Spatially resolved characterization of proteoforms for functional proteomics

功能蛋白质组学蛋白质型的空间分辨表征

• 批准号: 10256724
• 负责人: Ljiljana Pasa-Tolic
• 金额: $ 30万
• 依托单位: BATTELLE PACIFIC NORTHWEST LABORATORIES
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-08 至 2022-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10256724
• 关键词: 3-Dimensional; Ache; Address; Amino Acid Sequence; Area; Awareness; Bioinformatics; Biology; Bladder; Cell Differentiation process; Cell Separation; Cell physiology; Cells; Chromatin; Chromatography; Complex; Coupling; Custom; DNA Methylation; Data; Databases; Detection; Development; Diabetic Nephropathy; Disease; Dissociation; End stage renal failure; Endothelial Cells; Epigenetic Process; Exposure to; Fourier Transform; Genes; Goals; Health; Histones; Human; Human BioMolecular Atlas Program; Image; Kidney; Lasers; Liquid substance; Liver; Location; Maps; Mass Spectrum Analysis; Measurement; Measures; Methods; Microfluidics; Molecular; Morphology; Multimodal Imaging; Nucleosomes; Organ; Pathogenesis; Pattern; Peptides; Phase; Play; Post-Translational Protein Processing; Preparation; Process; Proteins; Proteolysis; Proteome; Proteomics; RNA methylation; Recovery; Research; Resolution; Role; Sampling; Series; Side; Source; System; Technology; Tissue imaging; Tissues; Toxic Environmental Substances; Transcriptional Regulation; Untranslated RNA; Variant; Visualization software; Work; base; bioinformatics tool; combinatorial; commercialization; cost; data integration; data visualization; design; high throughput analysis; histone modification; human tissue; image processing; image visualization; imaging approach; imaging modality; improved; innovation; interest; laser capture microdissection; mesangial cell; multimodal data; multimodality; nanoDroplet; next generation; novel; open source; podocyte; programs; stoichiometry; tool; transcriptomics; virtual

PROJECT SUMMARY/ABSTARCT Differentiated cells have distinctive patterns of epigenetic marks including various post-translational modifications (PTMs) on histones that may work in concert to control transcriptional programs. Since epigenetic marks are often altered following exposure to environmental toxins and play multiple roles in disease pathogenesis, the ability to measure histones in a tissue and cell context is a major analytical objective and challenge. Mass spectrometry (MS) based proteomics is a powerful tool for characterizing histone alterations in multiplexed and non-targeted fashion. However, conventional bottom-up (i.e. peptide-level) MS cannot provide complete characterization of the stoichiometry and combinations of multiple PTMs, and other combinatorial sources of variation, that collectively make up any single gene's set of proteoforms (i.e. functional units of a proteome). Top-down (i.e. proteoform-level) MS addresses this challenge by omitting the proteolysis and thus allowing access to the functional proteoforms. However, top-down MS suffers from low sensitivity and dynamic range due to challenges in separation and detection of large and low-abundance proteins and laborious purification steps required to achive high proteome coverage. This severely limits our ability to analyze small samples and employ top-down MS to generate proteoform-aware images of tissues required for a deeper understanding of human organ functioning in health and disease. We have recently developed nanodroplet sample preparation (nanoPOTS) for highly sensitive bottom-up proteomics and extended this approach to tissue imaging with 100 µm spatial resolution. Herein, we propose to develop and deploy nanoPOTS-based top-down MS to enable characterization of proteoforms in tissue sections with near single cell resolution. To increase the resolution from thousands of cells to near single cell, we will employ advanced MS imaging (MSI) approaches. MSI data will be cross-referenced with global proteomics data obtained via microscale top-down MS of microdissected tissue regions. The UG3 phase efforts will be focused on histones and kidney as a development platform and leverage a unique combination of microscale top-down LCMS, MSI and novel image processing and visualization tools. In the UH3 phase, we will construct comprehensive proteoform-specific maps of multiple tissue types and facilitate multimodal molecular mapping of specific functional units of the kidney by leveraging the HubMAP Consortium ongoing efforts. Successful completion of this research will allow for comprehensive characterization of the full spectrum of proteoforms in tissues and cells thus addressing an important and under- studied area of biology and critical gap in HuBMAP efforts.

项目概要/摘要 分化细胞具有独特的表观遗传标记模式，包括各种翻译后标记 组蛋白上的修饰（PTM）可能协同控制转录程序。由于表观遗传 接触环境毒素后，标记常常会发生改变，并在疾病中发挥多种作用 发病机制中，测量组织和细胞环境中组蛋白的能力是一个主要的分析目标 挑战。基于质谱 (MS) 的蛋白质组学是表征组蛋白改变的强大工具 多重和非靶向时尚。然而，传统的自下而上（即肽水平）MS 无法提供 多个 PTM 的化学计量和组合以及其他组合的完整表征 变异的来源，共同构成任何单个基因的一组蛋白质（即一个基因的功能单位） 蛋白质组）。自上而下（即蛋白型水平）MS 通过省略蛋白水解来解决这一挑战，从而 允许访问功能性蛋白质形式。然而，自上而下的 MS 存在灵敏度低和动态性差的问题。 由于分离和检测大丰度和低丰度蛋白质的挑战以及费力而导致的范围 实现高蛋白质组覆盖率所需的纯化步骤。这严重限制了我们分析小数据的能力 样本并采用自上而下的 MS 生成更深入研究所需的组织的蛋白质形式感知图像 了解人体器官在健康和疾病中的功能。我们最近开发了纳米液滴 用于高度灵敏的自下而上蛋白质组学的样品制备（nanoPOTS），并将这种方法扩展到组织 空间分辨率为 100 µm 的成像。在此，我们建议开发和部署基于nanoPOTS的自顶向下 MS 能够以接近单细胞的分辨率表征组织切片中的蛋白质形式。为了增加 分辨率从数千个细胞到接近单个细胞，我们将采用先进的 MS 成像 (MSI) 方法。 MSI 数据将与通过微尺度自上而下 MS 获得的全球蛋白质组学数据进行交叉引用 显微解剖的组织区域。 UG3 阶段的工作重点将放在组蛋白和肾脏的开发上 平台并利用微型自上而下 LCMS、MSI 和新颖图像处理的独特组合 和可视化工具。在UH3阶段，我们将构建多种蛋白质的综合蛋白质组特异性图谱。 组织类型并通过利用促进肾脏特定功能单位的多模式分子图谱 HubMAP 联盟正在不断努力。成功完成这项研究将有助于全面了解 组织和细胞中全谱蛋白质的表征，从而解决了一个重要且不足的问题 研究生物学领域和 HuBMAP 工作中的关键差距。