Literature DB >> 16396510

Systematic evaluation of sample preparation methods for gel-based human urinary proteomics: quantity, quality, and variability.

Visith Thongboonkerd1, Somchai Chutipongtanate, Rattiyaporn Kanlaya.   

Abstract

We performed systematic evaluation of 38 protocols to concentrate normal human urinary proteins prior to 2D-PAGE analysis. Recovery yield and pattern of resolved protein spots were compared among different methods and intra-/inter-individual variabilities were examined. Precipitation with 90% ethanol provided the greatest protein recovery yield (92.99%), whereas precipitation with 10% acetic acid had the least protein recovery (1.91%). In most of precipitation protocols, the higher percentage of applied organic compounds provided the greater recovery yield. With a fixed concentration at 75%, the urine precipitated with acetonitrile had the greatest number of protein spots visualized in 2D gel, whereas the acetic-precipitated sample had the smallest number of spots. For the intra-individual variability, the first morning urine had the greatest amount of total protein but provided the smallest number of protein spots visualized. Excessive water drinking, not caffeine ingestion, caused alterations in the urinary proteome profile with newly presenting spots and also proteins with decreased excretion levels. As expected, there was a considerable degree of inter-individual variability. Coefficients of variation for albumin and transferrin expression were greatest by inter-individual variables. Male urine had greater amount of total protein but provided smaller number of protein spots compared to female urine. These data offer a wealth of useful information for designing a high-quality, large-scale human urine proteome project.

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Year:  2006        PMID: 16396510     DOI: 10.1021/pr0502525

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


  40 in total

1.  One-step sample concentration, purification, and albumin depletion method for urinary proteomics.

Authors:  Ali R Vaezzadeh; Andrew C Briscoe; Hanno Steen; Richard S Lee
Journal:  J Proteome Res       Date:  2010-10-15       Impact factor: 4.466

2.  Optimizing a proteomics platform for urine biomarker discovery.

Authors:  Maryam Afkarian; Manoj Bhasin; Simon T Dillon; Manuel C Guerrero; Robert G Nelson; William C Knowler; Ravi Thadhani; Towia A Libermann
Journal:  Mol Cell Proteomics       Date:  2010-05-28       Impact factor: 5.911

Review 3.  Urine collection and processing for protein biomarker discovery and quantification.

Authors:  C Eric Thomas; Wade Sexton; Kaaron Benson; Rebecca Sutphen; John Koomen
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2010-03-23       Impact factor: 4.254

4.  Variation in protein levels obtained from human blood cells and biofluids for platelet, peripheral blood mononuclear cell, plasma, urine and saliva proteomics.

Authors:  L Katie Crosley; Susan J Duthie; Abigael C Polley; Freek G Bouwman; Carolin Heim; Francis Mulholland; Graham Horgan; Ian T Johnson; Edwin C Mariman; Ruan M Elliott; Hannelore Daniel; Baukje de Roos
Journal:  Genes Nutr       Date:  2009-04-29       Impact factor: 5.523

5.  Evaluation of urinary protein precipitation protocols for the multidisciplinary approach to the study of chronic pelvic pain research network.

Authors:  Karen R Jonscher; Andrea A Osypuk; Adrie van Bokhoven; M Scott Lucia
Journal:  J Biomol Tech       Date:  2014-12

6.  Comprehensive Analysis of Individual Variation in the Urinary Proteome Revealed Significant Gender Differences.

Authors:  Chen Shao; Mindi Zhao; Xizhao Chen; Haidan Sun; Yehong Yang; Xiaoping Xiao; Zhengguang Guo; Xiaoyan Liu; Yang Lv; Xiangmei Chen; Wei Sun; Di Wu; Youhe Gao
Journal:  Mol Cell Proteomics       Date:  2019-03-20       Impact factor: 5.911

7.  Simple Tip-Based Sample Processing Method for Urinary Proteomic Analysis.

Authors:  David J Clark; Yingwei Hu; Michael Schnaubelt; Yi Fu; Sean Ponce; Shao-Yung Chen; Yangying Zhou; Punit Shah; Hui Zhang
Journal:  Anal Chem       Date:  2019-04-08       Impact factor: 6.986

8.  Evaluation of the variation in sample preparation for comparative proteomics using stable isotope labeling by amino acids in cell culture.

Authors:  Guoan Zhang; David Fenyö; Thomas A Neubert
Journal:  J Proteome Res       Date:  2009-03       Impact factor: 4.466

9.  Optimizing sample handling for urinary proteomics.

Authors:  Richard S Lee; Flavio Monigatti; Andrew C Briscoe; Zachary Waldon; Michael R Freeman; Hanno Steen
Journal:  J Proteome Res       Date:  2008-07-29       Impact factor: 4.466

Review 10.  Quality assessment for clinical proteomics.

Authors:  David L Tabb
Journal:  Clin Biochem       Date:  2012-12-12       Impact factor: 3.281

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