Optimization of 2-dimensional gel electrophoresis for proteomic studies of solid tumor tissue samples
- Authors:
- Xu Liang
- Jing-Rong Wang
- Kam-Wai V. Wong
- Wen Luan Hsiao
- Hua Zhou
- Zhi-Hong Jiang
- Kin Ting R. Kam
- Liang Liu
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Affiliations: State Key Laboratory of Quality Research in Chinese Medicine/Macau Institute for Applied Research in Medicine and Health, Macau University of Science and Technology, Taipa, Macau 999078, Macau SAR, P.R. China, School of Chinese Medicine, Hong Kong Baptist University, Kowloon Tong, Kowloon, Hong Kong 999077, SAR, P.R. China
- Published online on: November 20, 2013 https://doi.org/10.3892/mmr.2013.1815
-
Pages:
626-632
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Abstract
The method of 2‑dimensional gel electrophoresis (2-DE) has been widely used for the proteomic profiling of solid biological samples, however, the analytical conditions have not been optimized. The present study optimized the major conditions of 2‑DE for determining the protein contents of solid tumor tissues, through enhancement of the separation efficiency and resolution. Three major analytical conditions of 2‑DE analysis, namely protein extraction, focusing time for isoelectric focusing (IEF), and pre‑reduction and alkylation prior to IEF, were carefully examined so that the optimal parameters and procedures were achieved. The use of a bead mill for protein extraction resulted in a higher protein yield in a minimal processing time. An optimal focusing time for IEF was established which improved the 2‑DE image quality and reproducibility. Furthermore, reduction and alkylation of the protein sample prior to IEF reduced the horizontal streaking caused by oxidation and improved the resolution at the cathode. The optimized 2‑DE analysis enabled the detection of 20% more protein spots compared with the previous reported conditions, with higher image quality and reproducibility. Accordingly, the optimized conditions may be used in the 2‑DE analysis of tumor tissue samples, by which novel biomarkers of cancerous diseases and molecular targets of drugs are expected to be identified.
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