Elimination of Thermodynamically Infeasible Loops in Steady-State Metabolic Models

被引:146
作者
Schellenberger, Jan [2 ]
Lewis, Nathan E. [1 ]
Palsson, Bernhard O. [1 ]
机构
[1] Univ Calif San Diego, Dept Bioengn, San Diego, CA 92103 USA
[2] Univ Calif San Diego, Bioinformat & Syst Biol Program, San Diego, CA 92103 USA
基金
美国国家科学基金会; 美国国家卫生研究院;
关键词
FLUX BALANCE ANALYSIS; GENOME-SCALE MODELS; ESCHERICHIA-COLI METABOLISM; BIOCHEMICAL NETWORKS; GENE-EXPRESSION; RECONSTRUCTION; CONSTRAINTS; CAPABILITIES; PERSPECTIVE; DEFINITION;
D O I
10.1016/j.bpj.2010.12.3707
中图分类号
Q6 [生物物理学];
学科分类号
071011 ;
摘要
The constraint-based reconstruction and analysis (COBRA) framework has been widely used to study steadystate flux solutions in genome-scale metabolic networks. One shortcoming of current COBRA methods is the possible violation of the loop law in the computed steady-state flux solutions. The loop law is analogous to Kirchhoff's second law for electric circuits, and states that at steady state there can be no net flux around a closed network cycle. Although the consequences of the loop law have been known for years, it has been computationally difficult to work with. Therefore, the resulting loop-law constraints have been overlooked. Here, we present a general mixed integer programming approach called loopless COBRA (II-COBRA), which can be used to eliminate all steady-state flux solutions that are incompatible with the loop law. We apply this approach to improve flux predictions on three common COBRA methods: flux balance analysis, flux variability analysis, and Monte Carlo sampling of the flux space. Moreover, we demonstrate that the imposition of loop-law constraints with II-COBRA improves the consistency of simulation results with experimental data. This method provides an additional constraint for many COBRA methods, enabling the acquisition of more realistic simulation results.
引用
收藏
页码:544 / 553
页数:10
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