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Sample multiplexing-based targeted pathway proteomics with real-time analytics reveals the impact of genetic variation on protein expression
Targeted proteomics enables hypothesis-driven research by measuring the cellular expression of protein cohorts related by function, disease, or class after perturbation. Here, we present a pathway-centric approach and an assay builder resource for targeting entire pathways of up to 200 proteins sele...
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/PMC9894840/ https://www.ncbi.nlm.nih.gov/pubmed/36732331 http://dx.doi.org/10.1038/s41467-023-36269-7 |
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author | Yu, Qing Liu, Xinyue Keller, Mark P. Navarrete-Perea, Jose Zhang, Tian Fu, Sipei Vaites, Laura P. Shuken, Steven R. Schmid, Ernst Keele, Gregory R. Li, Jiaming Huttlin, Edward L. Rashan, Edrees H. Simcox, Judith Churchill, Gary A. Schweppe, Devin K. Attie, Alan D. Paulo, Joao A. Gygi, Steven P. |
author_facet | Yu, Qing Liu, Xinyue Keller, Mark P. Navarrete-Perea, Jose Zhang, Tian Fu, Sipei Vaites, Laura P. Shuken, Steven R. Schmid, Ernst Keele, Gregory R. Li, Jiaming Huttlin, Edward L. Rashan, Edrees H. Simcox, Judith Churchill, Gary A. Schweppe, Devin K. Attie, Alan D. Paulo, Joao A. Gygi, Steven P. |
author_sort | Yu, Qing |
collection | PubMed |
description | Targeted proteomics enables hypothesis-driven research by measuring the cellular expression of protein cohorts related by function, disease, or class after perturbation. Here, we present a pathway-centric approach and an assay builder resource for targeting entire pathways of up to 200 proteins selected from >10,000 expressed proteins to directly measure their abundances, exploiting sample multiplexing to increase throughput by 16-fold. The strategy, termed GoDig, requires only a single-shot LC-MS analysis, ~1 µg combined peptide material, a list of up to 200 proteins, and real-time analytics to trigger simultaneous quantification of up to 16 samples for hundreds of analytes. We apply GoDig to quantify the impact of genetic variation on protein expression in mice fed a high-fat diet. We create several GoDig assays to quantify the expression of multiple protein families (kinases, lipid metabolism- and lipid droplet-associated proteins) across 480 fully-genotyped Diversity Outbred mice, revealing protein quantitative trait loci and establishing potential linkages between specific proteins and lipid homeostasis. |
format | Online Article Text |
id | pubmed-9894840 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-98948402023-02-04 Sample multiplexing-based targeted pathway proteomics with real-time analytics reveals the impact of genetic variation on protein expression Yu, Qing Liu, Xinyue Keller, Mark P. Navarrete-Perea, Jose Zhang, Tian Fu, Sipei Vaites, Laura P. Shuken, Steven R. Schmid, Ernst Keele, Gregory R. Li, Jiaming Huttlin, Edward L. Rashan, Edrees H. Simcox, Judith Churchill, Gary A. Schweppe, Devin K. Attie, Alan D. Paulo, Joao A. Gygi, Steven P. Nat Commun Article Targeted proteomics enables hypothesis-driven research by measuring the cellular expression of protein cohorts related by function, disease, or class after perturbation. Here, we present a pathway-centric approach and an assay builder resource for targeting entire pathways of up to 200 proteins selected from >10,000 expressed proteins to directly measure their abundances, exploiting sample multiplexing to increase throughput by 16-fold. The strategy, termed GoDig, requires only a single-shot LC-MS analysis, ~1 µg combined peptide material, a list of up to 200 proteins, and real-time analytics to trigger simultaneous quantification of up to 16 samples for hundreds of analytes. We apply GoDig to quantify the impact of genetic variation on protein expression in mice fed a high-fat diet. We create several GoDig assays to quantify the expression of multiple protein families (kinases, lipid metabolism- and lipid droplet-associated proteins) across 480 fully-genotyped Diversity Outbred mice, revealing protein quantitative trait loci and establishing potential linkages between specific proteins and lipid homeostasis. Nature Publishing Group UK 2023-02-02 /pmc/articles/PMC9894840/ /pubmed/36732331 http://dx.doi.org/10.1038/s41467-023-36269-7 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 Yu, Qing Liu, Xinyue Keller, Mark P. Navarrete-Perea, Jose Zhang, Tian Fu, Sipei Vaites, Laura P. Shuken, Steven R. Schmid, Ernst Keele, Gregory R. Li, Jiaming Huttlin, Edward L. Rashan, Edrees H. Simcox, Judith Churchill, Gary A. Schweppe, Devin K. Attie, Alan D. Paulo, Joao A. Gygi, Steven P. Sample multiplexing-based targeted pathway proteomics with real-time analytics reveals the impact of genetic variation on protein expression |
title | Sample multiplexing-based targeted pathway proteomics with real-time analytics reveals the impact of genetic variation on protein expression |
title_full | Sample multiplexing-based targeted pathway proteomics with real-time analytics reveals the impact of genetic variation on protein expression |
title_fullStr | Sample multiplexing-based targeted pathway proteomics with real-time analytics reveals the impact of genetic variation on protein expression |
title_full_unstemmed | Sample multiplexing-based targeted pathway proteomics with real-time analytics reveals the impact of genetic variation on protein expression |
title_short | Sample multiplexing-based targeted pathway proteomics with real-time analytics reveals the impact of genetic variation on protein expression |
title_sort | sample multiplexing-based targeted pathway proteomics with real-time analytics reveals the impact of genetic variation on protein expression |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9894840/ https://www.ncbi.nlm.nih.gov/pubmed/36732331 http://dx.doi.org/10.1038/s41467-023-36269-7 |
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