High-throughput label-free image cytometry and image-based classification of live Euglena gracilis

Cheng Lei; Takuro Ito; Masashi Ugawa; Taisuke Nozawa; Osamu Iwata; Masanori Maki; Genki Okada; Hirofumi Kobayashi; Xinlei Sun; Pimsiri Tiamsak; Norimichi Tsumura; Kengo Suzuki; Dino Di Carlo; Yasuyuki Ozeki; Keisuke Goda

doi:10.1364/BOE.7.002703

High-throughput label-free image cytometry and image-based classification of live Euglena gracilis

Biomed Opt Express. 2016 Jun 20;7(7):2703-8. doi: 10.1364/BOE.7.002703. eCollection 2016 Jul 1.

Authors

Cheng Lei¹, Takuro Ito², Masashi Ugawa³, Taisuke Nozawa³, Osamu Iwata⁴, Masanori Maki⁵, Genki Okada⁵, Hirofumi Kobayashi³, Xinlei Sun⁶, Pimsiri Tiamsak⁷, Norimichi Tsumura⁵, Kengo Suzuki⁴, Dino Di Carlo⁸, Yasuyuki Ozeki⁹, Keisuke Goda¹⁰

Affiliations

¹ Department of Chemistry, University of Tokyo, Tokyo, Japan; Department of Electronic Engineering, Tsinghua University, Beijing, China; leicheng@chem.s.u-tokyo.ac.jp.
² Institute for Advanced Biosciences, Keio University, Tsuruoka, Japan; Systems Biology Program, Graduate School of Media and Governance, Keio University, Fujisawa, Japan.
³ Department of Chemistry, University of Tokyo, Tokyo, Japan.
⁴ euglena Co. Ltd., Tokyo, Japan.
⁵ Graduate School of Advanced Integration Science, Chiba University, Chiba, Japan.
⁶ Department of Chemistry, University of Tokyo, Tokyo, Japan; Department of Mechanical Engineering, Tsinghua University, Beijing, China.
⁷ Department of Chemistry, University of Tokyo, Tokyo, Japan; Department of Medicine, Thammasat University, Bangkok, Thailand.
⁸ Department of Bioengineering, University of California, Los Angeles, USA; California NanoSystems Institute, University of California, Los Angeles, USA; Jonsson Comprehensive Cancer Center, University of California, Los Angeles, USA.
⁹ Department of Electrical Engineering and Information Systems, University of Tokyo, Tokyo, Japan.
¹⁰ Department of Chemistry, University of Tokyo, Tokyo, Japan; Department of Electrical Engineering, University of California, Los Angeles, USA; Japan Science and Technology Agency, Tokyo, Japan; goda@chem.s.u-tokyo.ac.jp.

Abstract

We demonstrate high-throughput label-free single-cell image cytometry and image-based classification of Euglena gracilis (a microalgal species) under different culture conditions. We perform it with our high-throughput optofluidic image cytometer composed of a time-stretch microscope with 780-nm resolution and 75-Hz line rate, and an inertial-focusing microfluidic device. By analyzing a large number of single-cell images from the image cytometer, we identify differences in morphological and intracellular phenotypes between E. gracilis cell groups and statistically classify them under various culture conditions including nitrogen deficiency for lipid induction. Our method holds promise for real-time evaluation of culture techniques for E. gracilis and possibly other microalgae in a non-invasive manner.

Keywords: (100.0100) Image processing; (110.0180) Microscopy; (120.0120) Instrumentation, measurement, and metrology.