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: 10687330
• 负责人: Ljiljana Pasa-Tolic
• 金额: $ 40万
• 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 2024-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10687330
• 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; mass spectrometric imaging; 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 分化的细胞具有独特的表观遗传标记模式，包括各种翻译后修饰。 组蛋白上的修饰（PTM）可以协同工作以控制转录程序。由于表观遗传 在暴露于环境毒素后，标记经常发生改变，并在疾病中发挥多种作用。 在发病机制中，测量组织和细胞背景中的组蛋白的能力是主要的分析目标， 挑战.基于质谱（MS）的蛋白质组学是表征细胞中组蛋白改变的有力工具。 多路复用和非靶向方式。然而，常规的自下而上（即肽水平）MS不能提供 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蛋白质组（即蛋白质组的功能单位）。 蛋白质组）。自上而下（即蛋白质型水平）MS通过省略蛋白水解解决了这一挑战， 从而能够接触到功能性蛋白质。然而，自顶向下MS具有低灵敏度和动态性的缺点， 由于在分离和检测大的和低丰度的蛋白质方面的挑战， 纯化步骤需要达到高蛋白质组覆盖率。这严重限制了我们分析小规模 样本，并采用自上而下的MS生成更深层次的组织所需的蛋白质组感知图像。 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 用于高灵敏度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 100 μm的空间分辨率。在此，我们建议自上而下开发和部署基于纳米POTS的 MS能够以接近单细胞分辨率表征组织切片中的蛋白质型。增加 为了实现从数千个细胞到近单个细胞的分辨率，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交叉引用， 显微解剖的组织区域。UG 3阶段的工作将集中在组蛋白和肾脏作为一个发展 平台并利用微尺度自上而下的LCMS、MSI和新型图像处理的独特组合 和可视化工具。在UH 3阶段，我们将构建多个蛋白质组的综合蛋白质组特异性图谱， 组织类型，并通过利用 HubMAP Consortium正在努力。这项研究的成功完成将使全面 组织和细胞中蛋白质型的全谱表征，从而解决了一个重要的和不足的问题， 生物学研究领域和HuBMAP努力的关键差距。