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Updated: Apr 28, 2026
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Deep Proteome Profiling by Isobaric Labeling, Extensive Liquid Chromatography, Mass Spectrometry, and Software-assisted Quantification
Published on: November 15, 2017
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Mass spectrometry-driven phosphoproteomics: patterning the systems biology mosaic
Martin A Jünger1, Ruedi Aebersold
1Department of Biology, Institute of Molecular Systems Biology, Zurich, Switzerland.
Summary
Phosphoproteomics, the study of protein phosphorylation, uses mass spectrometry to identify and map phosphorylation sites. This research outlines methods to enhance the scope, reliability, and data content of phosphoproteomic analyses.
Area of Science:
- Biochemistry
- Proteomics
- Molecular Biology
Background:
- Protein phosphorylation is a crucial posttranslational modification regulating diverse biological processes.
- Phosphoproteomics, the large-scale analysis of protein phosphorylation, employs mass spectrometry (MS)-based strategies.
- MS-based phosphoproteomics can be performed in discovery (shotgun) or targeted modes.
Purpose of the Study:
- To delineate experimental strategies for optimizing phosphoproteomic analyses.
- To enhance the scope, reliability, and information content of phosphoproteomic studies.
- To provide a comprehensive overview of phosphoproteomics methodologies.
Main Methods:
- Utilizing various chromatographic and chemical protocols for phosphopeptide enrichment.
- Employing mass spectrometry with fragmentation techniques (CID, ETD, HCD) for phosphopeptide identification and site localization.
- Leveraging computational tools for data analysis, database deposition, and biological interpretation.
Main Results:
- Established experimental levels for optimizing phosphoproteomic scope and reliability.
- Detailed various enrichment, MS fragmentation, and computational analysis strategies.
- Highlighted the importance of orthogonal approaches for validating phosphorylation sites.
Conclusions:
- Optimized phosphoproteomic analyses require careful consideration of experimental design and methodologies.
- Computational tools and data integration are vital for extracting biological insights from phosphoproteomic datasets.
- Orthogonal validation is essential for confirming newly identified phosphorylation sites.
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