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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.
Afiliação
  • Janschitz M; Department of Biochemistry, Max F. Perutz Laboratories, Vienna BioCenter, Vienna, Austria.
  • Romanov N; Children's Cancer Research Institute, St. Anna Kinderspital, Vienna, Austria.
  • Varnavides G; Structural and Computational Biology Unit, European Molecular Biology Laboratory, Meyerhofstrasse 1, 69117, Heidelberg, Germany.
  • Hollenstein DM; Current Address: Department of Molecular Sociology, Max Planck Institute of Biophysics, 60438, Frankfurt am Main, Germany.
  • Gérecová G; Mass Spectrometry Facility, Max F. Perutz Laboratories, University of Vienna, Vienna BioCenter, Vienna, Austria.
  • Ammerer G; Department of Biochemistry, Max F. Perutz Laboratories, Vienna BioCenter, Vienna, Austria.
  • Hartl M; Department of Biochemistry, Max F. Perutz Laboratories, Vienna BioCenter, Vienna, Austria.
  • Reiter W; Department of Biochemistry, Max F. Perutz Laboratories, Vienna BioCenter, Vienna, Austria.
Cell Commun Signal ; 17(1): 66, 2019 06 17.
Article em En | MEDLINE | ID: mdl-31208443
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.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Software / Transdução de Sinais / Proteínas Quinases Ativadas por Mitógeno / Proteínas de Saccharomyces cerevisiae / Proteômica Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2019 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Software / Transdução de Sinais / Proteínas Quinases Ativadas por Mitógeno / Proteínas de Saccharomyces cerevisiae / Proteômica Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2019 Tipo de documento: Article