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Ultrasensitive detection of plant hormone abscisic acid-based surface-enhanced Raman spectroscopy aptamer sensor
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Ultrasensitive detection of plant hormone abscisic acid-based surface-enhanced Raman spectroscopy aptamer sensor
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Journal Article
Ultrasensitive detection of plant hormone abscisic acid-based surface-enhanced Raman spectroscopy aptamer sensor
2022
Overview
Abscisic acid (ABA), as the most common plant hormone in the growth of wheat, can greatly affect the yield when its levels deviate from normal. Therefore, highly sensitive and selective detection of this hormone is greatly needed. In this work, we developed an aptamer sensor based on surface-enhanced Raman spectroscopy (SERS) and applied it for the high sensitivity detection of ABA. Biotin-modified ABA aptamer complement chains were modified on ferrosoferric oxide magnetic nanoparticles (Fe3O4MNPs) and acted as capture probes, and sulfhydryl aptamer (SH-Apt)-modified silver-coated gold nanospheres (Au@Ag NPs) were used as signal probes. Through the recognition of the ABA aptamer and its complementary chains, an aptamer sensor based on SERS was constructed. As SERS internal standard molecules of 4-mercaptobenzoic acid (4-MBA) were encapsulated between the gold core and silver shell of the signal probes; the constructed aptamer sensor generated a strong SERS signal of 4-MBA after magnetic separation. When there were ABA molecules in the detection system, with the preferential binding of ABA aptamer and ABA molecule, the signal probes were released from the capture probes, after magnetic separation, leading to a linear decrease in SERS intensity of 4-MBA. Thus, the detection response was linear over a logarithmic concentration range, with an ultra-low detection limit of 0.67 fM. In addition, the practical use of this assay method was demonstrated in ABA detection from fresh wheat leaves, with a relative error (RE) of 5.43–8.94% when compared with results from enzyme-linked immunosorbent assay (ELISA). The low RE value proves that the aptamer sensor will be a promising method for ABA detection.
Publisher
Springer Nature B.V
Subject
