Van Dien Stephen J, Iwatani Shintaro, Usuda Yoshihiro, Matsui Kazuhiko
Functional Genomics Group, Institute of Life Sciences, Ajinomoto Co., Inc., Kawasaki 210-8681, Japan.
J Biosci Bioeng. 2006 Jul;102(1):34-40. doi: 10.1263/jbb.102.34.
This work demonstrates a novel computational approach combining flux balance modeling with statistical methods to identify correlations among fluxes in a metabolic network, providing insight as to how the fluxes should be redirected to achieve maximum product yield. The procedure is demonstrated using the example of amino acid production from an industrial Escherichia coli production strain and a hypothetical engineered strain overexpressing two heterologous genes. Regression analysis based on a random sampling of 5,000 points within the feasible solution space of the E. coli stoichiometric network suggested that increased activity of the glyoxylate cycle or PEP carboxylase and elimination of malic enzyme will improve lysine and arginine synthesis.
这项工作展示了一种新颖的计算方法，该方法将通量平衡建模与统计方法相结合，以识别代谢网络中通量之间的相关性，从而深入了解应如何重新调整通量以实现最大的产品产量。以工业大肠杆菌生产菌株和过表达两个异源基因的假设工程菌株生产氨基酸为例，演示了该过程。基于在大肠杆菌化学计量网络的可行解空间内对5000个点进行随机采样的回归分析表明，乙醛酸循环或磷酸烯醇式丙酮酸羧化酶活性的增加以及苹果酸酶的消除将改善赖氨酸和精氨酸的合成。
