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"Cell Surface Capture" Workflow for Label-Free Quantification of the Cell Surface Proteome
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High-Throughput Workflow for Detergent-free Cell-Based Proteomic Characterization
Saeed Seyedmohammad1, Alejandro Rivas1, Maxim Zhgamadze1
1Smidt Heart Institute, Advanced Clinical Biosystems Research Institute, Cedars-Sinai Medical 7 Center, 8700 Beverly Blvd, Los Angeles 90048, California, United States.
Journal of Proteome Research
|April 21, 2025
Summary
A new automated workflow enables high-throughput (HTP) protein quantification using liquid chromatography-mass spectrometry (LC-MS) in just 4 hours per 96-well plate. This method efficiently processes cells for large-scale studies, identifying thousands of proteins with high reproducibility.
Area of Science:
- Proteomics
- Biochemistry
- Cell Biology
Background:
- High-throughput (HTP) protein quantification is crucial for large-scale biological studies.
- Current methods can be time-consuming and labor-intensive, limiting scalability.
- Automated workflows are needed to accelerate proteomic analyses.
Purpose of the Study:
- To develop an automated, high-throughput cell-based workflow for protein quantification using liquid chromatography-mass spectrometry (LC-MS).
- To enable large-scale perturbation studies in a 96-well plate format.
- To optimize cell lysis, protein solubilization, and peptide preparation for rapid analysis.
Main Methods:
- Utilized adaptive focused acoustics (AFA) for automated cell lysis and protein solubilization in a 96-well plate format.
- Integrated protein processing into tryptic peptides within 2 hours on an automated liquid handling platform.
- Employed data-independent acquisition mass spectrometry (DIA-MS) for protein quantification.
Main Results:
- Successfully quantified over 5100 unique proteins from AC16 human cardiomyocyte-like cells.
- Achieved high throughput, processing one 96-well plate in approximately 4 hours.
- Demonstrated high reproducibility, with 50% of measured proteins showing a coefficient of variation (CV) under 25% from ~30,000 cells.
- Identified over 30,000 peptides in total.
- An optimized detergent-free buffer yielded comparable results, identifying 5000 proteins with 40% having a CV under 25%.
Conclusions:
- The developed automated workflow significantly enhances throughput for cell-based protein quantification via LC-MS.
- This HTP approach is suitable for large-scale perturbation studies and complex biological investigations.
- The workflow demonstrates robust protein identification and quantification with high reproducibility.

