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      A Dual Pressure Linear Ion Trap Orbitrap Instrument with Very High Sequencing Speed*

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          Abstract

          Since its introduction a few years ago, the linear ion trap Orbitrap (LTQ Orbitrap) instrument has become a powerful tool in proteomics research. For high resolution mass spectrometry measurements ions are accumulated in the linear ion trap and passed on to the Orbitrap analyzer. Simultaneously with acquisition of this signal, the major peaks are isolated in turn, fragmented and recorded at high sensitivity in the linear ion trap, combining the strengths of both mass analyzer technologies. Here we describe a next generation LTQ Orbitrap system termed Velos, with significantly increased sensitivity and scan speed. This is achieved by a vacuum interface using a stacked ring radio frequency ion guide with 10-fold higher transfer efficiency in MS/MS mode and 3–5-fold in full scan spectra, by a dual pressure ion trap configuration, and by reduction of overhead times between scans. The first ion trap efficiently captures and fragments ions at relatively high pressure whereas the second ion trap realizes extremely fast scan speeds at reduced pressure. Ion injection times for MS/MS are predicted from full scans instead of performing automatic gain control scans. Together these improvements routinely enable acquisition of up to ten fragmentation spectra per second. Furthermore, an improved higher-energy collisional dissociation cell with increased ion extraction capabilities was implemented. Higher-collision energy dissociation with high mass accuracy Orbitrap readout is as sensitive as ion trap MS/MS scans in the previous generation of the instrument.

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          Most cited references16

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          Stable isotope labeling by amino acids in cell culture, SILAC, as a simple and accurate approach to expression proteomics.

          Quantitative proteomics has traditionally been performed by two-dimensional gel electrophoresis, but recently, mass spectrometric methods based on stable isotope quantitation have shown great promise for the simultaneous and automated identification and quantitation of complex protein mixtures. Here we describe a method, termed SILAC, for stable isotope labeling by amino acids in cell culture, for the in vivo incorporation of specific amino acids into all mammalian proteins. Mammalian cell lines are grown in media lacking a standard essential amino acid but supplemented with a non-radioactive, isotopically labeled form of that amino acid, in this case deuterated leucine (Leu-d3). We find that growth of cells maintained in these media is no different from growth in normal media as evidenced by cell morphology, doubling time, and ability to differentiate. Complete incorporation of Leu-d3 occurred after five doublings in the cell lines and proteins studied. Protein populations from experimental and control samples are mixed directly after harvesting, and mass spectrometric identification is straightforward as every leucine-containing peptide incorporates either all normal leucine or all Leu-d3. We have applied this technique to the relative quantitation of changes in protein expression during the process of muscle cell differentiation. Proteins that were found to be up-regulated during this process include glyceraldehyde-3-phosphate dehydrogenase, fibronectin, and pyruvate kinase M2. SILAC is a simple, inexpensive, and accurate procedure that can be used as a quantitative proteomic approach in any cell culture system.
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            Comprehensive mass-spectrometry-based proteome quantification of haploid versus diploid yeast.

            Mass spectrometry is a powerful technology for the analysis of large numbers of endogenous proteins. However, the analytical challenges associated with comprehensive identification and relative quantification of cellular proteomes have so far appeared to be insurmountable. Here, using advances in computational proteomics, instrument performance and sample preparation strategies, we compare protein levels of essentially all endogenous proteins in haploid yeast cells to their diploid counterparts. Our analysis spans more than four orders of magnitude in protein abundance with no discrimination against membrane or low level regulatory proteins. Stable-isotope labelling by amino acids in cell culture (SILAC) quantification was very accurate across the proteome, as demonstrated by one-to-one ratios of most yeast proteins. Key members of the pheromone pathway were specific to haploid yeast but others were unaltered, suggesting an efficient control mechanism of the mating response. Several retrotransposon-associated proteins were specific to haploid yeast. Gene ontology analysis pinpointed a significant change for cell wall components in agreement with geometrical considerations: diploid cells have twice the volume but not twice the surface area of haploid cells. Transcriptome levels agreed poorly with proteome changes overall. However, after filtering out low confidence microarray measurements, messenger RNA changes and SILAC ratios correlated very well for pheromone pathway components. Systems-wide, precise quantification directly at the protein level opens up new perspectives in post-genomics and systems biology.
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              A practical guide to the MaxQuant computational platform for SILAC-based quantitative proteomics.

              MaxQuant is a quantitative proteomics software package designed for analyzing large mass spectrometric data sets. It is specifically aimed at high-resolution mass spectrometry (MS) data. Currently, Thermo LTQ-Orbitrap and LTQ-FT-ICR instruments are supported and Mascot is used as a search engine. This protocol explains step by step how to use MaxQuant on stable isotope labeling by amino acids in cell culture (SILAC) data obtained with double or triple labeling. Complex experimental designs, such as time series and drug-response data, are supported. A standard desktop computer is sufficient to fulfill the computational requirements. The workflow has been stress tested with more than 1,000 liquid chromatography/mass spectrometry runs in a single project. In a typical SILAC proteome experiment, hundreds of thousands of peptides and thousands of proteins are automatically and reliably quantified. Additional information for identified proteins, such as Gene Ontology, domain composition and pathway membership, is provided in the output tables ready for further bioinformatics analysis. The software is freely available at the MaxQuant home page.
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                Author and article information

                Journal
                Mol Cell Proteomics
                mcprot
                mcprot
                MCP
                Molecular & Cellular Proteomics : MCP
                The American Society for Biochemistry and Molecular Biology
                1535-9476
                1535-9484
                December 2009
                14 October 2009
                14 October 2009
                : 8
                : 12
                : 2759-2769
                Affiliations
                [1]From ‖Thermo Fisher Scientific (Bremen) GmbH, Hanna-Kunath-Strasse 11, 28199 Bremen, Germany,
                [2]‡The Department of Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Am Klopferspitz 18, 82152 Martinsried, Germany, and
                [3]¶Thermo Fisher Scientific, 355 River Oak Parkway, San Jose, California 95134
                Author notes
                ** To whom correspondence may be addressed. E-mail: mmann@ 123456biochem.mpg.de .
                ‡‡ To whom correspondence may be addressed. E-mail: stevan.horning@ 123456thermofisher.com .

                § Present address: Novo Nordisk Foundation Center for Protein Research, Faculty of Health Sciences, University of Copenhagen, Blegdamsvej 3b, 2200 Copenhagen, Denmark.

                Article
                M900375-MCP200
                10.1074/mcp.M900375-MCP200
                2816009
                19828875
                0cc58a3c-1b7f-4bd5-8f3d-d85009910ffe
                © 2009 by The American Society for Biochemistry and Molecular Biology, Inc.

                Author's Choice—Final version full access.

                Creative Commons Attribution Non-Commercial License applies to Author Choice Articles

                History
                : 13 August 2009
                : 13 October 2009
                Categories
                Research

                Molecular biology
                Molecular biology

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