4.7 Article

Optimizing the extraction of anti-tumor alkaloids from the stem of Berberis amurensis by response surface methodology

Journal

INDUSTRIAL CROPS AND PRODUCTS
Volume 69, Issue -, Pages 68-75

Publisher

ELSEVIER SCIENCE BV
DOI: 10.1016/j.indcrop.2015.01.053

Keywords

Alkaloids of Berberis amurensis Rupr. (BAAs); Response surface methodology; Extraction optimization; Anti-tumor activity

Funding

  1. Key laboratory of Chinese Materia Medica of Heilongjiang University of Chinese Medicine [20110101]
  2. Outstanding young teacher support plan of Heilongjiang University of Chinese Medicine

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Response surface methodology (RSM) using a Box-Behnken design (BBD) was employed to optimize the conditions for extraction of anti-tumor alkaloids from the stem of Berberis amurensis Rupr. (BAAs). Four independent variables (ethanol concentration, pH value, ratio of liquid to material and extraction time) were investigated and the optimal conditions for BAAs were evaluated by means of response surface methodology (RSM). Moreover, the in vitro anti-tumor activity of BAAs was investigated. The results showed that the experimental data could be fitted to a quadratic polynomial model using correlation analysis of the mathematical regression model. Response surface plots showed that all independent variables significantly influenced the extraction yield of BAAs. The optimum extraction conditions were as follows: ethanol concentration of 67.28%, pH value of 1.81, the ratio of liquid to material of 11.24:1 (mL/g), and extraction time of 1.58 h. The average experimental BAAs yield under the optimum conditions was found to be 24.63 +/- 0.28 mg/g, which agreed with the predicted value of 24.33 mg/g. UPLC-PDA analysis showed that berberine was the principal alkaloid compound in B. amurensis Rupr stem. Additionally, BAAs could inhibit MCF-7 and HEPG2 cell proliferation in vitro, and the 50% inhibitory concentration (1050) at 48 h was around 402.25 and 477.17 mu g/mL, respectively. The anti-tumor activity of BAAs were dose-dependent. (C) 2015 Elsevier B.V. All rights reserved.

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