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Deceptive responsive genes in gel-based proteomics

Paper ID Volume ID Publish Year Pages File Format Full-Text
14925 1362 2016 7 PDF Available
Deceptive responsive genes in gel-based proteomics

•A mathematical formula was constructed in order to estimate the high abundant proteins impact on 2DE-based proteome analysis.•An experimental method was simulated by adding a new protein.•35% of root proteins were absent in the presence of 40 μg new protein.•2-DE without depletion of high-abundant proteins is a deceptive tool for gene expression analysis in some research areas.

The standard method of the global quantitative analysis of gene expression at the protein level combines high-resolution two-dimensional gel electrophoresis (2DE) with mass spectrometric identification of protein spots. One of the major concerns with the application of gel-based proteomics is the need for the analytical and biological accuracy of the datasets. We mathematically and empirically simulated the possibility of the technical regulations of gene expression using 2DE. Our developed equation predicted a detectable alteration in the quantity of protein spots in response to a new protein added in, with various amounts. Testing the predictability of the developed equation, we observed that a new protein could form deceptive expression profiles, classified using prevalent tools for the analysis of 2DE results. In spite of the theoretically predicted overall reduction of proteins that resulted from adding the new protein, the empirical data revealed differential amount of proteins when various quantities of the new protein were added to the protein sample. The present work emphasize that employment of 2DE would not be a reliable approach for biological samples with extensive proteome alterations such as the developmental and differentiation stages of cells without depletion of high abundant proteins.

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Two-dimensional electrophoresis (2DE); Proteomics; Mathematical equation
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Deceptive responsive genes in gel-based proteomics
Database: Elsevier - ScienceDirect
Journal: Computational Biology and Chemistry - Volume 61, April 2016, Pages 1–7
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Physical Sciences and Engineering Chemical Engineering Bioengineering