Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.14279/23095
Title: | Newly Developed System for the Robust Detection of Listeria monocytogenes Based on a Bioelectric Cell Biosensor | Authors: | Hadjilouka, Agni Loizou, Konstantinos Apostolou, Theofylaktos Dougiakis, Lazaros Inglezakis, Antonios Tsaltas, Dimitrios |
Major Field of Science: | Natural Sciences | Field Category: | Biological Sciences | Keywords: | Listeria monocytogenes;Bioelectric recognition assay;Cell-based biosensor;Membrane-engineering | Issue Date: | Nov-2020 | Source: | Biosensors, 2020, vol. 10, no. 11, articl. no. 178 | Volume: | 10 | Issue: | 11 | Journal: | Biosensors | Abstract: | Human food-borne diseases caused by pathogenic bacteria have been significantly increased in the last few decades causing numerous deaths worldwide. The standard analyses used for their detection have significant limitations regarding cost, special facilities and equipment, highly trained staff, and a long procedural time that can be crucial for foodborne pathogens with high hospitalization and mortality rates, such as Listeria monocytogenes. This study aimed to develop a biosensor that could detect L. monocytogenes rapidly and robustly. For this purpose, a cell-based biosensor technology based on the Bioelectric Recognition Assay (BERA) and a portable device developed by EMBIO Diagnostics, called B.EL.D (Bio Electric Diagnostics), were used. Membrane engineering was performed by electroinsertion of Listeria monocytogenes homologous antibodies into the membrane of African green monkey kidney (Vero) cells. The newly developed biosensor was able to detect the pathogen’s presence rapidly (3 min) at concentrations as low as 102 CFU mL−1, demonstrating a higher sensitivity than most existing biosensor-based methods. In addition, lack of cross-reactivity with other Listeria species, as well as with Escherichia coli, was shown, thus, indicating biosensor’s significant specificity against L. monocytogenes. | URI: | https://hdl.handle.net/20.500.14279/23095 | ISSN: | 20796374 | DOI: | 10.3390/bios10110178 | Rights: | © by the authors. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license. Attribution-NonCommercial-NoDerivatives 4.0 International |
Type: | Article | Affiliation : | EMBIO Diagnostics Ltd. Cyprus University of Technology |
Publication Type: | Peer Reviewed |
Appears in Collections: | Άρθρα/Articles |
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biosensors-10-00178.pdf | Fulltext | 4.44 MB | Adobe PDF | View/Open |
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