Xu Peng
Department of Chemical, Biochemical and Environmental Engineering, University of Maryland Baltimore County, Baltimore, MD 21250, USA.
Metab Eng Commun. 2020 Apr 24;10:e00127. doi: 10.1016/j.mec.2020.e00127. eCollection 2020 Jun.
Living organism is an intelligent system coded by hierarchically-organized information to perform precisely-controlled biological functions. Biophysical models are important tools to uncover the design rules underlying complex genetic-metabolic circuit interactions. Based on a previously engineered synthetic malonyl-CoA switch (Xu et al., PNAS, 2014), we have formulated nine differential equations to unravel the design principles underlying an ideal metabolic switch to improve fatty acids production in . By interrogating the physiologically accessible parameter space, we have determined the optimal controller architecture to configure both the metabolic source pathway and metabolic sink pathway. We determined that low protein degradation rate, medium strength of metabolic inhibitory constant, high metabolic source pathway induction rate, strong binding affinity of the transcriptional activator toward the metabolic source pathway, weak binding affinity of the transcriptional repressor toward the metabolic sink pathway, and a strong cooperative interaction of transcriptional repressor toward metabolic sink pathway benefit the accumulation of the target molecule (fatty acids). The target molecule (fatty acid) production is increased from 50% to 10-folds upon application of the autonomous metabolic switch. With strong metabolic inhibitory constant, the system displays multiple steady states. Stable oscillation of metabolic intermediate is the driving force to allow the system deviate from its equilibrium state and permits bidirectional ON-OFF gene expression control, which autonomously compensates enzyme level for both the metabolic source and metabolic sink pathways. The computational framework may facilitate us to design and engineer predictable genetic-metabolic switches, quest for the optimal controller architecture of the metabolic source/sink pathways, as well as leverage autonomous oscillation as a powerful tool to engineer cell function.
生物体是一个由层次组织化信息编码的智能系统,以执行精确控制的生物学功能。生物物理模型是揭示复杂遗传 - 代谢回路相互作用潜在设计规则的重要工具。基于先前设计的合成丙二酰辅酶A开关(Xu等人,《美国国家科学院院刊》,2014年),我们制定了九个微分方程,以揭示理想代谢开关提高脂肪酸产量的潜在设计原则。通过探究生理上可及的参数空间,我们确定了配置代谢源途径和代谢汇途径的最佳控制器架构。我们确定低蛋白质降解率、中等强度的代谢抑制常数、高代谢源途径诱导率、转录激活剂对代谢源途径的强结合亲和力、转录阻遏物对代谢汇途径的弱结合亲和力以及转录阻遏物对代谢汇途径的强协同相互作用有利于目标分子(脂肪酸)的积累。应用自主代谢开关后,目标分子(脂肪酸)的产量从50%提高到了10倍。在强代谢抑制常数下,系统显示出多个稳态。代谢中间体的稳定振荡是驱使系统偏离其平衡状态并允许双向开 - 关基因表达控制的驱动力,这可自主补偿代谢源和代谢汇途径的酶水平。该计算框架可能有助于我们设计和构建可预测的遗传 - 代谢开关,探索代谢源/汇途径的最佳控制器架构,以及利用自主振荡作为工程化细胞功能的强大工具。