Operator- and software-related post-experimental variability and source of error in 2-DE analysis

被引:6
作者
Millioni, Renato [1 ]
Puricelli, Lucia [1 ]
Sbrignadello, Stefano [1 ,2 ]
Iori, Elisabetta [1 ]
Murphy, Ellen [1 ]
Tessari, Paolo [1 ]
机构
[1] Univ Padua, Dept Clin & Expt Med, Div Metab, I-35128 Padua, Italy
[2] CNR, Inst Biomed Engn, Padua, Italy
关键词
2-DE; Post-experimental variability; Pixel-based method; Spot-based method; 2-DIMENSIONAL GEL-ELECTROPHORESIS; DIFFERENTIAL PROTEIN EXPRESSION; IMAGE-ANALYSIS SOFTWARE; PROTEOMICS; QUANTITATION; INFORMATION; CHALLENGES; PACKAGES; MELANIE; MODELS;
D O I
10.1007/s00726-011-0873-7
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
In the field of proteomics, several approaches have been developed for separating proteins and analyzing their differential relative abundance. One of the oldest, yet still widely used, is 2-DE. Despite the continuous advance of new methods, which are less demanding from a technical standpoint, 2-DE is still compelling and has a lot of potential for improvement. The overall variability which affects 2-DE includes biological, experimental, and post-experimental (software-related) variance. It is important to highlight how much of the total variability of this technique is due to post-experimental variability, which, so far, has been largely neglected. In this short review, we have focused on this topic and explained that post-experimental variability and source of error can be further divided into those which are software-dependent and those which are operator-dependent. We discuss these issues in detail, offering suggestions for reducing errors that may affect the quality of results, summarizing the advantages and drawbacks of each approach.
引用
收藏
页码:1583 / 1590
页数:8
相关论文
共 45 条
[11]   The myth of automated, high-throughput two-dimensional gel analysis [J].
Clark, Brittan N. ;
Gutstein, Howard B. .
PROTEOMICS, 2008, 8 (06) :1197-1203
[12]   Minimizing variability in two-dimensional electrophoresis gel image analysis [J].
Damodaran, Senthilkumar ;
Rabin, Richard A. .
OMICS-A JOURNAL OF INTEGRATIVE BIOLOGY, 2007, 11 (02) :225-230
[13]   Examination of 2-DE in the Human Proteome Organisation Brain Proteome Project pilot studies with the new RAIN gel matching technique [J].
Dowsey, Andrew W. ;
English, Jane ;
Pennington, Kyla ;
Cotter, David ;
Stuehler, Kai ;
Marcus, Katrin ;
Meyer, Helmut E. ;
Dunn, Michael J. ;
Yang, Guang-Zhong .
PROTEOMICS, 2006, 6 (18) :5030-5047
[14]   Alternative Experimental Design with an Applied Normalization Scheme Can Improve Statistical Power in 2D-DIGE Experiments [J].
Engelen, Kristof ;
Sifrim, Alejandro ;
Van de Plas, Babs ;
Laukens, Kris ;
Arckens, Lutgarde ;
Marchal, Kathleen .
JOURNAL OF PROTEOME RESEARCH, 2010, 9 (10) :4919-4926
[15]   Statistical challenges in the analysis of two-dimensional difference gel electrophoresis experiments using DeCyder™ [J].
Fodor, IK ;
Nelson, DO ;
Alegria-Hartman, M ;
Robbins, K ;
Langlois, RG ;
Turteltaub, KW ;
Corzett, TH ;
McCutchen-Maloney, SL .
BIOINFORMATICS, 2005, 21 (19) :3733-3740
[16]   Technical strategies to reduce the amount of "false significant" results in quantitative proteomics [J].
Fuxius, Sandra ;
Eravci, Murat ;
Broedel, Oliver ;
Weist, Stephanie ;
Mansmann, Ulrich ;
Eravci, Selda ;
Baumgartner, Andreas .
PROTEOMICS, 2008, 8 (09) :1780-1784
[17]   Challenges related to analysis of protein spot volumes from two-dimensional gel electrophoresis as revealed by replicate gels [J].
Grove, Harald ;
Hollung, Kristin ;
Uhlen, Anne Kjersti ;
Martens, Harald ;
Faergestad, Ellen Mosleth .
JOURNAL OF PROTEOME RESEARCH, 2006, 5 (12) :3399-3410
[18]  
Jessen F, 2002, PROTEOMICS, V2, P32, DOI 10.1002/1615-9861(200201)2:1<32::AID-PROT32>3.0.CO
[19]  
2-J
[20]   2-DIMENSIONAL ELECTROPHORESIS OF PROTEINS - AN UPDATED PROTOCOL AND IMPLICATIONS FOR A FUNCTIONAL-ANALYSIS OF THE GENOME [J].
KLOSE, J ;
KOBALZ, U .
ELECTROPHORESIS, 1995, 16 (06) :1034-1059