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

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

Author information

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

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