大肠杆菌JM101在氧化应激状态下代谢流量分配的内在机制
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摘要
在超氧化物氧化应激条件下,细菌细胞会产生适应性的反应,我们建立了一个大肠杆菌的细胞模型,通过对于氧化应激现象的研究进一步探讨了细胞是如何适应外界恶劣的环境变化的。超氧化物能促进产生对菌体自体代谢来说过多的活性氧自由基(ROS),过量的活性氧自由基会对细胞代谢及其它生理活动会产生不利的影响。为了消除这种不利的影响,细胞需要以一种适当的方式来调节一系列的代谢反应,使得细胞的代谢反应网络能在一个整体的水平上产生相应的代谢应激。
~(13)C标记代谢通量分析方法(MFA)经常被用来跟踪细菌,酵母,丝状真菌和动物细胞体内的中心碳代谢中的细胞内代谢通量。碳-13标记的代谢物可以在整个代谢系统中被追踪和监控,它们在某些代谢产物的分配可以由二维核磁共振(2D NMR)或用气相色谱/质谱法(GC– MS)的测定。依据这些测量值,细胞内的碳通量可以通过参数拟合程序进行估算。在我们的实验中,我们使用的是13C -通量软件来估算最优的流量值,流量值的90%的置信度区间则是用蒙特卡罗抽样方法计算的。
在研究中,我们使用MFA的方法用来研究的是大肠杆菌JM101暴露于百草枯(PQ)时的氧化应激状况,百草枯(PQ)是氧化应激的一个诱导剂。我们将野生型大肠杆菌JM101细胞分别在正常培养基和含PQ的培养基中进行恒化培养,在进行对两种状况下的一些基本生长参数和代谢产物的生成参数比较后,我们用稳定状态下的13C流量分析方法确定在中心碳代谢网络中的代谢流的分布变化情况。模型中的代谢网络途径包括糖酵解途径、磷酸戊糖途径、三羧酸循环、回补反应和乙醛酸支路以及ED途径。
在研究中,我们不仅使用了定量的代谢通量分析方法,而且同时测量了代谢中关键酶的基因表达量和它们的活性,以研究大肠杆菌细胞为适应被超氧化物—百草枯(PQ)所诱导的氧化应激现象时,菌体内中心碳代谢所发生的一系列变化情况,同时对所观察到的整体流量变化相关的细胞调节机制进行了深入的探讨。
我们的流量分析是基于核磁共振(NMR)及质谱(MS)的测量结果和计算机模拟的定量结果,从而分析当大肠杆菌处于百草枯诱导的氧化应激条件下时碳中心代谢流重新发生分配的情况的。糖酵解途径(EMP pathway)的代谢通量被重新导向到磷酸戊糖途径(PP pathway)。在氧化应激状态下,乙酸量明显地增加,与此同时TCA循环相关的通量下降,而在乙醛酸支路中的通量又增加。这些整体水平上的通量变化导致了NADPH:NADH的增加和α-酮戊二酸量的积累。
The cellular responses of bacteria to superoxide stress can be used to model adaptation to severe environmental changes. Superoxide stress promotes the excessive production of reactive oxygen species (ROS) that have detrimental effects on cell metabolic and other physiological activities. To antagonize such effects, the cell needs to regulate a range of metabolic reactions in a coordinated way, so that coherent metabolic responses are generated by the cellular metabolic reaction network as a whole. In the present study, we have used a quantitative metabolic flux analysis approach, together with measurement of gene expression and activity of key enzymes, to investigate changes in central carbon metabolism that occur in Escherichia coli in response to paraquat-induced superoxide stress. The cellular regulatory mechanisms involved in the observed global flux changes are discussed.
Metabolic flux analysis (MFA) using 13C labeling has been frequently used to follow the intracellular fluxes in the central metabolism in bacteria, yeast, filamentous fungi, and animal cells. 13C-labeled metabolites can be monitored throughout the metabolic system and their distribution in certain metabolites can be measured either by two-dimensional nuclear magnetic resonance (2D NMR) or by gas chromatography/mass spectrometry (GC-MS). From these measurements, intracellular fluxes can then be estimated by parameter fitting procedures. The 13C-FLUX software was used for estimation of optimal flux values and 90% confidence intervals of flux values were calculated by Monte Carlo sampling method.
In the present study, we used MFA to investigate the metabolic response of E. coli exposed to paraquat (PQ), a known inducer of oxidative stress. We have cultivated wild type E. coli cells in the normal minimum medium and in a PQ-containing one using chemostat cultivations. After comparing some general growth parameters and metabolite production parameters under the two conditions, we have used steady state 13C flux analysis to determine the metabolic flux distributions in the central carbon metabolism network. The network comprises the Embden-Meyerhof pathway (EMP), the pentose phosphate (PP) pathway, the Entner Dourodouf (ED) pathway, the tricarboxylic acid cycle (TCA cycle), the anaplerotic reaction, and the glyoxylate shunt.
