing of data quantity, the time-consuming manual reconstruction and analysis are far behind the improvement of models. Therefore, various automatic methods emerge. The automatic reconstruction and analysis have irreplaceable effect in the standardization and programming of reconstruction and analysis methods, as well as largely improving the speed of reconstruction and understanding of the metabolic network. In this review, we introduced the progress of automatic reconstruction and the main analysis tools of genome-scale metabolic network. We further summarized the workflow of automatic reconstruction. The difficulties and perspectives on this research field are also discussed.