Construction and application of high-quality genome-scale metabolic model of to guide rational design of microbial cell factories.

High-quality genome-scale metabolic models (GEMs) could play critical roles on rational design of microbial cell factories in the classical Design-Build-Test-Learn cycle of synthetic biology studies. Despite of the constant establishment and update of GEMs for model microorganisms such as and , high-quality GEMs for non-model industrial microorganisms are still scarce. subsp. ZM4 is a non-model ethanologenic microorganism with many excellent industrial characteristics that has been developing as microbial cell factories for biochemical production. Although five GEMs of have been constructed, these models are either generating ATP incorrectly, or lacking information of plasmid genes, or not providing standard format file. In this study, a high-quality GEM ZM516 of ZM4 was constructed. The information from the improved genome annotation, literature, datasets of Biolog Phenotype Microarray studies, and recently updated Gene-Protein-Reaction information was combined for the curation of ZM516. Finally, 516 genes, 1389 reactions, 1437 metabolites, and 3 cell compartments are included in ZM516, which also had the highest MEMOTE score of 91% among all published GEMs of Cell growth was then predicted by ZM516, which had 79.4% agreement with the experimental results of the substrate utilization. In addition, the potential endogenous succinate synthesis pathway of ZM4 was proposed through simulation and analysis using ZM516. Furthermore, metabolic engineering strategies to produce succinate and 1,4-butanediol (1,4-BDO) were designed and then simulated under anaerobic condition using ZM516. The results indicated that 1.68 mol/mol succinate and 1.07 mol/mol 1,4-BDO can be achieved through combinational metabolic engineering strategies, which was comparable to that of the model species Our study thus not only established a high-quality GEM ZM516 to help understand and design microbial cell factories for economic biochemical production using as the chassis, but also provided guidance on building accurate GEMs for other non-model industrial microorganisms.