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生物化学上均匀的突触囊泡群体中，但许多实验系统的大量工作表明突触囊泡属于对刺激的不同反应池。这些观察结果引起了两种相互竞争的假设，一种认为这些池在生物化学上是相同的，行为上的差异完全是随机的，或者是外在的，反映了与细胞骨架或先前历史的不同联系，而不是组成上的任何内在差异。另外，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，这些池可能在循环后保持其特性。尽管存在争议，但我们最近表明，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结构的光学成像，并且了解膜蛋白组成如何决定突触囊泡的特性需要更系统的方法。因此，我们将严格根据它们对活性的反应，用磁性纳米颗粒标记特定的突触囊泡池，并通过定量蛋白质组学分析确定它们的组成。目的1：优化从高度纯化的突触体中恢复突触囊泡。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相结合的方法优化突触eurosomes的突触囊泡恢复。目的2：优化磁纳米颗粒标记突触囊泡在刺激过程中的分离。我们将合成小磁性纳米颗粒，并通过不同的刺激模式优化标记不同的突触囊泡池。目的3：通过定量蛋白质组学，利用相对和绝对定量等压标记（iTRAQ）或哺乳动物稳定同位素标记（SILAM），确定循环和静息突触囊泡池的组成。确定不同突触囊泡池的分子组成，将为进一步探索所鉴定组分在递质释放、突触发育和可塑性中的功能奠定基础。

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.