Quantum dots based imprinting fluorescent nanosensor for the selective and sensitive detection of phycocyanin: A general imprinting strategy toward proteins

Content Provider	Semantic Scholar
Author	Wang, Xiaoyan Yu, Jialuo Li, Jinghong Kang, Qi Shen, Dazhong Chen, Lingxin
Copyright Year	2018
Abstract	Abstract Molecular imprinting as a versatile technology has gained popularity in various fields for diverse species; however, protein imprinting still remains challenging due to some inherent problems but is potentially rewarding work. Herein, we reported a facile strategy to imprint phycocyanin (PC), as a template, using quantum dots (QDs) co-capped by thioglycollic acid and glutathione directly as functional monomer via dopamine self-polymerization, which effectively simplified the imprinting process and afforded easy accessibility to recognition sites. The resulting QDs based imprinting nanosensor showed significant fluorescence decrease of QDs within less than 16 s upon binding PC owing to the ultrathin imprinting layer (ca. 3 nm), leading to a high detectability down to 0.075 μM. An excellent linearity was found within the wide range of 0.8–8.0 μM ( R 2 = 0.9935). Good recognition selectivity toward PC was displayed over other possible competing molecules, with a high imprinting factor of 7.3. Seawater and lake water samples spiked with PC were also analyzed, presenting satisfactory recoveries ranging from 90.8–110.1% with precisions below 4.6%, indicating the practicality of the imprinting nanosensor for accurately rapid nanoscale monitoring of algae blooms. By using another protein, bovine haemoglobin (BHb), as a convincing support model, the present study can provide a simple and general imprinting strategy toward various concerned proteins through rationally utilizing diverse functionalization and interactions.
Starting Page	268
Ending Page	274
Page Count	7
File Format	PDF HTM / HTML
DOI	10.1016/j.snb.2017.08.068
Volume Number	255
Alternate Webpage(s)	http://isiarticles.com/bundles/Article/pre/pdf/123004.pdf
Language	English
Access Restriction	Open
Content Type	Text
Resource Type	Article