Topograph, a software platform for precursor enrichment corrected global protein turnover measurements

Area of Science:

• Proteomics
• Biochemistry
• Systems Biology

Background:

• Protein turnover is crucial for cellular function and implicated in various diseases.
• Existing proteomics methods for measuring protein turnover are limited by software capabilities.
• Differentiating newly synthesized proteins from partially labeled precursor pools is challenging.

Purpose of the Study:

• To develop a novel software platform, Topograph, for precise measurement of protein turnover rates.
• To address limitations in current proteomics software for analyzing newly synthesized proteins.
• To enable accurate protein turnover calculations irrespective of stable isotope labeling and precursor pool enrichment.

Main Methods:

• Development of the Topograph software platform for quantitative proteomics.
• Calculation of the fraction of newly synthesized peptides and their turnover rates.
• Determination of amino acid precursor pool enrichment levels for accurate quantification.

Main Results:

• Topograph accurately calculates the fraction of newly synthesized proteins and their turnover rates.
• The software enables precise measurements even with partially labeled precursor pools.
• Validation using mouse labeling experiments confirmed the influence of precursor pool corrections on turnover measurements.

Conclusions:

• Topograph provides a robust solution for measuring protein turnover rates in proteomics.
• The software enhances accuracy by accounting for precursor pool enrichment.
• This advancement has significant implications for understanding disease mechanisms related to protein homeostasis.