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Detection of Metallothionein in Javanese Medaka (Oryzias javanicus), Using a scFv-Immobilized Protein Chipopen access

Authors
Lee, EuiyeonJeon, HyunjinKang, ChungwonWoo, SeonockYum, SeungshicKwon, Youngeun
Issue Date
Apr-2018
Publisher
MDPI
Keywords
metallothionein; single-chain fragment of variable region (scFv); surface plasmon resonance (SPR); biomarker; sensor chip
Citation
SENSORS, v.18, no.4
Indexed
SCIE
SCOPUS
Journal Title
SENSORS
Volume
18
Number
4
URI
https://scholarworks.dongguk.edu/handle/sw.dongguk/9607
DOI
10.3390/s18041069
ISSN
1424-8220
1424-3210
Abstract
Environmental pollution by various industrial chemicals and biological agents poses serious risks to human health. Especially, marine contamination by potentially toxic elements (PTEs) has become a global concern in recent years. Many efforts have been undertaken to monitor the PTE contamination of the aquatic environment. However, there are few approaches available to assess the PTE exposure of aquatic organisms. In this research, we developed a strategy to evaluate the heavy metal exposure of marine organisms, by measuring the expression levels of metallothionein protein derived from Oryzias javanicus (OjaMT). OjaMT is a biomarker of heavy metal exposure because the expression level increases upon heavy metal exposure. The developed assay is based on a real-time, label-free surface plasmon resonance (SPR) measurement. Anti-OjaMT antibody and anti-OjaMT single-chain fragment of variable region (scFv) were used as detection probes. Two types of SPR sensor chips were fabricated, by immobilizing antibody or Cys3-tagged scFv (scFv-Cys3) in a controlled orientation and were tested for in situ label-free OjaMT detection. Compared to the antibody-presenting sensor chips, the scFv-presenting sensor chips showed improved performance, displaying enhanced sensitivity and enabling semi-quantitative detection. The portable SPR system combined with scFv-immobilized sensor chips is expected to provide an excellent point-of-care testing system that can monitor target biomarkers in real time.
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