Language
English
Publication Date
9-19-2023
Journal
Nature Communications
DOI
10.1038/s41467-023-41558-2
PMID
37726316
PMCID
PMC10509223
PubMedCentral® Posted Date
9-19-2023
PubMedCentral® Full Text Version
Post-print
Abstract
Shotgun proteomics is essential for protein identification and quantification in biomedical research, but protein isoform characterization is challenging due to 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 maximize 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 isoform-level 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.
Keywords
Humans, Proteomics, Protein Isoforms, Biomedical Research, Carcinoma, Hepatocellular, Liver Neoplasms
Published Open-Access
yes
Recommended Citation
Dou, Yongchao; Liu, Yuejia; Yi, Xinpei; et al., "SEPepQuant Enhances the Detection of Possible Isoform Regulations in Shotgun Proteomics" (2023). Faculty and Staff Publications. 2340.
https://digitalcommons.library.tmc.edu/baylor_docs/2340
Included in
Biological Phenomena, Cell Phenomena, and Immunity Commons, Biomedical Informatics Commons, Genetics and Genomics Commons, Medical Genetics Commons, Medical Molecular Biology Commons, Medical Specialties Commons