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Sample multiplexing for targeted pathway proteomics in aging mice
Pathway proteomics strategies measure protein expression changes in specific cellular processes that carry out related functions. Using targeted tandem mass tags-based sample multiplexing, hundreds of proteins can be quantified across 10 or more samples simultaneously. To facilitate these highly com...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
National Academy of Sciences
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7211924/ https://www.ncbi.nlm.nih.gov/pubmed/32332170 http://dx.doi.org/10.1073/pnas.1919410117 |
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author | Yu, Qing Xiao, Haopeng Jedrychowski, Mark P. Schweppe, Devin K. Navarrete-Perea, Jose Knott, Jeffrey Rogers, John Chouchani, Edward T. Gygi, Steven P. |
author_facet | Yu, Qing Xiao, Haopeng Jedrychowski, Mark P. Schweppe, Devin K. Navarrete-Perea, Jose Knott, Jeffrey Rogers, John Chouchani, Edward T. Gygi, Steven P. |
author_sort | Yu, Qing |
collection | PubMed |
description | Pathway proteomics strategies measure protein expression changes in specific cellular processes that carry out related functions. Using targeted tandem mass tags-based sample multiplexing, hundreds of proteins can be quantified across 10 or more samples simultaneously. To facilitate these highly complex experiments, we introduce a strategy that provides complete control over targeted sample multiplexing experiments, termed Tomahto, and present its implementation on the Orbitrap Tribrid mass spectrometer platform. Importantly, this software monitors via the external desktop computer to the data stream and inserts optimized MS2 and MS3 scans in real time based on an application programming interface with the mass spectrometer. Hundreds of proteins of interest from diverse biological samples can be targeted and accurately quantified in a sensitive and high-throughput fashion. It achieves sensitivity comparable to, if not better than, deep fractionation and requires minimal total sample input (∼10 µg). As a proof-of-principle experiment, we selected four pathways important in metabolism- and inflammation-related processes (260 proteins/520 peptides) and measured their abundance across 90 samples (nine tissues from five old and five young mice) to explore effects of aging. Tissue-specific aging is presented here and we highlight the role of inflammation- and metabolism-related processes in white adipose tissue. We validated our approach through comparison with a global proteome survey across the tissues, work that we also provide as a general resource for the community. |
format | Online Article Text |
id | pubmed-7211924 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | National Academy of Sciences |
record_format | MEDLINE/PubMed |
spelling | pubmed-72119242020-05-15 Sample multiplexing for targeted pathway proteomics in aging mice Yu, Qing Xiao, Haopeng Jedrychowski, Mark P. Schweppe, Devin K. Navarrete-Perea, Jose Knott, Jeffrey Rogers, John Chouchani, Edward T. Gygi, Steven P. Proc Natl Acad Sci U S A Physical Sciences Pathway proteomics strategies measure protein expression changes in specific cellular processes that carry out related functions. Using targeted tandem mass tags-based sample multiplexing, hundreds of proteins can be quantified across 10 or more samples simultaneously. To facilitate these highly complex experiments, we introduce a strategy that provides complete control over targeted sample multiplexing experiments, termed Tomahto, and present its implementation on the Orbitrap Tribrid mass spectrometer platform. Importantly, this software monitors via the external desktop computer to the data stream and inserts optimized MS2 and MS3 scans in real time based on an application programming interface with the mass spectrometer. Hundreds of proteins of interest from diverse biological samples can be targeted and accurately quantified in a sensitive and high-throughput fashion. It achieves sensitivity comparable to, if not better than, deep fractionation and requires minimal total sample input (∼10 µg). As a proof-of-principle experiment, we selected four pathways important in metabolism- and inflammation-related processes (260 proteins/520 peptides) and measured their abundance across 90 samples (nine tissues from five old and five young mice) to explore effects of aging. Tissue-specific aging is presented here and we highlight the role of inflammation- and metabolism-related processes in white adipose tissue. We validated our approach through comparison with a global proteome survey across the tissues, work that we also provide as a general resource for the community. National Academy of Sciences 2020-05-05 2020-04-24 /pmc/articles/PMC7211924/ /pubmed/32332170 http://dx.doi.org/10.1073/pnas.1919410117 Text en Copyright © 2020 the Author(s). Published by PNAS. https://creativecommons.org/licenses/by-nc-nd/4.0/ https://creativecommons.org/licenses/by-nc-nd/4.0/This open access article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND) (https://creativecommons.org/licenses/by-nc-nd/4.0/) . |
spellingShingle | Physical Sciences Yu, Qing Xiao, Haopeng Jedrychowski, Mark P. Schweppe, Devin K. Navarrete-Perea, Jose Knott, Jeffrey Rogers, John Chouchani, Edward T. Gygi, Steven P. Sample multiplexing for targeted pathway proteomics in aging mice |
title | Sample multiplexing for targeted pathway proteomics in aging mice |
title_full | Sample multiplexing for targeted pathway proteomics in aging mice |
title_fullStr | Sample multiplexing for targeted pathway proteomics in aging mice |
title_full_unstemmed | Sample multiplexing for targeted pathway proteomics in aging mice |
title_short | Sample multiplexing for targeted pathway proteomics in aging mice |
title_sort | sample multiplexing for targeted pathway proteomics in aging mice |
topic | Physical Sciences |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7211924/ https://www.ncbi.nlm.nih.gov/pubmed/32332170 http://dx.doi.org/10.1073/pnas.1919410117 |
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