Methods for measuring matrisome molecule similarity during disease processes

项目概要/摘要： 该应用程序响应NIGMS PAR-19-367“最大化研究者研究奖（R35 -临床 试用可选）” 我的研究小组最初专注于糖胺聚糖（GAG）的分析方法。这些线性的， 硫酸化多糖附着在细胞表面上发现的蛋白聚糖分子的丝氨酸残基上， 在细胞内颗粒和细胞外基质中。GAG和蛋白质之间的结合相互作用是 对动物生理学的各个方面至关重要，包括细胞信号传导、细胞微环境和宿主- 宿主和宿主-病原体识别。我的团队开发了液相色谱-质谱联用技术 GAG的光谱分析和测序，从湿组织和组织载玻片中提取GAG，以及 用于解释GAG MS和串联MS数据的生物信息学程序。然后，我们开创了一种方法， 从生物标本组织切片中获取糖组学（GAG和N-聚糖）和蛋白质组学。我们应用这些 神经老化、癌症、神经发育和神经退行性疾病的研究方法。 根据NIGMS R 01 GM 133963“糖蛋白糖基化相似性测定方法”的资助 在疾病状态中，我的小组正在开发糖蛋白质组学的分析和生物信息学方法， 脑的细胞外基质分子（称为基质体）。主要重点是 糖蛋白质组学MS采集方法和生物信息学，用于分子的严格统计测定 相似之处的基质体分子，以及如何改变这些在正常老化与疾病的过程。 我现在建议扩大我们的大脑糖蛋白质组学分子相似性范围，包括表征 修饰特定基质体分子的GAG。我们的目标是提供有关 基质体分子的病理生理学变化，这些变化逃脱了使用传统的基于抗体的 检测方法我们将采用新的Omnitrap平台来表征多重糖基化肽， 用GAG链修饰的肽。我们还将利用离子迁移率的能力来测量分子 使用沃茨循环离子迁移率-质谱仪从糖蛋白组学数据中获得相似性。我们 将通过比较大脑区域之间的基质体分子相似性来展示这些方法，并作为一个 年龄的函数。

Project Summary/Abstract: The application responds to NIGMS PAR-19-367 “Maximizing Investigators' Research Award (R35 - Clinical Trial Optional)” My research group focused initially on analytical methods for glycosaminoglycans (GAGs). These linear, sulfated polysaccharides are attached to serine residues of proteoglycan molecules found on cellular surfaces, in intracellular granules and in extracellular matrices. Binding interactions between GAGs and proteins are central to aspects of animal physiology including cellular signaling, the cellular microenvironment, and host- host, and host-pathogen recognition. My group developed methods for liquid chromatography-mass spectrometry analysis and sequencing of GAGs, extraction of GAGs from wet tissue and tissue slides, and bioinformatics programs for interpretation of GAG MS and tandem MS data. We then pioneered methods to acquire glycomics (GAGs and N-glycans) and proteomics from biospecimen tissue slides. We applied these methods to study of neurological aging, cancer, neurodevelopmental, and neurodegenerative diseases. As funded through NIGMS R01GM133963 “Methods for determination of glycoprotein glycosylation similarities among disease states”, my group is developing analytical and bioinformatics methods for glycoproteomics of the extracellular matrix molecules (known as the matrisome) of brain. The primary focus has been on glycoproteomics MS acquisition methods and bioinformatics for rigorous statistical determination of molecular similarities for matrisome molecules and how these change during normal aging versus disease processes. I now propose to expand our brain glycoproteomics molecular similarity scope to include characterization of GAGs that modify specific matrisome molecules. Our goals will be to provide information on the pathophysiological changes to matrisome molecules that escape detection using traditional antibody-based detection methods. We will employ a new Omnitrap platform to characterize multiply glycosylated peptides and peptides modified with GAG chains. We will also exploit the capabilities of ion mobility for measuring molecular similarities from glycoproteomics data using a Waters Cyclic ion mobility-mass spectrometry instrument. We will demonstrate these approaches by comparing matrisome molecular similarity among brain regions and as a function of age.