Literature DB >> 34193562

Toward a living soft microrobot through optogenetic locomotion control of Caenorhabditis elegans.

Xianke Dong1,2, Sina Kheiri1, Yangning Lu3,4, Zhaoyi Xu1, Mei Zhen3,4, Xinyu Liu5,6.   

Abstract

Learning from the locomotion of natural organisms is one of the most effective strategies for designing microrobots. However, the development of bioinspired microrobots is still challenging because of technical bottlenecks such as design and seamless integration of high-performance actuation mechanism and high-density energy source for untethered locomotion. Directly harnessing the activation energy and intelligence of living tissues in synthetic micromachines provides an alternative route to developing biohybrid microrobots. Here, we propose an approach to engineering the genetic and nervous systems of a nematode worm, Caenorhabditis elegans, and creating an untethered, highly controllable living soft microrobot (called "RoboWorm"). A living worm is engineered through optogenetic and biochemical methods to shut down the signal transmissions between its neuronal and muscular systems while its muscle cells still remain optically excitable. Through dynamic modeling and experimental verification of the worm crawling, we found that the phase difference between the worm body curvature and the muscular activation pattern generates the thrust force for crawling locomotion. By reproducing the phase difference via optogenetic excitation of the worm body muscles, we emulated the major worm crawling behaviors in a controllable manner. Furthermore, with real-time visual feedback of the worm crawling, we realized closed-loop regulation of the movement direction and destination of single worms. This technology may facilitate scientific studies on the biophysics and neural basis of crawling locomotion of C. elegans and other nematode species.
Copyright © 2021 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

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Year:  2021        PMID: 34193562     DOI: 10.1126/scirobotics.abe3950

Source DB:  PubMed          Journal:  Sci Robot        ISSN: 2470-9476


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