DOI 10.1021/acs.analchem.6c00448
Fluidly Confined CRISPR-Magnetic Microbots Empowered Homogeneous Electrochemical Biosensor for Amplified Detection and Discrimination of Cancer-Derived Extracellular Vesicle Subtypes.
Аннотация
Accurate identification and profiling of multiple protein biomarkers on tumor-derived extracellular vesicles (tEVs) are crucial for noninvasive cancer subtyping diagnosis but remain technically challenging due to their high heterogeneity, low abundance in biofluids, and preisolation/purification processes. Herein, we developed a homogeneous electrochemical biosensor empowered by fluidly confined CRISPR-magnetic microbots for the amplified detection and sensitive discrimination of tEV subtypes. The CRISPR-magnetic microbots were constructed by engineering CRISPR/Cas12a and DNA icosahedra/doxorubicin (DNA-ICOS/DOX) on intracellularly gelated magnetic cells (IGMCs). Benefiting from the synergistic effects of spatial confinement and membrane fluidity to elevate the local concentration and collision efficiency, the activity of CRISPR/Cas12a was found to be greatly enhanced on IGMCs. For selective sorting of tEVs, a logic-gated aptamer system was used to orthogonally label tEV subpopulations, which further triggers the trans-cleavage activity of CRISPR/Cas12a, resulting in the release of massive DNA-ICOS/DOX into solution. After magnetic separation, the liberated DOX molecules generate a strong electrochemical signal. Particularly, the CRISPR-magnetic microbots could efficiently reduce the background signal, endowing a significantly improved signal-to-noise ratio. Therefore, by combining the CRISPR-magnetic microbots with the dual-target-guided orthogonal barcoding strategy in a homogeneous electrochemical biosensor, precise identification and sensitive detection of tEVs were successfully achieved. More significantly, this assay achieves accurate cancer subtyping in clinical samples, demonstrating its potential as a robust, noninvasive tool for high-accuracy disease screening, classification, and progression monitoring.
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Обработка статьи · этапы, ошибки и управление
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История · было → стало
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