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.

项目总结/ ABSTARCT