alexa Comparison of different depletion strategies for improved resolution in proteomic analysis of human serum samples.
Bioinformatics & Systems Biology

Bioinformatics & Systems Biology

Journal of Proteomics & Bioinformatics

Author(s): Bjrhall K, Miliotis T, Davidsson P

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Abstract Serum proteins may often serve as indicators of disease and is a rich source for biomarker discovery. However, the large dynamic range of proteins in serum makes the analysis very challenging because high-abundant proteins tend to mask those of lower abundance. A prefractionation step, such as depletion of a few high-abundant proteins before protein profiling, can assist in the discovery and detection of less abundant proteins that may prove to be informative biomarkers. In the present study, five different depletion columns were investigated considering efficiency, specificity, and reproducibility. Our research included quantitative determination of total protein, albumin, and immunoglobulin G (IgG) concentrations, one- and two-dimensional gels and mass spectrometric analysis of the serum samples before and after the depletion step. Our results showed that all five depletion columns tested removed albumin and IgG with high efficiency. We found that based on reproducibility and binding specificity, the Multiple Affinity Removal Column that removed a total of six high-abundant proteins (albumin, IgG, antitrypsin, IgA, transferring, and haptoglobin) offered the most promising depletion approach. Among the disposable (single-use) products, the ProteoExtract Albumin/IgG Removal kit displayed the best results. Depleted serum from the Multiple Affinity Removal column was further evaluated by 2-D gel electrophoresis (2-DE) analysis, and the results indicated increased resolution and improved intensity of low-abundant proteins in a reproducible fashion. Our study provides a comprehensive investigation of commercially available depletion columns and will be of high importance for future proteomic studies on serum samples. This article was published in Proteomics and referenced in Journal of Proteomics & Bioinformatics

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