Quantitative Characterization of Glycopeptide Isomers

由于迫切需要全面了解糖基化的生物学属性 许多关键的生物学功能，如免疫反应、细胞发育、细胞 分化/黏附和宿主-病原体的相互作用，糖蛋白质组学继续是一个高度动态的 研究领域。此外，几十年来异常的糖基化被认为是许多 哺乳动物疾病，包括骨关节炎、囊性纤维化和癌症。多聚糖的多种生物学作用 它们在疾病中的意义产生了对可靠的基于MS的糖蛋白组学方法的需求， 允许对生物系统中的糖蛋白进行灵敏监测。我们在这里提出三个具体的建议 目的：目的：1.多孔石墨柱分离和结构鉴定糖肽 高温耦合柱后酶反应器；目的2.双代谢稳定同位素标记 细胞培养中的糖蛋白(DSILGC)；以及目标3。开发软件工具，用于自动识别和 糖肽的定量。这些目标的结果将是促进明确的 生物相关糖蛋白异构体微异质性的定量评价 样本。这一建议的创新之处在于所提出的分析方法的独特性 和软件。一种创新的高温PGC分离糖肽异构体的方法 在我们实验室开发的，允许分离与蛋白质糖基化相关的所有糖链异构体。 尽管其他人已经证明了酶反应，但它们通常用于蛋白质消化或多糖。 释放中。据我们所知，这是第一次柱后反应器与MS对接 提出了糖肽同分异构体结构的表征(目标1)。同步双稳定同位素 我们在这里提出的蛋白质和多糖的标记将使糖组分的同时分析成为可能， 蛋白质组学和糖蛋白组学，更准确和有效的定量(目标2)。来自生物信息学 从观点来看，我们的项目有几个新的方面(目标3)。基于HCD/CID的糖链测序算法 糖肽的光谱报告了全部(或当MS/MS中缺少某些碎片离子时的部分) 光谱)糖链的拓扑结构(除了键)，而不仅仅是单糖组合物 上述方法均可澄清。此外，我们的算法可以潜在地识别新的糖链 结构，因为它不依赖于先前已知的多糖结构。更重要的是，糖链测序 算法为肽鉴定提供了补充信息(例如，从脱糖基化的CID谱 多肽或ETD。该提案的可交付成果是：(I)现成的分析方法， 适用于定量表征和分离糖肽异构体，且价格合理；(Ii)开放源码 允许自动解释、注释和定量来自以下来源的糖肽异构体的软件 生物样本。预计拟议的技术将使人们能够更好地了解生物 糖蛋白在食道癌、乳腺癌和肝癌发生发展中的属性。

Because of the pressing needs to comprehensively understand the biological attributes of glycosylation in many critical biological functions such as the immune response, cell development, cellular differentiation/adhesion and host-pathogen interactions, glycoproteomics continues to be a highly dynamic research area. Moreover, aberrant glycosylation for decades has been recognized as the attribute of many mammalian diseases, including osteoarthritis, cystic fibrosis, and cancer. The diverse biological roles of glycans and their implications in diseases have created a demand for reliable MS-based glycoproteomic approaches, permitting sensitive monitoring of glycoproteins in biological systems. We are proposing here three specific aims: Aim 1. Isomeric separation and structural identification of glycopeptides by porous graphitic columns at high temperatures coupled to post-column enzyme reactor; Aim 2. Double metabolic Stable Isotope Labeling of Glycoproteins in Cell cultures (DSILGC); and Aim 3. Develop software tools for automated identification and quantitation of glycopeptides. The outcome of these aims will be technologies that facilitate the unequivocal quantitative assessment of the isomeric microheterogenieties of glycoproteins associated with biological samples. The innovations of this proposal originate from the uniqueness of the proposed analytical methods and software. Isomeric separation of glycopeptides on PGC at high temperatures, a highly innovative method developed in our laboratory, permits the separation of all glycan isomers associated with protein glycosylation. Although enzyme reactors have been demonstrated by others, they usually used for protein digestion or glycan releasing. To our best knowledge, it is the first time a post-column reactor interfacing with MS for the characterization of isomeric glycopeptide structures is proposed (Aim 1). The simultaneous double stable isotope labeling of both proteins and glycans that we propose here will enable simultaneous analysis of glycomics, proteomics, and glycoproteomics with more accurate and effective quantitation (Aim 2). From the bioinformatics point of view, our project has several novel aspects (Aim 3). Our glycan sequencing algorithm based on HCD/CID spectra of glycopeptides reports the whole (or partial when some fragment ions are missing in the MS/MS spectra) topology of glycan (except linkages) instead of only the monosaccharide compositions that abovementioned methods can elucidate. Additionally, our algorithm can potentially identify new glycan structures, since it does not rely on previously known glycan structures. More importantly, the glycan sequencing algorithm provides complementary information to peptide identification (e.g., from CID spectra of de-glycosylated peptides or the ETD. The deliverables of this proposal are (i) analytical methods that are readily available, adaptable, and affordable to quantitively characterize and separate glycopeptide isomers and (ii) open-source software that allows automated interpretation, annotation, and quantitation of glycopeptide isomers derived from biological samples. The proposed technologies are expected to enable a better understanding of the biological attributes of glycoproteins in the development and progression of esophagus, breast and liver cancers.