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Deep Proteome Profiling by Isobaric Labeling, Extensive Liquid Chromatography, Mass Spectrometry, and Software-assisted Quantification
Published on: November 15, 2017
A fully automated system with online sample loading, isotope dimethyl labeling and multidimensional separation for
Fangjun Wang1, Rui Chen, Jun Zhu
1CAS Key Lab of Separation Sciences for Analytical Chemistry, National Chromatographic Research and Analysis Center, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China.
Analytical Chemistry
|March 17, 2010
Summary
A new automated system enhances proteome analysis using multidimensional separation and isotope labeling. This method improves quantification accuracy and identifies key proteins in hepatocellular carcinoma (HCC) tissues.
Area of Science:
- Proteomics
- Analytical Chemistry
- Biochemistry
Background:
- Multidimensional separation is crucial for large-scale proteome analysis.
- Current methods often involve manual labeling and off-line fractionation, which are time-consuming and prone to variability.
Purpose of the Study:
- To develop a fully automated system for online sample loading, isotope dimethyl labeling, and multidimensional separation of proteome samples.
- To improve the reproducibility and accuracy of quantitative proteome analysis.
Main Methods:
- Integration of a reversed-phase strong cation exchange (RP-SCX) biphasic trap column into a vented sample injection system.
- Utilizing a phosphate SCX monolith for high sample injection flow rate and high-resolution stepwise fractionation.
- Online isotope dimethyl labeling for quantitative analysis.
Main Results:
- The automated system achieved online sample loading, labeling, and multidimensional separation.
- Approximately 1000 proteins were quantified in about 30 hours, with potential for greater coverage.
- Analysis of hepatocellular carcinoma (HCC) versus normal liver tissues identified 94 up-regulated and 249 down-regulated proteins.
Conclusions:
- The developed automated system offers a time-saving and efficient approach for quantitative proteome analysis.
- The identified differentially expressed proteins in HCC provide insights into disease mechanisms, with observed down-regulation of enzymes in urea cycle, methylation cycle, and fatty acid metabolism.
