Influence of various endogenous and artefact modifications on large-scale proteomics analysis

Area of Science:

• Proteomics
• Biochemistry
• Analytical Chemistry

Background:

• Large-scale proteomics studies often yield unexplained spectra despite advanced techniques.
• Post-translational modifications (PTMs) like phosphorylation and N-α-acetylation are crucial but challenging to fully characterize.
• Unassigned spectra represent a significant portion of data in PTM dynamics studies.

Purpose of the Study:

• To investigate in-depth peptide modifications using a plant protein dataset.
• To evaluate the impact of various modifications, including N-α-acetylation and peptide cationization, on peptide identification scores.
• To explore advanced data processing for characterizing unassigned spectra in proteomics.

Main Methods:

• Utilized Mascot software and validation processes for peptide modification analysis.
• Focused on common modifications (methionine oxidation, phosphorylation, N-α-acetylation) and peptide cationization.
• Employed a large-scale proteomics dataset generated from plant protein studies.

Main Results:

• Methionine oxidation had minimal influence on peptide identification scores.
• Peptide cationization favored C-terminal peptide characterization with limited impact on scores.
• A combination of N-α-acetylation and potassium ions mimicked phosphorylation, affecting identification scores.

Conclusions:

• Computational analysis and statistical validation can be biased by initial search hypotheses.
• Limitations exist in current proteomics data processing, particularly concerning PTM characterization.
• Advanced data processing is essential for a comprehensive understanding of proteomes and PTM dynamics.