Reed Jennifer L, Patel Trina R, Chen Keri H, Joyce Andrew R, Applebee Margaret K, Herring Christopher D, Bui Olivia T, Knight Eric M, Fong Stephen S, Palsson Bernhard O
Department of Bioengineering, University of California at San Diego, 9500 Gilman Drive, La Jolla, CA 92093-0412, USA.
Proc Natl Acad Sci U S A. 2006 Nov 14;103(46):17480-4. doi: 10.1073/pnas.0603364103. Epub 2006 Nov 6.
Genome-scale models of Escherichia coli K-12 MG1655 metabolism have been able to predict growth phenotypes in most, but not all, defined growth environments. Here we introduce the use of an optimization-based algorithm that predicts the missing reactions that are required to reconcile computation and experiment when they disagree. The computer-generated hypotheses for missing reactions were verified experimentally in five cases, leading to the functional assignment of eight ORFs (yjjLMN, yeaTU, dctA, idnT, and putP) with two new enzymatic activities and four transport functions. This study thus demonstrates the use of systems analysis to discover metabolic and transport functions and their genetic basis by a combination of experimental and computational approaches.
大肠杆菌K-12 MG1655代谢的基因组规模模型已能够预测大多数（但并非全部）特定生长环境中的生长表型。在此，我们引入一种基于优化的算法，该算法可预测在计算结果与实验结果不一致时，使二者达成一致所需的缺失反应。针对缺失反应的计算机生成假设在五个案例中得到了实验验证，从而实现了对八个开放阅读框（yjjLMN、yeaTU、dctA、idnT和putP）的功能分配，这些开放阅读框具有两种新的酶活性和四种转运功能。因此，本研究证明了通过实验和计算方法相结合，利用系统分析来发现代谢和转运功能及其遗传基础。
