Mode-hop-free tuning over 135 GHz of external cavity diode lasers without anti-reflection coating

We report an external cavity diode laser (ECDL), using a diode whose front facet is not antireflection (AR) coated, that has a mode-hop-free (MHF) tuning range greater than 135 GHz. We achieved this using a short external cavity and by simultaneously tuning the internal and external modes of the laser. We find that the precise location of the pivot point of the grating in our laser is less critical than commonly believed. The general applicability of the method, combined with the compact portable mechanical and electronic design, makes it well suited for both research and industrial applications.Comment: 5 pages, 5 figure

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

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

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

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

OpenMS: a flexible open-source software platform for mass spectrometry data analysis

High-resolution mass spectrometry (MS) has become an important tool in the life sciences, contributing to the diagnosis and understanding of human diseases, elucidating biomolecular structural information and characterizing cellular signaling networks. However, the rapid growth in the volume and complexity of MS data makes transparent, accurate and reproducible analysis difficult. We present OpenMS 2.0 (http://www.openms.de), a robust, open-source, cross-platform software specifically designed for the flexible and reproducible analysis of high-throughput MS data. The extensible OpenMS software implements common mass spectrometric data processing tasks through a well-defined application programming interface in C++ and Python and through standardized open data formats. OpenMS additionally provides a set of 185 tools and ready-made workflows for common mass spectrometric data processing tasks, which enable users to perform complex quantitative mass spectrometric analyses with ease