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Protein Complex Identification and quantitative complexome by CN-PAGE
The majority of cellular processes are carried out by protein complexes. Various size fractionation methods have previously been combined with mass spectrometry to identify protein complexes. However, most of these approaches lack the quantitative information which is required to understand how chan...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6687828/ https://www.ncbi.nlm.nih.gov/pubmed/31395906 http://dx.doi.org/10.1038/s41598-019-47829-7 |
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author | Gorka, Michal Swart, Corné Siemiatkowska, Beata Martínez-Jaime, Silvia Skirycz, Aleksandra Streb, Sebastian Graf, Alexander |
author_facet | Gorka, Michal Swart, Corné Siemiatkowska, Beata Martínez-Jaime, Silvia Skirycz, Aleksandra Streb, Sebastian Graf, Alexander |
author_sort | Gorka, Michal |
collection | PubMed |
description | The majority of cellular processes are carried out by protein complexes. Various size fractionation methods have previously been combined with mass spectrometry to identify protein complexes. However, most of these approaches lack the quantitative information which is required to understand how changes of protein complex abundance and composition affect metabolic fluxes. In this paper we present a proof of concept approach to quantitatively study the complexome in the model plant Arabidopsis thaliana at the end of the day (ED) and the end of the night (EN). We show that size-fractionation of native protein complexes by Clear-Native-PAGE (CN-PAGE), coupled with mass spectrometry can be used to establish abundance profiles along the molecular weight gradient. Furthermore, by deconvoluting complex protein abundance profiles, we were able to drastically improve the clustering of protein profiles. To identify putative interaction partners, and ultimately protein complexes, our approach calculates the Euclidian distance between protein profile pairs. Acceptable threshold values are based on a cut-off that is optimized by a receiver-operator characteristic (ROC) curve analysis. Our approach shows low technical variation and can easily be adapted to study in the complexome in any biological system. |
format | Online Article Text |
id | pubmed-6687828 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-66878282019-08-13 Protein Complex Identification and quantitative complexome by CN-PAGE Gorka, Michal Swart, Corné Siemiatkowska, Beata Martínez-Jaime, Silvia Skirycz, Aleksandra Streb, Sebastian Graf, Alexander Sci Rep Article The majority of cellular processes are carried out by protein complexes. Various size fractionation methods have previously been combined with mass spectrometry to identify protein complexes. However, most of these approaches lack the quantitative information which is required to understand how changes of protein complex abundance and composition affect metabolic fluxes. In this paper we present a proof of concept approach to quantitatively study the complexome in the model plant Arabidopsis thaliana at the end of the day (ED) and the end of the night (EN). We show that size-fractionation of native protein complexes by Clear-Native-PAGE (CN-PAGE), coupled with mass spectrometry can be used to establish abundance profiles along the molecular weight gradient. Furthermore, by deconvoluting complex protein abundance profiles, we were able to drastically improve the clustering of protein profiles. To identify putative interaction partners, and ultimately protein complexes, our approach calculates the Euclidian distance between protein profile pairs. Acceptable threshold values are based on a cut-off that is optimized by a receiver-operator characteristic (ROC) curve analysis. Our approach shows low technical variation and can easily be adapted to study in the complexome in any biological system. Nature Publishing Group UK 2019-08-08 /pmc/articles/PMC6687828/ /pubmed/31395906 http://dx.doi.org/10.1038/s41598-019-47829-7 Text en © The Author(s) 2019 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 Gorka, Michal Swart, Corné Siemiatkowska, Beata Martínez-Jaime, Silvia Skirycz, Aleksandra Streb, Sebastian Graf, Alexander Protein Complex Identification and quantitative complexome by CN-PAGE |
title | Protein Complex Identification and quantitative complexome by CN-PAGE |
title_full | Protein Complex Identification and quantitative complexome by CN-PAGE |
title_fullStr | Protein Complex Identification and quantitative complexome by CN-PAGE |
title_full_unstemmed | Protein Complex Identification and quantitative complexome by CN-PAGE |
title_short | Protein Complex Identification and quantitative complexome by CN-PAGE |
title_sort | protein complex identification and quantitative complexome by cn-page |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6687828/ https://www.ncbi.nlm.nih.gov/pubmed/31395906 http://dx.doi.org/10.1038/s41598-019-47829-7 |
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