Systems Biology of Glycosylation

糖基化的系统生物学

• 批准号: 10558673
• 负责人: SRIRAM NEELAMEGHAM
• 金额: $ 54.98万
• 依托单位: STATE UNIVERSITY OF NEW YORK AT BUFFALO
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-09-05 至 2026-01-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10558673
• 关键词: Abbreviations; Address; Adhesions; Anabolism; Animals; Atlases; Bar Codes; Basic Science; Binding; Biochemical Pathway; Biochemical Process; Bioinformatics; Biological Assay; Biological Markers; Biological Process; Blood; Blood Cells; CD34 gene; CRISPR library; CRISPR screen; Cell Adhesion; Cell Adhesion Molecules; Cell Adhesion Process; Cell Line; Cell physiology; Cells; Cellular Metabolic Process; Clinic; Clustered Regularly Interspaced Short Palindromic Repeats; Communities; Complex; Computational Biology; Computers; Coupling; Data; Development; Disease; Ear; Early Diagnosis; Endothelial Cells; Enzymes; Epigenetic Process; Event; Experimental Models; Family; Flow Cytometry; Fucose; Funding; Galactose; Gene Expression Profile; Gene Mutation; Gene Targeting; Genes; Genetic; Glycoconjugates; Grant; HL60; Hematopoietic; Hematopoietic stem cells; Hemorrhage; Human; Immunity; Individual; Inflammation; Inflammatory; Knock-out; Knowledge; Lead; Lectin; Leukocytes; Libraries; Link; Macrophage; Mammalian Cell; Maps; Mass Spectrum Analysis; Measurement; Measures; Mechanics; Mediating; Methods; Microfluidics; Modeling; Molecular; Mononuclear; Mus; Myelogenous; Myeloid Cells; National Heart, Lung, and Blood Institute; Natural Immunity; Nature; Neoplasm Metastasis; Nomenclature; Organism; Pathway interactions; Pattern; Polysaccharides; Post-Translational Protein Processing; Proteins; Role; Selectins; Series; Sialic Acids; Signal Transduction; Specificity; Structure; System; Systems Biology; Technology; Testing; Transcript; Translating; Transplantation; Vascular Endothelial Cell; Work; carbohydrate binding protein; carbohydrate receptor; clinical diagnostics; computer framework; cost; disease diagnostic; genome-wide; glycoproteomics; glycosylation; glycosyltransferase; granulocyte; in vivo; inhibitor; model building; molecular scale; monocyte; network models; neutrophil; next generation sequencing; novel; outcome prediction; patient stratification; peripheral blood; precision medicine; programs; relational database; sequencing platform; sialyl Lewis x; single cell analysis; single-cell RNA sequencing; small molecule; small molecule inhibitor; sugar; tool; transcription factor; transcriptome; transcriptomics; user-friendly; web site

