Jahan Nusrat, Maeda Kazuhiro, Matsuoka Yu, Sugimoto Yurie, Kurata Hiroyuki
Department of Bioscience and Bioinformatics, Kyushu Institute of Technology, 680-4 Kawazu, Iizuka, Fukuoka, 820-8502, Japan.
Frontier Research Academy for Young Researchers, Kyushu Institute of Technology, 1-1 Sensui-cho, Tobata, Kitakyushu, Fukuoka, 804-8550, Japan.
Microb Cell Fact. 2016 Jun 21;15(1):112. doi: 10.1186/s12934-016-0511-x.
A kinetic model provides insights into the dynamic response of biological systems and predicts how their complex metabolic and gene regulatory networks generate particular functions. Of many biological systems, Escherichia coli metabolic pathways have been modeled extensively at the enzymatic and genetic levels, but existing models cannot accurately reproduce experimental behaviors in a batch culture, due to the inadequate estimation of a specific cell growth rate and a large number of unmeasured parameters.
In this study, we developed a detailed kinetic model for the central carbon metabolism of E. coli in a batch culture, which includes the glycolytic pathway, tricarboxylic acid cycle, pentose phosphate pathway, Entner-Doudoroff pathway, anaplerotic pathway, glyoxylate shunt, oxidative phosphorylation, phosphotransferase system (Pts), non-Pts and metabolic gene regulations by four protein transcription factors: cAMP receptor, catabolite repressor/activator, pyruvate dehydrogenase complex repressor and isocitrate lyase regulator. The kinetic parameters were estimated by a constrained optimization method on a supercomputer. The model estimated a specific growth rate based on reaction kinetics and accurately reproduced the dynamics of wild-type E. coli and multiple genetic mutants in a batch culture.
This model overcame the intrinsic limitations of existing kinetic models in a batch culture, predicted the effects of multilayer regulations (allosteric effectors and gene expression) on central carbon metabolism and proposed rationally designed fast-growing cells based on understandings of molecular processes.
动力学模型有助于深入了解生物系统的动态响应,并预测其复杂的代谢和基因调控网络如何产生特定功能。在众多生物系统中,大肠杆菌的代谢途径已在酶和基因水平上进行了广泛建模,但由于对特定细胞生长速率的估计不足以及大量未测量参数的存在,现有模型无法准确再现分批培养中的实验行为。
在本研究中,我们开发了一个用于分批培养中大肠杆菌中心碳代谢的详细动力学模型,该模型包括糖酵解途径、三羧酸循环、磷酸戊糖途径、Entner-Doudoroff途径、回补途径、乙醛酸分流、氧化磷酸化、磷酸转移酶系统(Pts)、非Pts以及由四种蛋白质转录因子(cAMP受体、分解代谢物阻遏物/激活剂、丙酮酸脱氢酶复合体阻遏物和异柠檬酸裂合酶调节剂)进行的代谢基因调控。通过超级计算机上的约束优化方法估计动力学参数。该模型基于反应动力学估计了特定生长速率,并准确再现了分批培养中野生型大肠杆菌和多个基因变体的动态变化。
该模型克服了现有分批培养动力学模型的固有局限性,预测了多层调控(变构效应物和基因表达)对中心碳代谢的影响,并基于对分子过程的理解提出了合理设计的快速生长细胞。