Issue 17, 2016

Sensitive and specific detection of a new β-agonist brombuterol in tissue and feed samples by a competitive polyclonal antibody based ELISA

Abstract

Brombuterol, a new β-adrenergic agonist which can enhance the lean meat-to-fat ratio, is forbidden as an additive in animal feeds for livestock production due to its adverse effects on consumers. In this study, a highly sensitive and specific competitive enzyme-linked immunosorbent assay (ELISA) for the detection of brombuterol in tissue and feed samples was developed. The immunogen and coating antigen were prepared by directly linking brombuterol to carrier proteins using the diazobenzidine method. The antisera against brombuterol were obtained from immunized rabbits. The IC50 and limit of detection (LOD) values of the superior ELISA were 0.165 ng mL−1 and 0.007 ng mL−1, respectively. The cross-reactivity (CR) values of ELISA with clenbuterol, terbutaline and cimbuterol were less than 6.2%; there was no CR of ELISA with nine other compounds. To investigate the accuracy and precision of the assay, liver, meat and feed samples were spiked with brombuterol at different concentrations and analyzed by ELISA. Acceptable recovery rates of 91.9–115.4% and intra-assay coefficients of variation of 1.5–9.5% (n = 3) were achieved. The ELISA was also validated by HPLC. As revealed, both methods were highly correlated (R2 = 0.9927–0.9994, n = 6). The proposed ELISA was proven to be a feasible method for quantitative analysis of brombuterol in tissue and feed samples.

Graphical abstract: Sensitive and specific detection of a new β-agonist brombuterol in tissue and feed samples by a competitive polyclonal antibody based ELISA

Supplementary files

Article information

Article type
Paper
Submitted
09 Jan 2016
Accepted
20 Mar 2016
First published
29 Mar 2016

Anal. Methods, 2016,8, 3578-3586

Sensitive and specific detection of a new β-agonist brombuterol in tissue and feed samples by a competitive polyclonal antibody based ELISA

H. Du, Y. Chu, H. Yang, K. Zhao, J. Li, P. She, X. Zhang and A. Deng, Anal. Methods, 2016, 8, 3578 DOI: 10.1039/C6AY00079G

To request permission to reproduce material from this article, please go to the Copyright Clearance Center request page.

If you are an author contributing to an RSC publication, you do not need to request permission provided correct acknowledgement is given.

If you are the author of this article, you do not need to request permission to reproduce figures and diagrams provided correct acknowledgement is given. If you want to reproduce the whole article in a third-party publication (excluding your thesis/dissertation for which permission is not required) please go to the Copyright Clearance Center request page.

Read more about how to correctly acknowledge RSC content.

Social activity

Spotlight

Advertisements