Yang Liu, Li Junyi, Zhang Yaping, Chen Linlin, Ouyang Zhilin, Liao Daocheng, Zhao Fengguang, Han Shuangyan
Guangdong Key Laboratory of Fermentation and Enzyme Engineering, School of Biology and Biological Engineering, South China University of Technology, Guangzhou, China.
School of Light Industry and Engineering, South China University of Technology, Guangzhou, China.
Front Bioeng Biotechnol. 2023 Nov 28;11:1296880. doi: 10.3389/fbioe.2023.1296880. eCollection 2023.
The model of intracellular metabolic network based on enzyme kinetics parameters plays an important role in understanding the intracellular metabolic process of , and constructing such a model requires a large number of enzymological parameters. In this work, the genes encoding the relevant enzymes of the EMP and HMP metabolic pathways from ATCC 13032 were cloned, and engineered strains for protein expression with BL21 and X33 as hosts were constructed. The twelve enzymes (GLK, GPI, TPI, GAPDH, PGK, PMGA, ENO, ZWF, RPI, RPE, TKT, and TAL) were successfully expressed and purified by Ni chelate affinity chromatography in their active forms. In addition, the kinetic parameters ( , , and ) of these enzymes were measured and calculated at the same pH and temperature. The kinetic parameters of enzymes associated with EMP and the HMP pathway were determined systematically and completely for the first time in . These kinetic parameters enable the prediction of key enzymes and rate-limiting steps within the metabolic pathway, and support the construction of a metabolic network model for important metabolic pathways in . Such analyses and models aid in understanding the metabolic behavior of the organism and can guide the efficient production of high-value chemicals using as a host.
基于酶动力学参数的细胞内代谢网络模型在理解[具体生物名称]的细胞内代谢过程中起着重要作用,构建这样一个模型需要大量的酶学参数。在这项工作中,克隆了来自[具体生物名称]ATCC 13032的EMP和HMP代谢途径相关酶的基因,并构建了以BL21和X33为宿主的蛋白质表达工程菌株。通过镍螯合亲和层析成功表达并纯化了十二种酶(GLK、GPI、TPI、GAPDH、PGK、PMGA、ENO、ZWF、RPI、RPE、TKT和TAL),且保持其活性形式。此外,在相同的pH和温度下测量并计算了这些酶的动力学参数([具体参数名称1]、[具体参数名称2]和[具体参数名称3])。在[具体生物名称]中首次系统且完整地测定了与EMP和HMP途径相关酶的动力学参数。这些动力学参数能够预测代谢途径中的关键酶和限速步骤,并支持构建[具体生物名称]重要代谢途径的代谢网络模型。此类分析和模型有助于理解生物体的代谢行为,并可指导以[具体生物名称]为宿主高效生产高价值化学品。