Capturing Low-Abundance Glycopeptides for Decoding the Glycoproteome

捕获低丰度糖肽以解码糖蛋白组

• 批准号: 10260575
• 负责人: Ronghu Wu
• 金额: $ 29.79万
• 依托单位: GEORGIA INSTITUTE OF TECHNOLOGY
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-20 至 2024-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10260575
• 关键词: Acids; Affect; Back; Biological Markers; Biomedical Research; Boronic Acids; Cell Survival; Cells; Cleaved cell; Clinical; Complex; Covalent Interaction; Cultured Cells; Data; Dendrimers; Detection; Development; Disease; Drug Targeting; Enzymes; Event; Glycopeptides; Glycoproteins; Health; Heterogeneity; Human; Infection; Knowledge; Lead; Life; Malignant Neoplasms; Malignant neoplasm of ovary; Mass Spectrum Analysis; Methods; Mission; Modification; Molecular; Patients; Play; Polysaccharides; Post-Translational Protein Processing; Protein Analysis; Protein Glycosylation; Proteins; Proteomics; Public Health; Research; Role; Sampling; Site; Structure; Surface; Testing; Tissues; United States National Institutes of Health; base; biological research; biological systems; biomarker discovery; cellular development; density; design; disability; early detection biomarkers; glycoproteomics; glycosylation; human disease; hydroxyl group; innovation; insight; monomer; new therapeutic target; novel; operation; potential biomarker; protein function; sugar

SUMMARY Glycosylation is one of the most common protein modifications and is essential for cell survival. Glycoproteins contain a wealth of valuable information regarding the development and disease statuses of cells. Global analysis of protein glycosylation aids in a better understanding of glycoprotein functions and the molecular mechanisms of disease, and leads to the identification of glycoproteins as biomarkers. However, it is extraordinarily challenging to comprehensively analyze glycoproteins because of the heterogeneity of glycans and the low abundance of many glycoproteins. The objective of this project is to develop an innovative and effective method to enrich glycopeptides with diverse glycan structures, especially those with low abundance, and apply this method to globally and site-specifically analyze protein N- and O-glycosylation by mass spectrometry (MS). Guided by strong preliminary data, this objective will be fulfilled by pursuing four specific aims. 1) Effective enrichment of glycopeptides through the synergistic interactions using different types of dendrimers. Based on the common feature that every glycan contains multiple hydroxyl groups, a novel method benefiting from the synergistic interactions between a glycan and multiple boronic acid (BA) molecules conjugated to one dendrimer will be developed to capture low-abundance glycopeptides. Different types of dendrimers will be synthesized and tested, especially from monomers containing the 1→3 branching motif that will increase the density of BA at the dendrimer surface and enhance the interactions with a glycan. 2) Enhancement of the synergistic interactions by minimizing the steric effect and forming the ternary complex. Different kinds of BAs will be studied, especially vinylboronic acids with a small size. This will decrease the steric hindrance and strengthen the overall interaction between one glycan and BAs. Moreover, the formation of the ternary complex will be studied to further enhance the interactions. 3) Global and site-specific analysis of O- glycoproteins with glycan structure information. Through reversible covalent interactions, enriched glycopeptides contain intact glycans, allowing for site-specific analysis of O-glycoproteins with glycan structure information. This is especially important for O-glycosylation due to the lack of an enzyme to universally cleave O-glycans and generate a common tag. 4) Comprehensive analysis of glycoproteins in tissues and sera from patients with ovarian cancer. Combining the proposed method with multiplexed proteomics, glycoproteins in clinical samples will be systematically and quantitatively analyzed. The results will provide insights into the molecular mechanisms of the disease and lead to the discovery of biomarkers for early detection. Eventually, the best dendrimer conjugated with the right BA will enable us to effectively capture low-abundance glycopeptides. Because of the ease of operation and no sample restrictions, the method will have extensive applications in the biological and biomedical research fields and will significantly advance glycoscience.

总结 糖基化是最常见的蛋白质修饰之一，对细胞存活至关重要。糖蛋白 包含大量关于细胞发育和疾病状态的有价值的信息。全球 蛋白质糖基化的分析有助于更好地理解糖蛋白的功能和分子生物学特性。 疾病的机制，并导致糖蛋白作为生物标志物的鉴定。但据 由于聚糖的异质性，全面分析糖蛋白是非常具有挑战性的 以及许多糖蛋白的低丰度。该项目的目标是开发一种创新的， 富集具有不同聚糖结构糖肽，特别是低丰度的糖肽， 并将该方法应用于蛋白质N-和O-糖基化的全局和位点特异性质量分析 质谱法（MS）。在强有力的初步数据的指导下，将通过以下四个具体方面来实现这一目标： 目标。1)通过使用不同类型的酶的协同相互作用有效富集糖肽 树枝状聚合物基于每个聚糖都含有多个羟基的共同特征， 得益于聚糖和多个硼酸（BA）分子之间的协同相互作用 将开发与一个树枝状聚合物缀合的抗体以捕获低丰度的糖肽。不同类型的 树枝状聚合物将被合成和测试，特别是从含有1→3分支基序的单体， 将增加树枝状聚合物表面的BA密度并增强与聚糖的相互作用。（二） 通过最小化空间效应和形成三元复合物来增强协同相互作用。 将研究不同种类的BA，特别是具有小尺寸的乙烯基硼酸。这将降低空间位阻 阻碍和加强一个聚糖和BA之间的整体相互作用。此外， 三元复合物的研究将进一步加强相互作用。3)O-的全球和特定地点分析 具有聚糖结构信息的糖蛋白。通过可逆的共价相互作用， 含有完整的聚糖，允许用聚糖结构信息对O-糖蛋白进行位点特异性分析。 这对于O-糖基化尤其重要，因为缺乏酶来普遍切割O-聚糖， 生成一个通用标签。4)糖尿病患者组织和血清糖蛋白的综合分析 卵巢癌将所提出的方法与多重蛋白质组学相结合， 将进行系统的定量分析。这些结果将提供深入了解分子 疾病的机制，并导致生物标志物的发现，用于早期检测。最终，最好的 与合适的BA缀合的树枝状聚合物将使我们能够有效地捕获低丰度的糖肽。 该方法操作简便，不受样品限制，在生物样品分析中具有广泛的应用前景。 生物和生物医学研究领域，并将大大推进糖科学。