Highly sensitive detection of a bio-threat pathogen by gold nanoparticle-based oligonucleotide-linked immunosorbent assay

Authors
Seo, Sang-HwanLee, Young-RanJeon, Jun HoHwang, Yi-RangPark, Pil-GuAhn, Dae-RoHan, Ki-CheolRhie, Gi-EunHong, Kee-Jong
Issue Date
2015-02-15
Publisher
ELSEVIER ADVANCED TECHNOLOGY
Citation
BIOSENSORS & BIOELECTRONICS, v.64, pp.69 - 73
Abstract
Francisella (F.) tularensis causes the zoonotic disease tularemia and categorized as one of the highestpriority biological agents. The sensing approaches utilized by conventional detection methods, including enzyme-linked immunosorbent assay (ELISA), are not sensitive enough to identify an infectious dose of this high-risk pathogen due to its low infective dose. As an attempt to detect E tularensis with high sensitivity, we utilized the highly sensitive immunoassay system named gold nanoparticle-based oligonucleotide-linked immunosorbent assay (GNP-OLISA) which uses antibody-gold nanoparticles conjugated with DNA strands as a signal generator and RNA oligonucleotides appended with a fluorophore as a quencher for signal amplification. We modified the GNP-OLISA for the detection E tularensis to utilize one antibody for both the capture of the target and for signal generation instead of using two different antibodies, which are usually employed to construct the antibody sandwich in the ELISA. The GNP-OLISA showed 37-fold higher sensitivity compared with ELISA and generated very consistent detection results in the sera. In addition, the detection specificity was not affected by the presence of non-target bacteria, suggesting that GNP-OLISA can be used as a sensitive detection platform for monitoring high-risk pathogens thereby overcoming the limit of the conventional assay system. (C) 2014 Elsevier B.V. All rights reserved.
Keywords
SALMONELLA; SALMONELLA; Francisella tularensis; Bacteria; ELISA; OLISA; Detection sensitivity; Gold-nanoparticle
ISSN
0956-5663
URI
https://pubs.kist.re.kr/handle/201004/125763
DOI
10.1016/j.bios.2014.08.038
Appears in Collections:
KIST Article > 2015
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