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Proceedings Paper

High-throughput label-free screening of euglena gracilis with optofluidic time-stretch quantitative phase microscopy
Author(s): Baoshan Guo; Cheng Lei; Takuro Ito; Yalikun Yaxiaer; Hirofumi Kobayashi; Yiyue Jiang; Yo Tanaka; Yasuyuki Ozeki; Keisuke Goda
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Paper Abstract

The development of reliable, sustainable, and economical sources of alternative fuels is an important, but challenging goal for the world. As an alternative to liquid fossil fuels, microalgal biofuel is expected to play a key role in reducing the detrimental effects of global warming since microalgae absorb atmospheric CO2 via photosynthesis. Unfortunately, conventional analytical methods only provide population-averaged lipid contents and fail to characterize a diverse population of microalgal cells with single-cell resolution in a noninvasive and interference-free manner. Here we demonstrate high-throughput label-free single-cell screening of lipid-producing microalgal cells with optofluidic time-stretch quantitative phase microscopy. In particular, we use Euglena gracilis – an attractive microalgal species that produces wax esters (suitable for biodiesel and aviation fuel after refinement) within lipid droplets. Our optofluidic time-stretch quantitative phase microscope is based on an integration of a hydrodynamic-focusing microfluidic chip, an optical time-stretch phase-contrast microscope, and a digital image processor equipped with machine learning. As a result, it provides both the opacity and phase contents of every single cell at a high throughput of 10,000 cells/s. We characterize heterogeneous populations of E. gracilis cells under two different culture conditions to evaluate their lipid production efficiency. Our method holds promise as an effective analytical tool for microalgaebased biofuel production.

Paper Details

Date Published: 22 February 2017
PDF: 12 pages
Proc. SPIE 10076, High-Speed Biomedical Imaging and Spectroscopy: Toward Big Data Instrumentation and Management II, 100760M (22 February 2017); doi: 10.1117/12.2251157
Show Author Affiliations
Baoshan Guo, The Univ. of Tokyo (Japan)
Cheng Lei, The Univ. of Tokyo (Japan)
Tsinghua Univ. (China)
Takuro Ito, Japan Science and Technology Agency (Japan)
Yalikun Yaxiaer, RIKEN (Japan)
Hirofumi Kobayashi, The Univ. of Tokyo (Japan)
Yiyue Jiang, The Univ. of Tokyo (Japan)
Yo Tanaka, RIKEN (Japan)
Yasuyuki Ozeki, The Univ. of Tokyo (Japan)
Keisuke Goda, The Univ. of Tokyo (Japan)
Japan Science and Technology Agency (Japan)
Univ. of California, Los Angeles (United States)


Published in SPIE Proceedings Vol. 10076:
High-Speed Biomedical Imaging and Spectroscopy: Toward Big Data Instrumentation and Management II
Kevin K. Tsia; Keisuke Goda, Editor(s)

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