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Published on: April 17, 2012
Single chain variable fragment displaying M13 phage library functionalized magnetic microsphere-based protein
Guijie Zhu1, Peng Zhao, Nan Deng
1Key Laboratory of Separation Science for Analytical Chemistry, National Chromatographic R. and A. Center, Dalian Institute of Chemical Physics, The Chinese Academy of Science, Dalian, China.
Magnetic microspheres functionalized with M13 phage single chain variable fragments (scFv) effectively reduced high-abundance proteins in human serum. This protein equalizer method improved overall protein identification by 100% in proteomic analysis.
Area of Science:
- Proteomics
- Biotechnology
- Analytical Chemistry
Background:
- Human serum proteomic analysis is challenging due to the high abundance of a few proteins masking low-abundance ones.
- Existing methods for high-abundance protein depletion often face limitations in efficiency and scope.
Purpose of the Study:
- To develop and evaluate a novel magnetic microsphere-based system for efficient depletion of high-abundance proteins in human serum.
- To assess the impact of this depletion method on subsequent proteomic identification.
Main Methods:
- Covalent immobilization of M13 phage single chain variable fragment (scFv) library onto magnetic microspheres (scFv@M13@MM).
- Incubation of scFv@M13@MM with human serum, followed by sequential elution of captured proteins.
- Analysis of eluates using SDS-PAGE and 2D-strong cation exchange-RPLC-ESI-MS/MS after trypsin digestion.
Main Results:
- scFv@M13@MM treatment significantly reduced the concentration differences of proteins in human serum fractions.
- A 100% increase in identified proteins was observed in serum treated with scFv@M13@MM compared to untreated samples.
- Spectral counts of 10 major high-abundance proteins, including albumin and transferrin, were markedly decreased.
Conclusions:
- scFv@M13@MM serves as an effective protein equalizer for human serum.
- This method enhances proteomic depth by reducing the dynamic range of protein concentrations.
- The approach facilitates more comprehensive identification of low-abundance proteins in complex biological samples.
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