化学
碱性磷酸酶
生物标志物
DNA
信号(编程语言)
四面体
生物物理学
纳米技术
生物化学
酶
结晶学
计算机科学
生物
材料科学
程序设计语言
作者
Mengde Zhao,Jiahui Zhang,Lihua Wang,Na Lü
标识
DOI:10.1021/acs.analchem.5c02300
摘要
Point-of-care (POC) detection of prostate-specific antigen (PSA) is critical for the early screening and monitoring of prostate cancer (PCa), which facilitates timely intervention and personalized treatment. However, existing POC platforms suffer from inadequate detection sensitivities, susceptibility to matrix interference, and complex sample pretreatment. To address these issues, we proposed a naked-eye and colorimetric sensing platform based on magnetic nanozyme (Fe3O4@ZIF-67@Pt) integrated with a tetrahedral DNA framework (TDF) and alkaline phosphatase (ALP)-triggered hydrolysis reaction for PSA detection with superior sensing performances. The as-prepared Fe3O4@ZIF-67@Pt nanocomposite synergistically integrates magnetic separation, DNA-conjugated interface engineering, and significantly enhanced peroxidase-like activity, thereby laying the foundation for the construction of high-performance colorimetric biosensors. TDF serves dual functions as a programmable biosensing element, including three vertex anchor ALP reporters for catalytic signal amplification, while the remaining vertex is hybridized with a PSA-specific aptamer to drive competitive target recognition. With the addition of PSA, it preferentially bound to the aptamer, creating a competitive reaction and leading to the release of TDF conjugated to the surface of the magnetic nanozyme. When the ALP-mediated hydrolysis reaction was introduced, the released TDF limited the generation of ascorbic acid (AA) to produce a colorimetric response, resulting in a "signal-on" colorimetric assay. The designed platform allowed for the naked-eye and colorimetric detection of PSA in the range of 0.1-1000 ng/mL, with a detection limit as low as 36 pg/mL, while exhibiting excellent selectivity. Additionally, it achieved a high accuracy and satisfactory reliability for PSA detection in human serum samples as well as successfully distinguished prostate cancer patients from healthy individuals. This work holds great potential for application in the development of a reliable POC platform for biomarker detection.
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