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Robust, reproducible and quantitative analysis of thousands of proteomes by micro-flow LC–MS/MS

Nano-flow liquid chromatography tandem mass spectrometry (nano-flow LC–MS/MS) is the mainstay in proteome research because of its excellent sensitivity but often comes at the expense of robustness. Here we show that micro-flow LC–MS/MS using a 1 × 150 mm column shows excellent reproducibility of chr...

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Autores principales: Bian, Yangyang, Zheng, Runsheng, Bayer, Florian P., Wong, Cassandra, Chang, Yun-Chien, Meng, Chen, Zolg, Daniel P., Reinecke, Maria, Zecha, Jana, Wiechmann, Svenja, Heinzlmeir, Stephanie, Scherr, Johannes, Hemmer, Bernhard, Baynham, Mike, Gingras, Anne-Claude, Boychenko, Oleksandr, Kuster, Bernhard
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6952431/
https://www.ncbi.nlm.nih.gov/pubmed/31919466
http://dx.doi.org/10.1038/s41467-019-13973-x
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author Bian, Yangyang
Zheng, Runsheng
Bayer, Florian P.
Wong, Cassandra
Chang, Yun-Chien
Meng, Chen
Zolg, Daniel P.
Reinecke, Maria
Zecha, Jana
Wiechmann, Svenja
Heinzlmeir, Stephanie
Scherr, Johannes
Hemmer, Bernhard
Baynham, Mike
Gingras, Anne-Claude
Boychenko, Oleksandr
Kuster, Bernhard
author_facet Bian, Yangyang
Zheng, Runsheng
Bayer, Florian P.
Wong, Cassandra
Chang, Yun-Chien
Meng, Chen
Zolg, Daniel P.
Reinecke, Maria
Zecha, Jana
Wiechmann, Svenja
Heinzlmeir, Stephanie
Scherr, Johannes
Hemmer, Bernhard
Baynham, Mike
Gingras, Anne-Claude
Boychenko, Oleksandr
Kuster, Bernhard
author_sort Bian, Yangyang
collection PubMed
description Nano-flow liquid chromatography tandem mass spectrometry (nano-flow LC–MS/MS) is the mainstay in proteome research because of its excellent sensitivity but often comes at the expense of robustness. Here we show that micro-flow LC–MS/MS using a 1 × 150 mm column shows excellent reproducibility of chromatographic retention time (<0.3% coefficient of variation, CV) and protein quantification (<7.5% CV) using data from >2000 samples of human cell lines, tissues and body fluids. Deep proteome analysis identifies >9000 proteins and >120,000 peptides in 16 h and sample multiplexing using tandem mass tags increases throughput to 11 proteomes in 16 h. The system identifies >30,000 phosphopeptides in 12 h and protein-protein or protein-drug interaction experiments can be analyzed in 20 min per sample. We show that the same column can be used to analyze >7500 samples without apparent loss of performance. This study demonstrates that micro-flow LC–MS/MS is suitable for a broad range of proteomic applications.
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spelling pubmed-69524312020-01-13 Robust, reproducible and quantitative analysis of thousands of proteomes by micro-flow LC–MS/MS Bian, Yangyang Zheng, Runsheng Bayer, Florian P. Wong, Cassandra Chang, Yun-Chien Meng, Chen Zolg, Daniel P. Reinecke, Maria Zecha, Jana Wiechmann, Svenja Heinzlmeir, Stephanie Scherr, Johannes Hemmer, Bernhard Baynham, Mike Gingras, Anne-Claude Boychenko, Oleksandr Kuster, Bernhard Nat Commun Article Nano-flow liquid chromatography tandem mass spectrometry (nano-flow LC–MS/MS) is the mainstay in proteome research because of its excellent sensitivity but often comes at the expense of robustness. Here we show that micro-flow LC–MS/MS using a 1 × 150 mm column shows excellent reproducibility of chromatographic retention time (<0.3% coefficient of variation, CV) and protein quantification (<7.5% CV) using data from >2000 samples of human cell lines, tissues and body fluids. Deep proteome analysis identifies >9000 proteins and >120,000 peptides in 16 h and sample multiplexing using tandem mass tags increases throughput to 11 proteomes in 16 h. The system identifies >30,000 phosphopeptides in 12 h and protein-protein or protein-drug interaction experiments can be analyzed in 20 min per sample. We show that the same column can be used to analyze >7500 samples without apparent loss of performance. This study demonstrates that micro-flow LC–MS/MS is suitable for a broad range of proteomic applications. Nature Publishing Group UK 2020-01-09 /pmc/articles/PMC6952431/ /pubmed/31919466 http://dx.doi.org/10.1038/s41467-019-13973-x 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/.
spellingShingle Article
Bian, Yangyang
Zheng, Runsheng
Bayer, Florian P.
Wong, Cassandra
Chang, Yun-Chien
Meng, Chen
Zolg, Daniel P.
Reinecke, Maria
Zecha, Jana
Wiechmann, Svenja
Heinzlmeir, Stephanie
Scherr, Johannes
Hemmer, Bernhard
Baynham, Mike
Gingras, Anne-Claude
Boychenko, Oleksandr
Kuster, Bernhard
Robust, reproducible and quantitative analysis of thousands of proteomes by micro-flow LC–MS/MS
title Robust, reproducible and quantitative analysis of thousands of proteomes by micro-flow LC–MS/MS
title_full Robust, reproducible and quantitative analysis of thousands of proteomes by micro-flow LC–MS/MS
title_fullStr Robust, reproducible and quantitative analysis of thousands of proteomes by micro-flow LC–MS/MS
title_full_unstemmed Robust, reproducible and quantitative analysis of thousands of proteomes by micro-flow LC–MS/MS
title_short Robust, reproducible and quantitative analysis of thousands of proteomes by micro-flow LC–MS/MS
title_sort robust, reproducible and quantitative analysis of thousands of proteomes by micro-flow lc–ms/ms
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6952431/
https://www.ncbi.nlm.nih.gov/pubmed/31919466
http://dx.doi.org/10.1038/s41467-019-13973-x
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