Related Experiment Video
Updated: Jun 15, 2026
Measurement of Protein Turnover Rates in Senescent and Non-Dividing Cultured Cells with Metabolic Labeling and Mass Spectrometry
Published on: April 6, 2022
Multitagging proteomic strategy to estimate protein turnover rates in dynamic systems
Karthik P Jayapal1, Siguang Sui, Robin J Philp
1Department of Chemical Engineering and Materials Science, University of Minnesota, 421 Washington Avenue SE, Minneapolis, Minnesota 55455, USA.
This study introduces a dual labeling method using Stable Isotope Labeling by Amino acids in Cell culture (SILAC) and Isobaric Tags for Relative and Absolute Quantitation (iTRAQ) to accurately measure protein turnover rates. This approach improves understanding of cellular dynamics, especially in dynamic biological systems.
Area of Science:
- Proteomics
- Biochemistry
- Molecular Biology
Background:
- Quantitative proteomics often measures net protein dynamics (synthesis/degradation).
- Understanding protein synthesis and degradation rates is crucial for cellular dynamics and linking transcriptome to proteome data.
- Existing "label-chase" methods assume steady-state, which may not apply to dynamic systems.
Purpose of the Study:
- To develop and validate a novel dual labeling strategy for estimating protein turnover rates.
- To apply this method to Streptomyces coelicolor during growth phase transitions.
- To investigate the onset of secondary metabolite synthesis in Streptomyces.
Main Methods:
- Utilized Stable Isotope Labeling by Amino acids in Cell culture (SILAC) for initial labeling.
- Incorporated a secondary labeling step with Isobaric Tags for Relative and Absolute Quantitation (iTRAQ) reagents.
- Employed tandem mass spectrometry (MS/MS) for peptide identification and degradation dynamics quantification.
Main Results:
- Successfully estimated degradation rates for 115 highly abundant proteins in Streptomyces coelicolor.
- Decoupled peptide identification (MS) from degradation dynamics quantification (MS/MS) using the dual labeling strategy.
- Compared dual labeling results with SILAC-only (steady-state) analysis, revealing significant differences in proteins with high temporal dynamics.
Conclusions:
- The novel dual labeling approach provides more accurate protein turnover rates in dynamic systems.
- This method is significant for understanding Streptomyces biology and secondary metabolite production.
- The findings highlight the limitations of steady-state assumptions in proteomic analyses of dynamic cellular processes.