Flux analysis based on nuclear magnetic resonance (NMR) and mass spectroscopy (MS) measurements and computation provided quantitative results on the metabolic fluxes redistribution of the E. coli central carbon network under paraquat-induced oxidative stress. The metabolic fluxes of the glycolytic pathway were redirected to the pentose phosphate pathway (PP pathway). The production of acetate increased significantly, the fluxes associated with the TCA cycle decreased, and the fluxes in the glyoxylate shunt increased in response to oxidative stress. These global flux changes resulted in an increased ratio of NADPH:NADH and in the accumulation ofα-ketoglutarate.
We have quantified a range of changes that occur in metabolic carbon flux during PQ stress in E. coli. These changes are, to a large extent, coherent and lead to systematic adjustments of cellular physiological states. One major adjustment is the increased NADPH generation and decreased NADH generation. This reflects a cellular strategy whereby efficiency is traded for survival under stressful conditions. Our results provide direct data of specific changes in the metabolic fluxes leading to such systematic changes, and suggest that global redistributions of metabolic fluxes upon superoxide exposure may have been achieved through the regulation of key enzyme expression/activities.
More generally, our study provide an example in which metabolic flux analyses present direct measurements of the physiological states of cells, while gene expression and proteomics studies measure the molecular states. In complex systems such as the metabolic networks, the different molecular processes that eventually determine the physiological states are tightly coupled to each other; i.e., there may not always be simple, process-by-process correspondence between changes in the physiological states and in the molecular states of cells. For instance, we have seen that the reduced akd flux is associated with the inactivation, but not the reduced expression, of AKGDH. Occasionally, reduced fluxes are found with unchanged or even increased expression of the respective genes and/or activities of associated enzymes (for example, the pgi step and the associated PGI enzyme). These types of results highlight the important complementarity between different types of systems level approaches. Used together, these approaches can provide comprehensive and undistorted pictures of how microorganisms respond to oxidative stress or other drastic environmental challenges.
Metabolic flux analysis provided a quantitative and global picture of responses of the E. coli central carbon metabolic network to oxidative stress. Systematic adjustments of cellular physiological state clearly occurred in response to changes in metabolic fluxes induced by oxidative stress. Quantitative flux analysis therefore could reveal the physiological state of the cell at the systems level and is a useful complement to molecular systems approaches, such as proteomics and transcription analyses.
~(13)C标记代谢通量分析方法(MFA)经常被用来跟踪细菌,酵母,丝状真菌和动物细胞体内的中心碳代谢中的细胞内代谢通量。碳-13标记的代谢物可以在整个代谢系统中被追踪和监控,它们在某些代谢产物的分配可以由二维核磁共振(2D NMR)或用气相色谱/质谱法(GC– MS)的测定。依据这些测量值,细胞内的碳通量可以通过参数拟合程序进行估算。在我们的实验中,我们使用的是13C -通量软件来估算最优的流量值,流量值的90%的置信度区间则是用蒙特卡罗抽样方法计算的。
在研究中,我们使用MFA的方法用来研究的是大肠杆菌JM101暴露于百草枯(PQ)时的氧化应激状况,百草枯(PQ)是氧化应激的一个诱导剂。我们将野生型大肠杆菌JM101细胞分别在正常培养基和含PQ的培养基中进行恒化培养,在进行对两种状况下的一些基本生长参数和代谢产物的生成参数比较后,我们用稳定状态下的13C流量分析方法确定在中心碳代谢网络中的代谢流的分布变化情况。模型中的代谢网络途径包括糖酵解途径、磷酸戊糖途径、三羧酸循环、回补反应和乙醛酸支路以及ED途径。
在研究中,我们不仅使用了定量的代谢通量分析方法,而且同时测量了代谢中关键酶的基因表达量和它们的活性,以研究大肠杆菌细胞为适应被超氧化物—百草枯(PQ)所诱导的氧化应激现象时,菌体内中心碳代谢所发生的一系列变化情况,同时对所观察到的整体流量变化相关的细胞调节机制进行了深入的探讨。
我们的流量分析是基于核磁共振(NMR)及质谱(MS)的测量结果和计算机模拟的定量结果,从而分析当大肠杆菌处于百草枯诱导的氧化应激条件下时碳中心代谢流重新发生分配的情况的。糖酵解途径(EMP pathway)的代谢通量被重新导向到磷酸戊糖途径(PP pathway)。在氧化应激状态下,乙酸量明显地增加,与此同时TCA循环相关的通量下降,而在乙醛酸支路中的通量又增加。这些整体水平上的通量变化导致了NADPH:NADH的增加和α-酮戊二酸量的积累。
The cellular responses of bacteria to superoxide stress can be used to model adaptation to severe environmental changes. Superoxide stress promotes the excessive production of reactive oxygen species (ROS) that have detrimental effects on cell metabolic and other physiological activities. To antagonize such effects, the cell needs to regulate a range of metabolic reactions in a coordinated way, so that coherent metabolic responses are generated by the cellular metabolic reaction network as a whole. In the present study, we have used a quantitative metabolic flux analysis approach, together with measurement of gene expression and activity of key enzymes, to investigate changes in central carbon metabolism that occur in Escherichia coli in response to paraquat-induced superoxide stress. The cellular regulatory mechanisms involved in the observed global flux changes are discussed.
