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Updated: Jun 11, 2026

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Large-scale Top-down Proteomics Using Capillary Zone Electrophoresis Tandem Mass Spectrometry
Published on: October 24, 2018
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Bottom-Up Proteomics: Advancements in Sample Preparation.
1College of Pharmacy, Gachon University, Incheon 21936, Republic of Korea.
International Journal of Molecular Sciences
|March 29, 2023
Summary
Liquid chromatography-tandem mass spectrometry (LC-MS/MS) proteomics relies heavily on sample preparation, which remains a bottleneck. This review explores novel methods to improve efficiency, throughput, and reproducibility in proteomic sample preparation.
Area of Science:
- Biochemistry
- Analytical Chemistry
- Molecular Biology
Background:
- Liquid chromatography-tandem mass spectrometry (LC-MS/MS) is vital for proteome profiling.
- Proteomic workflows involve sample preparation, LC-MS/MS analysis, and data analysis.
- Sample preparation is a critical yet challenging step, often limiting study efficiency and reproducibility.
Purpose of the Study:
- To review current sample preparation methods in proteomics.
- To highlight novel techniques that enhance efficiency and throughput.
- To discuss integrated approaches for sample preparation and fractionation.
Main Methods:
- Review of established methods: in-solution digestion and filter-aided sample preparation.
- Exploration of advanced techniques: on-membrane digestion, bead-based digestion, immobilized enzymatic digestion, and suspension trapping.
- Discussion of integrated devices and methods for combining sample preparation and peptide fractionation.
Main Results:
- Sample preparation significantly impacts proteomic study outcomes.
- Novel methods aim to reduce labor, increase throughput, and improve reproducibility.
- Integration of sample preparation and fractionation offers streamlined workflows.
Conclusions:
- Improving sample preparation is key to advancing LC-MS/MS proteomics.
- Emerging techniques show promise for overcoming current limitations.
- Further development in integrated systems can enhance overall proteomic analysis efficiency.

