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Target triggered proximity combination-based fluorescent sensing strategy for adenosine detection


Adenosine is a potent physiologic and pharmacologic regulator, and its abnormal level is closely related to disease development. Sensitive and specific detection of adenosine is crucial for health evaluation and disease diagnosis. In this work, a target triggered proximity combination-based fluorescent sensing strategy is developed for sensitive and specific detection of adenosine. A difunctional probe owning target recognition and signal amplification is designed, by integration of DNA linker-connected split aptamer fragments with a fragment-elongated polymerase/nicking template. The presence of adenosine would glue the split aptamers, which triggers the two distal aptamer fragments to combine with each other into proximity. The approaching aptamer fragment ends then initiate the strand displacement amplification (SDA) reaction, generating numerous DNA primers. The DNA primers further hybridize with a padlock probe and initiate the rolling circle amplification (RCA) reaction, producing numerous G-quadruplex sequences. The G-quadruplex sequences finally bind with Thioflavin T to obtain enhanced fluorescent signals. The method exhibits a linear correlation within the adenosine concentration range from 5.0 × 10-7 M to 2.0 × 10-5 M (R = 0.999) with a detection limit of 8.4 × 10-8 M, and a good selectivity to distinguish adenosine from its analogues. The recoveries of adenosine in human serum are from 91% to 94%, demonstrating that the system works well in biological fluid. The proposed sensing strategy is anticipated to hold promise in biochemical research, clinical diagnosis and disease treatment.

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Publication details

The article was received on 19 Apr 2017, accepted on 02 May 2017 and first published on 05 May 2017

Article type: Paper
DOI: 10.1039/C7AN00654C
Citation: Analyst, 2017, Accepted Manuscript
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    Target triggered proximity combination-based fluorescent sensing strategy for adenosine detection

    X. Xu, H. Wei and W. Jiang, Analyst, 2017, Accepted Manuscript , DOI: 10.1039/C7AN00654C

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