Physiology-based kinetic modeling of neuronal energy metabolism unravels the molecular basis of NAD(P)H fluorescence transients
Physiology-based kinetic modeling of neuronal energy metabolism unravels the molecular basis of NAD(P)H fluorescence transients
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DOI：
10.1038/jcbfm.2015.70
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发表时间：
2015-09-01
影响因子：
6.3
通讯作者：
Holzhuetter, Hermann-Georg
中科院分区：
文献类型：
--
作者：
Berndt, Nikolaus;Kann, Oliver;Holzhuetter, Hermann-Georg
还原型烟酰胺腺嘌呤二核苷酸（磷酸）（NAD（P）H）的细胞荧光成像是少数几种代谢读数之一，可以无创和时间分辨地监测神经元组织中线粒体的功能状态。刺激诱导的NAD（P）H荧光强度的瞬时变化经常显示出受各种分子过程影响的双相特征，例如，细胞内钙动力学、三羧酸循环活性、苹果酸-天冬氨酸穿梭、甘油-3-磷酸穿梭、氧供应或三磷酸腺苷（ATP）需求。为了评估这些过程的相对影响，我们开发并验证了神经元细胞能量代谢的详细生理数学模型，并使用该模型来模拟刺激诱导的活动和葡萄糖，丙酮酸盐或乳酸盐的不同营养供应的不同设置下的单细胞和组织切片的代谢变化。值得注意的是，所有实验确定的NAD（P）H反应可以用一个相同的通用细胞模型再现。我们的计算表明，（1）代谢状态完全不同的细胞可能产生几乎相同的NAD（P）H反应，（2）相同类型的细胞可能对脑切片中记录的聚集NAD（P）H反应有完全不同的贡献，这取决于组织内的空间位置。我们的计算方法调和了不同的，有时甚至是有争议的实验结果，并提高了我们对活细胞NAD（P）H荧光瞬变的代谢变化的机械理解。
Imaging of the cellular fluorescence of the reduced form of nicotinamide adenine dinucleotide (phosphate) (NAD(P)H) is one of the few metabolic readouts that enable noninvasive and time-resolved monitoring of the functional status of mitochondria in neuronal tissues. Stimulation-induced transient changes in NAD(P)H fluorescence intensity frequently display a biphasic characteristic that is influenced by various molecular processes, e.g., intracellular calcium dynamics, tricarboxylic acid cycle activity, the malate-aspartate shuttle, the glycerol-3-phosphate shuttle, oxygen supply or adenosine triphosphate (ATP) demand. To evaluate the relative impact of these processes, we developed and validated a detailed physiologic mathematical model of the energy metabolism of neuronal cells and used the model to simulate metabolic changes of single cells and tissue slices under different settings of stimulus-induced activity and varying nutritional supply of glucose, pyruvate or lactate. Notably, all experimentally determined NAD(P)H responses could be reproduced with one and the same generic cellular model. Our computations reveal that (1) cells with quite different metabolic status may generate almost identical NAD(P)H responses and (2) cells of the same type may quite differently contribute to aggregate NAD(P)H responses recorded in brain slices, depending on the spatial location within the tissue. Our computational approach reconciles different and sometimes even controversial experimental findings and improves our mechanistic understanding of the metabolic changes underlying live-cell NAD(P)H fluorescence transients.