A fluorescent biosensor for highly specific and ultrasensitive detection of adenosine triphosphate based on ligation-triggered branched rolling circle amplification. Issue 36 (29th August 2019)

• Record Type: Journal Article
• Authors: Jiang, Hongxin; Han, Guimei; Xu, Yaping; Li, Junxing; Liu, Xiaowei; Kong, Deming
• Is Part Of: Analytical methods. Volume 11:Issue 36(2019)
• Page Start: 4629
• Page End: 4636
• Publication Date: 2019-08-29
• Subjects: Chemistry, Analytic -- Periodicals; Analytical biochemistry -- Periodicals; Chemical laboratories -- Standards -- Periodicals; 543.1905
• DOI: 10.1039/c9ay01482a
• Languages: English
• ISSNs: 1759-9660

Abstract

Abstract : A fluorescent sensing strategy for ultrasensitive and highly selective detection of ATP was presented by taking advantage of the exponential amplification capability of BRCA and the extreme specificity of T4 DNA ligase toward ATP. Abstract : Herein, a fluorescence sensing strategy for ultrasensitive and highly selective detection of adenosine triphosphate (ATP) was presented by taking advantage of the exponential amplification efficiency of branched rolling circle amplification (BRCA) and the extreme specificity of T4 DNA ligase toward ATP. In this strategy, T4 DNA ligase is used to catalyze the cyclization of the template for the subsequent BRCA reaction. And the targeted ATP is the key component to activate the enzyme. The obtained products can then be probed with SYBR Green I (SG I), a kind of DNA duplex specific indicator, giving a dramatically increased fluorescence signal. The experimental results showed that the fluorescence enhancement is highly ATP concentration-dependent, thus making the label-free detection of ATP possible. By using the proposed method, sensitive ATP quantitation with a detection limit of 30 pM was achieved. Since the activity of T4 DNA ligase is highly specific ATP dependent, such a method successfully overcomes the drawback of poor selectivity faced by traditional aptamer-based ATP assays. Moreover, the proposed sensing platform was demonstrated to work well for real sample analysis, suggesting that it has promising potential in practical applications in clinical diagnosis and biochemical research.