Intelligent image-activated cell sorting 2.0
Intelligent image-activated cell sorting 2.0
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DOI：
10.1039/d0lc00080a
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发表时间：
2020-07-07
期刊：
影响因子：
6.1
通讯作者：
Goda, Keisuke
中科院分区：
文献类型：
--
作者：
Isozaki, Akihiro;Mikami, Hideharu;Goda, Keisuke
智能图像激活细胞分选（iIACS）的出现使得能够对来自异质群体的单个活细胞进行基于图像的高通量智能分选。iIACS是一种片上微流控技术，它建立在高通量荧光显微镜、细胞聚焦器、细胞分选器和深度神经网络在混合软件-硬件数据管理架构上的无缝集成基础上，从而提供了光学显微镜、荧光激活细胞分选（FACS）和深度学习的综合优势。在这里，我们报告了一台iIACS机器，它在系统性能上远远超过了最先进的iIACS机器，以扩大该技术的应用范围和发现。具体而言，它提供了类似于每秒2000个事件的高通量和类似于50个等效可溶性荧光团（MESF）分子的高灵敏度，这两者都比先前报道中所实现的高出20倍上级。这是通过采用（i）基于图像传感器的光学机械流动成像方法（称为虚拟冻结荧光成像）和（ii）配备8个多核CPU和GPU的8-PC服务器上的实时智能图像处理器来实现的，用于智能决策，以显着提高iIACS机器的成像性能和计算能力。我们表征的iIACS机与荧光颗粒和各种细胞类型，并表明iIACS机的性能接近其可实现的设计规格。新一代iIACS技术配备了改进的功能，有望在免疫学、微生物学、干细胞生物学、癌症生物学、病理学和合成生物学中实现各种应用。
The advent of intelligent image-activated cell sorting (iIACS) has enabled high-throughput intelligent image-based sorting of single live cells from heterogeneous populations. iIACS is an on-chip microfluidic technology that builds on a seamless integration of a high-throughput fluorescence microscope, cell focuser, cell sorter, and deep neural network on a hybrid software-hardware data management architecture, thereby providing the combined merits of optical microscopy, fluorescence-activated cell sorting (FACS), and deep learning. Here we report an iIACS machine that far surpasses the state-of-the-art iIACS machine in system performance in order to expand the range of applications and discoveries enabled by the technology. Specifically, it provides a high throughput of similar to 2000 events per second and a high sensitivity of similar to 50 molecules of equivalent soluble fluorophores (MESFs), both of which are 20 times superior to those achieved in previous reports. This is made possible by employing (i) an image-sensor-based optomechanical flow imaging method known as virtual-freezing fluorescence imaging and (ii) a real-time intelligent image processor on an 8-PC server equipped with 8 multi-core CPUs and GPUs for intelligent decision-making, in order to significantly boost the imaging performance and computational power of the iIACS machine. We characterize the iIACS machine with fluorescent particles and various cell types and show that the performance of the iIACS machine is close to its achievable design specification. Equipped with the improved capabilities, this new generation of the iIACS technology holds promise for diverse applications in immunology, microbiology, stem cell biology, cancer biology, pathology, and synthetic biology.