SEPepQuant enhances the detection of possible isoform regulations in shotgun proteomics

Yongchao Dou, Yuejia Liu, Xinpei Yi, Lindsey K. Olsen, Hongwen Zhu, Qiang Gao, Hu Zhou and Bing Zhang ()
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Yongchao Dou: Baylor College of Medicine
Yuejia Liu: Nanjing University of Chinese Medicine
Xinpei Yi: Baylor College of Medicine
Lindsey K. Olsen: Baylor College of Medicine
Hongwen Zhu: Shanghai Institute of Materia Medica, Chinese Academy of Sciences
Qiang Gao: Fudan University, and Key Laboratory of Carcinogenesis and Cancer Invasion of Ministry of Education
Hu Zhou: Nanjing University of Chinese Medicine
Bing Zhang: Baylor College of Medicine

Nature Communications, 2023, vol. 14, issue 1, 1-15

Abstract: 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.

Date: 2023
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DOI: 10.1038/s41467-023-41558-2

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