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Parallel sample processing for mass spectrometry-based single cell proteomics
Jing Wang1, Bo Xue2, Olanrewaju Awoyemi1
1C. Eugene Bennett Department of Chemistry, West Virginia University, Morgantown, WV, USA.
Analytica Chimica Acta
|October 13, 2024
Summary
This study introduces a novel parallel sample processing workflow for single-cell mass spectrometry (scMS) that avoids expensive robotic liquid handlers. This innovation significantly enhances throughput and accessibility for single-cell proteomics research.
Area of Science:
- Proteomics
- Analytical Chemistry
- Biotechnology
Background:
- Single-cell mass spectrometry (scMS) is a powerful technique for label-free proteomics.
- Current scMS workflows often rely on costly robotic liquid handlers, limiting throughput and adoption.
- Sequential sample processing in existing methods restricts overall efficiency.
Purpose of the Study:
- To develop a cost-effective, high-throughput parallel sample processing workflow for scMS.
- To eliminate the need for specialized robotic liquid handling equipment.
- To enable broader accessibility of single-cell proteomics.
Main Methods:
- A 3D-printed microfluidic device was used to create reagent arrays on a glass slide.
- A streamlined, magnetic bead-based protocol was employed for sample preparation.
- The workflow was optimized for processing 10 single cells in parallel.
Main Results:
- Demonstrated consistent quantification across 10 simultaneously processed single-cell samples.
- Successfully differentiated between distinct cell lines using the developed method.
- Showcased the ability to analyze proteome changes induced by drug treatments.
Conclusions:
- The developed method enables parallel sample processing for scMS without expensive liquid handlers.
- This approach significantly improves throughput and reduces the cost barrier for single-cell proteomics.
- The workflow holds great potential for advancing single-cell proteomic analyses.
