Literature DB >> 20104619

Quantitative analysis of SILAC data sets using spectral counting.

Sarah J Parker1, Brian D Halligan, Andrew S Greene.   

Abstract

We report a new quantitative proteomics approach that combines the best aspects of stable isotope labeling of amino acids in cell culture (SILAC) labeling and spectral counting. The SILAC peptide count ratio analysis (SPeCtRA, http://proteomics.mcw.edu/visualize) method relies on MS(2) spectra rather than ion chromatograms for quantitation and therefore does not require the use of high mass accuracy mass spectrometers. The inclusion of a stable isotope label allows the samples to be combined before sample preparation and analysis, thus avoiding many of the sources of variability that can plague spectral counting. To validate the SPeCtRA method, we have analyzed samples constructed with known ratios of protein abundance. Finally, we used SPeCtRA to compare endothelial cell protein abundances between high (20 mM) and low (11 mM) glucose culture conditions. Our results demonstrate that SPeCtRA is a protein quantification technique that is accurate and sensitive as well as easy to automate and apply to high-throughput analysis of complex biological samples.

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Year:  2010        PMID: 20104619      PMCID: PMC4326228          DOI: 10.1002/pmic.200900684

Source DB:  PubMed          Journal:  Proteomics        ISSN: 1615-9853            Impact factor:   3.984


  20 in total

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2.  Comparison of label-free methods for quantifying human proteins by shotgun proteomics.

Authors:  William M Old; Karen Meyer-Arendt; Lauren Aveline-Wolf; Kevin G Pierce; Alex Mendoza; Joel R Sevinsky; Katheryn A Resing; Natalie G Ahn
Journal:  Mol Cell Proteomics       Date:  2005-06-23       Impact factor: 5.911

3.  Relative quantification of peptide phosphorylation in a complex mixture using 18O labeling.

Authors:  Julia R Smith; Michael Olivier; Andrew S Greene
Journal:  Physiol Genomics       Date:  2007-08-07       Impact factor: 3.107

4.  MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification.

Authors:  Jürgen Cox; Matthias Mann
Journal:  Nat Biotechnol       Date:  2008-11-30       Impact factor: 54.908

5.  Stable isotope labeling of Arabidopsis thaliana cells and quantitative proteomics by mass spectrometry.

Authors:  Albrecht Gruhler; Waltraud X Schulze; Rune Matthiesen; Matthias Mann; Ole N Jensen
Journal:  Mol Cell Proteomics       Date:  2005-08-08       Impact factor: 5.911

6.  Conversion of arginine to proline in the chick.

Authors:  R E Austic
Journal:  J Nutr       Date:  1973-07       Impact factor: 4.798

7.  Improved mass spectrometric proteomic profiling of the secretome of rat vascular endothelial cells.

Authors:  M C Pellitteri-Hahn; M C Warren; D N Didier; E L Winkler; S P Mirza; A S Greene; M Olivier
Journal:  J Proteome Res       Date:  2006-10       Impact factor: 4.466

8.  Correlation of relative abundance ratios derived from peptide ion chromatograms and spectrum counting for quantitative proteomic analysis using stable isotope labeling.

Authors:  Boris Zybailov; Michael K Coleman; Laurence Florens; Michael P Washburn
Journal:  Anal Chem       Date:  2005-10-01       Impact factor: 6.986

9.  A proteomics strategy to elucidate functional protein-protein interactions applied to EGF signaling.

Authors:  Blagoy Blagoev; Irina Kratchmarova; Shao-En Ong; Mogens Nielsen; Leonard J Foster; Matthias Mann
Journal:  Nat Biotechnol       Date:  2003-02-10       Impact factor: 54.908

10.  Prevention of amino acid conversion in SILAC experiments with embryonic stem cells.

Authors:  Sean C Bendall; Chris Hughes; Morag H Stewart; Brad Doble; Mickie Bhatia; Gilles A Lajoie
Journal:  Mol Cell Proteomics       Date:  2008-05-16       Impact factor: 5.911

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  3 in total

1.  Visualize: a free and open source multifunction tool for proteomics data analysis.

Authors:  Brian D Halligan; Andrew S Greene
Journal:  Proteomics       Date:  2011-02-07       Impact factor: 3.984

2.  Global analysis of condition-specific subcellular protein distribution and abundance.

Authors:  Sunhee Jung; Jennifer J Smith; Priska D von Haller; David J Dilworth; Katherine A Sitko; Leslie R Miller; Ramsey A Saleem; David R Goodlett; John D Aitchison
Journal:  Mol Cell Proteomics       Date:  2013-01-24       Impact factor: 5.911

3.  SILAC peptide ratio calculator: a tool for SILAC quantitation of peptides and post-translational modifications.

Authors:  Xiaoyan Guan; Neha Rastogi; Mark R Parthun; Michael A Freitas
Journal:  J Proteome Res       Date:  2014-01-09       Impact factor: 4.466

  3 in total

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