Intelligent Image-Activated Cell Sorting

Nao Nitta¹, Takeaki Sugimura¹, Akihiro Isozaki², Hideharu Mikami², Kei Hiraki², Shinya Sakuma³, Takanori Iino⁴, Fumihito Arai³, Taichiro Endo⁵, Yasuhiro Fujiwaki⁴, Hideya Fukuzawa⁶, Misa Hase², Takeshi Hayakawa⁷, Kotaro Hiramatsu², Yu Hoshino⁸, Mary Inaba⁹, Takuro Ito¹, Hiroshi Karakawa², Yusuke Kasai³, Kenichi Koizumi⁹, SangWook Lee², Cheng Lei², Ming Li¹⁰, Takanori Maeno¹¹, Satoshi Matsusaka¹², Daichi Murakami⁹, Atsuhiro Nakagawa¹³, Yusuke Oguchi¹⁴, Minoru Oikawa¹⁵, Tadataka Ota², Kiyotaka Shiba¹⁶, Hirofumi Shintaku¹⁷, Yoshitaka Shirasaki¹⁴, Kanako Suga¹⁶, Yuta Suzuki⁴, Nobutake Suzuki¹⁴, Yo Tanaka¹⁸, Hiroshi Tezuka⁹, Chihana Toyokawa⁶, Yaxiaer Yalikun¹⁸, Makoto Yamada¹⁹, Mai Yamagishi¹⁴, Takashi Yamano⁶, Atsushi Yasumoto²⁰, Yutaka Yatomi²⁰, Masayuki Yazawa²¹, Dino Di Carlo²², Yoichiroh Hosokawa²³, Sotaro Uemura¹⁴, Yasuyuki Ozeki⁴, Keisuke Goda²⁴

Affiliations

¹ Department of Chemistry, The University of Tokyo, Tokyo 113-0033, Japan; Japan Science and Technology Agency, Saitama 332-0012, Japan.
² Department of Chemistry, The University of Tokyo, Tokyo 113-0033, Japan.
³ Department of Micro-Nano Mechanical Science and Engineering, Nagoya University, Nagoya 464-8603, Japan.
⁴ Department of Electrical Engineering and Information Systems, The University of Tokyo, Tokyo 113-8656, Japan.
⁵ Center for Advanced Intelligence Project, RIKEN, Tokyo 103-0027, Japan; ExaWizards Inc., Tokyo 105-0013, Japan.
⁶ Graduate School of Biostudies, Kyoto University, Kyoto 606-8502, Japan.
⁷ Department of Precision Mechanics, Chuo University, Tokyo 112-8551, Japan.
⁸ Department of Chemical Engineering, Kyushu University, Fukuoka 819-0395, Japan.
⁹ Department of Creative Informatics, The University of Tokyo, Tokyo 113-0033, Japan.
¹⁰ Department of Bioengineering, University of California, Los Angeles, Los Angeles, CA 90095, USA.
¹¹ Institute of Medical Science, The University of Tokyo, Tokyo 108-8639, Japan.
¹² Department of Gastroenterology, Cancer Institute Hospital, Japanese Foundation for Cancer Research, Tokyo 135-8550, Japan.
¹³ Department of Neurosurgery, Graduate School of Medicine, Tohoku University, Sendai 980-8577, Japan.
¹⁴ Department of Biological Sciences, The University of Tokyo, Tokyo 113-0033, Japan.
¹⁵ Science and Technology Unit, Natural Sciences Cluster, Kochi University, Kochi 780-8520, Japan.
¹⁶ Division of Protein Engineering, Cancer Institute, Japanese Foundation for Cancer Research, Tokyo 135-8550, Japan.
¹⁷ Department of Micro Engineering, Kyoto University, Kyoto 606-8501, Japan.
¹⁸ Center for Biosystems Dynamics Research, RIKEN, Osaka 565-0871, Japan.
¹⁹ Center for Advanced Intelligence Project, RIKEN, Tokyo 103-0027, Japan; Graduate School of Informatics, Kyoto University, Kyoto 606-8501, Japan.
²⁰ Department of Clinical Laboratory Medicine, Graduate School of Medicine, The University of Tokyo, Tokyo 113-0033, Japan.
²¹ Department of Rehabilitation and Regenerative Medicine, Pharmacology, Columbia University, New York, NY 10032, USA.
²² Department of Chemistry, The University of Tokyo, Tokyo 113-0033, Japan; Department of Bioengineering, University of California, Los Angeles, Los Angeles, CA 90095, USA; Department of Mechanical Engineering, University of California, Los Angeles, Los Angeles, CA 90095, USA; California NanoSystems Institute, University of California, Los Angeles, Los Angeles, CA 90095, USA.
²³ Graduate School of Materials Science, Nara Institute of Science and Technology, Ikoma 630-0192, Japan.
²⁴ Department of Chemistry, The University of Tokyo, Tokyo 113-0033, Japan; Japan Science and Technology Agency, Saitama 332-0012, Japan; Department of Electrical Engineering, University of California, Los Angeles, Los Angeles, CA 90095, USA. Electronic address: goda@chem.s.u-tokyo.ac.jp.

