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A high-resolution in situ proteomics atlas of salivary gland development

唾液腺发育的高分辨率原位蛋白质组学图谱

基本信息

批准号：
7933969
负责人：
MELINDA LARSEN
金额：
$ 29.7万
依托单位：
STATE UNIVERSITY OF NEW YORK AT ALBANY
依托单位国家：
美国
项目类别：
财政年份：
2009
资助国家：
美国
起止时间：
2009-09-17 至 2012-08-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/7933969
关键词：
Abbreviations Address Adult Algorithms Antibodies Area Atlases Biological Markers Cells Communities Complement Computer software Computers Data Data Analyses Data Set Databases Development Developmental Biology Differentiation Antigens Ductal Epithelium Dyes Economics Embryo Engineering Epithelium Event Female Fibroblasts Fluorescence Formalin Foundations Future Gene Expression Gene Proteins Generations Genomics Gland Human Image Imagery Immunohistochemistry In Situ Knowledge Label Mainstreaming Maps Messenger RNA Methods Microscope Molecular Molecular Profiling Morphogenesis Morphology Mus National Institute of Dental and Craniofacial Research Nerve Online Systems Organ Paraffin Embedding Pathway interactions Pattern Positioning Attribute Procedures Process Protein Kinase Proteins Proteomics Recovery Regulation Research Research Personnel Resolution Salivary Gland Tissue Salivary Glands Sampling Signal Pathway Signal Transduction Signal Transduction Pathway Signaling Molecule Signaling Protein Staging Structure Sublingual Gland Submandibular gland System Systems Biology Technology Testing Time Tissue Microarray Tissues Vendor Visual base cell type computerized data processing cost craniofacial fluorophore gland development innovation insight link protein male mathematical model novel postnatal programs protein expression

项目摘要

DESCRIPTION (provided by applicant): This application addresses broad Challenge Area (06) Enabling Technologies and specific Challenge Topic, 06-DE-102 Structural and Molecular Atlases of Craniofacial Development. A critical issue for understanding organ development at a systems level is knowledge of temporal and spatial patterns of gene and protein expression throughout development. We have developed a novel fluorescence-based multiplexing technology for simultaneously tracking dozens of proteins within single formalin-fixed, paraffin-embedded tissue sections and novel software algorithms for quantifying and categorizing protein localization patterns for these markers at the subcellular level. This method involves direct immunohistochemistry (IHC) and automated imaging followed by complete inactivation of fluorophores that are directly conjugated to antibody probes. This direct IHC approach allows sequential multiplexed probing of the same tissue with multiple antibodies to dramatically increase the number of markers that can be simultaneously visualized in a single sample when compared with classical indirect IHC. This method eliminates the need for multiple spectrally compatible fluorophores and for serial tissue sections, thus allowing large amounts of data to be generated from a small amount of material. The dye-inactivation multiplexing procedure has been thoroughly characterized and tested through 100 rounds of cycling with no loss in tissue morphology or antigenicity. In this project, we will apply this innovative multiplexing technology for the first time to a developmental system to profile expression patterns of signaling proteins during mouse submandibular and sublingual salivary gland morphogenesis and differentiation in a developmental salivary gland tissue array. The end product will include a high- resolution in situ proteomics-based atlas, which categorizes and quantifies active signaling protein expression levels within specific cell types and subcellular compartments, throughout all key developmental time-points. This high-resolution anatomical systems-level analysis would be impossible to create using traditional genomics methods, which are done at the level of mRNA, or by traditional proteomic methods, which destroy the tissue context. This data set will complement the gene expression atlases developed through the intramural NIDCR program (Salivary Gland Atlas project, Drs. K. Yamada and M. Hoffman) and will integrate with other databases in FaceBase, and provide a truly unique data component for systems biology. The morphogenesis-related dataset will also inform a mathematical model of the developing salivary gland, (RO1DE0192444-01, M. Larsen,) and the differentiation-related dataset will identify new differentiation markers and pathway components for intelligent engineering of an artificial salivary gland (R21DE0192444-01, M. Larsen). This study will provide a foundation of basic developmental biology knowledge needed to interpret future studies in other normal and diseased mouse and human craniofacial tissues. Finally, the proposed studies will facilitate economic recovery through direct materials costs (i.e. microscope, fluidics, computers and controllers, and antibodies and supplies, which will all purchased from US vendors) and by providing two new positions to complete the antibody labeling and to become a key operator in Dr. Larsen's lab so that the technology can be applied to her future studies. The technology being applied to the atlas; however, is not currently commercially available to the public research community, but this project will facilitate the adaptation and transition of this powerful multiplexing method to mainstream research applications. The proposed studies will create an atlas of protein expression patterns in developing salivary gland using novel high-content methods. These methods allow multiple markers to be examined in the same sample, allowing true co-localization of multiple proteins through developmental stages. These studies will provide insight into the fundamental signaling events occurring during the process of salivary gland development and differentiation.

