Literature DB >> 29116567

LC-SRM-Based Targeted Quantification of Urinary Protein Biomarkers.

Yuqian Gao1, Hui Wang1, Carrie D Nicora1, Tujin Shi1, Richard D Smith1, Tara K Sigdel2, Minnie M Sarwal2, David G Camp1, Wei-Jun Qian3.   

Abstract

Liquid chromatography (LC)-selected reaction monitoring (SRM) is a powerful protein quantification technique in terms of sensitivity, reproducibility, and multiplexing capability. LC-SRM can accurately measure the concentrations of surrogate proteotypic peptides for targeted proteins in complex biological samples by using their stable heavy isotope-labeled counterparts as internal standards. Herein, we describe a step-by-step protocol of the application of LC-SRM to quantify candidate protein biomarkers in human urine.

Entities:  

Keywords:  Biomarker; LC-SRM; Skyline; Stable heavy isotope-labeled peptide; Targeted quantification; Urine

Mesh：

Substances：

Year:  2018        PMID： 29116567      PMCID： PMC7224550          DOI： 10.1007/7651_2017_93

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN： 1064-3745


  17 in total

1.  Open source system for analyzing, validating, and storing protein identification data.

Authors:  Robertson Craig; John P Cortens; Ronald C Beavis
Journal:  J Proteome Res       Date:  2004 Nov-Dec       Impact factor: 4.466

Review 2.  Protein biomarker discovery and validation: the long and uncertain path to clinical utility.

Authors:  Nader Rifai; Michael A Gillette; Steven A Carr
Journal:  Nat Biotechnol       Date:  2006-08       Impact factor: 54.908

3.  Chemically etched open tubular and monolithic emitters for nanoelectrospray ionization mass spectrometry.

Authors:  Ryan T Kelly; Jason S Page; Quanzhou Luo; Ronald J Moore; Daniel J Orton; Keqi Tang; Richard D Smith
Journal:  Anal Chem       Date:  2006-11-15       Impact factor: 6.986

4.  Systematic quantification of peptides/proteins in urine using selected reaction monitoring.

Authors:  Nathalie Selevsek; Mariette Matondo; Marta Sanchez Carbayo; Ruedi Aebersold; Bruno Domon
Journal:  Proteomics       Date:  2011-02-16       Impact factor: 3.984

5.  Rapid verification of candidate serological biomarkers using gel-based, label-free multiple reaction monitoring.

Authors:  Hsin-Yao Tang; Lynn A Beer; Kurt T Barnhart; David W Speicher
Journal:  J Proteome Res       Date:  2011-07-26       Impact factor: 4.466

6.  The identification of novel potential injury mechanisms and candidate biomarkers in renal allograft rejection by quantitative proteomics.

Authors:  Tara K Sigdel; Nathan Salomonis; Carrie D Nicora; Soyoung Ryu; Jintang He; Van Dinh; Daniel J Orton; Ronald J Moore; Szu-Chuan Hsieh; Hong Dai; Minh Thien-Vu; Wenzhong Xiao; Richard D Smith; Wei-Jun Qian; David G Camp; Minnie M Sarwal
Journal:  Mol Cell Proteomics       Date:  2013-12-12       Impact factor: 5.911

7.  CONSeQuence: prediction of reference peptides for absolute quantitative proteomics using consensus machine learning approaches.

Authors:  Claire E Eyers; Craig Lawless; David C Wedge; King Wai Lau; Simon J Gaskell; Simon J Hubbard
Journal:  Mol Cell Proteomics       Date:  2011-08-03       Impact factor: 5.911

8.  Prediction of high-responding peptides for targeted protein assays by mass spectrometry.

Authors:  Vincent A Fusaro; D R Mani; Jill P Mesirov; Steven A Carr
Journal:  Nat Biotechnol       Date:  2009-01-25       Impact factor: 54.908

Review 9.  Advancing the sensitivity of selected reaction monitoring-based targeted quantitative proteomics.

Authors:  Tujin Shi; Dian Su; Tao Liu; Keqi Tang; David G Camp; Wei-Jun Qian; Richard D Smith
Journal:  Proteomics       Date:  2012-04       Impact factor: 3.984

10.  Expediting SRM assay development for large-scale targeted proteomics experiments.

Authors:  Chaochao Wu; Tujin Shi; Joseph N Brown; Jintang He; Yuqian Gao; Thomas L Fillmore; Anil K Shukla; Ronald J Moore; David G Camp; Karin D Rodland; Wei-Jun Qian; Tao Liu; Richard D Smith
Journal:  J Proteome Res       Date:  2014-09-04       Impact factor: 4.466
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.