Literature DB >> 21988777

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

Jong-Seo Kim1, Thomas L Fillmore, Tao Liu, Errol Robinson, Mahmud Hossain, Boyd L Champion, Ronald J Moore, David G Camp, Richard D Smith, Wei-Jun Qian.   

Abstract

Selected reaction monitoring (SRM)-MS is an emerging technology for high throughput targeted protein quantification and verification in biomarker discovery studies; however, the cost associated with the application of stable isotope-labeled synthetic peptides as internal standards can be prohibitive for screening a large number of candidate proteins as often required in the preverification phase of discovery studies. Herein we present a proof of concept study using an (18)O-labeled proteome reference as global internal standards (GIS) for SRM-based relative quantification. The (18)O-labeled proteome reference (or GIS) can be readily prepared and contains a heavy isotope ((18)O)-labeled internal standard for every possible tryptic peptide. Our results showed that the percentage of heavy isotope ((18)O) incorporation applying an improved protocol was >99.5% for most peptides investigated. The accuracy, reproducibility, and linear dynamic range of quantification were further assessed based on known ratios of standard proteins spiked into the labeled mouse plasma reference. Reliable quantification was observed with high reproducibility (i.e. coefficient of variance <10%) for analyte concentrations that were set at 100-fold higher or lower than those of the GIS based on the light ((16)O)/heavy ((18)O) peak area ratios. The utility of (18)O-labeled GIS was further illustrated by accurate relative quantification of 45 major human plasma proteins. Moreover, quantification of the concentrations of C-reactive protein and prostate-specific antigen was illustrated by coupling the GIS with standard additions of purified protein standards. Collectively, our results demonstrated that the use of (18)O-labeled proteome reference as GIS provides a convenient, low cost, and effective strategy for relative quantification of a large number of candidate proteins in biological or clinical samples using SRM.

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Year:  2011        PMID: 21988777      PMCID: PMC3237067          DOI: 10.1074/mcp.M110.007302

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


  33 in total

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5.  Plasma concentration of C-reactive protein and risk of ischemic stroke and transient ischemic attack: the Framingham study.

Authors:  N S Rost; P A Wolf; C S Kase; M Kelly-Hayes; H Silbershatz; J M Massaro; R B D'Agostino; C Franzblau; P W Wilson
Journal:  Stroke       Date:  2001-11       Impact factor: 7.914

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.  Plasma concentration of C-reactive protein and the calculated Framingham Coronary Heart Disease Risk Score.

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8.  Metabolic labeling of mammalian organisms with stable isotopes for quantitative proteomic analysis.

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10.  A method for calculating 16O/18O peptide ion ratios for the relative quantification of proteomes.

Authors:  Kenneth L Johnson; David C Muddiman
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5.  Resin-assisted enrichment of N-terminal peptides for characterizing proteolytic processing.

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Journal:  Anal Chem       Date:  2013-06-27       Impact factor: 6.986

6.  Targeted, Site-specific quantitation of N- and O-glycopeptides using 18O-labeling and product ion based mass spectrometry.

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8.  ExSTA: External Standard Addition Method for Accurate High-Throughput Quantitation in Targeted Proteomics Experiments.

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Review 9.  Proteomics for Early Detection of Non-Muscle-Invasive Bladder Cancer: Clinically Useful Urine Protein Biomarkers.

Authors:  Jae-Hak Ahn; Chan-Koo Kang; Eun-Mee Kim; Ah-Ram Kim; Aram Kim
Journal:  Life (Basel)       Date:  2022-03-09
  9 in total

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