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GproDIA enables data-independent acquisition glycoproteomics with comprehensive statistical control

Large-scale profiling of intact glycopeptides is critical but challenging in glycoproteomics. Data independent acquisition (DIA) is an emerging technology with deep proteome coverage and accurate quantitative capability in proteomics studies, but is still in the early stage of development in the fie...

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Autores principales: Yang, Yi, Yan, Guoquan, Kong, Siyuan, Wu, Mengxi, Yang, Pengyuan, Cao, Weiqian, Qiao, Liang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8523693/
https://www.ncbi.nlm.nih.gov/pubmed/34663801
http://dx.doi.org/10.1038/s41467-021-26246-3
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author Yang, Yi
Yan, Guoquan
Kong, Siyuan
Wu, Mengxi
Yang, Pengyuan
Cao, Weiqian
Qiao, Liang
author_facet Yang, Yi
Yan, Guoquan
Kong, Siyuan
Wu, Mengxi
Yang, Pengyuan
Cao, Weiqian
Qiao, Liang
author_sort Yang, Yi
collection PubMed
description Large-scale profiling of intact glycopeptides is critical but challenging in glycoproteomics. Data independent acquisition (DIA) is an emerging technology with deep proteome coverage and accurate quantitative capability in proteomics studies, but is still in the early stage of development in the field of glycoproteomics. We propose GproDIA, a framework for the proteome-wide characterization of intact glycopeptides from DIA data with comprehensive statistical control by a 2-dimentional false discovery rate approach and a glycoform inference algorithm, enabling accurate identification of intact glycopeptides using wide isolation windows. We further utilize a semi-empirical spectrum prediction strategy to expand the coverage of spectral libraries of glycopeptides. We benchmark our method for N-glycopeptide profiling on DIA data of yeast and human serum samples, demonstrating that DIA with GproDIA outperforms the data-dependent acquisition-based methods for glycoproteomics in terms of capacity and data completeness of identification, as well as accuracy and precision of quantification. We expect that this work can provide a powerful tool for glycoproteomic studies.
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spelling pubmed-85236932021-11-15 GproDIA enables data-independent acquisition glycoproteomics with comprehensive statistical control Yang, Yi Yan, Guoquan Kong, Siyuan Wu, Mengxi Yang, Pengyuan Cao, Weiqian Qiao, Liang Nat Commun Article Large-scale profiling of intact glycopeptides is critical but challenging in glycoproteomics. Data independent acquisition (DIA) is an emerging technology with deep proteome coverage and accurate quantitative capability in proteomics studies, but is still in the early stage of development in the field of glycoproteomics. We propose GproDIA, a framework for the proteome-wide characterization of intact glycopeptides from DIA data with comprehensive statistical control by a 2-dimentional false discovery rate approach and a glycoform inference algorithm, enabling accurate identification of intact glycopeptides using wide isolation windows. We further utilize a semi-empirical spectrum prediction strategy to expand the coverage of spectral libraries of glycopeptides. We benchmark our method for N-glycopeptide profiling on DIA data of yeast and human serum samples, demonstrating that DIA with GproDIA outperforms the data-dependent acquisition-based methods for glycoproteomics in terms of capacity and data completeness of identification, as well as accuracy and precision of quantification. We expect that this work can provide a powerful tool for glycoproteomic studies. Nature Publishing Group UK 2021-10-18 /pmc/articles/PMC8523693/ /pubmed/34663801 http://dx.doi.org/10.1038/s41467-021-26246-3 Text en © The Author(s) 2021 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
Yang, Yi
Yan, Guoquan
Kong, Siyuan
Wu, Mengxi
Yang, Pengyuan
Cao, Weiqian
Qiao, Liang
GproDIA enables data-independent acquisition glycoproteomics with comprehensive statistical control
title GproDIA enables data-independent acquisition glycoproteomics with comprehensive statistical control
title_full GproDIA enables data-independent acquisition glycoproteomics with comprehensive statistical control
title_fullStr GproDIA enables data-independent acquisition glycoproteomics with comprehensive statistical control
title_full_unstemmed GproDIA enables data-independent acquisition glycoproteomics with comprehensive statistical control
title_short GproDIA enables data-independent acquisition glycoproteomics with comprehensive statistical control
title_sort gprodia enables data-independent acquisition glycoproteomics with comprehensive statistical control
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8523693/
https://www.ncbi.nlm.nih.gov/pubmed/34663801
http://dx.doi.org/10.1038/s41467-021-26246-3
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