Surface Signatures of Neuronal and Glial Extracellular Vesicles

摘要 细胞外囊泡（EV）被认为是细胞与细胞之间的重要手段 中枢神经系统的通讯。人脑中的各种细胞都会分泌 电动汽车可能具有不同的功能。研究不同类型的电动汽车及其 在健康大脑和神经系统疾病中的作用需要可靠的方法来捕获 这些颗粒来自容易接触的体液，如血液。我们的目标是开发一种新方法 根据其表面存在的分子捕获特定类型的电动汽车。我们的 假设我们可以利用表面上存在的两个或多个特定分子 EV 来选择由特定细胞类型分泌的 EV。 MSD 此前已开发出高效、高灵敏度的 EV 筛查方法 以确定其表面上存在的蛋白质的组合。我们将使用这些方法 以及我们在国家老龄化研究所的合作者提供的样本，以识别 中央四种最常见细胞类型的特定表面标记特征 神经系统。 我们将开发一种新方法，利用这些表面标记来捕获电动汽车 签名。这种方法只会捕获具有所有目标表面的电动汽车 标记，应该大大提高捕获特异性，从而解决主要问题之一 现有 CNS EV 隔离方法的缺点。更高的特异性将能够实现更多 与目前进行的研究相比，对每种 CNS 细胞类型的 EV 进行了有针对性的研究。 我们将使用这种方法来确定哪些人体生物体液可以作为 EV 的可靠来源 中枢神经系统并估计外周体内每种类型 EV 的水平 液体。 我们还将测量 EV 中所含的蛋白质，这需要 异常灵敏的测定。我们最近将超灵敏免疫分析与 EV- 特定的捕获方法能够准确测量特定的 EV 货物蛋白。我们 将检测 EV 货物中四种 CNS 细胞类型中每种的特异性蛋白质，以帮助确认 分离的 EV 的细胞起源。我们还将测量已知的 EV 相关生物标志物 对患者样本中的阿尔茨海默病进行分析，以确定它们富含哪些 EV 类型 看看测量特定类型电动汽车中的生物标志物是否会增加其 预测能力。 最后，我们计划开发 EV 分离和货物蛋白的全自动版本 化验。这将使从数百个样品中快速可靠地制备 EV 样品成为可能。 一次采样，允许目前不可能或太耗时的研究 消费要划算。

Abstract Extracellular vesicles (EVs) are believed to be an important means of cell-to-cell communication in the central nervous system. Various types of cells in the human brain secrete EVs, which are each likely to have distinct functions. Studying different types of EVs and their roles in the healthy brain and in neurological disease requires a reliable means of capturing these particles from readily accessible body fluids, like blood. Our goal is to develop a new way to capture specific types of EVs based on the molecules present on their surfaces. Our hypothesis is that we can use the presence of two or more specific molecules on the surface of an EV to select EVs secreted by a particular cell type. MSD has previously developed efficient and highly sensitive methods for screening EVs to determine combinations of proteins present on their surfaces. We will use these methods along with samples provided by our collaborators at the National Institute on Aging to identify specific surface-marker signatures for each of the four most common types of cells in the central nervous system. We will develop a new approach to capturing EVs with each of these surface marker signatures. This approach, which will only capture the EVs having all of the targeted surface markers, should greatly improve the capture specificity, thus addressing one of the main shortcomings of the existing CNS EV isolation methods. Greater specificity will enable more targeted studies of the EVs from each CNS cell type than those that are presently performed. We will use this approach to determine which human biofluids can be a reliable source of EVs from the central nervous system and to estimate the level of each type of EV in peripheral body fluids. We will also measure the proteins contained within the EVs, something that requires exceptionally sensitive assays. We recently combined ultrasensitive immunoassays with EV- specific capture methods to enable accurate measurement of specific EV cargo proteins. We will assay the EV cargo for proteins specific to each of the four CNS cell types to help confirm the cellular origin of the isolated EVs. We will also measure known EV-associated biomarkers of Alzheimer’s disease in patient samples to determine in which EV types they are enriched and to see whether measuring the biomarker within a particular type of EV might increase its predictive power. Lastly we plan to develop a fully automated version of the EV isolation and cargo protein assays. This will enable rapid and reliable preparation of EV samples from hundreds of samples at a time, allowing studies that presently would be either impossible or too time- consuming to be cost-effective.