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.

项目摘要/摘要癌症组织表现出高度的表型异质性和可塑性，并包含许多细胞在各种状态下的亚群。在单细胞水平和分子上量化这种异质性大量单元的深度提供了无法在批量尺度上获得的信息，并且将最终导致改进的诊断和更有效的治疗方法。而单细胞核酸测序方法对癌症研究产生了重大影响，蛋白质介导了大部分细胞功能是大多数治疗剂的靶标。因此，迫切需要为大型技术开发新技术在单细胞水平上缩放直接蛋白质组分析。为了填补这一空白，质谱（MS）的分析最近通过实施更有效地证明了单细胞中的蛋白质表达样品处理工作流程，新颖的实验设计和提高的仪器灵敏度。无标签的MS- 基于蛋白质组学现在可以在> 4个数量级的动态级中量化每个细胞> 2,000个蛋白质基团范围，但是每天要介绍超过几十个细胞的努力已导致蛋白质组显着降低覆盖范围。这种低吞吐量不足表征癌细胞种群中异质性。为了增加测量吞吐量，多路复用基于同位串联质量标签（TMT）的工作流程可在LC-中测量多达18个单个单元 MS分析，但这些分析仍然仅限于约100个单元/天，并且通常实施，遭受了缺少价值和其他影响定量性能的问题。我们的总体目标是开发一个平台，将简化的无移液器的高通量样品制剂与快速，多彩色液体色谱分离和“贪婪”数据依赖于概况> 2000 每个细胞的蛋白质每天测量量> 1000个单细胞。我们假设先进的样本准备和分离，结合更有效的MS采集工作流程，将以10倍的吞吐量获得深入的SCP，从而为直接，深度和大规模提供了能力蛋白质定量类似于单细胞RNA-seq。 AIM 1的研究将集中于发展大规模平行离心纳米仪分配以每天总试剂准备> 10,000个单细胞，然后消耗品的成本<$ 0.40/单元。在AIM 2中，我们将发展快速，健壮和高峰值容量20分钟纳米克占空比100％的分离。在AIM 3中，我们将制定一种新颖的“贪婪”数据采集策略仅选择蛋白质型宠物进行碎片化，并具有自定义自动增益控制设置和每种肽的碎裂能，提供了灵敏度和吞吐量的前所未有的组合。使用此下一代平台，我们将介绍> 10,000个细胞以研究获得的自噬的抗性在自噬依赖性三重阴性乳腺癌的背景下抑制剂，从而建立了创新的推进生物医学研究和个性化疗法的平台。