描述（由申请人提供）：本申请涉及广泛的挑战领域（06）使能技术和特定的挑战主题，06-DE-102颅面发育的结构和分子生物学。在系统水平上理解器官发育的一个关键问题是了解整个发育过程中基因和蛋白质表达的时空模式。我们已经开发了一种新的基于荧光的多路复用技术，用于同时跟踪单个福尔马林固定的石蜡包埋的组织切片内的数十种蛋白质，以及用于在亚细胞水平上对这些标记物的蛋白质定位模式进行定量和分类的新型软件算法。该方法涉及直接免疫组织化学（MHC）和自动成像，然后完全灭活直接与抗体探针偶联的荧光团。这种直接IHC方法允许用多种抗体对相同组织进行连续多重探测，以显著增加与经典间接IHC相比时可在单个样品中同时可视化的标志物的数量。该方法消除了对多个光谱兼容的荧光团和连续组织切片的需要，从而允许从少量材料生成大量数据。已通过100轮循环对染料灭活多重程序进行了全面表征和检测，组织形态或抗原性均无损失。在这个项目中，我们将首次将这种创新的多路复用技术应用于发育系统，以在发育唾液腺组织阵列中描述小鼠下颌下和舌下唾液腺形态发生和分化过程中信号蛋白的表达模式。最终产品将包括基于高分辨率原位蛋白质组学的图谱，其在所有关键发育时间点对特定细胞类型和亚细胞区室内的活性信号蛋白表达水平进行分类和定量。这种高分辨率的解剖系统水平的分析将是不可能创建使用传统的基因组学方法，这是在mRNA水平上完成的，或通过传统的蛋白质组学方法，这破坏了组织背景。该数据集将补充通过壁内NIDCR程序（Salivary Gland Atlas project，Drs. K. Yamada和M.霍夫曼），并将与FaceBase中的其他数据库集成，为系统生物学提供真正独特的数据组件。形态发生相关的数据集还将提供发育中的唾液腺的数学模型（RO 1DE 0192444 -01，M. Larsen）和分化相关数据集将鉴定用于人工唾液腺的智能工程的新分化标记物和途径组分（R21 DE 0192444 -01，M. Larsen）。这项研究将为解释未来在其他正常和患病小鼠和人类颅面组织中的研究提供基础发育生物学知识。最后，拟议的研究将通过直接材料成本（即显微镜，射流，计算机和控制器，抗体和用品，这些都将从美国供应商购买）和提供两个新的职位来完成抗体标记，并成为Larsen博士实验室的关键操作员，以便该技术可以应用于她未来的研究，从而促进经济复苏。应用于地图集的技术目前还没有向公共研究界提供，但该项目将促进这种强大的多路复用方法的调整和过渡，使其成为主流研究应用。拟议的研究将使用新的高含量方法创建一个唾液腺发育中蛋白质表达模式的图谱。这些方法允许在同一样品中检查多个标记，从而允许在发育阶段中多种蛋白质的真正共定位。这些研究将为深入了解唾液腺发育和分化过程中发生的基本信号事件提供依据。