Unraveling the mammalian secretory pathway through systems biology and algorithm development

通过系统生物学和算法开发揭示哺乳动物的分泌途径

• 批准号: 9142975
• 负责人: Nathan Enoch Lewis
• 金额: $ 38.75万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN DIEGO
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-07-15 至 2021-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9142975
• 关键词: Algorithms; Alzheimer' s Disease; CRISPR screen; CRISPR/Cas technology; Cell Communication; Cell physiology; Cell surface; Cells; Communicable Diseases; Complex; Computer Simulation; Data; Data Analyses; Data Set; Development; Disease; Enzymes; Exhibits; Extracellular Matrix; Goals; Growth; Health; Hormones; Human; Imagery; Individual; Infection; Lipids; Membrane Proteins; Metabolism; Modeling; Modification; Molecular; Pathway interactions; Phenotype; Polysaccharides; Process; Protein Secretion; Proteins; Proteomics; Regulation; Research; Research Personnel; Role; Route; Structure; System; Systems Biology; Techniques; Time; Tissues; Translations; abstracting; cancer cell; chaperonin; data visualization; glycosylation; knowledge base; loss of function; macromolecule; member; metabolomics; models and simulation; novel; pathogen; programs; protein misfolding; reconstruction; stem; tool

Project Summary / Abstract Unraveling the mammalian secretory pathway through systems biology data analysis and algorithm development. The mammalian secretory system is key to organismal development, cell-cell communication, and all other cellular functions, since the pathway is the biosynthetic route for thousands of secreted hormones, extracellular matrix modifiers, membrane proteins, and glycans. Its central role also makes it a hub for disease. Alzheimer's disease is associated with plaques formed from proteins that are misfolded in the secretory pathway. Cancer cells alter their microenvironment through the secretion of growth factors and modification of cell surface glycans. Many infectious diseases interact with membrane proteins and glycans during the infection process. While the secretory pathway has been studied extensively for more than a century, the complexity of the system has made it difficult to unravel how thousands of chaperonins, enzymes, transporters, glycans, metabolites, lipids, and RNAs function together to influence health and disease. The goal of this proposed research program is to develop a detailed knowledge base of the secretory pathway and to develop algorithms and tools to use the network for data visualization, analysis, and model simulations, thereby enabling researchers to elucidate how each component influences the system. We will further to apply these tools with large scale single and dual sgRNA/CRISPR screens in order to elucidate novel interactions and mechanisms regulating protein secretion. Specifically, (i) the knowledge base will contain detailed information about all macromolecules involved in the translation, folding, modification, glycosylation, and secretion of proteins. This further includes metabolism, which fuels the pathway. The known functions of each pathway member will be detailed, and their interactions will be described. Since the knowledge base will be organized to enable its use for systems biology analyses, (ii) visualization tools and analysis algorithms will be developed and deployed to identify how changes in each component influence the ability to secrete individual proteins or synthesize specific glycans. (iii) We will leverage the model to integrate large omics data sets we are generating with collaborators (e.g., metabolomics, ribosomal profiling, proteomics, and CRISPR-Cas9 activation and loss-of-function screens) to study regulation of tissue-specific protein secretion. (iv) We will leverage the data to elucidate novel interactions and functions for poorly characterized members of the secretory pathway. This research program will provide, for the first time, a well-defined and curated knowledge base for this complex system, and enable the use of diverse computational systems biology tools to identify the molecular mechanisms underlying different cell phenotypes stemming from changes in the secretory pathway.

项目概要/摘要 通过系统生物学数据分析和算法揭示哺乳动物的分泌途径 发展。哺乳动物的分泌系统是有机体发育、细胞间通讯、 和所有其他细胞功能，因为该途径是数千种分泌物的生物合成途径 激素、细胞外基质修饰剂、膜蛋白和聚糖。它的核心作用也使其成为枢纽 为了疾病。阿尔茨海默病与由错误折叠的蛋白质形成的斑块有关。 分泌途径。癌细胞通过分泌生长因子和 细胞表面聚糖的修饰。许多传染病与膜蛋白和聚糖相互作用 在感染过程中。虽然分泌途径已被广泛研究了多年 世纪以来，该系统的复杂性使得很难解开数千个伴侣蛋白、酶、 转运蛋白、聚糖、代谢物、脂质和 RNA 共同发挥作用，影响健康和疾病。这 该拟议研究计划的目标是开发分泌物的详细知识库 途径并开发算法和工具以使用网络进行数据可视化、分析和 模型模拟，从而使研究人员能够阐明每个组件如何影响 系统。我们将进一步将这些工具应用于大规模单和双 sgRNA/CRISPR 筛选 为了阐明调节蛋白质分泌的新相互作用和机制。具体来说，(i) 知识库将包含有关翻译、折叠、 蛋白质的修饰、糖基化和分泌。这进一步包括新陈代谢，它为 途径。每个途径成员的已知功能将被详细描述，并且它们的相互作用将被描述 描述的。由于知识库的组织将使其能够用于系统生物学分析，(ii) 将开发和部署可视化工具和分析算法，以确定每个方面的变化 成分影响分泌单个蛋白质或合成特定聚糖的能力。 （三）我们将 利用该模型来整合我们与合作者生成的大型组学数据集（例如， 代谢组学、核糖体分析、蛋白质组学和 CRISPR-Cas9 激活和功能丧失筛选） 研究组织特异性蛋白质分泌的调节。 (iv) 我们将利用数据来阐明新颖的 分泌途径中特征不明的成员的相互作用和功能。本研究计划 将首次为这个复杂的系统提供一个定义明确且精心策划的知识库，并且 能够使用多种计算系统生物学工具来识别分子机制 由于分泌途径的变化而导致不同的细胞表型。