Literature DB >> 21293456

Use of stable isotope labeling by amino acids in cell culture as a spike-in standard in quantitative proteomics.

Tamar Geiger1, Jacek R Wisniewski, Juergen Cox, Sara Zanivan, Marcus Kruger, Yasushi Ishihama, Matthias Mann.   

Abstract

Mass spectrometry (MS)-based proteomics is increasingly applied in a quantitative format, often based on labeling of samples with stable isotopes that are introduced chemically or metabolically. In the stable isotope labeling by amino acids in cell culture (SILAC) method, two cell populations are cultured in the presence of heavy or light amino acids (typically lysine and/or arginine), one of them is subjected to a perturbation, and then both are combined and processed together. In this study, we describe a different approach--the use of SILAC as an internal or 'spike-in' standard--wherein SILAC is only used to produce heavy labeled reference proteins or proteomes. These are added to the proteomes under investigation after cell lysis and before protein digestion. The actual experiment is therefore completely decoupled from the labeling procedure. Spike-in SILAC is very economical, robust and in principle applicable to all cell- or tissue-based proteomic analyses. Applications range from absolute quantification of single proteins to the quantification of whole proteomes. Spike-in SILAC is especially advantageous when analyzing the proteomes of whole tissues or organisms. The protocol describes the quantitative analysis of a tissue sample relative to super-SILAC spike-in, a mixture of five SILAC-labeled cell lines that accurately represents the tissue. It includes the selection and preparation of the spike-in SILAC standard, the sample preparation procedure, and analysis and evaluation of the results.

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Year:  2011        PMID: 21293456     DOI: 10.1038/nprot.2010.192

Source DB:  PubMed          Journal:  Nat Protoc        ISSN: 1750-2799            Impact factor:   13.491


  44 in total

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4.  Combination of FASP and StageTip-based fractionation allows in-depth analysis of the hippocampal membrane proteome.

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5.  Isotope-labeled protein standards: toward absolute quantitative proteomics.

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6.  Quantitative phosphoproteomics applied to the yeast pheromone signaling pathway.

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7.  SILAC mouse for quantitative proteomics uncovers kindlin-3 as an essential factor for red blood cell function.

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8.  Unbiased quantitation of Escherichia coli membrane proteome using phase transfer surfactants.

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9.  FLEXIQuant: a novel tool for the absolute quantification of proteins, and the simultaneous identification and quantification of potentially modified peptides.

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10.  Protocol for micro-purification, enrichment, pre-fractionation and storage of peptides for proteomics using StageTips.

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Journal:  Nat Protoc       Date:  2007       Impact factor: 13.491

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  107 in total

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2.  Vibrational imaging of newly synthesized proteins in live cells by stimulated Raman scattering microscopy.

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3.  Rapid and deep human proteome analysis by single-dimension shotgun proteomics.

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4.  SILAC-based proteomics of human primary endothelial cell morphogenesis unveils tumor angiogenic markers.

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Journal:  Mol Cell Proteomics       Date:  2013-08-26       Impact factor: 5.911

5.  Dissection of affinity captured LINE-1 macromolecular complexes.

Authors:  Martin S Taylor; Ilya Altukhov; Kelly R Molloy; Paolo Mita; Hua Jiang; Emily M Adney; Aleksandra Wudzinska; Sana Badri; Dmitry Ischenko; George Eng; Kathleen H Burns; David Fenyö; Brian T Chait; Dmitry Alexeev; Michael P Rout; Jef D Boeke; John LaCava
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6.  SILAC-based quantitative proteomic analysis of Drosophila gastrula stage embryos mutant for fibroblast growth factor signalling.

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7.  Large-scale phosphosite quantification in tissues by a spike-in SILAC method.

Authors:  Mara Monetti; Nagarjuna Nagaraj; Kirti Sharma; Matthias Mann
Journal:  Nat Methods       Date:  2011-07-10       Impact factor: 28.547

8.  Comparability analysis of protein therapeutics by bottom-up LC-MS with stable isotope-tagged reference standards.

Authors:  Anton V Manuilov; Czeslaw H Radziejewski; David H Lee
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9.  Human platelets as a platform to monitor metabolic biomarkers using stable isotopes and LC-MS.

Authors:  Sankha S Basu; Eric C Deutsch; Alec A Schmaier; David R Lynch; Ian A Blair
Journal:  Bioanalysis       Date:  2013-12       Impact factor: 2.681

10.  Sources of technical variability in quantitative LC-MS proteomics: human brain tissue sample analysis.

Authors:  Paul D Piehowski; Vladislav A Petyuk; Daniel J Orton; Fang Xie; Ronald J Moore; Manuel Ramirez-Restrepo; Anzhelika Engel; Andrew P Lieberman; Roger L Albin; David G Camp; Richard D Smith; Amanda J Myers
Journal:  J Proteome Res       Date:  2013-04-10       Impact factor: 4.466

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