Year: 2022
Type: preprint
Abstract: Shotgun proteomics is essential for protein identification and quantification in biomedical research, but protein isoform characterization is inhibited by the extensive number of peptides shared across proteins, hindering our understanding of protein isoform regulation and their roles in normal and disease biology. We systematically assess the challenge and opportunities of shotgun proteomics-based protein isoform characterization using in silico and experimental data, and then present SEPepQuant, a graph theory-based approach to enable isoform characterization. Using published data from one induced pluripotent stem cell study and two human hepatocellular carcinoma studies, we demonstrate the ability of SEPepQuant in addressing the key limitations of existing methods, providing more comprehensive proteome characterization, identifying hundreds of isoform-level regulation events, and facilitating streamlined cross-study comparisons. Our analysis provides solid evidence to support a widespread role of protein isoform regulation in normal and disease processes, and SEPepQuant has broad applications to biological and translational research.
Institution: Baylor College of Medicine
Language: English
Subfield: Spectroscopy
Field: Chemistry
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4308305109