Virtual-freezing fluorescence imaging flow cytometry

Hideharu Mikami; Makoto Kawaguchi; Chun Jung Huang; Hiroki Matsumura; Takeaki Sugimura; Kangrui Huang; Cheng Lei; Shunnosuke Ueno; Taichi Miura; Takuro Ito; Kazumichi Nagasawa; Takanori Maeno; Hiroshi Watarai; Mai Yamagishi; Sotaro Uemura; Shinsuke Ohnuki; Yoshikazu Ohya; Hiromi Kurokawa; Satoshi Matsusaka; Chia Wei Sun; Yasuyuki Ozeki; Keisuke Goda

doi:10.1038/s41467-020-14929-2

Virtual-freezing fluorescence imaging flow cytometry

Hideharu Mikami^*, Makoto Kawaguchi, Chun Jung Huang, Hiroki Matsumura, Takeaki Sugimura, Kangrui Huang, Cheng Lei, Shunnosuke Ueno, Taichi Miura, Takuro Ito, Kazumichi Nagasawa, Takanori Maeno, Hiroshi Watarai, Mai Yamagishi, Sotaro Uemura, Shinsuke Ohnuki, Yoshikazu Ohya, Hiromi Kurokawa, Satoshi Matsusaka, Chia Wei SunYasuyuki Ozeki, Keisuke Goda

^*Corresponding author for this work

Department of Photonics

Research output: Contribution to journal › Article › peer-review

113 Scopus citations

Abstract

By virtue of the combined merits of flow cytometry and fluorescence microscopy, imaging flow cytometry (IFC) has become an established tool for cell analysis in diverse biomedical fields such as cancer biology, microbiology, immunology, hematology, and stem cell biology. However, the performance and utility of IFC are severely limited by the fundamental trade-off between throughput, sensitivity, and spatial resolution. Here we present an optomechanical imaging method that overcomes the trade-off by virtually freezing the motion of flowing cells on the image sensor to effectively achieve 1000 times longer exposure time for microscopy-grade fluorescence image acquisition. Consequently, it enables high-throughput IFC of single cells at >10,000 cells s⁻¹ without sacrificing sensitivity and spatial resolution. The availability of numerous information-rich fluorescence cell images allows high-dimensional statistical analysis and accurate classification with deep learning, as evidenced by our demonstration of unique applications in hematology and microbiology.

Original language	English
Article number	1162
Journal	Nature Communications
Volume	11
Issue number	1
DOIs	https://doi.org/10.1038/s41467-020-14929-2
State	Published - 2020

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Mikami, H., Kawaguchi, M., Huang, C. J., Matsumura, H., Sugimura, T., Huang, K., Lei, C., Ueno, S., Miura, T., Ito, T., Nagasawa, K., Maeno, T., Watarai, H., Yamagishi, M., Uemura, S., Ohnuki, S., Ohya, Y., Kurokawa, H., Matsusaka, S., ... Goda, K. (2020). Virtual-freezing fluorescence imaging flow cytometry. Nature Communications, 11(1), Article 1162. https://doi.org/10.1038/s41467-020-14929-2

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title = "Virtual-freezing fluorescence imaging flow cytometry",

abstract = "By virtue of the combined merits of flow cytometry and fluorescence microscopy, imaging flow cytometry (IFC) has become an established tool for cell analysis in diverse biomedical fields such as cancer biology, microbiology, immunology, hematology, and stem cell biology. However, the performance and utility of IFC are severely limited by the fundamental trade-off between throughput, sensitivity, and spatial resolution. Here we present an optomechanical imaging method that overcomes the trade-off by virtually freezing the motion of flowing cells on the image sensor to effectively achieve 1000 times longer exposure time for microscopy-grade fluorescence image acquisition. Consequently, it enables high-throughput IFC of single cells at >10,000 cells s−1 without sacrificing sensitivity and spatial resolution. The availability of numerous information-rich fluorescence cell images allows high-dimensional statistical analysis and accurate classification with deep learning, as evidenced by our demonstration of unique applications in hematology and microbiology.",

author = "Hideharu Mikami and Makoto Kawaguchi and Huang, {Chun Jung} and Hiroki Matsumura and Takeaki Sugimura and Kangrui Huang and Cheng Lei and Shunnosuke Ueno and Taichi Miura and Takuro Ito and Kazumichi Nagasawa and Takanori Maeno and Hiroshi Watarai and Mai Yamagishi and Sotaro Uemura and Shinsuke Ohnuki and Yoshikazu Ohya and Hiromi Kurokawa and Satoshi Matsusaka and Sun, {Chia Wei} and Yasuyuki Ozeki and Keisuke Goda",

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Mikami, H, Kawaguchi, M, Huang, CJ, Matsumura, H, Sugimura, T, Huang, K, Lei, C, Ueno, S, Miura, T, Ito, T, Nagasawa, K, Maeno, T, Watarai, H, Yamagishi, M, Uemura, S, Ohnuki, S, Ohya, Y, Kurokawa, H, Matsusaka, S, Sun, CW, Ozeki, Y & Goda, K 2020, 'Virtual-freezing fluorescence imaging flow cytometry', Nature Communications, vol. 11, no. 1, 1162. https://doi.org/10.1038/s41467-020-14929-2

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AU - Mikami, Hideharu

AU - Kawaguchi, Makoto

AU - Huang, Chun Jung

AU - Matsumura, Hiroki

AU - Sugimura, Takeaki

AU - Huang, Kangrui

AU - Lei, Cheng

AU - Ueno, Shunnosuke

AU - Miura, Taichi

AU - Ito, Takuro

AU - Nagasawa, Kazumichi

AU - Maeno, Takanori

AU - Watarai, Hiroshi

AU - Yamagishi, Mai

AU - Uemura, Sotaro

AU - Ohnuki, Shinsuke

AU - Ohya, Yoshikazu

AU - Kurokawa, Hiromi

AU - Matsusaka, Satoshi

AU - Sun, Chia Wei

AU - Ozeki, Yasuyuki

AU - Goda, Keisuke

PY - 2020

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AB - By virtue of the combined merits of flow cytometry and fluorescence microscopy, imaging flow cytometry (IFC) has become an established tool for cell analysis in diverse biomedical fields such as cancer biology, microbiology, immunology, hematology, and stem cell biology. However, the performance and utility of IFC are severely limited by the fundamental trade-off between throughput, sensitivity, and spatial resolution. Here we present an optomechanical imaging method that overcomes the trade-off by virtually freezing the motion of flowing cells on the image sensor to effectively achieve 1000 times longer exposure time for microscopy-grade fluorescence image acquisition. Consequently, it enables high-throughput IFC of single cells at >10,000 cells s−1 without sacrificing sensitivity and spatial resolution. The availability of numerous information-rich fluorescence cell images allows high-dimensional statistical analysis and accurate classification with deep learning, as evidenced by our demonstration of unique applications in hematology and microbiology.

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Virtual-freezing fluorescence imaging flow cytometry

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