Geometrical distortions in two-dimensional gels: applicable correction methods.

Two-dimensional electrophoresis (2-DE) provides a rapid means for separating thousands of proteins from cell and tissue samples in one run. Although this powerful research tool has been enthusiastically applied in many fields of biomedical research, accurate analysis and interpretation of the data have provided many challenges. Several analysis steps are needed to convert the large amount of noisy data obtained with 2-DE into reliable and interpretable biological information. The goals of such analysis steps include accurate protein detection and quantification, as well as the identification of differentially expressed proteins between samples run on different gels. To achieve these goals, systematic errors such as geometric distortions between the gels must be corrected by using computer-assisted methods. A wide range of computer software has been developed, but no general consensus exists as standard for 2-DE data analysis protocol. The choice of analysis approach is an important element depending both on the data and on the goals of the experiment. Therefore, basic understanding of the algorithms behind the software is required for optimal results. This review highlights some of the common themes in 2-DE data analysis, including protein spot detection and geometric image warping using both spot- and pixel-based approaches. Several computational strategies are overviewed and their relative merits and potential pitfalls discussed. Finally, we offer our own personal view of future trends and developments in large-scale proteome research.

[1]  A D Olson,et al.  Elsie 4: quantitative computer analysis of sets of two-dimensional gel electrophoretograms. , 1988, Analytical biochemistry.

[2]  T. Rabilloud,et al.  Proteome Research: Two-Dimensional Gel Electrophoresis and Identification Methods , 2000, Principles and Practice.

[3]  Jiří Vohradský,et al.  Adaptive classification of two‐dimensional gel electrophoretic spot patterns by neural networks and cluster analysis , 1997, Electrophoresis.

[4]  M. Quadroni,et al.  Proteomics and automation , 2007, Electrophoresis.

[5]  Lisa M. Brown,et al.  A survey of image registration techniques , 1992, CSUR.

[6]  H Alt,et al.  New algorithmic approaches to protein spot detection and pattern matching in two‐dimensional electrophoresis gel databases , 1999, Electrophoresis.

[7]  R D Appel,et al.  Melanie II – a third‐generation software package for analysis of two‐dimensional electrophoresis images: I. Features and user interface , 1997, Electrophoresis.

[8]  Anders Blomberg,et al.  Warping two‐dimensional electrophoresis gel images to correct for geometric distortions of the spot pattern , 2002, Electrophoresis.

[9]  Carola Wenk,et al.  An Applied Point Pattern Matching Problem: Comparing 2D Patterns of Protein Ppots , 1999, Discret. Appl. Math..

[10]  N. Xuong,et al.  Quantitative analysis of two-dimensional electrophoretograms. , 1979, The Journal of biological chemistry.

[11]  Kelvin H. Lee,et al.  The scaled volume as an image analysis variable for detecting changes in protein expression levels by silver stain , 2001, Electrophoresis.

[12]  R D Appel,et al.  Melanie II – a third‐generation software package for analysis of two‐dimensional electrophoresis images: II. Algorithms , 1997, Electrophoresis.

[13]  P F Lemkin,et al.  GELLAB: a computer system for 2D gel electrophoresis analysis I. Segmentation of spots and system preliminaries.. , 1981, Computers and biomedical research, an international journal.

[14]  T Voss,et al.  Observations on the reproducibility and matching efficiency of two‐dimensional electrophoresis gels: Consequences for comprehensive data analysis , 2000, Electrophoresis.

[15]  Eric Mjolsness,et al.  New Algorithms for 2D and 3D Point Matching: Pose Estimation and Correspondence , 1998, NIPS.

[16]  Studies of quantitative analysis of protein expression in Saccharomyces cerevisiae , 1999, Electrophoresis.

[17]  Z. Smilansky,et al.  Automatic registration for images of two‐dimensional protein gels , 2001, Electrophoresis.

[18]  Susanne Jacobsen,et al.  Explorative data analysis of two‐dimensional electrophoresis gels , 2004, Electrophoresis.

[19]  Babu Raman,et al.  Quantitative comparison and evaluation of two commercially available, two‐dimensional electrophoresis image analysis software packages, Z3 and Melanie , 2002, Electrophoresis.

[20]  S. Gygi,et al.  Quantitative analysis of complex protein mixtures using isotope-coded affinity tags , 1999, Nature Biotechnology.

[21]  Fred L. Bookstein,et al.  Principal Warps: Thin-Plate Splines and the Decomposition of Deformations , 1989, IEEE Trans. Pattern Anal. Mach. Intell..

[22]  N G Anderson,et al.  The TYCHO system for computer analysis of two-dimensional gel electrophoresis patterns. , 1981, Clinical chemistry.

[23]  J. Nishihara,et al.  Quantitative evaluation of proteins in one‐ and two‐dimensional polyacrylamide gels using a fluorescent stain , 2002, Electrophoresis.

[24]  Nicola Marchetti,et al.  Spot overlapping in two‐dimensional polyacrylamide gel electrophoresis separations: A statistical study of complex protein maps , 2002, Electrophoresis.

[25]  Mohammed Bennamoun.  Editorial: Correspondence And Registration Techniques , 2003, Int. J. Pattern Recognit. Artif. Intell..

[26]  Luc Vincent,et al.  Watersheds in Digital Spaces: An Efficient Algorithm Based on Immersion Simulations , 1991, IEEE Trans. Pattern Anal. Mach. Intell..

[27]  Valentina Gianotti,et al.  A new integrated statistical approach to the diagnostic use of two‐dimensional maps , 2003, Electrophoresis.

[28]  Veli Mäkinen,et al.  Parameterized Approximate String Matching and Local-Similarity-Based Point-Pattern Matching , 2003 .

[29]  K Kriegel,et al.  An alternative approach to deal with geometric uncertainties in computer analysis of two‐dimensional electrophoresis gels , 2000, Electrophoresis.

[30]  Brian Fenton,et al.  Superimposing two‐dimensional gels to study genetic variation in malaria parasites , 1992, Electrophoresis.

[31]  P F Lemkin,et al.  GELLAB: A computer system for 2D gel electrophoresis analysis. II. Pairing spots. , 1981, Computers and biomedical research, an international journal.

[32]  P. O’Farrell.  High resolution two-dimensional electrophoresis of proteins. , 1975, The Journal of biological chemistry.

[33]  P Dupree,et al.  Quantitative and reproducible two‐dimensional gel analysis using Phoretix 2D Full , 2001, Electrophoresis.

[34]  M M Skolnick,et al.  Computer programs for adapting two-dimensional gels to the study of mutation. , 1982, Clinical chemistry.

[35]  J. Garrels.  The QUEST system for quantitative analysis of two-dimensional gels. , 1989, The Journal of biological chemistry.

[36]  R. Aebersold,et al.  Quantitative profiling of differentiation-induced microsomal proteins using isotope-coded affinity tags and mass spectrometry , 2001, Nature Biotechnology.

[37]  N. Xuong,et al.  Computer analysis of two-dimensional gels. , 1981, Analytical biochemistry.

[38]  J. Vohradský,et al.  Point pattern matching in the analysis of two‐dimensional gel electropherograms , 1999, Electrophoresis.

[39]  M M Skolnick,et al.  An approach to completely automatic comparison of two-dimensional electrophoresis gels. , 1982, Clinical chemistry.

[40]  J R Scherrer,et al.  The MELANIE project: From a biopsy to automatic protein map interpretation by computer , 1991, Electrophoresis.