PMID: 30166209
DOI: 10.1016/j.cell.2018.08.028

Free article

Intelligent Image-Activated Cell Sorting

Nao Nitta et al. Cell. 2018.

Free article

. 2018 Sep 20;175(1):266-276.e13.

doi: 10.1016/j.cell.2018.08.028. Epub 2018 Aug 27.

Authors

Affiliations

¹ Department of Chemistry, The University of Tokyo, Tokyo 113-0033, Japan; Japan Science and Technology Agency, Saitama 332-0012, Japan.
² Department of Chemistry, The University of Tokyo, Tokyo 113-0033, Japan.
³ Department of Micro-Nano Mechanical Science and Engineering, Nagoya University, Nagoya 464-8603, Japan.
⁴ Department of Electrical Engineering and Information Systems, The University of Tokyo, Tokyo 113-8656, Japan.
⁵ Center for Advanced Intelligence Project, RIKEN, Tokyo 103-0027, Japan; ExaWizards Inc., Tokyo 105-0013, Japan.
⁶ Graduate School of Biostudies, Kyoto University, Kyoto 606-8502, Japan.
⁷ Department of Precision Mechanics, Chuo University, Tokyo 112-8551, Japan.
⁸ Department of Chemical Engineering, Kyushu University, Fukuoka 819-0395, Japan.
⁹ Department of Creative Informatics, The University of Tokyo, Tokyo 113-0033, Japan.
¹⁰ Department of Bioengineering, University of California, Los Angeles, Los Angeles, CA 90095, USA.
¹¹ Institute of Medical Science, The University of Tokyo, Tokyo 108-8639, Japan.
¹² Department of Gastroenterology, Cancer Institute Hospital, Japanese Foundation for Cancer Research, Tokyo 135-8550, Japan.
¹³ Department of Neurosurgery, Graduate School of Medicine, Tohoku University, Sendai 980-8577, Japan.
¹⁴ Department of Biological Sciences, The University of Tokyo, Tokyo 113-0033, Japan.
¹⁵ Science and Technology Unit, Natural Sciences Cluster, Kochi University, Kochi 780-8520, Japan.
¹⁶ Division of Protein Engineering, Cancer Institute, Japanese Foundation for Cancer Research, Tokyo 135-8550, Japan.
¹⁷ Department of Micro Engineering, Kyoto University, Kyoto 606-8501, Japan.
¹⁸ Center for Biosystems Dynamics Research, RIKEN, Osaka 565-0871, Japan.
¹⁹ Center for Advanced Intelligence Project, RIKEN, Tokyo 103-0027, Japan; Graduate School of Informatics, Kyoto University, Kyoto 606-8501, Japan.
²⁰ Department of Clinical Laboratory Medicine, Graduate School of Medicine, The University of Tokyo, Tokyo 113-0033, Japan.
²¹ Department of Rehabilitation and Regenerative Medicine, Pharmacology, Columbia University, New York, NY 10032, USA.
²² Department of Chemistry, The University of Tokyo, Tokyo 113-0033, Japan; Department of Bioengineering, University of California, Los Angeles, Los Angeles, CA 90095, USA; Department of Mechanical Engineering, University of California, Los Angeles, Los Angeles, CA 90095, USA; California NanoSystems Institute, University of California, Los Angeles, Los Angeles, CA 90095, USA.
²³ Graduate School of Materials Science, Nara Institute of Science and Technology, Ikoma 630-0192, Japan.
²⁴ Department of Chemistry, The University of Tokyo, Tokyo 113-0033, Japan; Japan Science and Technology Agency, Saitama 332-0012, Japan; Department of Electrical Engineering, University of California, Los Angeles, Los Angeles, CA 90095, USA. Electronic address: goda@chem.s.u-tokyo.ac.jp.

PMID: 30166209
DOI: 10.1016/j.cell.2018.08.028

Abstract

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.

Keywords: cellular heterogeneity; cellular morphology; convolutional neural network; deep learning; high-throughput microscopy; high-throughput screening; image-activated cell sorting; machine intelligence.

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Smarter cell sorting.
Strack R. Strack R. Nat Methods. 2018 Nov;15(11):859. doi: 10.1038/s41592-018-0198-5. Nat Methods. 2018. PMID: 30377354 No abstract available.

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Intelligent Image-Activated Cell Sorting

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Intelligent Image-Activated Cell Sorting

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