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Detection of Various Biomarkers and Enzymes via Nanocluster-Based Fluorescence Turn-On Sensing Platform

DOI:10.1021/acs.analchem.8b04691 期刊:Analytical Chemistry 出版年份:2018 更新时间:2025-09-09 09:28:46
摘要: The profiling of disease-related biomarkers is an essential procedure for the accurate diagnosis and intervention of metabolic disorders. Therefore, the development of ultrasensitive and highly selective fluorogenic biosensors for diverse biomarkers is extremely desirable. There is still a considerable challenge to prepare nanocluster-based fluorescence turn-on probes capable of recognizing multiple biomolecules. We herein provide a novel nanocluster-based chemical information processing system (CIPS) for the programmable detecting various metabolites and enzymes. This CIPS consists of the biocatalytic reactions between substrates and their respective oxidases to generate H2O2, which was then employed to synthesize bright fluorescent silver nanoclusters (Ag NCs). Utilizing this system, we are able to accurately probe a series of substrates/ corresponding oxidases with high sensitivity and specificity, including glucose/ glucose oxidase, uric acid/ uric acid oxidase, sarcosine/ sarcosine oxidase, choline/ choline oxidase, xanthine/ xanthine oxidase, and lactic acid/ lactic acid oxidase. Furthermore, this metabolite profiling CIPS can integrate with binary logic operations, which create an intelligently tool for the high throughput screening of various diseases in vitro (e.g., diabetes, gout, prostate cancer, cardiovascular disease, and lactic acidosis).
作者: Yue Zhao,Hou Liu,Yingnan Jiang,Shanliang Song,Yueqi Zhao,Chuan Zhang,Jingwei Xin,Bai Yang,Quan Lin
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The development of ultrasensitive and highly selective fluorogenic biosensors for diverse biomarkers to accurately diagnose and intervene metabolic disorders.

The nanocluster-based fluorescence turn-on CIPS was successfully established for the programmable detection of various crucial biomarkers/corresponding oxidases. The PL intensity of CIPS shows a linear relationship to the reactive biomolecular amounts. This metabolite profiling has been integrated to binary logic gates, providing a new strategy for future screening of metabolic diseases or medical diagnostics.

The technical and application constraints of the experiments, as well as potential areas for optimization, are not explicitly mentioned in the provided text.

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