A global optimization approach for metabolic flux analysis based on labeling balances
A global optimization approach for metabolic flux analysis based on labeling balances
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DOI：
10.1016/j.compchemeng.2004.08.012
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发表时间：
2005-02-15
影响因子：
4.3
通讯作者：
Pinto, JM
中科院分区：
文献类型：
--
作者：
Riascos, CAM;Gombert, AK;Pinto, JM
代谢通量分析(MFA)中的通量量化步骤包括新陈代谢的数学模型(基于代谢物和同位素平衡)及其最优化，它使测量和模型预测之间的加权距离最小化。利用GC-MS分析细胞内代谢物的C-13标记时，代谢通量量化问题源于一个双线性约束的非凸优化模型，其中多个局部极小值的存在是一个特殊的困难。在目前的工作中，我们提出了一种依赖于空间分支和界限搜索的全局优化技术。为了得到一个全局最优解的下界，将线性化技术应用于标记平衡的约束，以获得一个凸松弛问题；由于线性化的性质，初始变量(测量的)和参数(非测量的)界限强烈地影响模型的收敛。全局优化算法基于先前报道的实验数据来估计酿酒酵母中心代谢的通量[Gombert，A.K.，dos Santos，M.，Christensen，B.，Nielsen，J.(2001)]。不同葡萄糖抑制条件下酿酒酵母中心代谢的网络鉴定和通量定量。细菌学杂志，183(4)，1441-1451]。为了达到全局收敛，文中给出了一个详细的边界紧凑过程。以已测量的标号和未测量的净通量为分支变量，在凸模型和非凸模型中，对其值相差最大的变量进行分支。结果与使用进化算法获得的结果进行了比较，进化算法需要大量的计算工作才能获得可行的解。我们发现，在中心路径上存在着具有重要差异的局部解。在全局最优解中，中心路径的计算通量与进化搜索得到的最优结果相似，而变量集、测量标记和通量的平方误差较小。(C)2004爱思唯尔有限公司。保留所有权利。
The flux quantification step in metabolic flux analysis (MFA) includes the mathematical modeling of metabolism (based on both metabolite and isotope balancing) and its optimization, which minimizes a weighted distance between measurements and model predictions. When GC-MS is used for assessing the C-13-labeling in intracellular metabolites, the metabolic flux quantification problem originates a non-convex optimization model with bilinear constraints for which the existence of multiple local minima is a special difficulty. In the present work, we propose a global optimization technique that relies on a spatial branch and bound search. A linearization technique is applied on the constraints from labeling balances, in order to obtain a convex relaxed problem that provides a lower bound to the global optimum; due to the nature of the linearization, the initial variable (measured) and parameter (non-measured) bounds strongly affect the model convergence.The global optimization algorithm estimates fluxes in the central metabolism of Saccharomyces cerevisiae, based on experimental data previously reported [Gombert, A. K., dos Santos, M. M., Christensen, B., Nielsen, J. (2001). Network identification and flux quantification in the central metabolism of Saccharomyces cerevisiae under different conditions of glucose repression. Journal of Bacteriology, 183(4), 1441-1451]. To attain global convergence, a detailed bound tightening procedure is developed. Measured labelings and non-measured net fluxes are the branching variables, and the branching is performed on the one that has the largest difference between its values in the convex and non-convex models. Results were compared to the ones obtained using an evolutionary algorithm that requires extensive computational effort to achieve a feasible solution. We found that there are local solutions with important differences on the central pathways. In the global optimum, the calculated fluxes for the central pathways are similar to the best result obtained by evolutionary search, whereas the quadratic errors for both variable sets, measured labelings and fluxes, are smaller. (c) 2004 Elsevier Ltd. All rights reserved.