TY - JOUR
T1 - A practical guide to intelligent image-activated cell sorting
AU - Isozaki, Akihiro
AU - Mikami, Hideharu
AU - Hiramatsu, Kotaro
AU - Sakuma, Shinya
AU - Kasai, Yusuke
AU - Iino, Takanori
AU - Yamano, Takashi
AU - Yasumoto, Atsushi
AU - Oguchi, Yusuke
AU - Suzuki, Nobutake
AU - Shirasaki, Yoshitaka
AU - Endo, Taichiro
AU - Ito, Takuro
AU - Hiraki, Kei
AU - Yamada, Makoto
AU - Matsusaka, Satoshi
AU - Hayakawa, Takeshi
AU - Fukuzawa, Hideya
AU - Yatomi, Yutaka
AU - Arai, Fumihito
AU - Di Carlo, Dino
AU - Nakagawa, Atsuhiro
AU - Hoshino, Yu
AU - Hosokawa, Yoichiroh
AU - Uemura, Sotaro
AU - Sugimura, Takeaki
AU - Ozeki, Yasuyuki
AU - Nitta, Nao
AU - Goda, Keisuke
N1 - Funding Information:
This work was supported primarily by the ImPACT program of the Council for Science, Technology, and Innovation (Cabinet Office, Government of Japan) and partly by the JSPS Core-to-Core Program and White Rock Foundation. We thank M. Kanematsu, M. Urakawa, A. Komiya, and S. Aihara for assistance. N.N. is an ISAC Marylou Ingram Scholar.
Publisher Copyright:
© 2019, The Author(s), under exclusive licence to Springer Nature Limited.
PY - 2019/8/1
Y1 - 2019/8/1
N2 - Intelligent image-activated cell sorting (iIACS) is a machine-intelligence technology that performs real-time intelligent image-based sorting of single cells with high throughput. iIACS extends beyond the capabilities of fluorescence-activated cell sorting (FACS) from fluorescence intensity profiles of cells to multidimensional images, thereby enabling high-content sorting of cells or cell clusters with unique spatial chemical and morphological traits. Therefore, iIACS serves as an integral part of holistic single-cell analysis by enabling direct links between population-level analysis (flow cytometry), cell-level analysis (microscopy), and gene-level analysis (sequencing). Specifically, iIACS is based on a seamless integration of high-throughput cell microscopy (e.g., multicolor fluorescence imaging, bright-field imaging), cell focusing, cell sorting, and deep learning on a hybrid software–hardware data management infrastructure, enabling real-time automated operation for data acquisition, data processing, intelligent decision making, and actuation. Here, we provide a practical guide to iIACS that describes how to design, build, characterize, and use an iIACS machine. The guide includes the consideration of several important design parameters, such as throughput, sensitivity, dynamic range, image quality, sort purity, and sort yield; the development and integration of optical, microfluidic, electrical, computational, and mechanical components; and the characterization and practical usage of the integrated system. Assuming that all components are readily available, a team of several researchers experienced in optics, electronics, digital signal processing, microfluidics, mechatronics, and flow cytometry can complete this protocol in ~3 months.
AB - Intelligent image-activated cell sorting (iIACS) is a machine-intelligence technology that performs real-time intelligent image-based sorting of single cells with high throughput. iIACS extends beyond the capabilities of fluorescence-activated cell sorting (FACS) from fluorescence intensity profiles of cells to multidimensional images, thereby enabling high-content sorting of cells or cell clusters with unique spatial chemical and morphological traits. Therefore, iIACS serves as an integral part of holistic single-cell analysis by enabling direct links between population-level analysis (flow cytometry), cell-level analysis (microscopy), and gene-level analysis (sequencing). Specifically, iIACS is based on a seamless integration of high-throughput cell microscopy (e.g., multicolor fluorescence imaging, bright-field imaging), cell focusing, cell sorting, and deep learning on a hybrid software–hardware data management infrastructure, enabling real-time automated operation for data acquisition, data processing, intelligent decision making, and actuation. Here, we provide a practical guide to iIACS that describes how to design, build, characterize, and use an iIACS machine. The guide includes the consideration of several important design parameters, such as throughput, sensitivity, dynamic range, image quality, sort purity, and sort yield; the development and integration of optical, microfluidic, electrical, computational, and mechanical components; and the characterization and practical usage of the integrated system. Assuming that all components are readily available, a team of several researchers experienced in optics, electronics, digital signal processing, microfluidics, mechatronics, and flow cytometry can complete this protocol in ~3 months.
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U2 - 10.1038/s41596-019-0183-1
DO - 10.1038/s41596-019-0183-1
M3 - Article
C2 - 31278398
AN - SCOPUS:85068833715
SN - 1754-2189
VL - 14
SP - 2370
EP - 2415
JO - Nature Protocols
JF - Nature Protocols
IS - 8
ER -