Glycosylation Analysis by Sheath-Flow SERS

项目摘要 蛋白质糖基化在各种人类疾病中起重要作用，包括癌症、炎性和免疫性疾病。 神经退行性疾病因此，糖蛋白是疾病诊断，预后， 和治疗学。治疗性蛋白质的正确糖基化是获得最佳疗效和安全性所必需的。 然而，由于聚糖变异性的巨大复杂性，糖基化的分析具有挑战性。 目前最先进的技术是质谱法（MS），其已经是用于分析的有力方法。 糖基化分析;然而，存在对MS分析提出挑战的聚糖类别，例如 具有相同质量的众多组分单糖。 本项目旨在开发表面增强拉曼散射（SERS）作为在线检测方法， 在小糖肽和释放的聚糖水平上进行糖基化分析。该提案利用了 最近的进展结合了一种新的SERS检测器在线与化学分离的高灵敏度， 选择性表征已发表的结果成功地显示了在线分离，鉴定和 磷酸化单糖的定量，证明了SERS的巨大潜力， 对作为聚糖和糖肽的碳水化合物进行定性和定量分析。 该项目的具体目标如下： 1.演示鞘流SERS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证明 用于糖肽鉴定和定量的SERS流动检测器。 第二章.使用化学发光法定性和定量分析从糖蛋白释放的聚糖和肽 LC-SERS。这一目标将为我们的SERS技术识别和 定量复杂混合物中具有相似化学结构的聚糖和糖肽（例如异构体）， 证明了其作为MS的补充技术用于全面糖基化的潜力 分析糖肽和释放的聚糖的水平。 提供独特化学特定信息的新技术的开发将提供 增加糖蛋白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.