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"Cell Surface Capture" Workflow for Label-Free Quantification of the Cell Surface Proteome
Published on: March 24, 2023
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"Cell Surface Capture" Workflow for Label-Free Quantification of the Cell Surface Proteome
Akul Naik1, Sanjeeva Srivastava2, Arun P Wiita3
1Department of Laboratory Medicine, University of California, San Francisco.
Journal of Visualized Experiments : Jove
|April 10, 2023
Summary
This study presents a workflow to enrich and analyze cell surface proteins (surfaceome) from cancer cells using mass spectrometry. This method overcomes challenges in identifying disease-specific surface proteins for diagnostics and therapeutics.
Area of Science:
- Proteomics
- Cell Biology
- Biochemistry
Background:
- Mass spectrometry-based proteomics has advanced biological system characterization.
- The cell surface proteome (surfaceome) is crucial for understanding human diseases and developing therapeutics.
- Analyzing the surfaceome is challenging due to high-abundance proteins masking low-abundance targets in cell lysates.
Purpose of the Study:
- To develop and present a detailed workflow for the accurate characterization of the cell surface proteome.
- To overcome the technical limitations in analyzing membrane and surface proteins.
- To enable precise definition of the cell surface proteome for various cell types.
Main Methods:
- A workflow for labeling cell surface proteins from cancer cells.
- Enrichment of labeled cell surface proteins from complex cell lysates.
- Sample preparation optimized for subsequent mass spectrometry analysis.
Main Results:
- A robust method for isolating and preparing cell surface proteins.
- Improved identification of cell surface proteins in cancer cells.
- Demonstration of a workflow to overcome abundance challenges in surfaceome analysis.
Conclusions:
- The presented workflow enables accurate mass spectrometry-based characterization of the cell surface proteome.
- This method facilitates the identification of potential diagnostic markers and therapeutic targets.
- The workflow addresses a critical technical barrier in surfaceome research.

