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

• 批准号: 10796347
• 负责人: Ryan T Kelly
• 金额: $ 25万
• 依托单位: BRIGHAM YOUNG UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-05 至 2024-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10796347
• 关键词: Automation; Bar Codes; Biochemical; Cell Separation; Cell physiology; Cells; Development; Dissociation; Health; Human; Immunohistochemistry; Individual; Knowledge; Label; Mass Spectrum Analysis; Measurement; Measures; Mediating; Microdissection; Molecular; Population; Post-Translational Protein Processing; Preparation; Proteins; Proteome; Proteomics; RNA; Running; Sampling; Technology; Tissues; biological research; effective therapy; liquid chromatography mass spectrometry; nanoDroplet; nanolitre scale; population based; protein expression; prototype; single cell analysis; single cell proteins; single-cell RNA sequencing

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.

项目总结/摘要 开发有效的治疗方法以促进人类健康需要深入的分子水平 理解细胞过程和单个细胞之间的动态相互作用。传统人群- 基于生物化学的测量提供有限的效用，因为来自单个细胞的贡献被平均， 关键信息丢失。因此，需要直接测量单细胞的生化组成， 表征细胞过渡，调节机制和微环境的贡献。单身- 细胞RNA测序对生物学研究产生了巨大的影响，但蛋白质介导了大部分的 细胞功能以及RNA和蛋白质丰度之间的相关性通常很差。此外，RNA 测量无法告知重要的翻译后修饰，这些修饰可以通过 质谱分析法来目前直接定量单细胞中靶向蛋白质的努力，如CyTOF和 免疫组织化学共有的共同缺点是只能分析有限数量的蛋白质。 因此，迫切需要能够直接产生无偏见和深入的单- 细胞蛋白质谱，以提供细胞过程的更完整的图片。我们最近发明了一种 概念平台称为nanoPOTS（纳米液滴处理在一锅微量样品），有效地 将样品处理体积缩小到纳升规模，以减少样品损失。结合 超灵敏液相色谱-质谱（LC-MS），nanoPOTS使全球蛋白质组分析成为可能 通过细胞分选或组织切片的小区域分离的单个解离细胞中约1000个蛋白质组 通过显微切割分离。基于这个概念验证平台，我们的总体目标是开发一个 全自动化的原型，产生比目前可实现的更大的蛋白质组覆盖率和通量， 提供直接、深入和大规模蛋白质定量的能力，类似于单细胞 RNA测序目标1的研究将侧重于完全自动化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和增加蛋白质组覆盖率。Aim 2将自动化 将样品转移到分析平台，并开发全自动和超灵敏的LC-MS工作流程， 100%的MS利用效率。Aim 3将把这些在灵敏度、通量和自动化方面的进步扩展到 基于具有独特同量异序标记的条形码化的单细胞的多重分析。我们将联合收割机 多路复用方法，能够在单次运行中同时分析多达32个样品。完成的 平台将是完全自动化的，能够高度定量的无标记和多重单细胞蛋白质组 分析深度可达每个细胞>3000个蛋白质，并将实现前所未有的测量通量 每天>300个单细胞进行多重分析。这将构成一种独特的、广泛适用的技术 获取基本的生物医学知识。