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Updated: Jul 10, 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
Multidimensional liquid phase protein separations in conjunction with stable isotope labelling for quantitative
Bobby F Assiddiq1, James C Williamson, Ambrosius P L Snijders
1Biological and Environmental Systems, Department of Chemical and Process Engineering, University of Sheffield, Sheffield, UK.
Proteomics
|October 27, 2007
Summary
This study introduces a novel method for quantitative protein profiling using multidimensional liquid chromatography and stable isotope labeling. It accurately identifies differentially expressed proteins in Escherichia coli treated with 5-Azacytidine.
Area of Science:
- Proteomics
- Biochemistry
- Molecular Biology
Background:
- Quantitative protein profiling is crucial for understanding cellular processes.
- Multidimensional liquid phase protein separations offer high throughput but face quantitation challenges.
- Stable isotope labeling provides accurate relative protein quantitation.
Purpose of the Study:
- To develop and validate a method for quantitative protein profiling.
- To identify differentially expressed proteins in Escherichia coli under specific conditions.
- To overcome limitations of existing multidimensional protein separation techniques.
Main Methods:
- Utilized multidimensional liquid phase protein separations (ion exchange and RP capillary chromatography).
- Employed stable isotope labeling (15N/14N) for accurate protein quantitation.
- Integrated mass spectrometry for precise ratio measurements of stable isotopes.
Main Results:
- Identified differentially expressed proteins in Escherichia coli treated with 5-Azacytidine.
- Demonstrated high throughput, automated, and reproducible protein separations.
- Achieved accurate protein quantitation using mass spectrometry and stable isotope ratios.
Conclusions:
- The developed method enables accurate quantitative protein profiling.
- This approach enhances the reliability of identifying differentially expressed proteins.
- The technique addresses challenges in multidimensional protein separations, improving data quality.
