Peptide Level Turnover Measurements Enable the Study of Proteoform Dynamics

Area of Science:

• Proteomics
• Cellular Biology
• Biochemistry

Background:

• Protein synthesis and degradation are crucial for cellular homeostasis.
• Mass spectrometry enables proteome-wide protein turnover analysis.
• Standard dynamic SILAC (Stable Isotope Labeling in Cell Culture) methods can have missing data, limiting proteoform stability analysis.

Purpose of the Study:

• To evaluate combining dynamic SILAC and tandem mass tag (TMT)-labeling for comprehensive proteome-wide protein turnover analysis.
• To overcome data limitations in standard dynamic SILAC for accurate proteoform stability studies.
• To investigate the impact of post-translational modifications and protein properties on cellular protein half-lives.

Main Methods:

• Integration of dynamic SILAC and TMT-labeling across ten pulse time-points in a single experiment.
• Comparison of the novel pulsed SILAC-TMT approach with standard dynamic SILAC.
• Analysis of protein and peptide turnover rates for proteoform-resolved stability investigations.

Main Results:

• The pulsed SILAC-TMT approach provided more comprehensive data (average 6000 proteins) without missing values compared to standard dynamic SILAC.
• High concordance in protein turnover rates was observed between the methods, with improved reproducibility for peptides and proteins.
• Differential turnover of splice variants, impact of post-translational modifications (e.g., N-terminal processing), and proteolytic processing (e.g., FAU) were identified.
• New insights into post-translational regulation of cathepsin D and BLM stability were uncovered.
• High turnover of respiratory chain complex I proteins was potentially linked to oxidative stress.

Conclusions:

• The pulsed SILAC-TMT method enhances proteome-wide protein turnover analysis, enabling accurate proteoform-resolved stability studies.
• This approach reveals novel post-translational modifications and proteolytic events influencing protein stability and cellular regulation.
• The findings provide a comprehensive dataset for understanding protein stability determinants and cellular responses, such as oxidative stress.