Literature DB >> 19222237

A simple procedure for effective quenching of trypsin activity and prevention of 18O-labeling back-exchange.

Brianne O Petritis1, Wei-Jun Qian, David G Camp, Richard D Smith.   

Abstract

Trypsin-catalyzed stable isotope 16O/18O-labeling of the C-terminal carboxyl groups of peptides is increasingly used in shotgun proteomics for relative peptide/protein quantitation. However, precise quantitative measurements are often complicated by residual trypsin that can catalyze the back-exchange of 18O with 16O after labeling. Here, we demonstrate through a detailed evaluation that boiling the peptide sample for 10 min provides a simple means for completely quenching residual trypsin activity and preventing oxygen back-exchange in 18O-labeled samples. We also observed that the presence of organic solvents such as acetonitrile made boiling less efficient for inactivating trypsin. Finally, current 18O-labeling methods that typically employ immobilized trypsin result in significant sample losses due to nonspecific binding of peptides to the resin, making their application toward smaller biological samples increasingly impractical. We present here an improved 18O-labeling protocol that is more applicable to microscale biological samples by using solution-phase trypsin instead of immobilized trypsin. The ability to generate stably 18O-labeled samples without back-exchange should enable more effective applications of 18O-labeling toward large-scale biomarker discovery and validations where an 18O-labeled sample can be used as a common reference for quantitation.

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Year:  2009        PMID: 19222237      PMCID: PMC2728467          DOI: 10.1021/pr800971w

Source DB:  PubMed          Journal:  J Proteome Res        ISSN: 1535-3893            Impact factor:   4.466


  20 in total

1.  Trypsin catalyzed 16O-to-18O exchange for comparative proteomics: tandem mass spectrometry comparison using MALDI-TOF, ESI-QTOF, and ESI-ion trap mass spectrometers.

Authors:  Manfred Heller; Hassan Mattou; Christoph Menzel; Xudong Yao
Journal:  J Am Soc Mass Spectrom       Date:  2003-07       Impact factor: 3.109

Review 2.  Mass spectrometry-based proteomics turns quantitative.

Authors:  Shao-En Ong; Matthias Mann
Journal:  Nat Chem Biol       Date:  2005-10       Impact factor: 15.040

3.  Spatial mapping of protein abundances in the mouse brain by voxelation integrated with high-throughput liquid chromatography-mass spectrometry.

Authors:  Vladislav A Petyuk; Wei-Jun Qian; Mark H Chin; Haixing Wang; Eric A Livesay; Matthew E Monroe; Joshua N Adkins; Navdeep Jaitly; David J Anderson; David G Camp; Desmond J Smith; Richard D Smith
Journal:  Genome Res       Date:  2007-01-25       Impact factor: 9.043

4.  Enhanced detection of low abundance human plasma proteins using a tandem IgY12-SuperMix immunoaffinity separation strategy.

Authors:  Wei-Jun Qian; David T Kaleta; Brianne O Petritis; Hongliang Jiang; Tao Liu; Xu Zhang; Heather M Mottaz; Susan M Varnum; David G Camp; Lei Huang; Xiangming Fang; Wei-Wei Zhang; Richard D Smith
Journal:  Mol Cell Proteomics       Date:  2008-07-15       Impact factor: 5.911

5.  18O labeling: a tool for proteomics.

Authors:  I I Stewart; T Thomson; D Figeys
Journal:  Rapid Commun Mass Spectrom       Date:  2001       Impact factor: 2.419

6.  Quantitative proteome analysis of human plasma following in vivo lipopolysaccharide administration using 16O/18O labeling and the accurate mass and time tag approach.

Authors:  Wei-Jun Qian; Matthew E Monroe; Tao Liu; Jon M Jacobs; Gordon A Anderson; Yufeng Shen; Ronald J Moore; David J Anderson; Rui Zhang; Steve E Calvano; Stephen F Lowry; Wenzhong Xiao; Lyle L Moldawer; Ronald W Davis; Ronald G Tompkins; David G Camp; Richard D Smith
Journal:  Mol Cell Proteomics       Date:  2005-03-07       Impact factor: 5.911

7.  Large-scale multiplexed quantitative discovery proteomics enabled by the use of an (18)O-labeled "universal" reference sample.

Authors:  Wei-Jun Qian; Tao Liu; Vladislav A Petyuk; Marina A Gritsenko; Brianne O Petritis; Ashoka D Polpitiya; Amit Kaushal; Wenzhong Xiao; Celeste C Finnerty; Marc G Jeschke; Navdeep Jaitly; Matthew E Monroe; Ronald J Moore; Lyle L Moldawer; Ronald W Davis; Ronald G Tompkins; David N Herndon; David G Camp; Richard D Smith
Journal:  J Proteome Res       Date:  2009-01       Impact factor: 4.466

8.  Proteolytic labeling with 18O for comparative proteomics studies: preparation of 18O-labeled peptides and the 18O/16O peptide mixture.

