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Automated processing and manipulation of small samples for high throughput and ultrasensitive functional proteomics measurements

Automated processing and manipulation of small samples for high throughput and ultrasensitive functional proteomics measurements
自动处理和操作小样品,以实现高通量和超灵敏的功能蛋白质组学测量
批准号:
10220049
负责人:
Ryan T Kelly
金额:
$25.11万
依托单位国家:
美国
项目类别:
财政年份:
2003
资助国家:
美国
项目状态:
已结题
起止时间:
2003-09-15 至 2023-07-31

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Project Summary – TR&D 1 The overarching goal of the Resource is to dramatically improve on the existing proteomics paradigm by achieving orders-of-magnitude gains in both measurement sensitivity and throughput, as well as to address important measurement `blind spots' and shortcomings of current methods. At present, a minimum of thousands of cells are generally required for in-depth coverage of proteins in a biological sample, precluding many important applications involving extremely small samples, rare cell types or spatially resolved measurements. We have recently developed a Nanodroplet Processing in One-pot for Trace Samples (nanoPOTS) technology which, when coupled with ultrasensitive MS-based measurements, enables effective analysis of as few as 10 mammalian cells. The technology efforts of TR&D 1 will extend this robotic/microfluidic nanoPOTS platform to provide the `up-front' processing required to efficiently handle ultra-small samples (extending to single cells) and deliver these samples optimally to the Structures for Lossless Ion Manipulations (SLIM)-based ion mobility-mass spectrometry (IM-MS) platforms to be further advanced under TR&D 2. The robotic platform will enable samples to be transferred using nanoelectrospray ionization to the SLIM IM-MS platforms with high ionization and utilization efficiencies. The nanoPOTS platform and workflow will be optimized to enable broad proteome coverage for sample sizes in the range of 1-1000 cells so as to enable broad proteome coverage. The efforts will also establish seamless, automated integration of nanoPOTS with the widely used cell isolation technologies of fluorescence activated cell sorting (FACS) and laser-capture microdissection (LCM), enabling ultra-rare cell analysis and high-resolution proteome mapping of clinical tissues. We will also extend nanoPOTS processing to address the inherently small sample sizes and sensitivity challenges associated with functional proteomics measurements, including activity-based proteomics and measurements of key post-translational modifications such as phosphorylation, using a combination of direct surface functionalization, magnetic bead-based workflows within the nanowells and microcolumn fractionation to enrich and process functional protein subpopulations. We aim to reduce required sample sizes for such functional measurements by more than 100-fold. The efficient processing and greatly reduced sample losses enabled by the nanoPOTS platform will complement the large gains in throughput and sensitivity afforded by TR&D 2 and its fast and high-resolution gas-phase separations and manipulations in SLIM. The workflows to be developed will enable both online and offline separations (e.g., liquid chromatography) with SLIM IM-MS using nanoPOTS-prepared samples. The development of this platform will occur in close collaboration with the TR&D 2 and 3 efforts and is key to most of the driving biological projects.
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Advanced Sample Preparation, Separation and Multiplexed Analysis for In-Depth Proteome Profiling of >1000 Single Cells Per Day
  • 批准号:
    10642310
  • 项目类别:
  • 资助金额:
    $53.04万
  • 财政年份:
    2023
  • 负责人:
    Ryan T Kelly
  • 依托单位:
Fully automated and ultra-high-throughput platform for in-depth single-cell proteomics
  • 批准号:
    10034850
  • 项目类别:
  • 资助金额:
    $33.05万
  • 财政年份:
    2020
  • 负责人:
    Ryan T Kelly
  • 依托单位:
Fully automated and ultra-high-throughput platform for in-depth single-cell proteomics
  • 批准号:
    10796347
  • 项目类别:
  • 资助金额:
    $25.0万
  • 财政年份:
    2020
  • 负责人:
    Ryan T Kelly
  • 依托单位:
Fully automated and ultra-high-throughput platform for in-depth single-cell proteomics
  • 批准号:
    10473767
  • 项目类别:
  • 资助金额:
    $33.05万
  • 财政年份:
    2020
  • 负责人:
    Ryan T Kelly
  • 依托单位:
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