This is the renewal application of a grant that has been supported as part of the NHLBI Systems Biology program. It deals with the subject of glycosylation, a ubiquitous and complex post-translational modification in mammalian cells. Glycans decorate a vast majority of mammalian proteins. They absolutely control or fine-tune a number of cellular processes in higher organisms including development, immunity, inflammation, bleeding and metastasis. Glycan structures change due to alterations in cell metabolism, development and signaling events that perturb the underlying transcriptome. A systematic understanding of the factors (genetic and epigenetic) controlling glycosylation is currently unavailable. This is however important for two reasons: i. Such knowledge can help establish quantitative links between different cell systems, so that knowledge gained in the study of one system can be applied to predict the outcome in another. ii. Gene transcript measurements are now being used in clinical diagnostics, and the advent of next generation sequencing (NGS) has dramatically reduced the cost of such assays. If a relation between changes in the pattern of gene expression and alterations in glycan structures is established, disease-associated glycan biomarkers may be assayed using standard gene sequencing methods. This can enable both early diagnosis and patient stratification during precision medicine applications. Based on the above, the current proposal addresses the hypothesis that “Coupling systems based quantitative, analytical experimentation with model building can help relate cellular glycomics changes to the underlying transcriptome”. This proposition will be tested by performing a series of studies using blood leukocytes involved in innate immunity and by relating findings to inflammatory leukocyte-endothelial cell adhesion mechanics. The specific aims are: 1. To develop a blood glycan atlas using single-cell analysis on NGS platform and glycoProbe based mass spectrometry. This aim will result in a relational database that describes the glycoEnzymes regulating the biosynthesis of specific glycan structures in three myeloid/monocytic blood cell lines, primary human blood and in CD34+ hematopoietic stem/progenitor cells (HSPC). 2: To develop a complementary experiment-modeling framework to relate glycogene expression to glycan structure. This aim extends concepts in Aim 1, only focusing on blood cells that are being differentiated down neutrophil or macrophage lineages. Emerging data will yield glycogene regulatory network maps that identify novel controllers of cellular glycosylation profile. 3: To test the roles of selected small molecules, transcription factors (TFs) & glycogene checkpoints during leukocyte-endothelial cell adhesion ex vivo and in vivo. Here, we determine the ability of data-driven computer predictions and molecular studies, to identify new checkpoints regulating human inflammatory leukocyte adhesion. Overall, the study scales from the molecular, to cell and whole animal levels. It will result in state-of-the-art systems biology computational and experimental tools to enhance our understanding of cellular glycosylation, blood glycans, and its impact on human inflammatory diseases.

这是 NHLBI 系统生物学计划的一部分所支持的拨款续展申请。 它涉及糖基化的主题，糖基化是哺乳动物中普遍存在且复杂的翻译后修饰。 细胞。绝大多数哺乳动物蛋白质均由聚糖修饰。他们绝对控制或微调一些 高等生物体的细胞过程，包括发育、免疫、炎症、出血和转移。 由于细胞代谢、发育和信号事件的改变，聚糖结构发生变化 底层转录组。对控制因素（遗传和表观遗传）的系统理解 目前无法进行糖基化。然而，这很重要，原因有二：这些知识可以帮助 建立不同细胞系统之间的定量联系，以便在研究一个系统时获得知识 可以用来预测另一个结果。二.基因转录测量现已用于临床 诊断和下一代测序（NGS）的出现极大地降低了此类成本 化验。如果基因表达模式的变化与聚糖结构的改变之间的关系是 可以使用标准基因测序方法来分析已建立的、与疾病相关的聚糖生物标志物。 这可以在精准医学应用中实现早期诊断和患者分层。基于 如上所述，当前的提案提出了这样的假设：“基于定量的耦合系统， 模型构建的分析实验可以帮助将细胞糖组学的变化与 潜在的转录组”。这个命题将通过使用血液进行一系列研究来检验 白细胞参与先天免疫，并将发现与炎症白细胞内皮细胞相关 粘附力学。具体目标是： 1. 利用单细胞分析开发血液聚糖图谱 基于NGS 平台和糖探针的质谱分析。这个目标将导致一个关系数据库 描述了调节三种骨髓/单核细胞中特定聚糖结构生物合成的糖酶 血细胞系、原代人类血液和 CD34+ 造血干/祖细胞 (HSPC)。 2：开发 将糖基因表达与聚糖结构联系起来的补充实验建模框架。这个目标 扩展了目标 1 中的概念，仅关注正在分化为中性粒细胞或中性粒细胞的血细胞。 巨噬细胞谱系。新出现的数据将产生糖基因调控网络图，识别新的控制器 细胞糖基化谱。 3：测试所选小分子、转录因子 (TF) 和 白细胞-内皮细胞离体和体内粘附过程中的糖原检查点。在这里，我们确定 数据驱动的计算机预测和分子研究的能力，以确定调节人类的新检查点 炎症白细胞粘附。总体而言，该研究从分子水平扩展到细胞水平和整个动物水平。 它将带来最先进的系统生物学计算和实验工具，以增强我们的能力 了解细胞糖基化、血液聚糖及其对人类炎症性疾病的影响。