Sequential depletion of human serum for the search of osteoarthritis biomarkers

• Main Authors: Fernández-Costa Carolina, Calamia Valentina, Fernández-Puente Patricia, Capelo-Martínez José-Luis, Ruiz-Romero Cristina, Blanco Francisco J
• Format: Article
• Language: English
• Published: BMC 2012-09-01
• Series: Proteome Science
• Online Access: http://www.proteomesci.com/content/10/1/55

<p>Abstract</p> <p>Background</p> <p>The field of biomarker discovery, development and application has been the subject of intense interest and activity, especially with the recent emergence of new technologies, such as proteomics-based approaches. In proteomics, search for biomarkers in biological fluids such as human serum is a challenging issue, mainly due to the high dynamic range of proteins present in these types of samples. Methods for reducing the content of most highly abundant proteins have been developed, including immunodepletion or protein equalization. In this work, we report for the first time the combination of a chemical sequential depletion method based in two protein precipitations with acetonitrile and DTT, with a subsequent two-dimensional difference in-gel electrophoresis (2D-DIGE) analysis for the search of osteoarthritis (OA) biomarkers in human serum. The depletion method proposed is non-expensive, of easy implementation and allows fast sample throughput.</p> <p>Results</p> <p>Following this workflow, we have compared sample pools of human serum obtained from 20 OA patients and 20 healthy controls. The DIGE study led to the identification of 16 protein forms (corresponding to 14 different proteins) that were significantly (p < 0.05) altered in OA when compared to controls (8 increased and 7 decreased). Immunoblot analyses confirmed for the first time the increase of an isoform of Haptoglobin beta chain (HPT) in sera from OA patients.</p> <p>Conclusions</p> <p>Altogether, these data demonstrate the utility of the proposed chemical sequential depletion for the analysis of sera in protein biomarker discovery approaches, exhibit the usefulness of quantitative 2D gel-based strategies for the characterization of disease-specific patterns of protein modifications, and also provide a list of OA biomarker candidates for validation.</p>