Intelligent and robust DNA robots capable of swarming into leakless nonlinear amplification in response to a trigger

Nonlinear DNA signal amplification with an enzyme-free isothermal self-assembly process is uniquely useful in nanotechnology and nanomedicine. However, progress in this direction is hampered by the lack of effective design models of leak-resistant DNA building blocks. Here, we propose two conceptual models of intelligent and robust DNA robots to perform a leakless nonlinear signal amplification in response to a trigger. Two conceptual models are based on super-hairpin nanostructures, which are designed by innovating novel principles in methodology and codifying them into embedded programs. The dynamical and thermodynamical analyses reveal the critical elements and leak-resistant mechanisms of the designed models, and the leak-resistant behaviors of the intelligent DNA robots and morphologies of swarming into nonlinear amplification are separately verified. The applications of the designed models are also illustrated in specific signal amplification and targeted payload enrichment via integration with an aptamer, a fluorescent molecule and surface-enhanced Raman spectroscopy. This work has the potential to serve as design guidelines of intelligent and robust DNA robots and leakless nonlinear DNA amplification, and also as the design blueprint of cargo delivery robots with the performance of swarming into nonlinear amplification in response to a target automatically, facilitating their future applications in biosensing, bioimaging and biomedicine.

Automated summary

In this study, two conceptual models of intelligent and robust DNA robots are proposed to perform leakless nonlinear signal amplification in nanotechnology and nanomedicine. These models are based on super-hairpin nanostructures, designed with innovative principles and codified into embedded programs. Dynamic and thermodynamic analyses reveal the critical elements and leak-resistant mechanisms of the models, which are then validated experimentally. The applications of the models in specific signal amplification and targeted payload enrichment are demonstrated.