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Published on: April 24, 2020
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AUTO-SP: Automated Sample Preparation for Analyzing Proteins and Protein Modifications
T Mamie Lih1, Liyuan Jiao1, Lijun Chen1
1Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland 21231, United States.
Analytical Chemistry
|July 28, 2025
Summary
A new automated sample preparation platform, AUTO-SP, streamlines protein digestion and post-translational modification (PTM) enrichment for mass spectrometry. This method ensures reproducible proteomic analysis, identifying thousands of phosphopeptides and ubiquitinated peptides in breast cancer samples.
Area of Science:
- Proteomics
- Biochemistry
- Cancer Research
Background:
- Liquid chromatography tandem mass spectrometry (LC-MS/MS) is vital for studying protein alterations and post-translational modifications (PTMs) in disease.
- Bottom-up proteomics relies on enzymatic digestion of proteins into peptides for MS analysis.
- Reproducible PTM enrichment and protein digestion protocols are crucial for accurate proteomic characterization.
Purpose of the Study:
- To develop AUTO-SP, an automated sample preparation platform for protein digestion and PTM enrichment.
- To demonstrate the efficacy of AUTO-SP using patient-derived xenograft (PDX) breast cancer tissues.
- To enhance the reliability and reproducibility of mass spectrometry-based proteomic and PTM analyses.
Main Methods:
- Development of AUTO-SP for automated Bicinchoninic acid (BCA) analysis, protein digestion, and PTM enrichment.
- Application of AUTO-SP to basal-like and luminal subtype PDX breast cancer tumor tissues.
- Utilizing data-independent acquisition (DIA)-MS for proteomic and PTM analysis.
Main Results:
- AUTO-SP enabled highly correlated proteomic data within the same breast cancer subtypes (correlation coefficient ≥0.98).
- Identification of over 25,000 phosphopeptides and 14,000 ubiquitinated peptides using AUTO-SP.
- Discovery of unique enriched pathways from differentially expressed ubiquitinated peptides between basal-like and luminal subtypes.
Conclusions:
- AUTO-SP provides a reliable and reproducible automated sample preparation solution for MS-based proteomics.
- The platform effectively supports the analysis of protein alterations and PTMs in complex biological samples like cancer tissues.
- AUTO-SP facilitates deeper insights into subtype-specific molecular mechanisms in breast cancer through PTM analysis.
