Automated single-cell proteomics providing sufficient proteome depth to study complex biology beyond cell type classifications

自动化单细胞蛋白质组学提供足够的蛋白质组深度来研究超越细胞类型分类的复杂生物学

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作者:Claudia Ctortecka, Natalie M Clark, Brian W Boyle, Anjali Seth, D R Mani, Namrata D Udeshi, Steven A Carr

Abstract

The recent technological and computational advances in mass spectrometry-based single-cell proteomics have pushed the boundaries of sensitivity and throughput. However, reproducible quantification of thousands of proteins within a single cell remains challenging. To address some of those limitations, we present a dedicated sample preparation chip, the proteoCHIP EVO 96 that directly interfaces with the Evosep One. This, in combination with the Bruker timsTOF demonstrates double the identifications without manual sample handling and the newest generation timsTOF Ultra identifies up to 4000 with an average of 3500 protein groups per single HEK-293T without a carrier or match-between runs. Our workflow spans 4 orders of magnitude, identifies over 50 E3 ubiquitin-protein ligases, and profiles key regulatory proteins upon small molecule stimulation. This study demonstrates that the proteoCHIP EVO 96-based sample preparation with the timsTOF Ultra provides sufficient proteome depth to study complex biology beyond cell-type classifications.

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