||Y. Kasai, C. Leipe, M. Saito, H. Kitagawa, S. Lauterbach, A. Brauer, P. E. Tarasov, T. Goslar, F. Arai, S. Sakuma, Breakthrough in purification of fossil pollen for dating of sediments by a new large-particle on-chip sorter, Science Advances, 10.1126/sciadv.abe7327, 7, 16, Article number: eabe7327, 12 pages, 2021.04.
||Nao Nitta, Takanori Iino, Akihiro Isozaki, Mai Yamagishi, Yasutaka Kitahama, Shinya Sakuma, Yuta Suzuki, Hiroshi Tezuka, Minoru Oikawa, Fumihito Arai, Takuya Asai, Dinghuan Deng, Hideya Fukuzawa, Misa Hase, Tomohisa Hasunuma, Takeshi Hayakawa, Kei Hiraki, Kotaro Hiramatsu, Yu Hoshino, Mary Inaba, Yuki Inoue, Takuro Ito, Masataka Kajikawa, Hiroshi Karakawa, Yusuke Kasai, Yuichi Kato, Hirofumi Kobayashi, Cheng Lei, Satoshi Matsusaka, Hideharu Mikami, Atsuhiro Nakagawa, Keiji Numata, Tadataka Ota, Takeichiro Sekiya, Kiyotaka Shiba, Yoshitaka Shirasaki, Nobutake Suzuki, Shunji Tanaka, Shunnosuke Ueno, Hiroshi Watarai, Takashi Yamano, Masayuki Yazawa, Yusuke Yonamine, Dino Di Carlo, Yoichiroh Hosokawa, Sotaro Uemura, Takeaki Sugimura, Yasuyuki Ozeki, Keisuke Goda, Raman image-activated cell sorting, Nature Communications, 10.1038/s41467-020-17285-3, 11, Article number: 3452, 16 pages, 2020.07, The advent of image-activated cell sorting and imaging-based cell picking has advanced our knowledge and exploitation of biological systems in the last decade. Unfortunately, they generally rely on fluorescent labeling for cellular phenotyping, an indirect measure of the molecular landscape in the cell, which has critical limitations. Here we demonstrate Raman image-activated cell sorting by directly probing chemically specific intracellular molecular vibrations via ultrafast multicolor stimulated Raman scattering (SRS) microscopy for cellular phenotyping. Specifically, the technology enables real-time SRS-image-based sorting of single live cells with a throughput of up to ~100 events per second without the need for fluorescent labeling. To show the broad utility of the technology, we show its applicability to diverse cell types and sizes. The technology is highly versatile and holds promise for numerous applications that are previously difficult or undesirable with fluorescence-based technologies..
||Akihiro Isozaki, Hideharu Mikami, Hiroshi Tezuka, Hiroki Matsumura, Kangrui Huang, Marino Akamine, Kotaro Hiramatsu, Takanori Iino, Takuro Ito, Hiroshi Karakawa, Yusuke Kasai, Yan Li, Yuta Nakagawa, Shinsuke Ohnuki, Tadataka Ota, Yong Qian, Shinya Sakuma, Takeichiro Sekiya, Yoshitaka Shirasaki, Nobutake Suzuki, Ehsen Tayyabi, Tsubasa Wakamiya, Muzhen Xu, Mai Yamagishi, Haochen Yan, Qiang Yu, Sheng Yan, Dan Yuan, Wei Zhang, Yaqi Zhao, Fumihito Arai, Robert E. Campbell, Christophe Danelon, Dino Di Carlo, Kei Hiraki, Yu Hoshino, Yoichiroh Hosokawa, Mary Inaba, Atsuhiro Nakagawa, Yoshikazu Ohya, Minoru Oikawa, Sotaro Uemura, Yasuyuki Ozeki, Takeaki Sugimura, Nao Nitta, Keisuke Goda, Intelligent image-activated cell sorting 2.0, Lab on a chip, 10.1039/D0LC00080A, 20, 13, 2263-2273, 2020.05, 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 ∼2000 events per second and a high sensitivity of ∼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..
