High-Throughput De Novo Glycan Sequencing

高通量从头聚糖测序

• 批准号: 10000171
• 负责人: Pengyu Hong
• 金额: $ 44.73万
• 依托单位: BOSTON UNIVERSITY MEDICAL CAMPUS
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-01 至 2023-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10000171
• 关键词: Address; Adopted; Algorithm Design; Algorithms; Anabolism; Autoimmune Diseases; Behavior; Binding; Bioinformatics; Biological; Biological Markers; Biomedical Research; Biopolymers; Carbon; Cardiovascular Diseases; Cell Adhesion; Communities; Complex; Complex Mixtures; Computer software; Coupling; Data; Data Set; Databases; Development; Disease; Dissociation; Effectiveness; Electron Transport; Embryonic Development; Epitopes; Fourier transform ion cyclotron resonance; Genome; Glycoconjugates; Glycosides; Health; High Pressure Liquid Chromatography; Immune response; Impairment; Individual; Isomerism; Link; Liquid Chromatography; Liquid substance; Lung diseases; Machine Learning; Malignant Neoplasms; Mass Spectrum Analysis; Metabolic; Methods; Natural graphite; Nature; Pathologic Processes; Pathway interactions; Pattern; Phase; Physiological; Physiological Processes; Physiology; Play; Polysaccharides; Research; Research Project Grants; Role; Sampling; Scheme; Source; Specificity; Speed; Structure; Structure-Activity Relationship; Surface; Vacuum; Variant; analytical method; base; bioinformatics tool; catalyst; cell growth; design; genetic linkage analysis; glycosylation; improved; instrument; mass spectrometer; nervous system disorder; novel; pathogen; performance tests; programs; protein folding; reconstruction; tandem mass spectrometry; therapeutic target; tool; ultraviolet

Glycosylation fulfills important physiological functions, including protein folding, embryogenesis, cell adhesion, pathogen recognition, and immune response. The multifaceted roles glycosylation plays derive from the presence of a range of glycan epitopes, where a small structural variation can have a profound impact on functions. Further, a glycome consists of many closely related structures, with their relative amounts determined by metabolic conditions in a cell- and growth-specific manner. Altered glycosylation is linked to many diseases, including cardiovascular, pulmonary, neurological and autoimmune disorders, and cancer. Thus, there is a clear need for analytical methods that can rapidly identify and quantify the many glycoforms in a glycome from different health and disease states. Finally, no genome-predicted glycan database exists due to the unscripted nature of glycan biosynthesis, and discovery of new glycan structures must be achieved by de novo methods. Although tandem mass spectrometry-based biopolymer sequencing has been the major catalyst to the recent rapid advance of 'omics, the prevailing collisionally activated dissociation method often fails to provide sufficient glycan structural detail at the MS2 level, whereas the MSn approach lacks the speed, sensitivity, and quantitative potential for high-throughput glycome analysis. We have recently developed an electronic excitation dissociation (EED) method that can yield rich structural information in a single stage of MS/MS analysis. However, the impact of EED on glycomics research is currently limited by its poor accessibility, insufficient coupling to on-line glycan separation methods, and difficulty in interpretation of complex glycan EED tandem mass spectra. Here, we propose to develop an integrated approach that combines EED with on-line liquid chromatography (LC) separation and a novel bioinformatics tool to achieve high-throughput, de novo, and comprehensive glycome characterization. We will explore the potential of EED for analysis of glycans in various derivatized forms, study their fragmentation behaviors, and establish fragmentation rules for the development of bioinformatics software. We will optimize conditions for efficient coupling of EED to reversed-phase, and porous graphitic carbon LC, and develop an LC-EED-MS/MS approach for simultaneous characterization and quantitation of glycan mixtures. We will implement EED on a Q-TOF instrument to improve its access to the glycoscience community. Finally, we will develop and rigorously test the performance of a novel bioinformatics software that can rapidly and accurately determine each glycan's structure from its tandem MS spectra. The proposed algorithm is fundamentally different from most existing software, in that it no longer relies solely on glycosidic and cross-ring fragments for topology and linkage analysis, but rather adopts a machine learning approach that considers the contexts of various types of fragment peaks, and the spectral features associated with different linkage configurations and structural motifs. The availability of such a high-throughput, de novo glycan sequencing tool will have an immense impact on many biomedical research fields, as glycosylation plays critical roles in almost all biological pathways.

糖基化实现重要的生理功能，包括蛋白质折叠、胚胎发生、细胞粘附， 病原体识别和免疫反应。糖基化所起的多方面作用源于 存在一系列聚糖表位，其中小的结构变化可对 功能协调发展的此外，糖组由许多密切相关的结构组成，它们的相对量是确定的。 通过代谢条件以细胞和生长特异性的方式。糖基化改变与许多疾病有关， 包括心血管、肺、神经和自身免疫疾病以及癌症。因此，有一个明确的 需要能够快速鉴定和定量来自不同来源的糖组中的许多糖型的分析方法， 健康和疾病状态。最后，没有基因组预测的聚糖数据库存在，这是由于 聚糖生物合成和新聚糖结构的发现必须通过从头方法来实现。 尽管基于串联质谱的生物聚合物测序是最近生物聚合物测序的主要催化剂， 随着组学的快速发展，流行的碰撞活化解离方法通常不能提供足够的 在MS 2水平上的聚糖结构细节，而MSn方法缺乏速度，灵敏度和定量 高通量糖组分析的潜力。我们最近开发了一种电子激发解离 (EED)该方法可以在MS/MS分析的单个阶段中产生丰富的结构信息。然而，影响 糖组学研究的EED目前受到其可及性差、与在线聚糖偶联不足等限制 分离方法和复杂聚糖EED串联质谱解释的困难。 在这里，我们建议开发一个集成的方法，结合EED与在线液相色谱（LC） 分离和一种新的生物信息学工具，以实现高通量，从头开始，和全面的糖组 特征化我们将探索EED分析各种衍生形式聚糖的潜力，研究 研究了它们的裂解行为，建立了生物信息学软件开发所需的裂解规则。 我们将优化EED与反相和多孔石墨碳LC有效耦合的条件， 开发用于同时表征和定量聚糖混合物的LC-EED-MS/MS方法。我们 将在Q-TOF仪器上实施EED，以改善其与糖科学界的联系。最后我们将 开发并严格测试一种新型生物信息学软件的性能， 根据串联MS光谱确定每个聚糖的结构。所提出的算法是根本不同的 从大多数现有的软件，因为它不再仅仅依赖于糖苷和交叉环片段的拓扑结构 和链接分析，而是采用考虑各种类型的上下文的机器学习方法 的片段峰，以及与不同的连接配置和结构相关的光谱特征， 图案这种高通量的从头聚糖测序工具的可用性将产生巨大的影响 在许多生物医学研究领域，糖基化在几乎所有生物途径中发挥着关键作用。