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Metabolic Pathway Confirmation and Discovery Through 13C-labeling of Proteinogenic Amino Acids
Published on: January 26, 2012
Quantitative proteomics by metabolic labeling of model organisms
Joost W Gouw1, Jeroen Krijgsveld, Albert J R Heck
1Biomolecular Mass Spectrometry and Proteomics Group, Bijvoet Center for Biomolecular Research, and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Netherlands Proteomics Centre, 3584CH Utrecht, The Netherlands.
Molecular & Cellular Proteomics : MCP
|December 4, 2009
Summary
Stable isotope labeling in model organisms enables dynamic proteome analysis. This approach advances understanding of biological processes and diseases across diverse species, from yeast to mammals.
Area of Science:
- Biological Sciences
- Proteomics
- Systems Biology
Background:
- Model organisms are crucial for understanding biological processes and disease.
- Genetics and genomics have been primary approaches, but protein-level analysis is essential.
- Mass spectrometry-based proteomics is advancing comprehensive proteome analysis.
Purpose of the Study:
- To review methodologies for stable isotope labeling in vivo across various model organisms.
- To highlight the transition from static to dynamic proteome monitoring.
- To illustrate the application of these methods in studying health and disease.
Main Methods:
- Metabolic incorporation of stable isotopes in vivo.
- Stable isotope labeling in bacteria, yeast, Caenorhabditis elegans, Drosophila, Arabidopsis, rats, and mice.
- Quantitative proteomics using mass spectrometry.
Main Results:
- Stable isotope labeling allows accurate quantification of differential protein expression.
- Dynamic proteome analysis reveals biological process regulation.
- Cross-species comparisons highlight conserved and varied protein-level responses.
Conclusions:
- In vivo stable isotope labeling is a powerful strategy for dynamic proteome analysis in diverse model organisms.
- This approach is vital for advancing protein-level research in biology and medicine.
- Understanding protein dynamics across the tree of life offers insights into evolution and disease mechanisms.
