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A comprehensive CHO SWATH-MS spectral library for robust quantitative profiling of 10,000 proteins

Sequential window acquisition of all theoretical fragment-ion spectra (SWATH) is a data-independent acquisition (DIA) strategy that requires a specific spectral library to generate unbiased and consistent quantitative data matrices of all peptides. SWATH-MS is a promising approach for in-depth prote...

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Autores principales: Sim, Kae Hwan, Liu, Lillian Chia-Yi, Tan, Hwee Tong, Tan, Kelly, Ng, Daniel, Zhang, Wei, Yang, Yuansheng, Tate, Stephen, Bi, Xuezhi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7419519/
https://www.ncbi.nlm.nih.gov/pubmed/32782267
http://dx.doi.org/10.1038/s41597-020-00594-z
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author Sim, Kae Hwan
Liu, Lillian Chia-Yi
Tan, Hwee Tong
Tan, Kelly
Ng, Daniel
Zhang, Wei
Yang, Yuansheng
Tate, Stephen
Bi, Xuezhi
author_facet Sim, Kae Hwan
Liu, Lillian Chia-Yi
Tan, Hwee Tong
Tan, Kelly
Ng, Daniel
Zhang, Wei
Yang, Yuansheng
Tate, Stephen
Bi, Xuezhi
author_sort Sim, Kae Hwan
collection PubMed
description Sequential window acquisition of all theoretical fragment-ion spectra (SWATH) is a data-independent acquisition (DIA) strategy that requires a specific spectral library to generate unbiased and consistent quantitative data matrices of all peptides. SWATH-MS is a promising approach for in-depth proteomic profiling of Chinese hamster Ovary (CHO) cell lines, improving mechanistic understanding of process optimization, and real-time monitoring of process parameters in biologics R&D and manufacturing. However, no spectral library for CHO cells is publicly available. Here we present a comprehensive CHO global spectral library to measure the abundance of more than 10,000 proteins consisting of 199,102 identified peptides from a CHO-K1 cell proteome. The robustness, accuracy and consistency of the spectral library were validated for high confidence in protein identification and reproducible quantification in different CHO-derived cell lines, instrumental setups and downstream processing samples. The availability of a comprehensive SWATH CHO global spectral library will facilitate detailed characterization of upstream and downstream processes, as well as quality by design (QbD) in biomanufacturing. The data have been deposited to ProteomeXchange (PXD016047).
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spelling pubmed-74195192020-08-18 A comprehensive CHO SWATH-MS spectral library for robust quantitative profiling of 10,000 proteins Sim, Kae Hwan Liu, Lillian Chia-Yi Tan, Hwee Tong Tan, Kelly Ng, Daniel Zhang, Wei Yang, Yuansheng Tate, Stephen Bi, Xuezhi Sci Data Data Descriptor Sequential window acquisition of all theoretical fragment-ion spectra (SWATH) is a data-independent acquisition (DIA) strategy that requires a specific spectral library to generate unbiased and consistent quantitative data matrices of all peptides. SWATH-MS is a promising approach for in-depth proteomic profiling of Chinese hamster Ovary (CHO) cell lines, improving mechanistic understanding of process optimization, and real-time monitoring of process parameters in biologics R&D and manufacturing. However, no spectral library for CHO cells is publicly available. Here we present a comprehensive CHO global spectral library to measure the abundance of more than 10,000 proteins consisting of 199,102 identified peptides from a CHO-K1 cell proteome. The robustness, accuracy and consistency of the spectral library were validated for high confidence in protein identification and reproducible quantification in different CHO-derived cell lines, instrumental setups and downstream processing samples. The availability of a comprehensive SWATH CHO global spectral library will facilitate detailed characterization of upstream and downstream processes, as well as quality by design (QbD) in biomanufacturing. The data have been deposited to ProteomeXchange (PXD016047). Nature Publishing Group UK 2020-08-11 /pmc/articles/PMC7419519/ /pubmed/32782267 http://dx.doi.org/10.1038/s41597-020-00594-z Text en © The Author(s) 2020 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/. The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ applies to the metadata files associated with this article.
spellingShingle Data Descriptor
Sim, Kae Hwan
Liu, Lillian Chia-Yi
Tan, Hwee Tong
Tan, Kelly
Ng, Daniel
Zhang, Wei
Yang, Yuansheng
Tate, Stephen
Bi, Xuezhi
A comprehensive CHO SWATH-MS spectral library for robust quantitative profiling of 10,000 proteins
title A comprehensive CHO SWATH-MS spectral library for robust quantitative profiling of 10,000 proteins
title_full A comprehensive CHO SWATH-MS spectral library for robust quantitative profiling of 10,000 proteins
title_fullStr A comprehensive CHO SWATH-MS spectral library for robust quantitative profiling of 10,000 proteins
title_full_unstemmed A comprehensive CHO SWATH-MS spectral library for robust quantitative profiling of 10,000 proteins
title_short A comprehensive CHO SWATH-MS spectral library for robust quantitative profiling of 10,000 proteins
title_sort comprehensive cho swath-ms spectral library for robust quantitative profiling of 10,000 proteins
topic Data Descriptor
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7419519/
https://www.ncbi.nlm.nih.gov/pubmed/32782267
http://dx.doi.org/10.1038/s41597-020-00594-z
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