Bordel Sergio, Martín-González Diego, Börner Tim, Muñoz Raúl, Santos-Beneit Fernando
Department of Chemical Engineering and Environmental Technology, School of Industrial Engineering, University of Valladolid, Valladolid, Spain.
2Institute of Sustainable Processes, Valladolid, Spain.
mSystems. 2024 Feb 20;9(2):e0107723. doi: 10.1128/msystems.01077-23. Epub 2024 Jan 5.
A genome scale metabolic model of the bacterium has been constructed. The model containing 972 metabolic genes, 1,371 reactions, and 1,388 unique metabolites has been reconstructed. The model was used to carry out quantitative predictions of biomass yields on 10 different carbon sources under aerobic conditions. Yields on C1 compounds suggest that formate is oxidized by a formate dehydrogenase O, which uses ubiquinone as redox co-factor. The model also predicted the threshold methanol/mannitol uptake ratio, above which ribulose biphosphate carboxylase has to be expressed in order to optimize biomass yields. Biomass yields on acetate, formate, and succinate, when NO is used as electron acceptor, were also predicted correctly. The model reconstruction revealed the capability of to grow on several non-conventional substrates such as adipic acid, 1,4-butanediol, 1,3-butanediol, and ethylene glycol. The capacity to grow on these substrates was tested experimentally, and the experimental biomass yields on these substrates were accurately predicted by the model.IMPORTANCE has been broadly used as a model denitrifying organism. It grows on a large portfolio of carbon sources, under aerobic and anoxic conditions. These characteristics, together with its amenability to genetic manipulations, make a promising cell factory for industrial biotechnology. This paper presents and validates the first functional genome-scale metabolic model for , which is a key tool to enable as a platform for metabolic engineering and industrial biotechnology. Optimization of the biomass yield led to accurate predictions in a broad scope of substrates.
已构建了该细菌的全基因组规模代谢模型。该模型包含972个代谢基因、1371个反应和1388种独特代谢物,已经完成重建。该模型用于对有氧条件下10种不同碳源上的生物量产量进行定量预测。对C1化合物的产量预测表明,甲酸由甲酸脱氢酶O氧化,该酶使用泛醌作为氧化还原辅助因子。该模型还预测了甲醇/甘露醇的阈值摄取比,高于此比值时,必须表达核酮糖二磷酸羧化酶以优化生物量产量。当以NO作为电子受体时,对乙酸盐、甲酸盐和琥珀酸盐上的生物量产量也做出了正确预测。模型重建揭示了该细菌在几种非常规底物上生长的能力,如己二酸、1,4 - 丁二醇、1,3 - 丁二醇和乙二醇。对这些底物上生长能力进行了实验测试,并且模型准确预测了这些底物上的实验生物量产量。重要性该细菌已被广泛用作反硝化生物模型。它在有氧和缺氧条件下能利用大量碳源生长。这些特性,连同其对基因操作的适应性,使其成为工业生物技术中一个有前景的细胞工厂。本文展示并验证了首个针对该细菌的功能性全基因组规模代谢模型,这是使该细菌成为代谢工程和工业生物技术平台的关键工具。生物量产量的优化在广泛的底物范围内实现了准确预测。