化学
色谱法
蛋白质组
蛋白质组学
多路复用
质谱法
赫拉
肽
吞吐量
样品制备
Jurkat细胞
分析化学(期刊)
细胞
T细胞
生物化学
生物信息学
电信
生物
计算机科学
无线
基因
免疫系统
免疫学
作者
Kei G. I. Webber,Thy Truong,S. Madisyn Johnston,Sebastian E. Zapata,Yiran Liang,Jacob M. Davis,Alexander D. Buttars,Fletcher B. Smith,Hailey Jones,Arianna C. Mahoney,Richard H. Carson,Andikan J. Nwosu,Jacob L. Heninger,Andrey Liyu,Gregory P. Nordin,Ying Zhu,Ryan Kelly
标识
DOI:10.1021/acs.analchem.2c00646
摘要
Single-cell proteomics (SCP) has great potential to advance biomedical research and personalized medicine. The sensitivity of such measurements increases with low-flow separations (<100 nL/min) due to improved ionization efficiency, but the time required for sample loading, column washing, and regeneration in these systems can lead to low measurement throughput and inefficient utilization of the mass spectrometer. Herein, we developed a two-column liquid chromatography (LC) system that dramatically increases the throughput of label-free SCP using two parallel subsystems to multiplex sample loading, online desalting, analysis, and column regeneration. The integration of MS1-based feature matching increased proteome coverage when short LC gradients were used. The high-throughput LC system was reproducible between the columns, with a 4% difference in median peptide abundance and a median CV of 18% across 100 replicate analyses of a single-cell-sized peptide standard. An average of 621, 774, 952, and 1622 protein groups were identified with total analysis times of 7, 10, 15, and 30 min, corresponding to a measurement throughput of 206, 144, 96, and 48 samples per day, respectively. When applied to single HeLa cells, we identified nearly 1000 protein groups per cell using 30 min cycles and 660 protein groups per cell for 15 min cycles. We explored the possibility of measuring cancer therapeutic targets with a pilot study comparing the K562 and Jurkat leukemia cell lines. This work demonstrates the feasibility of high-throughput label-free single-cell proteomics.
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