Authors:  Catherine Fenselau; Xudong Yao
Journal:  Methods Mol Biol       Date:  2007

9.  Mitochondrial dysfunction, oxidative stress, and apoptosis revealed by proteomic and transcriptomic analyses of the striata in two mouse models of Parkinson's disease.

Authors:  Mark H Chin; Wei-Jun Qian; Haixing Wang; Vladislav A Petyuk; Joshua S Bloom; Daniel M Sforza; Goran Laćan; Dahai Liu; Arshad H Khan; Rita M Cantor; Diana J Bigelow; William P Melega; David G Camp; Richard D Smith; Desmond J Smith
Journal:  J Proteome Res       Date:  2008-02       Impact factor: 4.466

Review 10.  The use of two-dimensional SDS-PAGE to analyze the glycan heterogeneity of the respiratory syncytial virus fusion protein.

Authors:  Terence P McDonald; Richard J Sugrue
Journal:  Methods Mol Biol       Date:  2007
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  16 in total

1.  Targeted 18O-labeling for improved proteomic analysis of carbonylated peptides by mass spectrometry.

Authors:  Mikel R Roe; Thomas F McGowan; LaDora V Thompson; Timothy J Griffin
Journal:  J Am Soc Mass Spectrom       Date:  2010-03-29       Impact factor: 3.109

2.  Quantitative proteomics analysis of adsorbed plasma proteins classifies nanoparticles with different surface properties and size.

Authors:  Haizhen Zhang; Kristin E Burnum; Maria L Luna; Brianne O Petritis; Jong-Seo Kim; Wei-Jun Qian; Ronald J Moore; Alejandro Heredia-Langner; Bobbie-Jo M Webb-Robertson; Brian D Thrall; David G Camp; Richard D Smith; Joel G Pounds; Tao Liu
Journal:  Proteomics       Date:  2011-11-04       Impact factor: 3.984

Review 3.  Unraveling pancreatic islet biology by quantitative proteomics.

Authors:  Jian-Ying Zhou; Geoffrey P Dann; Chong Wee Liew; Richard D Smith; Rohit N Kulkarni; Wei-Jun Qian
Journal:  Expert Rev Proteomics       Date:  2011-08       Impact factor: 3.940

4.  Compensatory Islet Response to Insulin Resistance Revealed by Quantitative Proteomics.

Authors:  Abdelfattah El Ouaamari; Jian-Ying Zhou; Chong Wee Liew; Jun Shirakawa; Ercument Dirice; Nicholas Gedeon; Sevim Kahraman; Dario F De Jesus; Shweta Bhatt; Jong-Seo Kim; Therese Rw Clauss; David G Camp; Richard D Smith; Wei-Jun Qian; Rohit N Kulkarni
Journal:  J Proteome Res       Date:  2015-07-30       Impact factor: 4.466

Review 5.  Liquid chromatography-mass spectrometry-based quantitative proteomics.

Authors:  Fang Xie; Tao Liu; Wei-Jun Qian; Vladislav A Petyuk; Richard D Smith
Journal:  J Biol Chem       Date:  2011-06-01       Impact factor: 5.157

6.  Proteomic analysis of early response lymph node proteins in mice treated with titanium dioxide nanoparticles.

Authors:  Yuan Gao; Neera V Gopee; Paul C Howard; Li-Rong Yu
Journal:  J Proteomics       Date:  2011-08-22       Impact factor: 4.044

7.  Enzyme Kinetics for Complex System Enables Accurate Determination of Specificity Constants of Numerous Substrates in a Mixture by Proteomics Platform.

Authors:  Zhenzhen Deng; Jiawei Mao; Yan Wang; Hanfa Zou; Mingliang Ye
Journal:  Mol Cell Proteomics       Date:  2016-11-16       Impact factor: 5.911

8.  Identification of Novel N-Glycosylation Sites at Noncanonical Protein Consensus Motifs.

Authors:  Mark S Lowenthal; Kiersta S Davis; Trina Formolo; Lisa E Kilpatrick; Karen W Phinney
Journal:  J Proteome Res       Date:  2016-06-14       Impact factor: 4.466

9.  18O-labeled proteome reference as global internal standards for targeted quantification by selected reaction monitoring-mass spectrometry.

Authors:  Jong-Seo Kim; Thomas L Fillmore; Tao Liu; Errol Robinson; Mahmud Hossain; Boyd L Champion; Ronald J Moore; David G Camp; Richard D Smith; Wei-Jun Qian
Journal:  Mol Cell Proteomics       Date:  2011-10-11       Impact factor: 5.911

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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