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用于精确识别肿瘤细胞中多种微小RNA的DNA逻辑纳米机器。

DNA logic nanomachine for the accurate identification of multiple microRNAs in tumor cells.

作者信息

Dong Zhe, Zhu Wenjun, Ren Yingjie, Xiao Yuliang, Wu Han

机构信息

Department of Gastrointestinal Surgery, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, 250021, China.

School of Public Health, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, Shandong, 250117, China.

出版信息

Talanta. 2025 May 15;287:127590. doi: 10.1016/j.talanta.2025.127590. Epub 2025 Jan 13.

Abstract

The use of dynamic DNA logic circuits for disease diagnosis at the molecular level plays a considerable role in biomedical fields. Nevertheless, how to create programmable nanomachines based on molecular logical gates to accurately identify multiple biomarkers from tumor cells remains a pivotal challenge. Herein, we developed a DNA-based nanomachine for analyzing and imaging multiple microRNAs (miRNAs) in cancerous cells with a logical AND operation. The triangular prism design of DNA nanomachine improved its performance in living cell research with high stability and served as a modularized framework for toehold-mediated strand displacement reactions and catalytic hairpin assembly circuits. The results suggested that the nanomachine could efficiently enter cells with great biocompatibility and rapidly recognize the correct biomolecules with high sensitivity. The well-designed DNA-logic gate nanomachine enabled accurate diagnosis on multiple miRNA patterns in different cell lines and differentiation of aberrant expression in target cells, which provided a novel possibility for intelligent disease diagnosis using smart nanomachines at the molecular level.

摘要

在分子水平上使用动态DNA逻辑电路进行疾病诊断在生物医学领域发挥着重要作用。然而,如何基于分子逻辑门创建可编程纳米机器以准确识别肿瘤细胞中的多种生物标志物仍然是一个关键挑战。在此,我们开发了一种基于DNA的纳米机器,用于通过逻辑与运算分析和成像癌细胞中的多种微小RNA(miRNA)。DNA纳米机器的三棱柱设计提高了其在活细胞研究中的性能,具有高稳定性,并作为用于引发介导的链置换反应和催化发夹组装电路的模块化框架。结果表明,该纳米机器能够以良好的生物相容性高效进入细胞,并以高灵敏度快速识别正确的生物分子。精心设计的DNA逻辑门纳米机器能够对不同细胞系中的多种miRNA模式进行准确诊断,并区分靶细胞中的异常表达,这为在分子水平上使用智能纳米机器进行智能疾病诊断提供了新的可能性。

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