Yeast membrane proteomics using leucine metabolic labelling: Bioinformatic data processing and exemplary application to the ER-intramembrane protease Ypf1.

Autor:	Nilse L; Institute of Molecular Medicine and Cell Research, University of Freiburg, D-79104 Freiburg, Germany., Avci D; Zentrum für Molekulare Biologie der Universität Heidelberg (ZMBH), DKFZ-ZMBH Allianz, Im Neuenheimer Feld 282, 69120 Heidelberg, Germany., Heisterkamp P; Institute of Molecular Medicine and Cell Research, University of Freiburg, D-79104 Freiburg, Germany., Serang O; Freie Universität Berlin, Department of Informatik, Takustr. 9, 14195 Berlin, Germany; Leibniz-Institute of Freshwater Ecology and Inland Fisheries (IGB), Müggelsee 310, 12587 Berlin, Germany., Lemberg MK; Zentrum für Molekulare Biologie der Universität Heidelberg (ZMBH), DKFZ-ZMBH Allianz, Im Neuenheimer Feld 282, 69120 Heidelberg, Germany. Electronic address: m.lemberg@zmbh.uni-heidelberg.de., Schilling O; Institute of Molecular Medicine and Cell Research, University of Freiburg, D-79104 Freiburg, Germany; BIOSS Centre for Biological Signalling Studies, University of Freiburg, D-79104 Freiburg, Germany. Electronic address: oliver.schilling@mol-med.uni-freiburg.de.
Jazyk:	angličtina
Zdroj:	Biochimica et biophysica acta [Biochim Biophys Acta] 2016 Oct; Vol. 1864 (10), pp. 1363-71. Date of Electronic Publication: 2016 Jul 15.
DOI:	10.1016/j.bbapap.2016.07.002
Abstrakt:	We describe in detail the usage of leucine metabolic labelling in yeast in order to monitor quantitative proteome alterations, e.g. upon removal of a protease. Since laboratory yeast strains are typically leucine auxotroph, metabolic labelling with trideuterated leucine (d3-leucine) is a straightforward, cost-effective, and ubiquitously applicable strategy for quantitative proteomic studies, similar to the widely used arginine/lysine metabolic labelling method for mammalian cells. We showcase the usage of advanced peptide quantification using the FeatureFinderMultiplex algorithm (part of the OpenMS software package) for robust and reliable quantification. Furthermore, we present an OpenMS bioinformatics data analysis workflow that combines accurate quantification with high proteome coverage. In order to enable visualization, peptide-mapping, and sharing of quantitative proteomic data, especially for membrane-spanning and cell-surface proteins, we further developed the web-application Proteator (http://proteator.appspot.com). Due to its simplicity and robustness, we expect metabolic leucine labelling in yeast to be of great interest to the research community. As an exemplary application, we show the identification of the copper transporter Ctr1 as a putative substrate of the ER-intramembrane protease Ypf1 by yeast membrane proteomics using d3-leucine isotopic labelling. (Copyright © 2016 Elsevier B.V. All rights reserved.)
Databáze:	MEDLINE
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