Improved quantitative analysis of mass spectrometry using quadratic equations

Area of Science:

• Proteomics
• Computational Biology
• Analytical Chemistry

Background:

• Accurate peptide quantification is crucial for reliable protein quantification in mass spectrometry (MS).
• Stable isotope labeling is a popular technique for relative peptide quantification.
• Overlapping isotopic clusters pose a significant challenge in peptide quantification, particularly with small mass differences.

Purpose of the Study:

• To develop a novel algorithm for resolving overlapping isotopic clusters in peptide quantification.
• To improve the accuracy and reliability of peptide quantification in MS-based proteomics.
• To provide an alternative to existing quantification algorithms like XPRESS within the Trans-Proteomic Pipeline (TPP).

Main Methods:

• Development of a new algorithm employing quadratic equations to separate overlapping isotopic clusters.
• Application of the algorithm to mTRAQ-labeled peptides analyzed by Orbitrap mass spectrometry.
• Comparison of the new algorithm's performance against the XPRESS algorithm.

Main Results:

• The proposed algorithm demonstrated more accurate ratios and better standard deviations than XPRESS for mTRAQ-labeled peptides.
• The discrepancy between the new algorithm and XPRESS increased with higher peptide masses, especially for peptides lacking lysine.
• The algorithm effectively separates overlapping isotopic clusters, enhancing quantification accuracy.

Conclusions:

• The novel quadratic equation-based algorithm offers improved peptide quantification in MS-based proteomics.
• This method provides a more accurate alternative to XPRESS, particularly for challenging peptide samples.
• The algorithm's applicability is expected to extend to other labeling techniques like (18)O and acrylamide labeling.