LIMMS, CNRS, Institute of Industrial Science, University of Tokyo, 153-8505 Tokyo, Japan.
Laboratoire Gulliver, CNRS, ESPCI Paris, PSL Research University, 10 rue Vauquelin, 75005 Paris, France.
Nat Nanotechnol. 2017 May;12(4):351-359. doi: 10.1038/nnano.2016.299. Epub 2017 Jan 30.
Information stored in synthetic nucleic acids sequences can be used in vitro to create complex reaction networks with precisely programmed chemical dynamics. Here, we scale up this approach to program networks of microscopic particles (agents) dispersed in an enzymatic solution. Agents may possess multiple stable states, thus maintaining a memory and communicate by emitting various orthogonal chemical signals, while also sensing the behaviour of neighbouring agents. Using this approach, we can produce collective behaviours involving thousands of agents, for example retrieving information over long distances or creating spatial patterns. Our systems recapitulate some fundamental mechanisms of distributed decision making and morphogenesis among living organisms and could find applications in cases where many individual clues need to be combined to reach a decision, for example in molecular diagnostics.
储存在合成核酸序列中的信息可用于体外构建具有精确编程化学动力学的复杂反应网络。在这里,我们扩展了这种方法,以编程分散在酶溶液中的微观粒子(agents)网络。agents 可以具有多个稳定状态,从而保持记忆并通过发出各种正交化学信号进行通信,同时还可以感知相邻 agents 的行为。使用这种方法,我们可以产生涉及数千个 agents 的集体行为,例如远距离检索信息或创建空间模式。我们的系统再现了生物体内分布式决策和形态发生的一些基本机制,并且可能在需要结合许多单个线索才能做出决策的情况下找到应用,例如在分子诊断中。