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

Claudia Ctortecka (), Natalie M. Clark, Brian W. Boyle, Anjali Seth, D. R. Mani, Namrata D. Udeshi and Steven A. Carr ()
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Claudia Ctortecka: Broad Institute of MIT and Harvard
Natalie M. Clark: Broad Institute of MIT and Harvard
Brian W. Boyle: Broad Institute of MIT and Harvard
Anjali Seth: Cellenion SASU
D. R. Mani: Broad Institute of MIT and Harvard
Namrata D. Udeshi: Broad Institute of MIT and Harvard
Steven A. Carr: Broad Institute of MIT and Harvard

Nature Communications, 2024, vol. 15, issue 1, 1-10

Abstract: 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.

Date: 2024
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DOI: 10.1038/s41467-024-49651-w

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