High content glycomics analysis using next generation sequencing technology

使用下一代测序技术进行高内涵糖组学分析

• 批准号: 9765667
• 负责人: SRIRAM NEELAMEGHAM
• 金额: $ 19.82万
• 依托单位: STATE UNIVERSITY OF NEW YORK AT BUFFALO
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-05-01 至 2021-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9765667
• 关键词: Address; Anabolism; Antigens; Area; Basic Science; Binding; Biochemical; Biochemical Pathway; Biochemical Reaction; Bioinformatics; Biological; Biological Assay; Biology; Blood; Blood Cells; Breast; Breast Cancer Cell; Breast Cancer cell line; CRISPR library; CRISPR screen; CRISPR/Cas technology; Cancer Biology; Carbohydrates; Cardiovascular Diseases; Catalogs; Cell Line; Cell physiology; Cells; Chemistry; Clustered Regularly Interspaced Short Palindromic Repeats; Code; Communities; Complex Mixtures; Computer Simulation; Cytometry; Data; Data Analyses; Development; Diagnosis; Disease model; Epitopes; Fixatives; Flow Cytometry; Future; Genes; Genetic Screening; Goals; Human; Individual; Investigation; Knock-out; Label; Lead; Lectin; Libraries; Literature; Malignant Neoplasms; Mammalian Cell; Mammary Gland Parenchyma; Mammary Neoplasms; Maps; Measurement; Measures; Methodology; Methods; MicroRNAs; Molecular; Monitor; Monoclonal Antibodies; Neurosciences; Oligonucleotides; Output; Pathologic; Pathology; Pathway Analysis; Pathway interactions; Patient Care; Patients; Phenotype; Physiology; Polysaccharides; Population; Preparation; Procedures; Process; Property; Reagent; Regenerative Medicine; Research; Sampling; Selection Criteria; Series; Specificity; Specimen; System; Technology; Testing; Tissues; Transcriptional Regulation; Transition Elements; Viral; base; biological systems; carbohydrate binding protein; carbohydrate biosynthesis; carbohydrate structure; cell type; computerized tools; density; design; experimental study; fluorophore; functional loss; genome editing; genome-wide; glycosylation; human tissue; interest; knockout gene; mathematical analysis; mathematical model; next generation sequencing; novel; preservation; response; scale up; tool; web site; whole genome

Biological systems are typically robust since many different biochemical reaction pathways and processes partially control system stability. In some instances, loss of a single pathway results in compensatory contributions from others to maintain system-status. In others, many different biological pathways partially contribute to regulating a single function, with complete functional loss only being observed upon loss or knocking-out of all individual contributors. Large-scale experimental and computational interrogation of biological assemblies is necessary in order to develop a systems-level understanding. The scope of such investigations has been vastly enhanced in recent years with the development of new multiplex tools based on next-generation sequencing (NGS). This is commonly enabled by the tagging of individual cells, monoclonal antibodies or other antigen binders with oligonucleotide barcodes or unique molecular identifiers (UMIs). Such barcodes/UMIs can be followed independently using NGS. In addition, it is now possible to develop CRISPR based knockout libraries and screens targeting the entire genomes, or a subset of genes related to a certain function (e.g. cellular glycosylation). This project aims to combine recent advances in NGS and CRISPR-Cas9 by addressing the hypothesis that ‘the combined use of CRISPR-Cas to knockout genes in large scale combined with NGS to measure related cell-system response can inform us of system properties at an unprecedented scale’. We test this possibility using examples from the Glycosciences. The specific aims are: Aim 1. To develop ‘Lectin-Tag- seq’, a method to assay the glycome of individual cells in complex mixtures. Here, a panel of lectins and related mAbs are tagged with uniquely barcoded oligonucleotides. The simultaneous binding of these reagents to diverse cell types in human blood and breast tissue is measured at a large scale using NGS. The lectin binding specificity of a vast number of carbohydrate binding proteins is now available in literature, and thus bioinformatics analysis will be applied to relate the lectin-binding measurements on individual cells to glycan epitopes and potential carbohydrate structures that exist on the single cells. Aim 2. To develop ‘CRISPR-Tag-seq’ in order to simultaneously measure, at a single cell level, the sgRNA editing a given cell and the corresponding changes in multiplex lectin/mAb binding profiles. Here, a glycogene-CRISPR library targeting 347 genes regulating cellular glycosylation is introduced into breast cancer cells. The effects of such biochemical pathway perturbations are related to lectin binding on individual cells. Mathematical analysis is performed to analyze the effect of sgRNA perturbations. All data will be available to the research community at our website VirtualGlycome.org. In the long run, methods developed in this project can be extended to additional cell types and biological problems to ultimately streamline and simplify our understanding of the mammalian glycome.

生物系统通常是健壮的，因为有许多不同的生化反应途径和过程 部分控制系统稳定性。在某些情况下，失去一条通路会导致补偿 其他人对维持系统地位的贡献。在另一些情况下，许多不同的生物途径部分 有助于调节单一功能，只有在丧失或完全丧失功能时才能观察到 淘汰所有个人贡献者。生物学的大规模实验和计算讯问 为了形成对系统级别的理解，组装是必要的。这类调查的范围 近年来，随着基于下一代的新多路复用工具的开发，该功能得到了极大的增强 测序(NGS)。这通常是通过标记单个细胞、单抗或其他 带有寡核苷酸条形码或唯一分子识别符(UMI)的抗原结合体。这样的条形码/UMI可以 使用NGS独立跟踪。此外，现在还可以开发基于CRISPR的基因敲除文库 以及针对整个基因组或与特定功能相关的基因子集(例如，细胞)的筛选 糖基化)。该项目旨在将NGS和CRISPR-CAS9的最新进展结合起来，通过解决 CRISPR-CA结合NGS大规模敲除基因的假说 测量与细胞-系统相关的响应可以让我们以前所未有的规模了解系统的特性。我们测试 这种可能性来自于糖类科学的例子。具体目标是：目标1.研制凝集素-标签 SEQ‘，一种测定复杂混合物中单个细胞糖基的方法。在这里，一组凝集素和相关的 单抗被唯一的条形码寡核苷酸标记。这些试剂同时结合到 使用NGS大规模测量人类血液和乳房组织中的不同细胞类型。凝集素结合 大量碳水化合物结合蛋白的特异性现在可以在文献中找到，因此生物信息学也是如此。 分析将用于将单个细胞上的凝集素结合测量与糖链表位和 存在于单个细胞上的潜在碳水化合物结构。目的2.开发“CRISPR-TAG-SEQ”以便 同时在单个细胞水平上测量编辑给定细胞的sgRNA以及 多重凝集素/单抗结合图谱。在这里，针对347个调控细胞的基因的糖基因-CRISPR文库 糖基化被引入到乳腺癌细胞中。这种生物化学途径扰动的影响是 与单个细胞上的凝集素结合有关。对sgRNA的作用进行了数学分析。 微扰。所有数据将在我们的网站VirtualGlycome.org上提供给研究社区。在漫长的岁月里 运行，这个项目中开发的方法可以扩展到其他细胞类型和生物学问题，以 最终简化和简化我们对哺乳动物糖蛋白的理解。