Magnetic silica nanotube-assisted impedimetric immunosensor for the separation and label-free detection of Salmonella typhimurium
- Authors
- Nguyen, Phuong-Diem; Tran, Trong Binh; Nguyen, Dung Thi Xuan; Min, Junhong
- Issue Date
- Jul-2014
- Publisher
- ELSEVIER SCIENCE SA
- Keywords
- Magnetic silica nanotube; Magnetic particles; Impedimetric; Microelectrode; Bacterial adsorption
- Citation
- SENSORS AND ACTUATORS B-CHEMICAL, v.197, pp 314 - 320
- Pages
- 7
- Journal Title
- SENSORS AND ACTUATORS B-CHEMICAL
- Volume
- 197
- Start Page
- 314
- End Page
- 320
- URI
- https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/12058
- DOI
- 10.1016/j.snb.2014.02.089
- ISSN
- 0925-4005
- Abstract
- This study describes a simple but effective combinatory effect of magnetic silica nanotubes (MSNTs) in bacterial separation and impedimetric signal enhancement for the label-free detection of Salmonella typhimurium. The outer surface of MSNTs was functionalized with positive charges for the successful concentration and the isolation of bacteria from a high-volume sample. Scanning electron microscopy (SEM) was used to confirm the bacterial adsorption on MSNT. Antibody specific to S. typhimurium was immobilized on the interdigitated microelectrode of an impedimetric sensor. Bacteria binding MSNT (bacteria-MSNT complex) was successfully conjugated with antibody immobilized impedimetric sensor. The decrease of the impedance response was automatically shown due to the antigen-antibody recognition between bacteria and antibody immobilized impedimetric microelectrodes. The presence of MSNT significantly enhanced the impedimetric sensor performance by generating highly discriminated impedance signals in correspond with different bacterial concentrations 10(3)-10(7) CFU. The total detection time from bacteria isolation to measurement was completed within roughly 30 min with low cost and an ease of operation. This study shows the potential use of MSNT in antibody-free bio-separation and in impedimetric signal enhancement with the effort to develop a label-free, automatic pathogenic detection system. (C) 2014 Elsevier B.V. All rights reserved.
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