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
[1]   On the statistical analysis of the GS-NS0 cell proteome: Imputation, clustering and variability testing [J].
Ahmad, Norhaiza ;
Zhang, Jian ;
Brown, Phillip J. ;
James, David C. ;
Birch, John R. ;
Racher, Andrew J. ;
Smales, C. Mark .
BIOCHIMICA ET BIOPHYSICA ACTA-PROTEINS AND PROTEOMICS, 2006, 1764 (07) :1179-1187
[2]   Missing values in gel-based proteomics [J].
Albrecht, Daniela ;
Kniemeyer, Olaf ;
Brakhage, Axel A. ;
Guthke, Reinhard .
PROTEOMICS, 2010, 10 (06) :1202-1211
[3]   Melanie II - a third-generation software package for analysis of two-dimensional electrophoresis images: II. Algorithms [J].
Appel, RD ;
Vargas, JR ;
Palagi, PM ;
Walther, D ;
Hochstrasser, DF .
ELECTROPHORESIS, 1997, 18 (15) :2735-2748
[4]   The state of the art in the analysis of two-dimensional gel electrophoresis images [J].
Berth, Matthias ;
Moser, Frank Michael ;
Kolbe, Markus ;
Bernhardt, Joerg .
APPLIED MICROBIOLOGY AND BIOTECHNOLOGY, 2007, 76 (06) :1223-1243
[5]  
Bettens E, 1999, THESIS U ANTWERP
[6]   The pitfalls of proteomics experiments without the correct use of bioinformatics tools [J].
Biron, David G. ;
Brun, Christine ;
Lefevre, Thierry ;
Lebarbenchon, Camille ;
Loxdale, Hugh D. ;
Chevenet, Francois ;
Brizard, Jean-Paul ;
Thomas, Frederic .
PROTEOMICS, 2006, 6 (20) :5577-5596
[7]   Trends in sample preparation for classical and second generation proteomics [J].
Canas, Benito ;
Pineiro, Carmen ;
Calvo, Enrique ;
Lopez-Ferrer, Daniel ;
Manuel Gallardo, Jose .
JOURNAL OF CHROMATOGRAPHY A, 2007, 1153 (1-2) :235-258
[8]   Median-modified Wiener filter provides efficient denoising, preserving spot edge and morphology in 2-DE image processing [J].
Cannistraci, Carlo V. ;
Montevecchi, Franco M. ;
Alessio, Massimo .
PROTEOMICS, 2009, 9 (21) :4908-4919
[9]  
Choe LH, 2000, ELECTROPHORESIS, V21, P993, DOI 10.1002/(SICI)1522-2683(20000301)21:5<993::AID-ELPS993>3.0.CO
[10]  
2-9