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Comparison of SDS gel capillary electrophoresis with microfluidic lab‐on‐a‐chip technology to quantify relative amounts of 7S and 11S proteins from 20 soybean cultivars
Author(s) -
Blazek Vladimir,
Caldwell Robert A.
Publication year - 2009
Publication title -
international journal of food science and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.831
H-Index - 96
eISSN - 1365-2621
pISSN - 0950-5423
DOI - 10.1111/j.1365-2621.2009.02049.x
Subject(s) - repeatability , capillary electrophoresis , chromatography , electrophoresis , lab on a chip , microfluidic chip , chemistry , gel electrophoresis , capillary action , microfluidics , analytical chemistry (journal) , materials science , biochemistry , nanotechnology , composite material
Summary SDS gel capillary electrophoresis (Beckman–Coulter ProteomeLab) and the lab‐on‐a‐chip technology (Agilent 2100 Bioanalyzer) were used to quantify the relative amount of 7S and 11S fractions in twenty different soybean cultivars. The better repeatability of the migration times and peak areas was achieved for the Bioanalyzer. Both lab‐on‐a‐chip instrument and a traditional capillary gel electrophoresis were shown to be adequate for analysis of soy‐based products. Integrating the area of peaks within a certain range of molecular weights was used to calculate the relative content of each protein subunit. Poor agreement in the classification in the protein subunit groups between the two instruments was observed. Therefore, the approach of visual identification taking into account both the variability in the position of the peaks and the detection of different number of peaks between the profiles was applied. This resulted in statistically significant correlation being observed between 11S/7S ratios determined by Bioanalyzer and ProteomeLab ( R = 0.82). The reported differences in 11S and 7S content between the studies are likely to be affected by the differences in the techniques used to analyse soy protein subunits. A brief presentation of the chemometric analysis of electrophoretic profiles as a common method for transforming electrophoretograms to multivariate data sets is shown.