Literature DB >> 34043553

A cellular platform for the development of synthetic living machines.

Douglas Blackiston1, Emma Lederer1, Sam Kriegman2, Simon Garnier3, Joshua Bongard2, Michael Levin4,5.   

Abstract

Robot swarms have, to date, been constructed from artificial materials. Motile biological constructs have been created from muscle cells grown on precisely shaped scaffolds. However, the exploitation of emergent self-organization and functional plasticity into a self-directed living machine has remained a major challenge. We report here a method for generation of in vitro biological robots from frog (Xenopus laevis) cells. These xenobots exhibit coordinated locomotion via cilia present on their surface. These cilia arise through normal tissue patterning and do not require complicated construction methods or genomic editing, making production amenable to high-throughput projects. The biological robots arise by cellular self-organization and do not require scaffolds or microprinting; the amphibian cells are highly amenable to surgical, genetic, chemical, and optical stimulation during the self-assembly process. We show that the xenobots can navigate aqueous environments in diverse ways, heal after damage, and show emergent group behaviors. We constructed a computational model to predict useful collective behaviors that can be elicited from a xenobot swarm. In addition, we provide proof of principle for a writable molecular memory using a photoconvertible protein that can record exposure to a specific wavelength of light. Together, these results introduce a platform that can be used to study many aspects of self-assembly, swarm behavior, and synthetic bioengineering, as well as provide versatile, soft-body living machines for numerous practical applications in biomedicine and the environment.
Copyright © 2021 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

Entities:  

Mesh:

Substances:

Year:  2021        PMID: 34043553     DOI: 10.1126/scirobotics.abf1571

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


  9 in total

1.  Technological Approach to Mind Everywhere: An Experimentally-Grounded Framework for Understanding Diverse Bodies and Minds.

Authors:  Michael Levin
Journal:  Front Syst Neurosci       Date:  2022-03-24

2.  Mathematical model and genomics construction of developmental biology patterns using digital image technology.

Authors:  Shiwei Ni; Fei Chen; Guolong Chen; Yufeng Yang
Journal:  Front Genet       Date:  2022-08-10       Impact factor: 4.772

3.  From the origin of life to pandemics: emergent phenomena in complex systems.

Authors:  Oriol Artime; Manlio De Domenico
Journal:  Philos Trans A Math Phys Eng Sci       Date:  2022-05-23       Impact factor: 4.019

4.  Some Characteristics and Arguments in Favor of a Science of Machine Behavior Analysis.

Authors:  Marc J Lanovaz
Journal:  Perspect Behav Sci       Date:  2022-03-31

5.  Biology, Buddhism, and AI: Care as the Driver of Intelligence.

Authors:  Thomas Doctor; Olaf Witkowski; Elizaveta Solomonova; Bill Duane; Michael Levin
Journal:  Entropy (Basel)       Date:  2022-05-16       Impact factor: 2.738

6.  Kinematic self-replication in reconfigurable organisms.

Authors:  Sam Kriegman; Douglas Blackiston; Michael Levin; Josh Bongard
Journal:  Proc Natl Acad Sci U S A       Date:  2021-12-07       Impact factor: 11.205

Review 7.  Behaviorist approaches to investigating memory and learning: A primer for synthetic biology and bioengineering.

Authors:  Charles I Abramson; Michael Levin
Journal:  Commun Integr Biol       Date:  2021-12-14

8.  Competency in Navigating Arbitrary Spaces as an Invariant for Analyzing Cognition in Diverse Embodiments.

Authors:  Chris Fields; Michael Levin
Journal:  Entropy (Basel)       Date:  2022-06-12       Impact factor: 2.738

9.  Minimal Developmental Computation: A Causal Network Approach to Understand Morphogenetic Pattern Formation.

Authors:  Santosh Manicka; Michael Levin
Journal:  Entropy (Basel)       Date:  2022-01-10       Impact factor: 2.524

  9 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.