Coyle Scott M
Department of Biochemistry, University of Wisconsin, Madison, Madison, Wisconsin 53706.
Mol Biol Cell. 2020 Oct 15;31(22):2415-2420. doi: 10.1091/mbc.E20-04-0275.
Place a drop of pond water under the microscope, and you will likely find an ocean of extraordinary and diverse single-celled organisms called . This remarkable group of single-celled organisms wield microtubules, active systems, electrical signaling, and chemical sensors to build intricate geometrical structures and perform complex behaviors that can appear indistinguishable from those of macroscopic animals. Advances in computer vision and machine learning are making it possible to completely digitize and track the dynamics of complex ciliates and mine these data for the hidden structure, patterns, and motifs that are responsible for their behaviors. By deconstructing the diversity of ciliate behaviors in the natural world, themes for organizing and controlling matter at the microscale are beginning to take hold, suggesting new modular approaches for the design of autonomous molecular machines that emulate nature's finest examples.
在显微镜下滴一滴池塘水,你很可能会发现一个由非凡多样的单细胞生物组成的“海洋”,这些生物被称为纤毛虫。这群非凡的单细胞生物利用微管、活性系统、电信号和化学传感器来构建复杂的几何结构,并执行一些复杂行为,这些行为可能与宏观动物的行为难以区分。计算机视觉和机器学习的进步使得完全数字化和跟踪复杂纤毛虫的动态成为可能,并挖掘这些数据以寻找隐藏的结构、模式和基序,这些因素决定了它们的行为。通过解构自然界中纤毛虫行为的多样性,在微观尺度上组织和控制物质的主题开始确立,这为设计模仿自然界最佳范例的自主分子机器提出了新的模块化方法。