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迈向全球代谢网络的动力学建模:以扭脱甲基杆菌AM1的生长作为验证

Towards kinetic modeling of global metabolic networks: Methylobacterium extorquens AM1 growth as validation.

作者信息

Ao Ping, Lee Lik Wee, Lidstrom Mary E, Yin Lan, Zhu Xiaomei

机构信息

Department of Mechanical Engineering, University of Washington, Seattle, WA 98195, USA.

出版信息

Sheng Wu Gong Cheng Xue Bao. 2008 Jun;24(6):980-94. doi: 10.1016/s1872-2075(08)60046-1.

Abstract

Here we report a systematic method for constructing a large scale kinetic metabolic model and its initial application to the modeling of central metabolism of Methylobacterium extorquens AM1, a methylotrophic and environmental important bacterium. Its central metabolic network includes formaldehyde metabolism, serine cycle, citric acid cycle, pentose phosphate pathway, gluconeogensis, PHB synthesis and acetyl-CoA conversion pathway, respiration and energy metabolism. Through a systematic and consistent procedure of finding a set of parameters in the physiological range we overcome an outstanding difficulty in large scale kinetic modeling: the requirement for a massive number of enzymatic reaction parameters. We are able to construct the kinetic model based on general biological considerations and incomplete experimental kinetic parameters. Our method consists of the following major steps: (1) using a generic enzymatic rate equation to reduce the number of enzymatic parameters to a minimum set while still preserving their characteristics; (2) using a set of steady state fluxes and metabolite concentrations in the physiological range as the expected output steady state fluxes and metabolite concentrations for the kinetic model to restrict the parametric space of enzymatic reactions; (3) choosing enzyme constants K's and K'(eqS) optimized for reactions under physiological concentrations, if their experimental values are unknown; (4) for models which do not cover the entire metabolic network of the organisms, designing a dynamical exchange for the coupling between the metabolism represented in the model and the rest not included.

摘要

在此,我们报告一种构建大规模动力学代谢模型的系统方法及其在甲基营养型且对环境重要的细菌——嗜甲基甲基杆菌AM1中心代谢建模中的初步应用。其中心代谢网络包括甲醛代谢、丝氨酸循环、柠檬酸循环、磷酸戊糖途径、糖异生、聚羟基丁酸酯合成以及乙酰辅酶A转化途径、呼吸作用和能量代谢。通过在生理范围内寻找一组参数的系统且一致的程序,我们克服了大规模动力学建模中的一个突出难题:对大量酶促反应参数的需求。我们能够基于一般生物学考量和不完整的实验动力学参数构建动力学模型。我们的方法包括以下主要步骤:(1) 使用通用酶促速率方程将酶促参数数量减少到最小集,同时仍保留其特性;(2) 使用生理范围内的一组稳态通量和代谢物浓度作为动力学模型的预期输出稳态通量和代谢物浓度,以限制酶促反应的参数空间;(3) 如果酶常数K和K'(eqS)的实验值未知,则选择针对生理浓度下反应优化的酶常数;(4) 对于未涵盖生物体整个代谢网络的模型,设计一种动态交换,用于模型中所表示的代谢与未包括的其余部分之间的耦合。

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