||Akihiro Isozaki, Hideharu Mikami, Kotaro Hiramatsu, Shinya Sakuma, Yusuke Kasai, Takanori Iino, Takashi Yamano, Atsushi Yasumoto, Yusuke Oguchi, Nobutake Suzuki, Yoshitaka Shirasaki, Taichiro Endo, Takuro Ito, Kei Hiraki, Makoto Yamada, Satoshi Matsusaka, Takeshi Hayakawa, Hideya Fukuzawa, Yutaka Yatomi, Fumihito Arai, Dino Di Carlo, Atsuhiro Nakagawa, Yu Hoshino, Yoichiroh Hosokawa, Sotaro Uemura, Takeaki Sugimura, Yasuyuki Ozeki, Nao Nitta, Keisuke Goda, A practical guide to intelligent image-activated cell sorting, Nature Protocol, 10.1038/s41596-019-0183-1, 14, 2370-2415, 2019.07.
||Shinya Sakuma, Ko Nakahara, Fumihito Arai, Continuous mechanical indexing of single-cell spheroids using a robot-integrated microfluidic chip, IEEE Robotics and Automation Letters, 10.1109/LRA.2019.2923976, 4, 3, 2973-2980, 2019.06.
||Nao Nitta, Takeaki Sugimura, Akihiro Isozaki, Hideharu Mikami, Kei Hiraki, Shinya Sakuma, Takanori Iino, Fumihito Arai, Taichiro Endo, Yasuhiro Fujiwaki, Hideya Fukuzawa, Misa Hase, Takeshi Hayakawa, Kotaro Hiramatsu, Yu Hoshino, Mary Inaba, Takuro Ito, Hiroshi Karakawa, Yusuke Kasai, Kenichi Koizumi, SangWook Lee, Cheng Lei, Ming Li, Takanori Maeno, Satoshi Matsusaka, Daichi Murakami, Atsuhiro Nakagawa, Yusuke Oguchi, Minoru Oikawa, Tadataka Ota, Kiyotaka Shiba, Hirofumi Shintaku, Yoshitaka Shirasaki, Kanako Suga, Yuta Suzuki, Nobutake Suzuki, Yo Tanaka, Hiroshi Tezuka, Chihana Toyokawa, Yaxiaer Yalikun, Makoto Yamada, Mai Yamagishi, Takashi Yamano, Atsushi Yasumoto, Yutaka Yatomi, Masayuki Yazawa, Dino Di Carlo, Yoichiroh Hosokawa, Sotaro Uemura, Yasuyuki Ozeki, Keisuke Goda, Intelligent Image-Activated Cell Sorting, Cell, 10.1016/j.cell.2018.08.028, 175, 1, 266-276, 266-276.e13, 2018.09.
||Kou Nakahara, Shinya Sakuma, Manabu Kawahara, Masashi Takahashi, Fumihito Arai, Time-Lapse Mechanical Characterization of Zona Pellucida Using a Cell Carrier Chip, Journal of Microelectromechanical Systems, 10.1109/JMEMS.2018.2818183, 27, 3, 464-471, 2018.06.
||Shinya Sakuma, Yusuke Kasai, Takeshi Hayakawa, Fumihito Arai, On-chip cell sorting by high-speed local-flow control using dual membrane pumps, Lab on a chip, 10.1039/C7LC00536A, 17, 16, 2685-2884, 2017.01.
||Shinya Sakuma, Keisuke Kuroda, Chia-Hung Dylan Tsai, Wataru Fukui, Fumihito Arai, Makoto Kaneko, Red blood cell fatigue evaluation based on the close-encountering point between extensibility and recoverability, Lab on a Chip, 10.1039/C3LC51003D, 14, 1135-1141, 2014.01.
||Shinya Sakuma, Fumihito Arai, Cellular force measurement using a nanometric-probe-integrated microfluidic chip with a displacement reduction mechanism, Journal of Robotics and Mechatronics, 10.20965/jrm.2013.p0277, 25, 2, 277-284, 2013.04.