Monitoring of pesticide amount in fruit and vegetables by a fluorescence-based sensor

Faster, sensitive and real-time methods for detecting organophosphate (OP) pesticides are urged for in situ monitoring of these widely spread contaminants. For this reason, several efforts have been addressed for the development of performant biosensors. The thermostable enzyme esterase-2 from Alicyclobacillus acidocaldarius (EST2), with a lipase-like Ser-His-Asp catalytic triad with a high affinity to OPs, is a promising candidate as a bioreceptor for biosensor development. Within this EU-FORA fellowship project, two different components of the biosensor were evaluated: (i) the use of the enzymatic bioreceptor in solution or immobilised in a solid membrane; (ii) the measurement of fluorescence quenching by direct measurement of the fluorescence probe intensity signal or by fluorescence resonance energy transfer (FRET) from the tryptophans located in the catalytic site of the enzyme to a binded fluorescence probe. Fluorescence spectroscopy is among the most used techniques in analytical chemistry laboratories, mainly due to its high sensitivity and simplicity. To this aim, the developed IAEDANS-labelled EST2-S35C mutant has been used. Fluorometric measurements with both methods showed linearity with increased EST2-S35C concentrations. No significant interference on FRET measurements was observed due to changes in medium pH or due to the addition of other organic components (glucose, ascorbic acid, yeast extract). Both methods presented similar sensitivity towards detecting OPs, with fluorescence quenching due to the presence of paraoxon at environmentally relevant concentrations from 0.09 µM. The obtained results are of high relevance to further development of biosensors for the pesticide monitoring that: (i) decrease the expenses of the analysis; (ii) simplify the procedures for pesticide detection; (iii) reduce the time of response. Furthermore, the use of biosensors for pesticides real-time and in situ detection of pesticides promises to increase the number of samples analysed, providing a larger amount of data for food safety risk assessment.