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中文摘要
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描述(由申请人提供):本研究的长期目标是使用量子点(qdots)进行单粒子跟踪,以进一步了解SNARE蛋白在神经元膜融合中的作用。突触前融合是囊泡运输的关键步骤,并且囊泡运输涉及重要神经递质如多巴胺和其他在信号传导和发育中重要的分泌激素的递送。对突触前融合的进一步了解将有助于更好地理解囊泡运输,从而更好地理解抑郁症和成瘾等神经精神疾病的病理生理学。此外,理解SNARE的功能甚至可能导致设计更好的药物/治疗,因为人们设想将SNARE用于融合增强的靶向药物递送。将进行量子点的单粒子追踪(SPT)以研究t-SNARE在具有筏形成脂质的支撑双层膜上的横向扩散,以解决最近几项研究中涉及t-SNARE的相偏好的不一致观察结果。首先将进行原理验证实验,以优化实验设计和设置,并确定使用量子点进行单粒子跟踪的功效。量子点共轭脂质的SPT将用于研究脂质在支持的均质双层和具有筏形成脂质的异质双层中的扩散。t-SNARE扩散在支持异质双层,然后将使用量子点共轭SNARE的SPT研究。将使用不同摩尔分数的t-SNARE和不同的筏形成脂质混合物,并且将使用累积分布函数来拟合数据以揭示多组分扩散行为。
英文摘要
DESCRIPTION (provided by applicant): The long range goal for this research is to perform single particle tracking with quantum dots (qdots) to further our understanding of the role of SNARE proteins in neuronal membrane fusion. Presynaptic fusion is a key step in vesicle transport, and vesicle transport is involved in the delivery of vital neurotransmitters such as dopamine and other secretory hormones that are important in signaling and development. Further understanding of presynaptic fusion will enable better understanding of vesicle transport and thus the pathophysiology of neuropsychiatric conditions such as depression and addiction. In addition, understanding the functioning of SNAREs may even lead to the design of better drugs/therapy as one envisions enlisting SNAREs for fusion-enhanced targeted drug delivery Single particle tracking (SPT) of qdots will be performed to study the lateral diffusion of t-SNAREs on supported bilayer membranes with raft-forming lipids to address the inconsistent observations involving the phase preference for t-SNAREs in several recent studies. Proof-of-principle experiments will first be performed to optimize the experimental design and setup and to ascertain the efficacy of using qdots for single particle tracking. SPT of qdot-conjugated lipid will be used to study lipid diffusion in supported homogenous bilayers and heterogeneous bilayers with raft-forming lipids. t-SNARE diffusion in supported heterogenous bilayers will then be studied using SPT of qdot-conjugated SNAREs. Different mole fractions of t-SNAREs and different raft-forming lipid mixtures will be used, and cumulative distribution function will be used to fit the data to reveal multi-component diffusive behavior.
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