Title Towards electrochemical sensor based on molecularly imprinted polypyrrole for the detection of bacteria-Listeria monocytogenes /
Authors Liustrovaitė, Viktorija ; Pogorielov, Maksym ; Bogužaitė, Raimonda ; Ratautaitė, Vilma ; Ramanavičienė, Almira ; Pilvenytė, Greta ; Holubnycha, Viktoriia ; Korniienko, Viktoriia ; Diedkova, Kateryna ; Viter, Roman ; Ramanavičius, Arūnas
DOI 10.3390/polym15071597
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Is Part of Polymers.. Basel : MDPI AG. 2023, vol. 15, iss. 7, art. no. 1597, p. 1-16.. eISSN 2073-4360
Keywords [eng] molecularly imprinted polymer ; molecularly imprinted polypyrrole ; Listeria monocytogenes ; whole-cell imprinting ; pulsed amperometric detection ; template extraction method ; trypsin ; L-lysine ; acetic acid ; sulphuric acid
Abstract [eng] Detecting bacteria—Listeria monocytogenes—is an essential healthcare and food industry issue. The objective of the current study was to apply platinum (Pt) and screen-printed carbon (SPCE) electrodes modified by molecularly imprinted polymer (MIP) in the design of an electrochemical sensor for the detection of Listeria monocytogenes. A sequence of potential pulses was used to perform the electrochemical deposition of the non-imprinted polypyrrole (NIP-Ppy) layer and Listeria monocytogenes-imprinted polypyrrole (MIP-Ppy) layer over SPCE and Pt electrodes. The bacteria were removed by incubating Ppy-modified electrodes in different extraction solutions (sulphuric acid, acetic acid, L-lysine, and trypsin) to determine the most efficient solution for extraction and to obtain a more sensitive and repeatable design of the sensor. The performance of MIP-Ppy- and NIP-Ppy-modified electrodes was evaluated by pulsed amperometric detection (PAD). According to the results of this research, it can be assumed that the most effective MIP-Ppy/SPCE sensor can be designed by removing bacteria with the proteolytic enzyme trypsin. The LOD and LOQ of the MIP-Ppy/SPCE were 70 CFU/mL and 210 CFU/mL, respectively, with a linear range from 300 to 6700 CFU/mL.
Published Basel : MDPI AG
Type Journal article
Language English
Publication date 2023
CC license CC license description