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Novel interconnections of HOG signaling revealed by combined use of two proteomic software packages

Modern quantitative mass spectrometry (MS)-based proteomics enables researchers to unravel signaling networks by monitoring proteome-wide cellular responses to different stimuli. MS-based analysis of signaling systems usually requires an integration of multiple quantitative MS experiments, which rem...

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Autores principales: Janschitz, Marion, Romanov, Natalie, Varnavides, Gina, Hollenstein, David Maria, Gérecová, Gabriela, Ammerer, Gustav, Hartl, Markus, Reiter, Wolfgang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6572760/
https://www.ncbi.nlm.nih.gov/pubmed/31208443
http://dx.doi.org/10.1186/s12964-019-0381-z
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author Janschitz, Marion
Romanov, Natalie
Varnavides, Gina
Hollenstein, David Maria
Gérecová, Gabriela
Ammerer, Gustav
Hartl, Markus
Reiter, Wolfgang
author_facet Janschitz, Marion
Romanov, Natalie
Varnavides, Gina
Hollenstein, David Maria
Gérecová, Gabriela
Ammerer, Gustav
Hartl, Markus
Reiter, Wolfgang
author_sort Janschitz, Marion
collection PubMed
description Modern quantitative mass spectrometry (MS)-based proteomics enables researchers to unravel signaling networks by monitoring proteome-wide cellular responses to different stimuli. MS-based analysis of signaling systems usually requires an integration of multiple quantitative MS experiments, which remains challenging, given that the overlap between these datasets is not necessarily comprehensive. In a previous study we analyzed the impact of the yeast mitogen-activated protein kinase (MAPK) Hog1 on the hyperosmotic stress-affected phosphorylome. Using a combination of a series of hyperosmotic stress and kinase inhibition experiments, we identified a broad range of direct and indirect substrates of the MAPK. Here we re-evaluate this extensive MS dataset and demonstrate that a combined analysis based on two software packages, MaxQuant and Proteome Discoverer, increases the coverage of Hog1-target proteins by 30%. Using protein-protein proximity assays we show that the majority of new targets gained by this analysis are indeed Hog1-interactors. Additionally, kinetic profiles indicate differential trends of Hog1-dependent versus Hog1-independent phosphorylation sites. Our findings highlight a previously unrecognized interconnection between Hog1 signaling and the RAM signaling network, as well as sphingolipid homeostasis. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12964-019-0381-z) contains supplementary material, which is available to authorized users.
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spelling pubmed-65727602019-06-24 Novel interconnections of HOG signaling revealed by combined use of two proteomic software packages Janschitz, Marion Romanov, Natalie Varnavides, Gina Hollenstein, David Maria Gérecová, Gabriela Ammerer, Gustav Hartl, Markus Reiter, Wolfgang Cell Commun Signal Short Report Modern quantitative mass spectrometry (MS)-based proteomics enables researchers to unravel signaling networks by monitoring proteome-wide cellular responses to different stimuli. MS-based analysis of signaling systems usually requires an integration of multiple quantitative MS experiments, which remains challenging, given that the overlap between these datasets is not necessarily comprehensive. In a previous study we analyzed the impact of the yeast mitogen-activated protein kinase (MAPK) Hog1 on the hyperosmotic stress-affected phosphorylome. Using a combination of a series of hyperosmotic stress and kinase inhibition experiments, we identified a broad range of direct and indirect substrates of the MAPK. Here we re-evaluate this extensive MS dataset and demonstrate that a combined analysis based on two software packages, MaxQuant and Proteome Discoverer, increases the coverage of Hog1-target proteins by 30%. Using protein-protein proximity assays we show that the majority of new targets gained by this analysis are indeed Hog1-interactors. Additionally, kinetic profiles indicate differential trends of Hog1-dependent versus Hog1-independent phosphorylation sites. Our findings highlight a previously unrecognized interconnection between Hog1 signaling and the RAM signaling network, as well as sphingolipid homeostasis. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12964-019-0381-z) contains supplementary material, which is available to authorized users. BioMed Central 2019-06-17 /pmc/articles/PMC6572760/ /pubmed/31208443 http://dx.doi.org/10.1186/s12964-019-0381-z Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided 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 Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Short Report
Janschitz, Marion
Romanov, Natalie
Varnavides, Gina
Hollenstein, David Maria
Gérecová, Gabriela
Ammerer, Gustav
Hartl, Markus
Reiter, Wolfgang
Novel interconnections of HOG signaling revealed by combined use of two proteomic software packages
title Novel interconnections of HOG signaling revealed by combined use of two proteomic software packages
title_full Novel interconnections of HOG signaling revealed by combined use of two proteomic software packages
title_fullStr Novel interconnections of HOG signaling revealed by combined use of two proteomic software packages
title_full_unstemmed Novel interconnections of HOG signaling revealed by combined use of two proteomic software packages
title_short Novel interconnections of HOG signaling revealed by combined use of two proteomic software packages
title_sort novel interconnections of hog signaling revealed by combined use of two proteomic software packages
topic Short Report
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6572760/
https://www.ncbi.nlm.nih.gov/pubmed/31208443
http://dx.doi.org/10.1186/s12964-019-0381-z
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