Development of a sensitive biosensor method for the detection of food contaminants

Abstract

The use of food contaminants in food production is a major concern due to their negative effects on public health, animal welfare and the environment. In particular, chemical contamination from illegal or banned food additives, and trace levels entering the food chain have been of great concern over the last few decades. Recently a number of analytical methods have been used to detect food contaminants such as liquid chromatography mass spectrometry (LC-MS), high performance liquid chromatography (HPLC), and capillary electrophoresis (CE), however these methods are time consuming, tedious, and require a lot of sample preparation. Therefore it is necessary to develop a low cost, sensitive, reproducible detection method that can be completed with little sample waste. Although well established methods exist, such as Enzyme Linked Immunosorbant Assay (ELISA), biosensors can provide label-free, real time detection of the binding events between molecules, whilst enhancing sensitivity limits over conventional methods. Biosensors are capable of single molecule detection, allowing behavioural characteristics and interactions between single molecules and particles to be observed. In comparison, an ELISA is based on the antigen-antibody interaction, and requires the use of an enzyme to generate signal for readout, therefore allowing the presence or quantity of an analyte in a sample to be identified. However, ELISA's cannot provide any information about the biological activity of a sample, and cannot distinguish between active and non-active protein. Therefore, lower concentrations of analyte can be detected using biosensor methods. Localised Surface Plasmon Resonance (LSPR) spectroscopy and Surface Enhanced Raman Spectroscopy (SERS), have been applied to develop sensitive biosensor methods for the analysis of potential food contaminants, alongside electron microscopy for characterisation. The method attempts to covalently bind molecules to the surface of gold nanoparticles (AuNps), using thiol-gold surface chemistry. The proposed LSPR method takes advantage of the surface plasmon resonance (SPR) technique, and detects changes in refractive index at the surface of AuNps, with an average size of 80nm. Bovine Serum Albumin (BSA) is a serum albumin protein derived from bovine with a molecular weight of67kDa. BSA is a readily available laboratory protein standard, and is used as a large food contaminant model to demonstrate the sensitivity of the LSPR technology. The proposed SERS method takes advantage of the scattering effect light has on matter, and enhances the electromagnetic field by absorbing molecules onto roughened surfaces, i.e. gold (Au) film substrates coupled with 80nm AuNps. Pazufloxacin is a relatively new fluoroquinolone antibiotic with a molecular weight of 318.29Da and is used as a small food contaminant model to demonstrate the sensitivity of the SERS technology. The aim of the study was to compare the sensitivity and detection limits of the biosensor methods, with the conventional ELISA. The results from this project confirm the sensitivity of the indirect ELISA with a detection limit of 1ng/ml, and also the reliability and reproducibility of the method was confirmed by performing spiked sample assays, and by calculating the coefficient of variation (CV%). However, as mentioned previously biosensor methods detect single molecules, therefore should have improved sensitivity and detection limits over the conventional method. However, in this study detection limits for LSPR, SERS and ELISA were 100ng/ml, 50ng/ml and 1ng/ml, respectively, so the assumption made on biosensor sensitivity could not be confirmed in this study. Overall, based on the theoretical assumption of chemical bonding, the developed biosensor method could form the basis of a sensitive platform to detect food contaminants. In the future the method could also be incorporated with portable technology to improve the point-of-care detection of food contaminants. However, more developments to the method are required if this method is to be used to detect trace levels of harmful food contaminants, and confirming sensitivity levels should be priority. As the project was a preliminary study with limited timeframe, several recommendations have been made and these should be considered for future research projects in this area.

Date of Award	Jul 2016
Original language	English
Awarding Institution	Queen's University Belfast
Supervisor	Chen Situ (Supervisor) & Fumin Huang (Supervisor)