Metabolic flux analysis (MFA) using 13C labeling has been frequently used to follow the intracellular fluxes in the central metabolism in bacteria, yeast, filamentous fungi, and animal cells. 13C-labeled metabolites can be monitored throughout the metabolic system and their distribution in certain metabolites can be measured either by two-dimensional nuclear magnetic resonance (2D NMR) or by gas chromatography/mass spectrometry (GC-MS). From these measurements, intracellular fluxes can then be estimated by parameter fitting procedures. The 13C-FLUX software was used for estimation of optimal flux values and 90% confidence intervals of flux values were calculated by Monte Carlo sampling method.
In the present study, we used MFA to investigate the metabolic response of E. coli exposed to paraquat (PQ), a known inducer of oxidative stress. We have cultivated wild type E. coli cells in the normal minimum medium and in a PQ-containing one using chemostat cultivations. After comparing some general growth parameters and metabolite production parameters under the two conditions, we have used steady state 13C flux analysis to determine the metabolic flux distributions in the central carbon metabolism network. The network comprises the Embden-Meyerhof pathway (EMP), the pentose phosphate (PP) pathway, the Entner Dourodouf (ED) pathway, the tricarboxylic acid cycle (TCA cycle), the anaplerotic reaction, and the glyoxylate shunt.
Flux analysis based on nuclear magnetic resonance (NMR) and mass spectroscopy (MS) measurements and computation provided quantitative results on the metabolic fluxes redistribution of the E. coli central carbon network under paraquat-induced oxidative stress. The metabolic fluxes of the glycolytic pathway were redirected to the pentose phosphate pathway (PP pathway). The production of acetate increased significantly, the fluxes associated with the TCA cycle decreased, and the fluxes in the glyoxylate shunt increased in response to oxidative stress. These global flux changes resulted in an increased ratio of NADPH:NADH and in the accumulation ofα-ketoglutarate.
We have quantified a range of changes that occur in metabolic carbon flux during PQ stress in E. coli. These changes are, to a large extent, coherent and lead to systematic adjustments of cellular physiological states. One major adjustment is the increased NADPH generation and decreased NADH generation. This reflects a cellular strategy whereby efficiency is traded for survival under stressful conditions. Our results provide direct data of specific changes in the metabolic fluxes leading to such systematic changes, and suggest that global redistributions of metabolic fluxes upon superoxide exposure may have been achieved through the regulation of key enzyme expression/activities.
More generally, our study provide an example in which metabolic flux analyses present direct measurements of the physiological states of cells, while gene expression and proteomics studies measure the molecular states. In complex systems such as the metabolic networks, the different molecular processes that eventually determine the physiological states are tightly coupled to each other; i.e., there may not always be simple, process-by-process correspondence between changes in the physiological states and in the molecular states of cells. For instance, we have seen that the reduced akd flux is associated with the inactivation, but not the reduced expression, of AKGDH. Occasionally, reduced fluxes are found with unchanged or even increased expression of the respective genes and/or activities of associated enzymes (for example, the pgi step and the associated PGI enzyme). These types of results highlight the important complementarity between different types of systems level approaches. Used together, these approaches can provide comprehensive and undistorted pictures of how microorganisms respond to oxidative stress or other drastic environmental challenges.
Metabolic flux analysis provided a quantitative and global picture of responses of the E. coli central carbon metabolic network to oxidative stress. Systematic adjustments of cellular physiological state clearly occurred in response to changes in metabolic fluxes induced by oxidative stress. Quantitative flux analysis therefore could reveal the physiological state of the cell at the systems level and is a useful complement to molecular systems approaches, such as proteomics and transcription analyses.
引文
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