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Main Title: Graphene Quantum Dots as Nanozymes for Electrochemical Sensing of Yersinia enterocolitica in Milk and Human Serum
Author(s): Savas, Sumeyra
Altintas, Zeynep
Type: Article
Abstract: The genus Yersinia contains three well-recognized human pathogens, including Y. enterocolitica, Y. pestis, and Y. pseudotuberculosis. Various domesticated and wild animals carry Yersinia in their intestines. Spread to individuals arises from eating food or water contaminated by infected human or animal faeces. Interaction with infected pets and domestic stock may also lead to infection. Yersinia is able to multiply at temperatures found in normal refrigerators; hence, a large number of the bacteria may be present if meat is kept without freezing. Yersinia is also rarely transmitted by blood transfusion, because it is able to multiply in stored blood products. Infection with Yersinia can cause yersiniosis, a serious bacterial infection associated with fever, abdominal pain and cramps, diarrhea, joint pain, and symptoms similar to appendicitis in older children and adults. This paper describes a novel immunosensor approach using graphene quantum dots (GQDs) as enzyme mimics in an electrochemical sensor set up to provide an efficient diagnostic method for Y. enterecolitica. The optimum assay conditions were initially determined and the developed immunosensor was subsequently used for the detection of the bacterium in milk and human serum. The GQD-immunosensor enabled the quantification of Y. enterocolitica in a wide concentration range with a high sensitivity (LODmilk = 5 cfu mL−1 and LODserum = 30 cfu mL−1) and specificity. The developed method can be used for any pathogenic bacteria detection for clinical and food samples without pre-sample treatment. Offering a very rapid, specific and sensitive detection with a label-free system, the GQD-based immunosensor can be coupled with many electrochemical biosensors.
Subject(s): Yersinia enterocolitica
pathogen detection
graphene quantum dots
enzyme mimics
infectious diseases
Issue Date: 8-Jul-2019
Date Available: 26-Aug-2019
Language Code: en
DDC Class: 540 Chemie und zugeordnete Wissenschaften
Journal Title: Materials
Publisher: MDPI
Volume: 12
Issue: 13
Article Number: 2189
Publisher DOI: 10.3390/ma12132189
EISSN: 1996-1944
TU Affiliation(s): Fak. 2 Mathematik und Naturwissenschaften » Inst. Chemie
Appears in Collections:Technische Universität Berlin » Publications

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