Unraveling the mammalian secretory pathway through systems biology and algorithm development

项目总结/摘要 通过系统生物学数据分析和算法揭示哺乳动物分泌途径 发展哺乳动物的分泌系统是生物体发育、细胞间通讯、 以及所有其他细胞功能，因为该途径是数千种分泌的 激素、细胞外基质修饰剂、膜蛋白和聚糖。它的中心作用也使它成为一个枢纽 疾病。阿尔茨海默氏病与斑块有关，这些斑块是由在大脑中错误折叠的蛋白质形成的。 分泌途径癌细胞通过分泌生长因子改变其微环境， 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。虽然分泌途径已经被广泛研究了一个多世纪， 世纪以来，系统的复杂性使得很难解开数千种伴侣蛋白，酶， 转运蛋白、聚糖、代谢物、脂质和RNA一起起作用以影响健康和疾病。的 这项研究计划的目标是开发一个详细的知识库的分泌 途径，并开发算法和工具，使用网络进行数据可视化，分析， 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， 以阐明新的相互作用和调节蛋白质分泌的机制。具体而言，（一） 知识库将包含关于涉及翻译，折叠， 蛋白质的修饰、糖基化和分泌。这进一步包括新陈代谢，它为代谢提供燃料。 通路每个通路成员的已知功能将被详细描述，它们的相互作用将被详细描述。 介绍了由于知识库的组织将使其能够用于系统生物学分析， 将开发和部署可视化工具和分析算法，以确定 蛋白质组分影响分泌单个蛋白质或合成特定聚糖的能力。(iii)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活化和功能丧失筛选）， 研究组织特异性蛋白分泌调节。(iv)我们将利用这些数据来阐明新的 相互作用和功能的分泌途径的成员表征不佳。这个研究项目 将首次为这个复杂的系统提供一个定义明确、精心策划的知识库， 能够使用不同的计算系统生物学工具来识别分子机制 潜在的不同细胞表型源于分泌途径的变化。

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.