Please login first

Newly developed system for Listeria monocytogenes detection in food products based on a bioelectric cell biosensor
AGNI HADJILOUKA * 1 , Konstantinos Loizou 2 , Theofylaktos Apostolou 2 , Lazaros Dougiakis 2 , Antonios Inglezakis 2 , Dimitris Tsaltas 3
1  Department of Agricultural Sciences, Biotechnology and Food Science, Cyprus University of Technology, 30 Archbishop Kyprianos, 3036, Limassol, Cyprus EMBIO Diagnostics Ltd, Athalassas Avenue 8b, Strovolos, 2018 Nicosia, Cyprus
2  EMBIO Diagnostics Ltd, Athalassas Avenue 8b, Strovolos, 2018 Nicosia, Cyprus
3  Department of Agricultural Sciences, Biotechnology and Food Science, Cyprus University of Technology, 30 Archbishop Kyprianos, 3036, Limassol, Cyprus

10.3390/IECB2020-07018 (registering DOI)
Abstract:

Human food-borne diseases have been significantly increased in the last decades, causing numerous deaths, as well as money and time loss in the agri-food sector and food supply chain worldwide. The standard analyses that are currently used for bacteria detection have significant limitations regarding cost, special facilities, 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. Improved and accurate techniques that provide fast detection are of great importance since it is very crucial to detect pathogenic microorganisms and withdraw the contaminated products from the markets before their distribution to consumers. Aim of this study was to develop a biosensor able to perform robust and accurate detection of L. monocytogenes in various food substrates within 3 minutes. For this purpose, a cell-based biosensor technology (BERA) and a portable device developed by EMBIO Diagnostics called B.EL.D (Bio Electric Diagnostics), were used. Biosensors were created for L. monocytogenes detection using anti-Listeria monocytogenes antibodies and tests were conducted in ready-to-eat lettuce salads, milk, and halloumi cheese samples. Results indicated that the biosensor managed to differentiate samples with and without Listeria with 90%, 89% and 91% accuracy in ready-to-eat lettuce salads, milk, and halloumi samples, respectively, after a primary enrichment step. Method’s sensitivity, specificity, positive and negative predictive values ranged from 83-95%, while the limit of detection was determined to be 102 CFU mL-1 or g-1 in all food substrates.

Keywords: Listeria monocytogenes; cell-based biosensors; food safety; bioelectric recognition assay
Top