Metabolic engineering is the field of introducing genetic changes in organisms so as to modify their function towards synthesizing new products of high impact to society. However, engineered cells frequently have impaired growth rates thus seriously limiting the rate at which such products are made. The problem is attributable to inadequate understanding of how a metabolic network functions in a dynamic sense. Predictions of mutant strain behavior in the past have been based on steady state theories such as flux balance analysis (FBA), minimization of metabolic adjustment (MOMA), and regulatory on/off minimization (ROOM). Such predictions are restricted to product yields and cannot address productivity, which is of focal interest to applications. We demonstrate that our framework (Song and Ramkrishna, 2010, Song and Ramkrishna, 2011), based on a “cybernetic” view of metabolic systems, makes predictions of the dynamic behavior of mutant strains of Escherichia coli from a limited amount of data obtained from the wild-type. Dynamic frameworks must necessarily address the issue of metabolic regulation, which the cybernetic approach does by postulating that metabolism is an optimal dynamic response of the organism to the environment in driving reactions towards ensuring survival. The predictions made in this paper are without parallel in the literature and lay the foundation for rational metabolic engineering.

代谢工程是在生物中引入遗传变化，从而改变其功能以合成对社会具有重大影响的新产品的领域。然而，工程细胞经常损害生长速率，因此严重限制了此类产品的制备速度。该问题归因于对代谢网络如何在动态意义上起作用的理解不足。过去，对突变株行为的预测是基于稳态理论，例如通量平衡分析（FBA），最小化代谢调节（MOMA）和最小化开/关（ROOM）。这样的预测仅限于产品产量，无法解决生产率问题，这是应用程序关注的焦点。我们证明了我们的框架（Song和Ramkrishna，2010； Song和Ramkrishna，2011）基于代谢系统的“ cybernetic”观点，可从有限的数据中预测大肠埃希氏菌突变株的动态行为。野生型。动态框架必须解决代谢调控问题，控制论方法通过假设代谢是有机体对环境的最佳动态响应，从而推动了确保生存的反应。本文所做的预测在文献中是无与伦比的，为合理的代谢工程奠定了基础。