Proteomic Analysis of Synaptic Vesicle Pools

描述（由申请人提供）：突触传递领域的经典研究假设神经递质释放发生在突触囊泡的生物化学同质群体中，但许多实验系统的大量工作表明，突触囊泡属于对刺激反应不同的池。这些观察结果产生了两个相互竞争的假设，一个是池是生化相同的，在行为上的差异严格随机的，或外在的，反映了差异与细胞骨架或以前的历史，而不是任何内在的差异组成。或者，分子组成的差异是不同突触囊泡池行为的基础，最近的研究表明，这些池在回收后可能会保持其身份。虽然存在争议，但我们最近发现不同的突触囊泡蛋白对刺激的反应不同，这为突触囊泡池的组成不同提供了一些初步证据。然而，这些实验涉及单个报告构建体的光学成像，并且理解膜蛋白组成如何决定突触囊泡的性质需要更系统的方法。因此，我们将标记特定的突触囊泡池与磁性纳米粒子严格的基础上，他们对活动的反应，并确定其组成的定量蛋白质组学分析：目的1：优化突触囊泡恢复高度纯化的突触神经元。标准程序无法恢复与质膜相关的突触囊泡，因此我们将使用物理和化学方法的组合来优化突触囊泡从突触神经体的恢复。目的2：优化在刺激过程中用磁性纳米颗粒标记的突触囊泡的分离。我们将合成小的磁性纳米颗粒，并通过不同的刺激模式优化不同突触囊泡池的标记。目标3：通过定量蛋白质组学，使用同量异位素标签进行相对和绝对定量（iTRAQ）或哺乳动物稳定同位素标记（SILAM），确定再循环和静息突触囊泡池的组成。识别不同突触囊泡池的分子组成将为未来研究所识别的组分在递质释放、突触发育和可塑性中的功能提供基础。

DESCRIPTION (provided by applicant): Classical studies in the field of synaptic transmission have assumed that neurotransmitter release occurs from a biochemically homogeneous population of synaptic vesicles, but considerable work from many experimental systems has shown that synaptic vesicles belong to pools that differ in their response to stimulation. These observations have given rise to two competing hypotheses, one that the pools are biochemically the same, with differences in behavior strictly stochastic, or extrinsic, reflecting differential association with the cytoskeleton or prior history rather than any intrinsic differences in composition. Alternatively, differences in molecular composition underlie the behavior of different synaptic vesicle pools, and recent work has suggested that the pools may retain their identity after recycling. Although controversial, we have recently shown that different synaptic vesicle proteins respond differently to stimulation, providing some of the first evidence that synaptic vesicle pools differ in composition. However, these experiments involved optical imaging of individual reporter constructs, and understanding how membrane protein composition determines the properties of synaptic vesicles requires a more systematic approach. We will thus label specific synaptic vesicle pools with magnetic nanoparticles strictly on the basis of their response to activity, and determine their composition by quantitative proteomic analysis: Aim 1: Optimize synaptic vesicle recovery from highly purified synaptoneurosomes. Standard procedures fail to recover synaptic vesicles associated with the plasma membrane, so we will optimize synaptic vesicle recovery from synaptoneurosomes using a combination of physical and chemical approaches. Aim 2: Optimize isolation of synaptic vesicles labeled with magnetic nanoparticles during stimulation. We will synthesize small magnetic nanoparticles, and optimize the labeling of different synaptic vesicle pools by different patterns of stimulation. Aim 3: Determine the composition of recycling and resting synaptic vesicle pools by quantitative proteomics using isobaric tag for relative and absolute quantitation (iTRAQ) or stable isotope labeling in mammals (SILAM). Identifying the molecular composition of different synaptic vesicle pools will provide a foundation for future work to explore the functin of the identified components in transmitter release, synapse development and plasticity.