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Matic Krivec

Matic Krivec

Carinthian Tech Research, Austria

Title: Biosensor based on CYP2D6-functionalised carbon nanotube transducer for continuous detection of xenobiotics

Biography

Biography: Matic Krivec

Abstract

The rising demand of personalised therapeutic products has led to an increasing interest in the investigation of sensing approaches for the detection of drugs, food compounds, and natural substances including potential mutual interferences. Although enzyme-based electro-chemical bio-sensors show significant potential towards the construction of a sensitive and selective sensor, a direct quantitative detection of the enzyme’s catalytic activity still remains challenging. Distinct properties of the enzyme are required as well as an electrode in order to enhance the direct electron transfer (DET) between the enzyme’s catalytic active site and the electrode. Cytochrome P450 enzymes (CYPs) comprise for about 80% of the Phase-I drug-metabolizing enzymes in the human liver, whereas they functionalize chemicals that are foreign to the human body (xenobiotics) and endogenous substrates in order to increase their excretion. In our study, a screen printed working electrode with an additional carbon nanotube layer was functionalised with microsomes prepared from insect cells infected with recombinant baculovirus containing human isoenzyme cytochrome P450 2D6 (CYP2D6) and cytochrome P450 reductase, using a drop-casting technique and the immobilisation was additionally stabilised using two different cross-linkers, i.e. glutaraldehyde and poly(ethyleneglycol) diglycidyl ether, and an additional stabilising agent Nafion. The characterisation of the biosensor was conducted in a micro-cell, the activity of the immobilised CYP2D6 enzyme was measured by conversion of two model substrates, i.e. Luciferin-ME EGE and dextromethorphan, where the concentration of the products, i.e. Luciferin EGE and dextrorphan, were determined using high-performance liquid chromatography. The stability, selectivity and sensitivity of the biosensor were evaluated using a cyclic-voltametrical and chronoamperometrical processing of the induced signal.