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Applying asymptotic methods to synthetic biology: Modelling the reaction kinetics of the mevalonate pathway

机译:将渐近方法应用于合成生物学:模拟甲羟戊酸途径的反应动力学

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摘要

The mevalonate pathway is normally found in eukaryotes, and allows for the production of isoprenoids, a useful class of organic compounds. This pathway has been successfully introduced to Escherichia coli, enabling a biosynthetic production route for many isoprenoids. In this paper, we develop and solve a mathematical model for the concentration of metabolites in the mevalonate pathway over time, accounting for the loss of acetyl-CoA to other metabolic pathways. Additionally, we successfully test our theoretical predictions experimentally by introducing part of the pathway into Cupriavidus necator. In our model, we exploit the natural separation of time scales as well as of metabolite concentrations to make significant asymptotic progress in understanding the system. We confirm that our asymptotic results agree well with numerical simulations, the former enabling us to predict the most important reactions to increase isopentenyl diphosphate production whilst minimizing the levels of HMG-CoA, which inhibits cell growth. Thus, our mathematical model allows us to recommend the upregulation of certain combinations of enzymes to improve production through the mevalonate pathway.
机译:甲羟戊酸途径通常在真核生物中发现,并允许产生类异戊二烯,有用的一类有机化合物。该途径已成功引入大肠杆菌,为许多类异戊二烯提供了生物合成生产途径。在本文中,我们开发并解决了甲羟戊酸途径中代谢物浓度随时间变化的数学模型,并考虑了乙酰辅酶A丢失至其他代谢途径的情况。此外,我们通过将部分途径引入Cupriavidus necator,成功地通过实验测试了我们的理论预测。在我们的模型中,我们利用时间尺度和代谢物浓度的自然分离来在理解系统方面取得显着的渐近性。我们确认我们的渐近结果与数值模拟非常吻合,前者使我们能够预测最重要的反应,以增加异戊烯基二磷酸的产生,同时最小化抑制细胞生长的HMG-CoA的水平。因此,我们的数学模型使我们可以推荐某些酶组合的上调,以改善甲羟戊酸途径的生产。

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