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Phosphopeptide Enrichment Coupled with Label-free Quantitative Mass Spectrometry to Investigate the Phosphoproteome in Prostate Cancer
Published on: August 2, 2018
R2HaPpY: Rapid-robust phosphotyrosine peptide enrichment using HaloTag-Src SH2 pY superbinder
Alexis Chang1, Ricard A Rodriguez-Mias1, Matthew D Berg1
1Department of Genome Sciences, University of Washington, Seattle, USA, 98105.
We developed a faster, cheaper method to study phosphotyrosine signaling. This new technique efficiently enriches phosphotyrosine peptides, enabling comprehensive analysis of signaling pathways in cells.
Area of Science:
- Molecular Biology
- Cell Signaling
- Biochemistry
Background:
- Phosphotyrosine signaling is crucial for cellular functions like proliferation and immune response.
- Analyzing phosphotyrosine signaling comprehensively is challenging due to expensive reagents and complex protocols.
- Previous automated methods improved sample preparation but reagent preparation remained a bottleneck.
Purpose of the Study:
- To optimize an automated phosphotyrosine enrichment method for faster and more cost-effective reagent preparation.
- To enhance the efficiency of phosphotyrosine peptide binding for improved detection sensitivity.
- To enable a more comprehensive and quantitative analysis of tyrosine phosphorylation dynamics.
Main Methods:
- Fused an SH2 phosphotyrosine superbinder to the HaloTag protein for reagent development.
- Developed a method for cost-effective preparation of enrichment beads directly from bacterial lysate.
- Applied the optimized method to analyze phosphotyrosine sites in EGF-stimulated HeLa cells.
Main Results:
- Expedited reagent preparation from days to hours.
- Achieved higher binding efficiency for phosphotyrosine peptides compared to existing reagents.
- Detected and quantified 1,651 unique phosphotyrosine sites, including 878 regulated sites, with ~1 mg of input peptides.
Conclusions:
- The streamlined and sensitive method significantly improves the efficiency of phosphotyrosine enrichment.
- This approach facilitates comprehensive mapping of tyrosine phosphorylation dynamics.
- Enables broader integration of phosphotyrosine signaling data into multiomic and network models for diverse biological studies.
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