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SEPepQuant enhances the detection of possible isoform regulations in shotgun proteomics
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 norma...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10509223/ https://www.ncbi.nlm.nih.gov/pubmed/37726316 http://dx.doi.org/10.1038/s41467-023-41558-2 |
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author | Dou, Yongchao Liu, Yuejia Yi, Xinpei Olsen, Lindsey K. Zhu, Hongwen Gao, Qiang Zhou, Hu Zhang, Bing |
author_facet | Dou, Yongchao Liu, Yuejia Yi, Xinpei Olsen, Lindsey K. Zhu, Hongwen Gao, Qiang Zhou, Hu Zhang, Bing |
author_sort | Dou, Yongchao |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-10509223 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-105092232023-09-21 SEPepQuant enhances the detection of possible isoform regulations in shotgun proteomics Dou, Yongchao Liu, Yuejia Yi, Xinpei Olsen, Lindsey K. Zhu, Hongwen Gao, Qiang Zhou, Hu Zhang, Bing Nat Commun Article 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. Nature Publishing Group UK 2023-09-19 /pmc/articles/PMC10509223/ /pubmed/37726316 http://dx.doi.org/10.1038/s41467-023-41558-2 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Dou, Yongchao Liu, Yuejia Yi, Xinpei Olsen, Lindsey K. Zhu, Hongwen Gao, Qiang Zhou, Hu Zhang, Bing SEPepQuant enhances the detection of possible isoform regulations in shotgun proteomics |
title | SEPepQuant enhances the detection of possible isoform regulations in shotgun proteomics |
title_full | SEPepQuant enhances the detection of possible isoform regulations in shotgun proteomics |
title_fullStr | SEPepQuant enhances the detection of possible isoform regulations in shotgun proteomics |
title_full_unstemmed | SEPepQuant enhances the detection of possible isoform regulations in shotgun proteomics |
title_short | SEPepQuant enhances the detection of possible isoform regulations in shotgun proteomics |
title_sort | sepepquant enhances the detection of possible isoform regulations in shotgun proteomics |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10509223/ https://www.ncbi.nlm.nih.gov/pubmed/37726316 http://dx.doi.org/10.1038/s41467-023-41558-2 |
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