One-Tip enables comprehensive proteome coverage in minimal cells and single zygotes

Zilu Ye (), Pierre Sabatier, Javier Martin-Gonzalez, Akihiro Eguchi, Maico Lechner, Ole Østergaard, Jingsheng Xie, Yuan Guo, Lesley Schultz, Rafaela Truffer, Dorte B. Bekker-Jensen, Nicolai Bache and Jesper V. Olsen ()
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Zilu Ye: Chinese Academy of Medical Sciences & Peking Union Medical College
Pierre Sabatier: University of Copenhagen
Javier Martin-Gonzalez: University of Copenhagen
Akihiro Eguchi: University of Copenhagen
Maico Lechner: University of Copenhagen
Ole Østergaard: University of Copenhagen
Jingsheng Xie: Chinese Academy of Medical Sciences & Peking Union Medical College
Yuan Guo: Tecan Group Ltd.
Lesley Schultz: Tecan Group Ltd.
Rafaela Truffer: Tecan Group Ltd.
Dorte B. Bekker-Jensen: Evosep Biosystems
Nicolai Bache: Evosep Biosystems
Jesper V. Olsen: University of Copenhagen

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

Abstract: Abstract Mass spectrometry (MS)-based proteomics workflows typically involve complex, multi-step processes, presenting challenges with sample losses, reproducibility, requiring substantial time and financial investments, and specialized skills. Here we introduce One-Tip, a proteomics methodology that seamlessly integrates efficient, one-pot sample preparation with precise, narrow-window data-independent acquisition (nDIA) analysis. One-Tip substantially simplifies sample processing, enabling the reproducible identification of >9000 proteins from ~1000 HeLa cells. The versatility of One-Tip is highlighted by nDIA identification of ~6000 proteins in single cells from early mouse embryos. Additionally, the study incorporates the Uno Single Cell Dispenser™, demonstrating the capability of One-Tip in single-cell proteomics with >3000 proteins identified per HeLa cell. We also extend One-Tip workflow to analysis of extracellular vesicles (EVs) extracted from blood plasma, demonstrating its high sensitivity by identifying >3000 proteins from 16 ng EV preparation. One-Tip expands capabilities of proteomics, offering greater depth and throughput across a range of sample types.

Date: 2024
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DOI: 10.1038/s41467-024-46777-9

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