Open access publications in the SLU publication database

Abstract

The use of drugs to improve animal growth is banned in the European Union. Nevertheless, illegal use has been demonstrated in several countries and Member States have to run extensive control programs to ensure that the ban is respected. The aim of this work was to explore the possibility of using surface plasmon resonance (SPR) biosensors to develop fast and robust screening assays for hormones and ß-agonists. Modified standard procedures for hapten synthesis were employed to immobilise stable analyte specific sensor chip surfaces used for analysis. Sensor chips for clenbuterol, ethinylestradiol and trenbolone gave assays with IC50 values in the region of 0.5 ng/ml. Sample matrix interference from urine and serum with the antibody-antigen interaction and non-specific binding from samples to the sensor surface was systematically studied. Strategies to minimise these effects were investigated and described. Biosensor assays for clenbuterol in bovine hair and urine, suitable for routine use, were developed and validated. For hair, a sandwich assay format was used. A rapid and simple extraction using 100 mM NaOH was developed, and the assay was validated by analysis of hair samples from animals treated with clenbuterol. The critical factor for assay sensitivity was non-specific binding to the sensor chip surface from hair extracts, which was controlled by ultrafiltration of samples and by the use of a secondary antibody. The limit of detection (LOD) of the hair assay was 10 ng/ml. In the urine assay, the cross-reaction for several ß-agonists, including salbutamol, mabuterol and brombuterol was high, enabling detection of concentrations below 1 ng/ml. Analysis of these low analyte concentrations in urine without sample pre-treatment was limited by high sample-to-sample variation, inhibition of antibody binding to the surface and occasional non-specific binding. A rapid and simple sample clean-up using integrated immunofiltration was developed to minimise these sample matrix effects. With this method, at least 48 samples could be processed and analysed by one person in one working day.