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"Cell Surface Capture" Workflow for Label-Free Quantification of the Cell Surface Proteome
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Surfactant-assisted one-pot sample preparation for label-free single-cell proteomics
Chia-Feng Tsai1, Pengfei Zhang1,2, David Scholten3
1Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA.
Communications Biology
|March 2, 2021
Summary
This study introduces SOP-MS, a novel method for single-cell proteomics that minimizes sample loss using a surfactant. This technique enables sensitive, label-free protein quantification from individual cells and rare cell populations.
Area of Science:
- Biochemistry
- Proteomics
- Cell Biology
Background:
- Quantitative global proteome profiling typically requires large cell numbers, limiting analysis of rare cells and obscuring cell heterogeneity.
- Surface adsorption during sample processing leads to significant sample loss in traditional bulk measurements.
Purpose of the Study:
- To develop a sensitive, label-free method for global single-cell proteomics.
- To overcome limitations of bulk measurements and enable proteomic profiling of rare cell populations like circulating tumor cells (CTCs).
Main Methods:
- Development of a surfactant-assisted one-pot sample preparation coupled with mass spectrometry (MS) method named SOP-MS.
- Utilizing a MS-compatible nonionic surfactant (n-Dodecyl-β-D-maltoside) and hydrophobic low-bind surfaces for 'all-in-one' sample preparation.
- Elimination of sample transfer steps to minimize surface adsorption losses.
Main Results:
- SOP-MS enables label-free quantification of hundreds of proteins from single human cells.
- The method can profile approximately 1200 proteins from small tissue sections (~20 cells).
- Application to a patient CTC-derived xenograft (PCDX) model revealed distinct protein signatures between primary and metastatic cells.
Conclusions:
- SOP-MS significantly improves detection sensitivity for single-cell proteomics by reducing sample loss.
- The approach facilitates precise, quantitative proteomic analysis of individual cells and rare cell populations.
- This method paves the way for routine quantitative single-cell proteomics, aiding in understanding cell heterogeneity and disease mechanisms.
