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An “off–on” phosphorescent aptasensor for the detection of thrombin based on PRET

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Abstract

Thrombin plays an important role in the blood coagulation cascade and it stimulates the process of platelet aggregation. Herein, we developed a highly efficient and sensitive phosphorescent aptasensor system for the quantitative analysis of thrombin. The phosphorescence of 3-mercaptopropionic acid capped Mn-doped ZnS quantum dots (MPA-Mn:ZnS QDs) was gradually quenched with the addition of thrombin binding aptamers-BHQ2 (TBA-BHQ2) based on phosphorescence resonance energy transfer (PRET). With the addition of the target analyte thrombin into the system, TBA-BHQ2 could change its spatial structure from a random coil to an antiparallel G-quadruplex which resulted from the combination of thrombin and TBA-BHQ2, leading to the phosphorescence recovery. Finally, the concentration of thrombin could be accurately determined by means of measuring the phosphorescence intensity change value (ΔP). The limit of detection (LOD) was obtained as low as 15.26 pM with wide linear ranges both from 60 to 2000 pM and from 2 to 900 nM. The proposed strategy was also successfully applied for thrombin detection in human serum samples and plasma samples with satisfactory recoveries from 96% to 99% and 95% to 104%, respectively. The long lifetime of phosphorescent QDs possessed a suitable time delay to eliminate autofluorescence and scattered light interference from biological matrices effectively. Thus, the signal to noise ratio of the phosphorescent aptasensor was improved visibly for the analysis of target analytes.

Graphical abstract: An “off–on” phosphorescent aptasensor for the detection of thrombin based on PRET

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Publication details

The article was received on 14 Aug 2018, accepted on 01 Oct 2018 and first published on 02 Oct 2018


Article type: Paper
DOI: 10.1039/C8AN01571F
Citation: Analyst, 2018, Advance Article
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    An “off–on” phosphorescent aptasensor for the detection of thrombin based on PRET

    Y. Xiong, M. Liang, Y. Cheng, J. Zou and Y. Li, Analyst, 2018, Advance Article , DOI: 10.1039/C8AN01571F

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