The sensitive detection of ODAM by using sandwich-type biosensors with a cognate pair of aptamers for the early diagnosis of periodontal disease

适体 生物传感器 牙周病 表面等离子共振 唾液 费斯特共振能量转移 圆二色性 纳米技术 化学 荧光 生物物理学 材料科学 生物化学 纳米颗粒 医学 生物 牙科 分子生物学 物理 量子力学
作者
Bang Hyun Lee,Sang Hoon Kim,Youngkyung Ko,Joo‐Cheol Park,Sang-Hoon Ji,Man Bock Gu
出处
期刊:Biosensors and Bioelectronics [Elsevier]
卷期号:126: 122-128 被引量:33
标识
DOI:10.1016/j.bios.2018.10.040
摘要

This research aims to develop biosensors which could diagnose periodontal diseases in early phases and predict the illness stage of patients, in order to give them adequate treatment timely. Human odontogenic ameloblast-associated protein (ODAM) is considered to be a potential biomarker for periodontal diseases, based on high correlation between the level of ODAM in gingival crevicular fluid (GCF) and the degree of periodontitis. Many aptamers, including a cognate pair of aptamers which can bind to the different sites of ODAM, were successfully screened in a very stringent condition employing saliva as a counter target through the graphene oxide-based systemic evolution of ligands by exponential enrichment (GO-SELEX). For the characterization of the aptamer candidates, GO-based fluorescence resonance energy transfer (GO-FRET) and surface plasmon resonance (SPR) assays were conducted. The sandwich-type binding of a cognate pair of aptamers to ODAM was additionally confirmed by employing circular dichroism (CD) and magnetic beads-based fluorescence imaging methods. The resulting cognate pair of aptamers, OD64 and OD35, were found to have their dissociation constant (Kd), 47.71 nM and 51.36 nM, respectively. The minimum detectable concentrations of a sandwich-type SPR biosensor were found to be 0.24 nM and 1.63 nM, respectively, for both buffered and saliva samples. Finally, using this cognate pair of aptamers, a sandwich-type lateral flow strip biosensor was successfully realized. This research shows the potential for implementation of a cognate pair of aptamers on point-of-care biosensors which enables simple, rapid, and non-invasive saliva-based diagnosis of periodontal-related diseases that can overcome current diagnostic methods and improve health care system.
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