Quantitative live-cell imaging of secretion activity reveals dynamic immune responses
Mai Yamagishi,
Kaede Miyata,
Takashi Kamatani,
Hiroki Kabata,
Rie Baba,
Yumiko Tanaka,
Nobutake Suzuki,
Masako Matsusaka,
Yasutaka Motomura,
Tsuyoshi Kiniwa,
Satoshi Koga,
Keisuke Goda,
Osamu Ohara,
Takashi Funatsu,
Koichi Fukunaga,
Kazuyo Moro,
Sotaro Uemura,
Yoshitaka Shirasaki
Affiliations
Mai Yamagishi
Graduate School of Pharmaceutical Sciences, The University of Tokyo, Tokyo 113-0033, Japan; Department of Biological Sciences, Graduate School of Science, The University of Tokyo, Tokyo 113-0033, Japan; Live Cell Diagnosis, Ltd., Saitama 351-0022, Japan
Kaede Miyata
Department of Biological Sciences, Graduate School of Science, The University of Tokyo, Tokyo 113-0033, Japan
Takashi Kamatani
Department of Biological Sciences, Graduate School of Science, The University of Tokyo, Tokyo 113-0033, Japan; Division of Pulmonary Medicine, Department of Medicine, Keio University School of Medicine, Tokyo 160-8582, Japan; Department of AI Technology Development, M&D Data Science Center, Tokyo Medical and Dental University, Tokyo 113-8519, Japan; Division of Precision Cancer Medicine, Tokyo Medical and Dental University, Tokyo 113-8519, Japan
Hiroki Kabata
Division of Pulmonary Medicine, Department of Medicine, Keio University School of Medicine, Tokyo 160-8582, Japan
Rie Baba
Division of Pulmonary Medicine, Department of Medicine, Keio University School of Medicine, Tokyo 160-8582, Japan
Yumiko Tanaka
Department of Biological Sciences, Graduate School of Science, The University of Tokyo, Tokyo 113-0033, Japan
Nobutake Suzuki
Graduate School of Pharmaceutical Sciences, The University of Tokyo, Tokyo 113-0033, Japan; Department of Biological Sciences, Graduate School of Science, The University of Tokyo, Tokyo 113-0033, Japan
Masako Matsusaka
Division of Pulmonary Medicine, Department of Medicine, Keio University School of Medicine, Tokyo 160-8582, Japan
Yasutaka Motomura
Department of Microbiology and Immunology, Graduate School of Medicine, Osaka University, Suita, Osaka 565-0871, Japan
Tsuyoshi Kiniwa
RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa 230-0045, Japan
Satoshi Koga
RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa 230-0045, Japan
Keisuke Goda
Department of Chemistry, Graduate School of Science, The University of Tokyo, Tokyo 113-0033, Japan; Department of Bioengineering, University of California, Los Angeles, Los Angeles, CA 90095, USA; Institute of Technological Sciences, Wuhan University, Hubei 430072, China
Osamu Ohara
KAZUSA DNA Research Institute, Kisarazu, Chiba 292-0818, Japan
Takashi Funatsu
Graduate School of Pharmaceutical Sciences, The University of Tokyo, Tokyo 113-0033, Japan
Koichi Fukunaga
Division of Pulmonary Medicine, Department of Medicine, Keio University School of Medicine, Tokyo 160-8582, Japan
Kazuyo Moro
Department of Microbiology and Immunology, Graduate School of Medicine, Osaka University, Suita, Osaka 565-0871, Japan; RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa 230-0045, Japan; Corresponding author
Sotaro Uemura
Department of Biological Sciences, Graduate School of Science, The University of Tokyo, Tokyo 113-0033, Japan; Corresponding author
Yoshitaka Shirasaki
Graduate School of Pharmaceutical Sciences, The University of Tokyo, Tokyo 113-0033, Japan; Department of Biological Sciences, Graduate School of Science, The University of Tokyo, Tokyo 113-0033, Japan; Corresponding author
Summary: Quantification of cytokine secretion has facilitated advances in the field of immunology, yet the dynamic and varied secretion profiles of individual cells, particularly those obtained from limited human samples, remain obscure. Herein, we introduce a technology for quantitative live-cell imaging of secretion activity (qLCI-S) that enables high-throughput and dual-color monitoring of secretion activity at the single-cell level over several days, followed by transcriptome analysis of individual cells based on their phenotype. The efficacy of qLCI-S was demonstrated by visualizing the characteristic temporal pattern of cytokine secretion of group 2 innate lymphoid cells, which constitute less than 0.01% of human peripheral blood mononuclear cells, and by revealing minor subpopulations with enhanced cytokine production. The underlying mechanism of this feature was linked to the gene expression of stimuli receptors. This technology paves the way for exploring gene expression signatures linked to the spatiotemporal dynamic nature of various secretory functions.
