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

基本信息

项目摘要

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

项目成果

期刊论文数量(4)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Spatial top-down proteomics for the functional characterization of human kidney.
用于人类肾脏功能表征的空间自上而下蛋白质组学。
  • DOI:
    10.1101/2024.02.13.580062
  • 发表时间:
    2024
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Zemaitis,KevinJ;Fulcher,JamesM;Kumar,Rashmi;Degnan,DavidJ;Lewis,LoganA;Liao,Yen-Chen;Veličković,Marija;Williams,SarahM;Moore,RonaldJ;Bramer,LisaM;Veličković,Dušan;Zhu,Ying;Zhou,Mowei;Paša-Tolić,Ljiljana
  • 通讯作者:
    Paša-Tolić,Ljiljana
Spatially Resolved Top-Down Proteomics of Tissue Sections Based on a Microfluidic Nanodroplet Sample Preparation Platform.
  • DOI:
    10.1016/j.mcpro.2022.100491
  • 发表时间:
    2023-02
  • 期刊:
  • 影响因子:
    7
  • 作者:
    Liao, Yen -Chen;Fulcher, James M.;Degnan, David J.;Williams, Sarah M.;Bramer, Lisa M.;Velickovic, Dusan;Zemaitis, Kevin J.;Velickovic, Marija;Sontag, Ryan L.;Moore, Ronald J.;Pasa-Tolic, Ljiljana;Zhu, Ying;Zhou, Mowei
  • 通讯作者:
    Zhou, Mowei
193 nm Ultraviolet Photodissociation for the Characterization of Singly Charged Proteoforms Generated by MALDI.
193 nm 紫外光解离用于表征 MALDI 生成的单电荷蛋白质形式。
Enhanced Spatial Mapping of Histone Proteoforms in Human Kidney Through MALDI-MSI by High-Field UHMR-Orbitrap Detection.
  • DOI:
    10.1021/acs.analchem.2c01034
  • 发表时间:
    2022-09-20
  • 期刊:
  • 影响因子:
    7.4
  • 作者:
    Zemaitis, Kevin J.;Velickovic, Dusan;Kew, William;Fort, Kyle L.;Reinhardt-Szyba, Maria;Pamreddy, Annapurna;Ding, Yanli;Kaushik, Dharam;Sharma, Kumar;Makarov, Alexander A.;Zhou, Mowei;Pasa-Tolic, Ljiljana
  • 通讯作者:
    Pasa-Tolic, Ljiljana
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Ljiljana Pasa-Tolic其他文献

Ljiljana Pasa-Tolic的其他文献

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{{ truncateString('Ljiljana Pasa-Tolic', 18)}}的其他基金

Massive single cell proteomics for cancer biology
用于癌症生物学的大规模单细胞蛋白质组学
  • 批准号:
    10707321
  • 财政年份:
    2022
  • 资助金额:
    $ 60万
  • 项目类别:
Spatially-resolved proteome mapping of senescent cells and their tissue microenvironment at single-cell resolution
单细胞分辨率下衰老细胞及其组织微环境的空间分辨蛋白质组图谱
  • 批准号:
    10684865
  • 财政年份:
    2022
  • 资助金额:
    $ 60万
  • 项目类别:
Spatially-resolved proteome mapping of senescent cells and their tissue microenvironment at single-cell resolution
单细胞分辨率下衰老细胞及其组织微环境的空间分辨蛋白质组图谱
  • 批准号:
    10552842
  • 财政年份:
    2022
  • 资助金额:
    $ 60万
  • 项目类别:
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
  • 财政年份:
    2020
  • 资助金额:
    $ 60万
  • 项目类别:
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:
    10118771
  • 财政年份:
    2020
  • 资助金额:
    $ 60万
  • 项目类别:
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
  • 财政年份:
    2020
  • 资助金额:
    $ 60万
  • 项目类别:

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