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The state of the art in the analysis of two-dimensional gel electrophoresis images.

Berth M, Moser FM, Kolbe M, Bernhardt J - Appl. Microbiol. Biotechnol. (2007)

Bottom Line: Recent significant advances in image processing methods combined with powerful computing hardware have enabled the routine analysis of large experiments.Challenges for analysis software as well as good practices are highlighted.We close with an overview of visualization and presentation methods (proteome maps) and current challenges in the field.

View Article: PubMed Central - PubMed

Affiliation: DECODON GmbH, Rathenau-Strasse 49a, 17489 Greifswald, Germany.

ABSTRACT
Software-based image analysis is a crucial step in the biological interpretation of two-dimensional gel electrophoresis experiments. Recent significant advances in image processing methods combined with powerful computing hardware have enabled the routine analysis of large experiments. We cover the process starting with the imaging of 2-D gels, quantitation of spots, creation of expression profiles to statistical expression analysis followed by the presentation of results. Challenges for analysis software as well as good practices are highlighted. We emphasize image warping and related methods that are able to overcome the difficulties that are due to varying migration positions of spots between gels. Spot detection, quantitation, normalization, and the creation of expression profiles are described in detail. The recent development of consensus spot patterns and complete expression profiles enables one to take full advantage of statistical methods for expression analysis that are well established for the analysis of DNA microarray experiments. We close with an overview of visualization and presentation methods (proteome maps) and current challenges in the field.

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Related in: MedlinePlus

2-D gel image registration by warping. Two images are combined pixel by pixel using a false color display (a). Vectors connecting corresponding points (spots) on both images are determined automatically (b). Transforming the image geometry (warping) according to the vectors produces an exact overlay (c). Corresponding spots (black color) as well as differences in spot patterns can be easily identified. Data about differences in spot position are used in later image analysis steps (image fusion, transfer of consensus spot pattern)
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Fig7: 2-D gel image registration by warping. Two images are combined pixel by pixel using a false color display (a). Vectors connecting corresponding points (spots) on both images are determined automatically (b). Transforming the image geometry (warping) according to the vectors produces an exact overlay (c). Corresponding spots (black color) as well as differences in spot patterns can be easily identified. Data about differences in spot position are used in later image analysis steps (image fusion, transfer of consensus spot pattern)

Mentions: Unfortunately, the position of a protein on a 2-D gel fluctuates from separation to separation. Even a very experienced experimenter will not be able to produce “perfect” gels whose spot patterns show exact congruency (Fig. 7a). Reasons for changing spot positions may be variations in the pH value of the running buffer, problems of incomplete polymerization of the gel matrix, current leakage (Gustafsson et al. 2002), air bubbles in the gel, or highly abundant proteins that may influence the pH gradient in the IPG gel by their own locally concentrated buffer capacity. Some of these problems can be mitigated by using the DIGE setup or similar techniques (see below) that let multiple samples comigrate on the same gel. However, differing spot positions will still occur in any nontrivial experiment that includes more than one gel. Differences in spot positions are a major challenge in image processing because they impede accurate spot matching and thus the construction of expression profiles.Fig. 7


The state of the art in the analysis of two-dimensional gel electrophoresis images.

Berth M, Moser FM, Kolbe M, Bernhardt J - Appl. Microbiol. Biotechnol. (2007)

2-D gel image registration by warping. Two images are combined pixel by pixel using a false color display (a). Vectors connecting corresponding points (spots) on both images are determined automatically (b). Transforming the image geometry (warping) according to the vectors produces an exact overlay (c). Corresponding spots (black color) as well as differences in spot patterns can be easily identified. Data about differences in spot position are used in later image analysis steps (image fusion, transfer of consensus spot pattern)
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2279157&req=5

Fig7: 2-D gel image registration by warping. Two images are combined pixel by pixel using a false color display (a). Vectors connecting corresponding points (spots) on both images are determined automatically (b). Transforming the image geometry (warping) according to the vectors produces an exact overlay (c). Corresponding spots (black color) as well as differences in spot patterns can be easily identified. Data about differences in spot position are used in later image analysis steps (image fusion, transfer of consensus spot pattern)
Mentions: Unfortunately, the position of a protein on a 2-D gel fluctuates from separation to separation. Even a very experienced experimenter will not be able to produce “perfect” gels whose spot patterns show exact congruency (Fig. 7a). Reasons for changing spot positions may be variations in the pH value of the running buffer, problems of incomplete polymerization of the gel matrix, current leakage (Gustafsson et al. 2002), air bubbles in the gel, or highly abundant proteins that may influence the pH gradient in the IPG gel by their own locally concentrated buffer capacity. Some of these problems can be mitigated by using the DIGE setup or similar techniques (see below) that let multiple samples comigrate on the same gel. However, differing spot positions will still occur in any nontrivial experiment that includes more than one gel. Differences in spot positions are a major challenge in image processing because they impede accurate spot matching and thus the construction of expression profiles.Fig. 7

Bottom Line: Recent significant advances in image processing methods combined with powerful computing hardware have enabled the routine analysis of large experiments.Challenges for analysis software as well as good practices are highlighted.We close with an overview of visualization and presentation methods (proteome maps) and current challenges in the field.

View Article: PubMed Central - PubMed

Affiliation: DECODON GmbH, Rathenau-Strasse 49a, 17489 Greifswald, Germany.

ABSTRACT
Software-based image analysis is a crucial step in the biological interpretation of two-dimensional gel electrophoresis experiments. Recent significant advances in image processing methods combined with powerful computing hardware have enabled the routine analysis of large experiments. We cover the process starting with the imaging of 2-D gels, quantitation of spots, creation of expression profiles to statistical expression analysis followed by the presentation of results. Challenges for analysis software as well as good practices are highlighted. We emphasize image warping and related methods that are able to overcome the difficulties that are due to varying migration positions of spots between gels. Spot detection, quantitation, normalization, and the creation of expression profiles are described in detail. The recent development of consensus spot patterns and complete expression profiles enables one to take full advantage of statistical methods for expression analysis that are well established for the analysis of DNA microarray experiments. We close with an overview of visualization and presentation methods (proteome maps) and current challenges in the field.

Show MeSH
Related in: MedlinePlus