Determining enzyme kinetics for systems biology with nuclear magnetic resonance spectroscopy.
Determining enzyme kinetics for systems biology with nuclear magnetic resonance spectroscopy.
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通过核磁共振光谱确定用于系统生物学的酶动力学。
DOI：
10.3390/metabo2040818
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发表时间：
2012-11-06
期刊：
影响因子：
4.1
通讯作者：
Rohwer JM
中科院分区：
文献类型：
--
作者：
Eicher JJ;Snoep JL;Rohwer JM
系统生物学的酶动力学应该理想地产生关于酶在体内条件下的活性的信息，包括底物协同性、可逆性和变构性等反应特征，并且适用于具有多种底物的酶促反应。文献中的大量酶动力学数据是基于单底物Michaelis-Menten方程，其对酶反应做出了不自然的假设（例如，不可逆性），因此其在系统生物学模型中的应用受到限制。为了克服这一限制，我们利用NMR时程数据在一个结合的理论和实验方法参数化的通用可逆希尔方程，这是能够描述酶反应的所有上述属性，并具有更少的参数比详细的机械动力学方程;这些参数，而且定义操作。传统上，酶动力学数据已从初始速率研究中获得，通常使用与NAD（P）H产生或NAD（P）H消耗反应偶联的测定。然而，这些测定是非常劳动密集型的，特别是对于多底物反应的详细表征。在这里，我们提出了一个具有成本效益的和相对快速的方法，从代谢产物的时间过程中产生的数据，使用NMR光谱获得酶动力学参数。该方法需要更少的运行比传统的初始速率的研究，并产生更多的信息，每个实验，整个时间过程进行分析，并用于参数拟合。此外，该方法允许实时同时定量测定系统中存在的所有代谢物（包括产物和变构改性剂），这证明了NMR优于传统的分光光度偶联酶测定。所提出的方法适用于阐明两个耦合的糖酵解酶从大肠杆菌（磷酸葡萄糖异构酶和磷酸果糖激酶）的动力学参数。通过将细胞提取物与不同初始浓度的底物、产物和改性剂一起孵育来收集31 P-NMR时程数据。随后使用以Python编程语言编写的定制软件模块处理NMR动力学数据，并将其整体拟合至适当修改的Hill方程。
Enzyme kinetics for systems biology should ideally yield information about the enzyme’s activity under in vivo conditions, including such reaction features as substrate cooperativity, reversibility and allostery, and be applicable to enzymatic reactions with multiple substrates. A large body of enzyme-kinetic data in the literature is based on the uni-substrate Michaelis-Menten equation, which makes unnatural assumptions about enzymatic reactions (e.g., irreversibility), and its application in systems biology models is therefore limited. To overcome this limitation, we have utilised NMR time-course data in a combined theoretical and experimental approach to parameterize the generic reversible Hill equation, which is capable of describing enzymatic reactions in terms of all the properties mentioned above and has fewer parameters than detailed mechanistic kinetic equations; these parameters are moreover defined operationally. Traditionally, enzyme kinetic data have been obtained from initial-rate studies, often using assays coupled to NAD(P)H-producing or NAD(P)H-consuming reactions. However, these assays are very labour-intensive, especially for detailed characterisation of multi-substrate reactions. We here present a cost-effective and relatively rapid method for obtaining enzyme-kinetic parameters from metabolite time-course data generated using NMR spectroscopy. The method requires fewer runs than traditional initial-rate studies and yields more information per experiment, as whole time-courses are analyzed and used for parameter fitting. Additionally, this approach allows real-time simultaneous quantification of all metabolites present in the assay system (including products and allosteric modifiers), which demonstrates the superiority of NMR over traditional spectrophotometric coupled enzyme assays. The methodology presented is applied to the elucidation of kinetic parameters for two coupled glycolytic enzymes from Escherichia coli (phosphoglucose isomerase and phosphofructokinase). 31P-NMR time-course data were collected by incubating cell extracts with substrates, products and modifiers at different initial concentrations. NMR kinetic data were subsequently processed using a custom software module written in the Python programming language, and globally fitted to appropriately modified Hill equations.