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Robust ultra-high sensitivity proteomic technologies for limited samples

Robust ultra-high sensitivity proteomic technologies for limited samples
适用于有限样品的稳健超高灵敏度蛋白质组技术
批准号:
10388993
负责人:
Alexander R. Ivanov
金额:
$1.26万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2020
资助国家:
美国
项目状态:
未结题
起止时间:
2020-07-01 至 2025-06-30

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中文摘要
翻译
项目总结 大多数高度多样化的生物过程是通过蛋白质、蛋白质翻译后 修饰/蛋白形式、蛋白质相互作用、PI(例如,蛋白质-蛋白质、PPI、蛋白质-配体、PLI)以及 这种相互作用的丰度、活性、功能和完整性的异常可能导致严重的疾病, 包括癌症。此外,通过新的靶向治疗来破坏这些基于蛋白质的特征 在个体化药物治疗方法中,可作为这些药物反应的重要生物标志物。临床 生物标本往往数量有限,这大大阻碍了在这方面的进展。 诊断学、治疗发展和生物医学研究。含有稀有物质的显微活检和液体活检 循环肿瘤细胞、造血干细胞(HSCs)和免疫细胞等细胞群可能 只包含几千或数百个细胞,并且是异质的。学习传统技术 蛋白质组图谱、蛋白质形式、蛋白质复合体和PPI(例如,常规蛋白质组学、核磁共振、X射线 结晶学、酵母双杂交筛选和免疫亲和纯化(IP)-质谱学 (MS))不能很容易地用于分析小细胞群体、显微镜临床样本和 单个细胞主要是由于敏感性的限制。因此,许多生物学和临床相关的研究 由于缺乏对如此低水平样品的技术,因此没有进行。在此,我们建议 开发分析平台,实现对稀缺样品的高灵敏度分析 消化、完整的蛋白形式和天然的复合体。这一任务将要求小说的发展 样品制备、超低流液相分离与MS、MS数据对接的方法 数据采集和数据分析。开发这种彻底分析微尺度样品的新方法 并将它们集成到能够高效和高灵敏度的创新的“即插即用”自动化平台中 利用MS对完整的蛋白质形式、蛋白质复合体和PTMS进行表征将是获得 对该病分子机制的生物学见解以及治疗靶点和 用于诊断和预后目的的生物标记物。开发的平台将使用Well-Well- 受控模型系统,并应用于最临床相关的环境中以检查(1)模型系统 细胞分化和激活;(2)转录因子STAT3的相互作用组和生物学作用 它在绝大多数卵巢癌细胞系和原代样本中异常激活;以及(2) MHC相关的新生儿肽。
英文摘要
PROJECT SUMMARY The majority of highly diverse biological processes are enabled through proteins, protein post-translational modifications/proteoforms, protein interactions, PIs (e.g., protein-protein, PPIs, protein- ligand, PLIs), and aberrations of abundances, activities, functions, and integrity of such interactions can lead to severe diseases, including cancer. Furthermore, disruption of these protein-based characteristics by novel targeted therapies can be an important biomarker for the response to these drugs in personalized medicine approaches. Clinical and biological specimens are often available in limited amounts, which greatly hampers the progress in diagnostics, therapy development, and biomedical research. Microbiopsy and liquid biopsies containing rare cell populations such as circulating tumor cells, hematopoietic stem cells (HSCs) and immune cells may contain only low thousands or hundreds of cells and be heterogeneous. Traditional techniques to study proteomic profiles, proteoforms, protein complexes, and PPIs (e.g., conventional proteomics, NMR, X-ray crystallography, yeast two-hybrid screening and immunoaffinity purification (IP) followed by mass spectrometry (MS)) cannot be readily used for the analysis of small cell populations, microscopic clinical samples and individual cells mainly due to limitations in sensitivity. Therefore, many biological and clinically relevant studies are not undertaken because of the lack of technology for such low level samples. Here, we propose to develop analytical platforms that will enable high sensitivity analysis of scarce samples at the level of digests, intact proteoforms, and native complexes. This task will demand the development of novel approaches in sample preparation, ulra-low flow liquid phase separations interfaced with MS, MS data acquisition, and data analysis. Developing such novel methods for thorough profiling of microscale samples and integrating them in innovative “plug-and-play” automated platforms capable of efficient and high sensitivity characterization of intact proteoforms, protein complexes and PTMs by MS will be highly desirable for gaining biological insights into molecular mechanisms of the disease and discovery of therapeutic targets and biomarkers for diagnostic and prognostic purposes. The developed platforms will be evaluated using well- controlled model systems and applied in the most clinically relevant settings to examine (1) model systems for cell differentiation and activation; (2) the interactome and biological role of STAT3, the transcription factor which is aberrantly activated in the vast majority of ovarian cancer cell lines and primary samples; and (2) MHC-associated neontigenic peptides.
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Robust ultra-high sensitivity proteomic technologies for limited samples
  • 批准号:
    10202666
  • 项目类别:
  • 资助金额:
    $41.18万
  • 财政年份:
    2020
  • 负责人:
    Alexander R. Ivanov
  • 依托单位:
Robust ultra-high sensitivity proteomic technologies for limited samples
  • 批准号:
    10448500
  • 项目类别:
  • 资助金额:
    $41.18万
  • 财政年份:
    2020
  • 负责人:
    Alexander R. Ivanov
  • 依托单位:
Robust ultra-high sensitivity proteomic technologies for limited samples
  • 批准号:
    10580146
  • 项目类别:
  • 资助金额:
    $24.1万
  • 财政年份:
    2020
  • 负责人:
    Alexander R. Ivanov
  • 依托单位:
Robust ultra-high sensitivity proteomic technologies for limited samples
  • 批准号:
    10660980
  • 项目类别:
  • 资助金额:
    $41.18万
  • 财政年份:
    2020
  • 负责人:
    Alexander R. Ivanov
  • 依托单位:
海外基金