Glycosylation Analysis by Sheath-Flow SERS

项目摘要 蛋白质糖基化在多种人类疾病中发挥重要作用，包括癌症、炎症和 神经退行性疾病。因此，糖蛋白是疾病诊断、预后、 和治疗学。治疗蛋白的正确糖基化是最佳疗效和安全性所必需的。 然而，由于糖链变异的巨大复杂性，糖基化的分析是具有挑战性的。 目前最先进的技术是质谱仪(MS)，它已经成为一种强有力的方法 糖基化分析；然而，有几类多糖对MS分析提出了挑战，例如 具有相同质量的众多组分的单糖。 本项目致力于发展表面增强拉曼散射(SERS)作为在线检测方法 在小糖肽和释放的多糖水平上进行糖基化分析。这项提议充分利用了 将新型表面增强拉曼光谱检测器与化学分离相结合用于高灵敏度和高灵敏度的最新进展 有选择性的定性。已发表的结果成功地在线显示了分离、识别和 磷酸化单糖的定量，展示了SERS在 作为糖链和糖肽的碳水化合物的定性和定量分析。 该项目的具体目标如下： 目的1.证明鞘流动表面增强拉曼散射检测器在糖肽结构分析中的应用。 我们将使用一组结构相似的糖肽类似物来演示 SERS流动检测器用于糖肽的鉴定和定量。 目标2.定性和定量分析糖蛋白释放的多糖和多肽 LC-SERS。这一目标将为我们的SERS技术识别和识别和 定量复杂混合物中具有相似化学结构(例如同分异构体)的多糖和糖肽， 显示其作为MS的补充技术在全面糖基化方面的潜力 分析糖肽和释放的多糖的水平。 提供独特化学特定信息的新技术的发展将提供一种 增加糖蛋白质组覆盖率的替代工具，促进糖生物学的进展。

Project Abstract Protein glycosylation plays important roles in various human diseases, including cancer, inflammatory, and neurodegenerative diseases. Glycoproteins, therefore, are important targets for disease diagnosis, prognosis, and therapeutics. Correct glycosylation of therapeutic proteins is required for optimal efficacy and safety. However, analysis of glycosylation is challenging due to the enormous complexity of glycan variability. The current state of art technique is mass spectrometry (MS), which has been a powerful approach for glycosylation analysis; however, there are classes of glycans that present challenges for MS analysis, such as the numerous component monosaccharides with the same mass. This project seeks to develop surface enhanced Raman scattering (SERS) as online detection method for glycosylation analysis at the levels of small glycopeptides and released glycans. This proposal leverages recent advances incorporating a novel SERS detector online with chemical separations for highly sensitive and selective characterization. Published results have successfully shown online separation, identification and quantification of phosphorylated monosaccharides, demonstrating the tremendous potential of SERS for qualitative and quantitative analysis of carbohydrates that serve as glycans and glycopeptides. The specific aims of this project are as follows:  Aim 1. Demonstrate the utility of the sheath-flow SERS detector for structural analysis of glycopeptides. We will use a set of structurally similar glycopeptide analogues to demonstrate the capability of the SERS flow detector for identification and quantification of glycopeptides.  Aim 2. Qualitative and quantitative analysis of glycans and peptides released from glycoproteins using LC- SERS. This aim will provide evidence for the capability of our SERS technology to identify and quantify glycans and glycopeptides with similar chemical structure (e.g. isomers) in complex mixtures, demonstrating its potential, as a complementary technique to MS, for comprehensive glycosylation analysis of the levels of glycopeptides and released glycans. The development of new technologies that provide unique chemical specific information will provide an alternative tool for increased coverage of the glycoproteome, facilitating the progress in glycobiology.