Spot overlapping in two-dimensional polyacrylamide gel electrophoresis separations: A statistical study of complex protein maps

Abstract

A statistical approach able to extract the information contained in a two-dimenisional polyacrylamide gel electrophoresis (2-D PAGE) separation is here reported. The method is based on the quantitative theory of peak overlapping, a procedure previously developed by the authors and here extended to 2-D separations. The whole map is divided into many strips in order to obtain 1-D separations on which the statistic procedure is applied: the developed algorithms, on the basis of spot experimental data (intensity and spatial coordinates) permit to estimate the intrinsic number of components and to single out the specific order present in spot positions. The procedure was validated on computer-simulated maps. Its applicability to real samples was tested on maps obtained from literature sources. The following important information on protein mixtures can be extracted: (i) the number of proteins can be accurately estimated, on the basis of the spatial coordinates and intensities of spots detected in the 2-D PAGE map; (ii) the model describing distribution of interdistance between adjacent spots can be identified in both the separation dimensions; (iii) the presence of repeated interdistances in spot positions in the maps can be easily singled out: these regularities suggest specific protein modifications.

Spot overlapping in two‐dimensional polyacrylamide gel electrophoresis maps: Relevance to proteomics

“…The situation is a consequence of the mixture complexity itself and results in a drop in the quality of analytical information contained in the map; this loss is proportional to the degree of randomness of the map itself [18][19][20]. As a consequence of spot overlapping [18][19][20][21][22][23][24][25][26][27][28][29][30] (i) the number of spots, p, detectable in the map is always lower than the number m of components present in the mixture. The number of spots, p, does not represent the real complexity of the mixture: the loss of analytical information is represented by the separation degree g = p/m and is proportional to the degree of overlapping present in the mixture [18][19] Therefore, the total number of detectable spots, p, is given by:…”

“…A statistical model of peak overlap allows a quantitative description of spot overlapping [18,19,[28][29][30][31][32][33]: it regards the separation as an ensemble whose average properties can be estimated using mathematical statistics. The fundamental basis is the separation model, i.e., the mathematical function describing the way by which the SCs arrange themselves over the available separation space.…”

“…Many statistic theories have been developed to describe spot overlapping in 2-D separations [19][20][21][22][23][24][25][26][27][28][29][30][31][32][33]: they all have been tested extensively by computer-simulated data [19][20][21][22][23][24]26] as well as by experimental data [25,30]. In the simplest and more general model, spots formed by only 1 SC are randomly distributed on all the separation space [19,20].…”

“…A previous paper [28] demonstrated that the Quantitative Theory of Peak Overlapping, a procedure previously developed by the authors for 1-D chromatograms, can be successfully extended to 2-D separations. The whole map is divided into many strips in order to obtain 1-D separations on which the statistic procedure is applied (see Fig.…”

Intelligent Spot Detection for 2-DE Gel Image

“…In fact, spots may be distorted [1,5], overlapping [6] and suffered with noise. These factors make spot detection more difficult and un-reliable.…”