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Advanced Sample Preparation, Separation and Multiplexed Analysis for In-Depth Proteome Profiling of >1000 Single Cells Per Day

先进的样品制备、分离和多重分析，每天对超过 1000 个单细胞进行深入的蛋白质组分析

基本信息

批准号：
10642310
负责人：
Ryan T Kelly
金额：
$ 53.04万
依托单位：
BRIGHAM YOUNG UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2023
资助国家：
美国
起止时间：
2023-08-01 至 2026-07-31
项目状态：
未结题

项目摘要

PROJECT SUMMARY/ABSTRACT Cancer tissues exhibit a high degree of phenotypic heterogeneity and plasticity and contain numerous subpopulations of cells in various states. Quantifying this heterogeneity at the single-cell level and with molecular depth across large numbers of cells provides information that cannot be obtained at the bulk scale and will ultimately lead to improved diagnostics and more effective treatments. While single-cell nucleic acid sequencing approaches are having a significant impact on cancer research, proteins mediate the bulk of cellular function and are the targets of most therapeutics. There is thus an urgent need to develop new technologies for large- scale direct proteome profiling at the single-cell level. To fill this gap, mass spectrometry (MS)-based profiling of protein expression in single cells has recently been demonstrated through the implementation of more efficient sample processing workflows, novel experimental designs and improved instrument sensitivity. Label-free MS- based proteomics can now quantify >2,000 protein groups per cell across >4 orders of magnitude of dynamic range, but efforts to profile more than a few dozen cells per day have resulted in significantly reduced proteome coverage. This low throughput is insufficient for the large-scale statistically powered studies required to characterize heterogeneity in cancer cell populations. To increase measurement throughput, multiplexed workflows based on isobaric tandem mass tags (TMTs) enable up to 18 single cells to be measured in an LC- MS analysis, but these have still been limited to ~100 cells/day and, as generally implemented, suffer from a large proportion of missing values and other issues affecting quantitative performance. Our overall objective is to develop a platform that combines simplified pipette-free high-throughput sample preparation with rapid, multicolumn liquid chromatography separations and ‘greedy’ data-dependent acquisition to profile >2000 proteins per cell with a measurement throughput of >1000 single cells per day. We hypothesize that the advanced sample preparation and separation, combined with a far more efficient MS acquisition workflow, will achieve in-depth SCP with a 10× throughput gain, thus 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 developing massively parallel centrifugal nanoliter dispensing to prepare >10,000 single-cells per day at a total reagent and consumables cost of <$0.40/cell. In Aim 2, we will develop rapid, robust and high-peak-capacity 20-min nanoLC separations with 100% duty cycle. In Aim 3, we will develop a novel ‘greedy’ data acquisition strategy in which only proteotypic peptides are selected for fragmentation, and with custom automatic gain control settings and fragmentation energy for each peptide, providing an unprecedented combination of sensitivity and throughput. With this next-generation platform, we will profile >10,000 cells to study acquired resistance to autophagy inhibitors in the context of autophagy-dependent triple negative breast cancer, thus establishing an innovative platform for advancing biomedical research and individualizing therapy.

项目总结/摘要癌组织表现出高度的表型异质性和可塑性，并且含有大量的癌基因。不同状态的细胞亚群。在单细胞水平和分子水平上定量这种异质性，大量单元的深度提供了在批量规模下无法获得的信息，最终导致更好的诊断和更有效的治疗。而单细胞核酸测序方法对癌症研究产生重大影响，蛋白质介导大部分细胞功能并且是大多数疗法的靶点。因此，迫切需要开发新的技术，用于大规模生产。在单细胞水平上进行直接蛋白质组分析。为了填补这一空白，基于质谱（MS）的分析，最近已经通过实施更有效的方法证明了单细胞中的蛋白质表达样品处理流程、新颖的实验设计和改进的仪器灵敏度。无标记MS- 基于蛋白质组学的蛋白质组学现在可以在>4个数量级的动态范围内量化每个细胞> 2，000个蛋白质组范围，但每天对几十个细胞进行分析的努力导致蛋白质组显著减少，覆盖这种低通量不足以进行所需的大规模统计功效研究，表征癌细胞群体的异质性。为了增加测量吞吐量，基于同量异位串联质量标签（TMT）的工作流程能够在LC中测量多达18个单细胞， MS分析，但是这些仍然被限制在~100个细胞/天，并且如通常实施的那样，遭受了大部分缺失值和其他影响定量性能的问题。我们的总体目标是为了开发一种平台，该平台将简化的无移液管高通量样品制备与快速，多柱液相色谱分离和“贪婪”数据依赖采集，以实现>2000的配置文件每个细胞的蛋白质，测量通量>1000个单细胞/天。我们假设先进的样品制备和分离，结合更高效的MS采集工作流程，以10倍的吞吐量增益实现深度SCP，从而提供直接、深度和大规模的能力类似于单细胞RNA-seq的蛋白质定量。目标1的研究将侧重于开发大规模并行离心纳升分配，以每天制备> 10，000个单细胞，总试剂和消耗品成本<0.40美元/电池。在目标2中，我们将开发快速，耐用和高峰值容量的20分钟nanoLC 100%占空比的分离。在目标3中，我们将开发一种新的“贪婪”数据采集策略，只有蛋白型肽被选择用于片段化，并且具有定制的自动增益控制设置，这是一种针对每个肽的片段化能量，提供了灵敏度和通量的前所未有的组合。有了这个下一代平台，我们将分析> 10，000个细胞，以研究对自噬的获得性抗性自噬依赖性三阴性乳腺癌背景下的抑制剂，从而建立了一个创新的这是推进生物医学研究和个性化治疗的平台。