Methods for measuring matrisome molecule similarity during disease processes

项目摘要/摘要： 该应用程序响应NIGMS PAR-19-367“最大化调查人员研究奖(R35-临床)” 试用版(可选)“ 我的研究小组最初专注于糖胺多聚糖(GAG)的分析方法。这些线性的， 硫酸多糖附着在细胞表面蛋白多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作用是 动物生理学的核心，包括细胞信号、细胞微环境和宿主- 寄主，以及寄主-病原体识别。我的团队开发了液-质联用的方法 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Tandem MS数据的生物信息学程序。然后，我们开创了各种方法来 从生物组织载玻片中获取糖组分(GAG和N-葡聚糖)和蛋白质组学。我们用了这些 方法对神经衰老、癌症、神经发育和神经退行性疾病进行研究。 由NIGMS R01GM133963《糖蛋白糖基化相似性测定方法》资助 在疾病状态中，我的团队正在开发分析和生物信息学方法，用于糖蛋白组学 大脑的细胞外基质分子(称为母体)。主要的关注点是 糖蛋白组学、MS获取方法和生物信息学用于分子的严格统计测定 母体分子的相似性以及在正常衰老和疾病过程中这些分子是如何变化的。 我现在建议扩大我们的脑糖蛋白质组分子相似性范围，以包括 修饰特定的母体分子的口香糖。我们的目标将是提供有关 传统抗体检测不到的基质分子的病理生理变化 检测方法。我们将使用一个新的Omnitrap平台来表征多个糖基化多肽和 用Gag链修饰的多肽。我们还将利用离子迁移率的能力来测量分子 与使用Waters环离子迁移率-质谱仪的糖蛋白组学数据的相似性。我们 将通过比较大脑区域之间的母体分子相似性和作为一种 年龄的作用。

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.