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

• 批准号: 7824319
• 负责人: MELINDA LARSEN
• 金额: $ 30.48万
• 依托单位: STATE UNIVERSITY OF NEW YORK AT ALBANY
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-17 至 2011-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7824319
• 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

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) 支持技术和具体挑战主题，06-DE-102 颅面发育的结构和分子图谱。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间和空间模式。我们开发了一种新型的基于荧光的多重技术，用于同时跟踪单个福尔马林固定、石蜡包埋的组织切片中的数十种蛋白质，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量化和分类的新型软件算法。该方法涉及直接免疫组织化学 (IHC) 和自动成像，然后完全灭活直接与抗体探针缀合的荧光团。与传统的间接 IHC 相比，这种直接 IHC 方法允许使用多种抗体对同一组织进行连续多重探测，从而显着增加可在单个样品中同时可视化的标记物数量。该方法不需要多个光谱兼容的荧光团和连续的组织切片，从而可以从少量材料中生成大量数据。染料灭活多重程序已经过 100 轮循环的彻底表征和测试，组织形态或抗原性没有损失。在这个项目中，我们将首次将这种创新的多重技术应用于发育系统，以分析发育唾液腺组织阵列中小鼠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原位蛋白质组学的高分辨率图谱，该图谱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量化，贯穿所有关键的发育时间点。使用传统的基因组学方法（在 mRNA 水平上完成）或传统的蛋白质组学方法（破坏组织环境）不可能创建这种高分辨率解剖系统级分析。该数据集将补充通过校内 NIDCR 计划（唾液腺图谱项目、K. Yamada 博士和 M. Hoffman 博士）开发的基因表达图谱，并将与 FaceBase 中的其他数据库集成，并为系统生物学提供真正独特的数据组件。形态发生相关数据集还将为发育中的唾液腺的数学模型提供信息（RO1DE0192444-01，M. Larsen），而分化相关数据集将为人工唾液腺的智能工程识别新的分化标记和途径组件（ R21DE0192444-01，M.拉森）。这项研究将为解释其他正常和患病小鼠和人类颅面组织的未来研究提供所需的基本发育生物学知识基础。最后，拟议的研究将通过直接材料成本（即显微镜、流体、计算机和控制器以及抗体和用品，全部从美国供应商购买）以及通过提供两个新位置来完成抗体标记并成为拉森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。应用于图谱的技术；然而，目前尚未向公共研究界商业化，但该项目将促进这种强大的多重方法向主流研究应用的适应和过渡。拟议的研究将使用新颖的高内涵方法创建唾液腺发育过程中蛋白质表达模式的图谱。这些方法允许在同一样本中检查多个标记，从而允许多个蛋白质在发育阶段真正共定位。这些研究将深入了解唾液腺发育和分化过程中发生的基本信号事件。