Analysis of the cellular secretome by targeted subcellular proteomics

描述(申请人提供)：分泌蛋白在细胞间通讯中发挥重要作用，并控制几个生理过程。因此，鉴定细胞分泌的蛋白质具有重要的意义。传统的分泌组学方法通常依赖于细胞培养上清液的质谱分析。然而，细胞培养液中分泌蛋白的低丰度(信号)和血清蛋白的高浓度(噪声)构成了一个巨大的挑战。无血清培养液的使用缓解了低信噪比问题，但反过来又会影响细胞生理。此外，细胞培养系统不能有效地在体内复制细胞的微环境。在这里，我们提出了一种替代的分泌组分析策略来克服这些问题-针对富含分泌小泡的亚细胞组分的MS分析。分泌的蛋白质通过分泌小泡运输到细胞外部。我们建议建立一种免疫沉淀的方法来分离富含分泌小泡的亚细胞部分；随后，对这些样品进行MS分析将用于鉴定被困在分泌小泡中的分泌货物。因此，在目标1中，我们将产生结合蛋白，可用于通过类似免疫沉淀的程序从细胞裂解物中分离分泌囊泡。在目标2中，我们将进行MS分析，以确定分离的粘合剂的蛋白质靶标 目的1.我们还将对使用这些结合蛋白从hESCs中分离的亚细胞组分进行MS分析；我们希望严格验证这种方法确实可以用于细胞分泌体的分析。最后，在目标3中，我们将研究我们的方法是否可以用于从动物癌症模型获得的冷冻组织的分泌学分析。我们期待我们在该项目中开发的实验和试剂的结果将具有广泛的适用性，特别是在干细胞生物学和肿瘤生物标记物发现方面。我们的策略可以在至少三种不能使用传统MS方法的场景中独特地实现分泌组分析：(I)研究细胞外线索(例如干细胞中的分化触发)的瞬时蛋白质分泌反应；(Ii)识别异质群体中细胞分泌的蛋白质，前提是可以分离目标细胞，例如使用免疫亲和方法；以及(Iii)从原始组织(例如从肿瘤活检获得的组织)进行分泌组分析。值得注意的是，这种方法与冷冻组织样本的兼容性将使现有的人类组织储存库能够用于发现疾病的分泌蛋白生物标记物。这反过来将允许开发用于疾病诊断的微创检测方法。

DESCRIPTION (provided by applicant): Secreted proteins play an important role in intercellular communication and control several physiological processes. Therefore identification of proteins secreted by a cell is of significant interest and importance. Conventional approaches to secretomics typically rely on mass spectrometry (MS) analysis of cell culture supernatants. However the low abundance of secreted proteins (signal) and high concentration of serum proteins (noise) in cell culture medium poses a significant challenge. The use of serum-free medium alleviates the low signal-to-noise problem but in turn can affect cellular physiology. Moreover, cell culture systems cannot effectively reproduce the microenvironment of cells in vivo. Here we propose an alternative strategy for secretome analysis to overcome these problems - targeted MS analysis of subcellular fractions enriched in secretory vesicles. Secreted proteins are transported to the cell exterior by secretory vesicles. We propose to develop an immunoprecipitation method for isolation of subcellular fractions enriched in secretory vesicles; subsequently, MS analysis of these samples will be used for identification of secretory cargo trapped in the secretory vesicles. Accordingly, in Aim 1, we will generate binding proteins that can be used to isolate secretory vesicles from cell lysates by an immunoprecipitation-like procedure. In Aim 2, we will conduct MS analysis to identify protein targets of binders isolated in Aim 1. We will also conduct MS analysis on subcellular fractions, isolated from hESCs using these binding proteins; we expect to rigorously validate that this approach can indeed be used for analysis of the cellular secretome. Finally, in Aim 3, we will investigate if our approach can be used for secretomic analysis of frozen tissues obtained from an animal cancer model. We expect that findings from our experiments and reagents developed in this project will have broad applicability, particularly in stem cell biology and tumor biomarker discovery. Our strategy can uniquely enable secretome analysis in at least three scenarios where traditional MS approaches cannot be employed: (i) to study the temporal protein secretion response to an extracellular cue, e.g. a differentiation trigger in stem cells, (ii) to identify proteins secreted by cells in a heterogeneous population provided the target cells can be isolated, e.g. using immunoaffinity methods, and (iii) secretome analysis from primary tissues such as those obtained from tumor biopsies. Notably, compatibility of this approach with frozen tissue samples will enable the use of existing human tissue repositories for discovery of secreted protein biomarkers of disease. This in turn will allow the development of minimally invasive assays for disease diagnosis.