DNA has shown great biocompatibility, programmable mechanical properties, and precise structural addressability at the nanometer scale, rendering it a material for constructing versatile nanorobots for biomedical applications. Here, we present the design principle, synthesis, and characterization of a DNA nanorobotic hand, called DNA NanoGripper, that contains a palm and four bendable fingers as inspired by naturally evolved human hands, bird claws, and bacteriophages. Each NanoGripper finger consists of three phalanges connected by three rotatable joints that are bendable in response to the binding of other entities. NanoGripper functions are enabled and driven by the interactions between moieties attached to the fingers and their binding partners. We demonstrate that the NanoGripper can be engineered to effectively interact with and capture nanometer-scale objects, including gold nanoparticles, gold NanoUrchins, and SARS-CoV-2 virions. With multiple DNA aptamer nanoswitches programmed to generate a fluorescent signal that is enhanced on a photonic crystal platform, the NanoGripper functions as a highly sensitive biosensor that selectively detects intact SARS-CoV-2 virions in human saliva with a limit of detection of ~100 copies per milliliter, providing a sensitivity equal to that of reverse transcription quantitative polymerase chain reaction (RT-qPCR). Quantified by flow cytometry assays, we demonstrated that the NanoGripper-aptamer complex can effectively block viral entry into the host cells, suggesting its potential for inhibiting virus infections. The design, synthesis, and characterization of a sophisticated nanomachine that can be tailored for specific applications highlight a promising pathway toward feasible and efficient solutions to the detection and potential inhibition of virus infections.
Bioinspired designer DNA NanoGripper for virus sensing and potential inhibition.
用于病毒检测和潜在抑制的仿生设计DNA纳米抓取器
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作者:Zhou Lifeng, Xiong Yanyu, Dwivedy Abhisek, Zheng Mengxi, Cooper Laura, Shepherd Skye, Song Tingjie, Hong Wei, Le Linh T P, Chen Xin, Umrao Saurabh, Rong Lijun, Wang Tong, Cunningham Brian T, Wang Xing
| 期刊: | Science Robotics | 影响因子: | 27.500 |
| 时间: | 2024 | 起止号: | 2024 Nov 27; 9(96):eadi2084 |
| doi: | 10.1126/scirobotics.adi2084 | 研究方向: | 其它 |
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