Literature DB >> 18511481

An integrated, directed mass spectrometric approach for in-depth characterization of complex peptide mixtures.

Alexander Schmidt1, Nils Gehlenborg, Bernd Bodenmiller, Lukas N Mueller, Dave Campbell, Markus Mueller, Ruedi Aebersold, Bruno Domon.   

Abstract

LC-MS/MS has emerged as the method of choice for the identification and quantification of protein sample mixtures. For very complex samples such as complete proteomes, the most commonly used LC-MS/MS method, data-dependent acquisition (DDA) precursor selection, is of limited utility. The limited scan speed of current mass spectrometers along with the highly redundant selection of the most intense precursor ions generates a bias in the pool of identified proteins toward those of higher abundance. A directed LC-MS/MS approach that alleviates the limitations of DDA precursor ion selection by decoupling peak detection and sequencing of selected precursor ions is presented. In the first stage of the strategy, all detectable peptide ion signals are extracted from high resolution LC-MS feature maps or aligned sets of feature maps. The selected features or a subset thereof are subsequently sequenced in sequential, non-redundant directed LC-MS/MS experiments, and the MS/MS data are mapped back to the original LC-MS feature map in a fully automated manner. The strategy, implemented on an LTQ-FT MS platform, allowed the specific sequencing of 2,000 features per analysis and enabled the identification of more than 1,600 phosphorylation sites using a single reversed phase separation dimension without the need for time-consuming prefractionation steps. Compared with conventional DDA LC-MS/MS experiments, a substantially higher number of peptides could be identified from a sample, and this increase was more pronounced for low intensity precursor ions.

Entities:  

Mesh:

Substances:

Year:  2008        PMID: 18511481      PMCID: PMC2577211          DOI: 10.1074/mcp.M700498-MCP200

Source DB:  PubMed          Journal:  Mol Cell Proteomics        ISSN: 1535-9476            Impact factor:   5.911


  40 in total

1.  Mass measurement errors caused by 'local" frequency perturbations in FTICR mass spectrometry.

Authors:  Christophe Masselon; Aleksey V Tolmachev; Gordon A Anderson; Richard Harkewicz; Richard D Smith
Journal:  J Am Soc Mass Spectrom       Date:  2002-01       Impact factor: 3.109

2.  An integrated mass spectrometric and computational framework for the analysis of protein interaction networks.

Authors:  Oliver Rinner; Lukas N Mueller; Martin Hubálek; Markus Müller; Matthias Gstaiger; Ruedi Aebersold
Journal:  Nat Biotechnol       Date:  2007-02-25       Impact factor: 54.908

3.  Development and validation of a spectral library searching method for peptide identification from MS/MS.

Authors:  Henry Lam; Eric W Deutsch; James S Eddes; Jimmy K Eng; Nichole King; Stephen E Stein; Ruedi Aebersold
Journal:  Proteomics       Date:  2007-03       Impact factor: 3.984

4.  Approaching complete peroxisome characterization by gas-phase fractionation.

Authors:  Eugene C Yi; Marcello Marelli; Hookeun Lee; Samuel O Purvine; Ruedi Aebersold; John D Aitchison; David R Goodlett
Journal:  Electrophoresis       Date:  2002-09       Impact factor: 3.535

5.  The implications of proteolytic background for shotgun proteomics.

Authors:  Paola Picotti; Ruedi Aebersold; Bruno Domon
Journal:  Mol Cell Proteomics       Date:  2007-05-28       Impact factor: 5.911

6.  Parts-per-billion mass measurement accuracy achieved through the combination of multiple linear regression and automatic gain control in a Fourier transform ion cyclotron resonance mass spectrometer.

Authors:  D Keith Williams; David C Muddiman
Journal:  Anal Chem       Date:  2007-06-01       Impact factor: 6.986

7.  Identification of cross-linked peptides from large sequence databases.

Authors:  Oliver Rinner; Jan Seebacher; Thomas Walzthoeni; Lukas N Mueller; Martin Beck; Alexander Schmidt; Markus Mueller; Ruedi Aebersold
Journal:  Nat Methods       Date:  2008-03-09       Impact factor: 28.547

8.  SuperHirn - a novel tool for high resolution LC-MS-based peptide/protein profiling.

Authors:  Lukas N Mueller; Oliver Rinner; Alexander Schmidt; Simon Letarte; Bernd Bodenmiller; Mi-Youn Brusniak; Olga Vitek; Ruedi Aebersold; Markus Müller
Journal:  Proteomics       Date:  2007-10       Impact factor: 3.984

9.  Protein identification with a single accurate mass of a cysteine-containing peptide and constrained database searching.

