The use of chemometrics to analyse protein patterns from gel electrophoresis

Abstract

Chemometrics involves strategies to analyse multivariate data using interdisciplinary approaches aiming to extract relevant information from complex data. Chemometric strategies comprise both the pre-processing of the data, where the choice of methodology is domain-specific, and analysis of the resulting data after preprocessing using multivariate methodology. Although use of multivariate data analysis for gel electrophoresis images has increased substantially in the last decade, its use is still much less frequent than use of univariate approaches. Considering the complexity of the electrophoresis gel images and the multivariate nature of the proteome, applying multivariate data analysis for gel electrophoresis images gives information which is otherwise lost. This paper is written as a review and guideline of chemometric strategies used for analysis of gel electrophoresis images. The multivariate data analyses described are, however, also relevant for other proteome data, for example mass spectrometry, and for functional genomics in general.

Gel2DE - A software tool for correlation analysis of 2D gel electrophoresis data

“…This figure also shows the characteristic streaking or laddering that probably occurs as a result of different degrees of ubiquitination in the multiple p53 molecules analysed. This is also a feature that may be removed as noise by some types of commercial software [6]. It should be noted that the “long tail” activation of full length p53 shown in Figure 2B is well developed already at two hours and remains high for the remainder of the time points (not shown).…”

“…In this report we have focused on analysis of the p53 protein, a tumour suppressor protein with numerous protein modifications and where analysis by spot detection has not been feasible [5,6]. Activation of p53 using ionizing radiation is a standard way of studying p53 stabilization and subsequent activation of p53-induced genes [12,13].…”

“…Some existing commercial software has been shown to introduce variance during image analysis [6,16]. The Gel2DE software does not use warping or harsh normalization methods.…”

“…We have previously demonstrated that use of an improved alignment standard increases the sensitivity of feature detection, allowing the discovery of potentially novel splice variants of p53 in peripheral blood mononuclear cells in a population of more than 500 healthy volunteers [7]. Pixel-by-pixel analysis is also well suited for increased automatization of the various steps in image pre-processing as the method is further developed [6]. …”

“…For the separation and detection of these proteins in a single assay two-dimensional gel electrophoresis has so far proven to be the superior technology [4], robust and well suited for parallelism [1]. Most commercial software for image analysis of 2D gels still relies on detection of spots with a regular shape [5,6]. Pixel-by-pixel correlation of stacked and aligned 2D gel images may provide information that is otherwise lost and can therefore be used as an alternative to commercial methods to resolve several types of analytical problems [5].…”