Fully automated and ultra-high-throughput platform for in-depth single-cell proteomics

用于深入单细胞蛋白质组学的全自动和超高通量平台

基本信息

批准号：
10683998
负责人：
Ryan T Kelly
金额：
$ 33.05万
依托单位：
BRIGHAM YOUNG UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2020
资助国家：
美国
起止时间：
2020-09-05 至 2024-08-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10683998
关键词：
Automation Bar Codes Biochemical Biological Process Biomedical Research Cell Separation Cell physiology Cells Complex Cytometry Development Disease Dissociation Fluorescence-Activated Cell Sorting Genes Health Human Immunohistochemistry Incubated Individual Injections Isotopes Knowledge Label Manuals Mass Spectrum Analysis Measurement Measures Mediating Microdissection Molecular Population Post-Translational Protein Processing Predisposition Preparation Process Proteins Proteome Proteomics RNA Reagent Reproducibility Resolution Running Sampling Surface System Techniques Technology Tissues biological research blind cell type cohort effective therapy flexibility human error laser capture microdissection liquid chromatography mass spectrometry miniaturize nano nanoDroplet nanolitre nanolitre scale next generation novel operation population based protein expression prototype single cell analysis single cell proteins single-cell RNA sequencing tool

项目摘要

PROJECT SUMMARY/ABSTRACT The development of effective therapies to advance human health requires an in-depth molecular-level understanding of cellular processes and dynamic interactions between individual cells. Conventional population- based biochemical measurements provide limited utility, as contributions from individual cells are averaged and crucial information is lost. Direct measurements of the biochemical makeup of single cells are thus needed to characterize cellular transitions, regulatory mechanisms and the contribution of the microenvironment. Single- cell RNA sequencing is making a tremendous impact on biological research, but proteins mediate the bulk of cellular function and the correlation between RNA and protein abundance is often poor. In addition, RNA measurements are unable to inform on important posttranslational modifications that are readily measured by mass spectrometry. Current efforts to directly quantify targeted proteins in single cells such as CyTOF and immunohistochemistry share common shortcomings in that only a limited number of proteins can be analyzed. There is thus an urgent unmet need for technologies capable of directly generating unbiased and in-depth single- cell protein profiles to provide a more complete picture of cellular processes. We recently developed a proof-of- concept platform termed nanoPOTS (Nanodroplet Processing in One pot for Trace Samples) that effectively downscales sample processing volumes to the nanoliter scale to reduce sample losses. In combination with ultrasensitive liquid chromatography-mass spectrometry (LC-MS), nanoPOTS enables global proteome profiling of ~1000 protein groups in individual dissociated cells isolated by cell sorting or small regions of tissue sections isolated by microdissection. Building upon this proof-of-concept platform, our overall objective is to develop a fully automated prototype that yields far greater proteome coverage and throughput than is currently achievable, providing a capability for direct, in-depth and large-scale protein quantification that is analogous to single-cell RNA-seq. Studies in Aim 1 will focus on fully automating sample preparation and decreasing sample processing volumes at least tenfold to further reduce sample losses and increase proteome coverage. Aim 2 will automate sample transfer to the analytical platform and develop a fully automated and ultrasensitive LC-MS workflow with 100% MS utilization efficiency. Aim 3 will extend these advances in sensitivity, throughput and automation to the multiplexed analysis of single cells based on barcoding with unique isobaric labels. We will combine two distinct multiplexing approaches to enable simultaneous analysis of up to 32 samples in a single run. The completed platform will be fully automated, capable of highly quantitative label-free and multiplexed single cell proteome profiling to a depth of >3000 proteins per cell, and will achieve an unprecedented measurement throughput of >300 single cells per day for multiplexed analyses. This will constitute a unique and broadly enabling technology for the acquisition of basic biomedical knowledge.

项目概要/摘要开发有效的疗法来促进人类健康需要深入的分子水平了解细胞过程和单个细胞之间的动态相互作用。常规人口—— 基于生化测量的效用有限，因为单个细胞的贡献是平均的，并且关键信息丢失。因此需要直接测量单细胞的生化组成表征细胞转变、调节机制和微环境的贡献。单身的- 细胞 RNA 测序对生物学研究产生了巨大影响，但蛋白质介导了大部分细胞功能以及 RNA 和蛋白质丰度之间的相关性通常较差。此外，RNA 测量无法告知重要的翻译后修饰，而这些修饰很容易通过质谱分析。目前直接量化单细胞中靶蛋白的努力，例如 CyTOF 和免疫组织化学的共同缺点是只能分析有限数量的蛋白质。因此，迫切需要能够直接生成公正且深入的单一数据的技术。细胞蛋白质谱可提供更完整的细胞过程图谱。我们最近开发了一个证明- 称为 nanoPOTS（微量样品一锅纳米液滴处理）的概念平台，可有效地将样品处理量缩小至纳升规模，以减少样品损失。结合超灵敏液相色谱-质谱 (LC-MS)，nanoPOTS 可实现全局蛋白质组分析通过细胞分选或组织切片小区域分离的单个解离细胞中约 1000 个蛋白质组通过显微解剖分离。在这个概念验证平台的基础上，我们的总体目标是开发一个完全自动化的原型可产生比目前可实现的更大的蛋白质组覆盖率和通量，提供类似于单细胞的直接、深入和大规模蛋白质定量的能力 RNA测序。目标 1 的研究将侧重于全自动样品制备和减少样品处理体积至少十倍，以进一步减少样品损失并增加蛋白质组覆盖率。目标 2 将实现自动化将样品转移到分析平台，并开发全自动且超灵敏的 LC-MS 工作流程 MS利用效率100%。目标 3 将把这些在灵敏度、吞吐量和自动化方面的进步扩展到基于具有独特同量异序标签的条形码的单细胞多重分析。我们将结合两个不同的多重方法可在一次运行中同时分析多达 32 个样品。已完成的平台将完全自动化，能够高度定量无标记和多重单细胞蛋白质组每个细胞 >3000 个蛋白质的深度分析，并将实现前所未有的测量吞吐量每天超过 300 个单细胞用于多重分析。这将构成一项独特且具有广泛应用前景的技术以获得基本的生物医学知识。