Authors:  D R Goodlett; J E Bruce; G A Anderson; B Rist; L Pasa-Tolic; O Fiehn; R D Smith; R Aebersold
Journal:  Anal Chem       Date:  2000-03-15       Impact factor: 6.986

10.  A high-quality catalog of the Drosophila melanogaster proteome.

Authors:  Erich Brunner; Christian H Ahrens; Sonali Mohanty; Hansruedi Baetschmann; Sandra Loevenich; Frank Potthast; Eric W Deutsch; Christian Panse; Ulrik de Lichtenberg; Oliver Rinner; Hookeun Lee; Patrick G A Pedrioli; Johan Malmstrom; Katja Koehler; Sabine Schrimpf; Jeroen Krijgsveld; Floyd Kregenow; Albert J R Heck; Ernst Hafen; Ralph Schlapbach; Ruedi Aebersold
Journal:  Nat Biotechnol       Date:  2007-04-22       Impact factor: 54.908

View more
  53 in total

1.  Generic comparison of protein inference engines.

Authors:  Manfred Claassen; Lukas Reiter; Michael O Hengartner; Joachim M Buhmann; Ruedi Aebersold
Journal:  Mol Cell Proteomics       Date:  2011-11-04       Impact factor: 5.911

2.  Synthetic peptide arrays for pathway-level protein monitoring by liquid chromatography-tandem mass spectrometry.

Authors:  Johannes A Hewel; Jian Liu; Kento Onishi; Vincent Fong; Shamanta Chandran; Jonathan B Olsen; Oxana Pogoutse; Mike Schutkowski; Holger Wenschuh; Dirk F H Winkler; Larry Eckler; Peter W Zandstra; Andrew Emili
Journal:  Mol Cell Proteomics       Date:  2010-05-13       Impact factor: 5.911

3.  Options and considerations when selecting a quantitative proteomics strategy.

Authors:  Bruno Domon; Ruedi Aebersold
Journal:  Nat Biotechnol       Date:  2010-07-09       Impact factor: 54.908

4.  SILACtor: software to enable dynamic SILAC studies.

Authors:  Michael R Hoopmann; Juan D Chavez; James E Bruce
Journal:  Anal Chem       Date:  2011-10-27       Impact factor: 6.986

Review 5.  Quantitative strategies to fuel the merger of discovery and hypothesis-driven shotgun proteomics.

Authors:  Kelli G Kline; Greg L Finney; Christine C Wu
Journal:  Brief Funct Genomic Proteomic       Date:  2009-03

6.  Halogenated peptides as internal standards (H-PINS): introduction of an MS-based internal standard set for liquid chromatography-mass spectrometry.

Authors:  Hamid Mirzaei; Mi-Youn Brusniak; Lukas N Mueller; Simon Letarte; Julian D Watts; Ruedi Aebersold
Journal:  Mol Cell Proteomics       Date:  2009-05-01       Impact factor: 5.911

7.  Prequips--an extensible software platform for integration, visualization and analysis of LC-MS/MS proteomics data.

Authors:  Nils Gehlenborg; Wei Yan; Inyoul Y Lee; Hyuntae Yoo; Kay Nieselt; Daehee Hwang; Ruedi Aebersold; Leroy Hood
Journal:  Bioinformatics       Date:  2009-01-06       Impact factor: 6.937

8.  Instant spectral assignment for advanced decision tree-driven mass spectrometry.

Authors:  Derek J Bailey; Christopher M Rose; Graeme C McAlister; Justin Brumbaugh; Pengzhi Yu; Craig D Wenger; Michael S Westphall; James A Thomson; Joshua J Coon
Journal:  Proc Natl Acad Sci U S A       Date:  2012-05-14       Impact factor: 11.205

9.  Comprehensive characterization of extracellular herpes simplex virus type 1 virions.

Authors:  Sandra Loret; Ginette Guay; Roger Lippé
Journal:  J Virol       Date:  2008-07-02       Impact factor: 5.103

10.  Advanced Precursor Ion Selection Algorithms for Increased Depth of Bottom-Up Proteomic Profiling.

Authors:  Simion Kreimer; Mikhail E Belov; William F Danielson; Lev I Levitsky; Mikhail V Gorshkov; Barry L Karger; Alexander R Ivanov
Journal:  J Proteome Res       Date:  2016-09-07       Impact factor: 4.466

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.