DeuteRater: a tool for quantifying peptide isotope precision and kinetic proteomics

Area of Science:

• Biochemistry
• Proteomics
• Analytical Chemistry

Background:

• Mass spectrometry enables the measurement of protein concentration and turnover, crucial for determining synthesis and degradation rates.
• Existing software effectively analyzes protein concentration but lacks robust methods for turnover analysis.
• Current data analysis workflows often fail to leverage the full precision and accuracy information available in peptide isotopic envelope measurements.

Purpose of the Study:

• To develop a novel data analysis tool, DeuteRater, for measuring protein turnover rates from metabolic deuterium (D2O) labeling.
• To improve the accuracy and precision of protein turnover measurements by incorporating isotope distribution and neutromer spacing.
• To optimize mass spectrometry data acquisition parameters and data processing steps for enhanced protein turnover analysis.

Main Methods:

• DeuteRater utilizes theoretical predictions of label-dependent changes in isotope abundance and inter-peak (neutromer) spacing within isotope envelopes.
• The software analyzes these metrics to calculate protein turnover rates.
• Metrics derived from isotope distribution and neutromer spacing are used to evaluate peptide measurement accuracy and precision.

Main Results:

• Development of DeuteRater, a software tool for measuring protein turnover from metabolic D2O labeling.
• Demonstrated that combined analysis of isotope distribution and neutromer spacing enhances protein turnover measurement confidence.
• Identified optimal data acquisition parameters for different instruments and assessed the impact of data processing steps.

Conclusions:

• DeuteRater provides a robust method for calculating protein turnover rates, addressing a gap in current proteomic analysis software.
• The tool's approach of utilizing both isotope distribution and neutromer spacing improves the reliability and accuracy of protein turnover measurements.
• This method effectively removes noise and increases confidence in the calculated turnover rates for individual proteins.