Intelligent Image-Activated Cell Sorting
Intelligent Image-Activated Cell Sorting
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DOI：
10.1016/j.cell.2018.08.028
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发表时间：
2018-09-20
期刊：
影响因子：
64.5
通讯作者：
Goda, Keisuke
中科院分区：
文献类型：
--
作者：
Nitta, Nao;Sugimura, Takeaki;Goda, Keisuke
生物学的一个基本挑战是了解细胞的巨大异质性，特别是细胞组成，结构和形态如何与细胞生理学联系在一起。不幸的是，传统技术在揭示这些关系方面受到限制。我们提出了一种基于完全不同的架构的机器智能技术，该技术以前所未有的速度实现了基于图像的实时智能细胞分选。这项技术，我们称之为智能图像激活细胞分选，将高通量细胞显微镜，聚焦和分选集成在混合软件-硬件数据管理基础设施上，实现数据采集，数据处理，决策和驱动的实时自动化操作。我们用它来展示实时分选的微藻和血细胞的细胞内蛋白定位和细胞间的相互作用，从大型异质群体研究光合作用和动脉粥样硬化血栓形成，分别。该技术具有高度通用性，有望在生物、制药和医学科学领域实现基于机器的科学发现。
A fundamental challenge of biology is to understand the vast heterogeneity of cells, particularly how cellular composition, structure, and morphology are linked to cellular physiology. Unfortunately, conventional technologies are limited in uncovering these relations. We present a machine-intelligence technology based on a radically different architecture that realizes real-time image-based intelligent cell sorting at an unprecedented rate. This technology, which we refer to as intelligent image-activated cell sorting, integrates high-throughput cell microscopy, focusing, and sorting on a hybrid software-hardware data-management infrastructure, enabling real-time automated operation for data acquisition, data processing, decision-making, and actuation. We use it to demonstrate real-time sorting of microalgal and blood cells based on intracellular protein localization and cell-cell interaction from large heterogeneous populations for studying photosynthesis and atherothrombosis, respectively. The technology is highly versatile and expected to enable machine-based scientific discovery in biological, pharmaceutical, and medical sciences.