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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...

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Autores principales: Gorka, Michal, Swart, Corné, Siemiatkowska, Beata, Martínez-Jaime, Silvia, Skirycz, Aleksandra, Streb, Sebastian, Graf, Alexander
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
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.
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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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