描绘细胞代谢目标的全貌。
Mapping the landscape of metabolic goals of a cell.
作者信息
Zhao Qi, Stettner Arion I, Reznik Ed, Paschalidis Ioannis Ch, Segrè Daniel
机构信息
Department of Electrical and Computer Engineering, and Division of Systems Engineering, Boston University, Boston, MA, 02215, USA.
Department of Biomedical Engineering, Boston University, Boston, MA, 02215, USA.
出版信息
Genome Biol. 2016 May 23;17(1):109. doi: 10.1186/s13059-016-0968-2.
Genome-scale flux balance models of metabolism provide testable predictions of all metabolic rates in an organism, by assuming that the cell is optimizing a metabolic goal known as the objective function. We introduce an efficient inverse flux balance analysis (invFBA) approach, based on linear programming duality, to characterize the space of possible objective functions compatible with measured fluxes. After testing our algorithm on simulated E. coli data and time-dependent S. oneidensis fluxes inferred from gene expression, we apply our inverse approach to flux measurements in long-term evolved E. coli strains, revealing objective functions that provide insight into metabolic adaptation trajectories.
代谢的基因组规模通量平衡模型通过假设细胞正在优化一个被称为目标函数的代谢目标，来提供对生物体中所有代谢率的可测试预测。我们基于线性规划对偶性引入了一种高效的逆通量平衡分析（invFBA）方法，以表征与测量通量兼容的可能目标函数的空间。在对模拟的大肠杆菌数据和从基因表达推断出的随时间变化的嗜水栖热袍菌通量进行算法测试后，我们将逆方法应用于长期进化的大肠杆菌菌株的通量测量，揭示了能够深入了解代谢适应轨迹的目标函数。
Zotero 插件