Development of a rapid glycosylation profiling system using mass spec data

描述（由申请人提供）：本提案的最终目标是开发一种全自动的糖肽分析方法，并将该方法应用于几种不同的HIV-Env糖蛋白的分析。这项工作将通过完成三个特定目标来完成：目标1：使用质谱数据作为输入，开发一种快速识别单糖基化糖肽组成的算法。目标2：开发一种表征多个糖基化糖肽的算法。目标3：使用目标1和目标2中的工具筛选HIV Env蛋白上可接近的和遗传保守的点。大部分工作，即目标1和目标2，将通过将质谱（MS）数据采集和分析的专业知识与软件设计/开发的专业知识协同结合来完成。这项工作可以广泛地影响人类健康研究，因为糖肽分析是一种有利的生物分析技术，可用于筛选疾病或疾病状态的生物标志物；它可以用来帮助验证糖蛋白类药物的安全性和一致性；它可以用来分析HIV包膜蛋白上的糖肽，这是HIV疫苗开发的主要目标。在完成自动糖基化分析系统（目标1和目标2）后，该系统将用于识别各种HIV- Env候选疫苗的糖肽组成，这些候选疫苗是与杜克大学医学中心的Barton F. Haynes博士合作制作的。该方法包括制备每种糖蛋白的色氨酸酶切产物，对酶切产物进行HPLC-MS和LC-MS/MS分析，并使用开发的糖肽分析软件解释结果。这项工作完成后，Env蛋白的糖肽谱将提供关于Env表位可及性的信息。这与人类健康有关，因为识别在HIV-1进化支中持续暴露的蛋白质上的表位是设计HIV疫苗的第一步，该疫苗模仿这些表位并引发广泛中和的HIV-1抗体。公共卫生相关性：我们的目标是开发快速分析糖肽的工具。糖肽是HIV Env蛋白的组成部分，它们的分析可以用来识别病毒表面的“阿喀琉斯之踵”（持续暴露，因此容易受到抗体攻击的区域）。

DESCRIPTION (provided by applicant): The ultimate goal of this proposal is to develop a fully-automated approach for analysis of glycopeptides and to apply that approach to the analysis of several different HIV-Env glycoproteins. This work would be accomplished by completing three specific aims: AIM 1: Using MS data as the input, develop an algorithm that rapidly identifies glycopeptide compositions for singly glycosylated glycopeptides. AIM 2: Develop an algorithm that characterizes multiply glycosylated glycopeptides. AIM 3: Use the tools in AIMS 1 and 2 to screen for accessible and genetically conserved points on the HIV Env protein. The bulk of the work, Aims 1 and 2, would be completed by synergistically incorporating expertise in mass spectral (MS) data acquisition and analysis with expertise in software design/development. This work can broadly impact human health research because glycopeptide analysis is an enabling bioanalytical technology that can be used to screen for biomarkers of disease or disease state; it can be used to help verify the safety and consistency of glycoprotein-based pharmaceuticals; and it can be used to analyze glycopeptides on HIV Envelope proteins, a major target for HIV vaccine development. After completion of the automated glycosylation profiling system (Aims 1 and 2) this system would be used to identify the glycopeptide composition on a variety of HIV- Env vaccine candidates generated in collaboration with Dr. Barton F. Haynes at Duke University Medical Center. The method for this approach includes preparing tryptic digests of each of the glycoproteins, conducing HPLC-MS and LC-MS/MS analyses on the digested products, and interpreting the results using the developed glycopeptide analysis software. After completion of this work, the glycopeptide profiles of the Env proteins would provide information about epitope accessibility on Env. This is relevant to human health because identifying epitopes on the protein that are consistently exposed across HIV-1 clades is a first step in designing an HIV vaccine that mimics these epitopes and elicits broadly neutralizing antibodies to HIV-1. PUBLIC HEALTH RELEVANCE: We aim to develop tools for the rapid analysis of glycopeptides. Glycopeptides are components of the HIV Env protein, and their analysis could be used to identify Achilles Heels (regions which are consistently exposed and thus vulnerable to antibodies) on the surface of the virus.