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Automated Coupling of Nanodroplet Sample Preparation with Liquid Chromatography-Mass Spectrometry for High-Throughput Single-Cell Proteomics.
Analytical Chemistry ( IF 6.7 ) Pub Date : 2020-07-08 , DOI: 10.1021/acs.analchem.0c01551
Sarah M Williams 1 , Andrey V Liyu 1 , Chia-Feng Tsai 2 , Ronald J Moore 2 , Daniel J Orton 2 , William B Chrisler 2 , Matthew J Gaffrey 2 , Tao Liu 2 , Richard D Smith 2 , Ryan T Kelly 1, 3 , Ljiljana Pasa-Tolic 1 , Ying Zhu 1
Affiliation  

Single-cell proteomics can provide critical biological insight into the cellular heterogeneity that is masked by bulk-scale analysis. We have developed a nanoPOTS (nanodroplet processing in one pot for trace samples) platform and demonstrated its broad applicability for single-cell proteomics. However, because of nanoliter-scale sample volumes, the nanoPOTS platform is not compatible with automated LC-MS systems, which significantly limits sample throughput and robustness. To address this challenge, we have developed a nanoPOTS autosampler allowing fully automated sample injection from nanowells to LC-MS systems. We also developed a sample drying, extraction, and loading workflow to enable reproducible and reliable sample injection. The sequential analysis of 20 samples containing 10 ng tryptic peptides demonstrated high reproducibility with correlation coefficients of >0.995 between any two samples. The nanoPOTS autosampler can provide analysis throughput of 9.6, 16, and 24 single cells per day using 120, 60, and 30 min LC gradients, respectively. As a demonstration for single-cell proteomics, the autosampler was first applied to profiling protein expression in single MCF10A cells using a label-free approach. At a throughput of 24 single cells per day, an average of 256 proteins was identified from each cell and the number was increased to 731 when the Match Between Runs algorithm of MaxQuant was used. Using a multiplexed isobaric labeling approach (TMT-11plex), ∼77 single cells could be analyzed per day. We analyzed 152 cells from three acute myeloid leukemia cell lines, resulting in a total of 2558 identified proteins with 1465 proteins quantifiable (70% valid values) across the 152 cells. These data showed quantitative single-cell proteomics can cluster cells to distinct groups and reveal functionally distinct differences.

中文翻译:

纳米液滴样品制备与液相色谱-质谱联用,用于高通量单细胞蛋白质组学。

单细胞蛋白质组学可以为被批量分析掩盖的细胞异质性提供重要的生物学洞察力。我们开发了一个 nanoPOTS(用于痕量样品的一锅纳米液滴处理)平台,并证明了其在单细胞蛋白质组学中的广泛适用性。然而,由于纳升级样品体积,nanoPOTS 平台与自动化 LC-MS 系统不兼容,这显着限制了样品通量和稳定性。为了应对这一挑战,我们开发了一种 nanoPOTS 自动进样器,允许从纳米孔到 LC-MS 系统的全自动样品注射。我们还开发了样品干燥、萃取和加载工作流程,以实现可重现和可靠的样品注射。对含有 10 ng 胰蛋白酶肽的 20 个样品进行的连续分析表明,任意两个样品之间的相关系数 >0.995 具有很高的重现性。nanoPOTS 自动进样器可以分别使用 120、60 和 30 分钟的 LC 梯度提供每天 9.6、16 和 24 个单细胞的分析通量。作为单细胞蛋白质组学的演示,自动进样器首先用于使用无标记方法分析单个 MCF10A 细胞中的蛋白质表达。在每天 24 个单细胞的通量下,从每个细胞中平均鉴定出 256 种蛋白质,当使用 MaxQuant 的运行匹配算法时,数量增加到 731。使用多重等压标记方法 (TMT-11plex),每天可以分析约 77 个单细胞。我们分析了来自三个急性髓系白血病细胞系的 152 个细胞,总共有 2558 个鉴定的蛋白质,其中 152 个细胞中有 1465 个可量化的蛋白质(70% 的有效值)。这些数据表明定量单细胞蛋白质组学可以将细胞聚集到不同的组中,并揭示功能上的不同差异。
更新日期:2020-08-04
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