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Proceedings Paper

High-throughput optofluidic profiling of Euglena gracilis with morphological and chemical specificity
Author(s): Baoshan Guo; Cheng Lei; Takuro Ito; Yiyue Jiang; Yasuyuki Ozeki; Keisuke Goda
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Paper Abstract

The world is faced with environmental problems and the energy crisis due to the combustion and depletion of fossil fuels. 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, algal biofuel is expected to play a key role in alleviating global warming since algae absorb atmospheric CO2 via photosynthesis. Among various algae for fuel production, Euglena gracilis is an attractive microalgal species as it is known to produce wax ester (good for biodiesel and aviation fuel) within lipid droplets. To date, while there exist many techniques for inducing microalgal cells to produce and accumulate lipid with high efficiency, few analytical methods are available for characterizing a population of such lipid-accumulated microalgae including E. gracilis with high throughout, high accuracy, and single-cell resolution simultaneously. Here we demonstrate a high-throughput optofluidic Euglena gracilis profiler which consists of an optical time-stretch microscope and a fluorescence analyzer on top of an inertial-focusing microfluidic device that can detect fluorescence from lipid droplets in their cell body and provide images of E. gracilis cells simultaneously at a high throughput of 10,000 cells/s. With the multi-dimensional information acquired by the system, we classify nitrogen-sufficient (ordinary) and nitrogen-deficient (lipid-accumulated) E. gracilis cells with a low false positive rate of 1.0%. This method provides a promise for evaluating the efficiency of lipid-inducing techniques for biofuel production, which is also applicable for identifying biomedical samples such as blood cells and cancer cells.

Paper Details

Date Published: 4 November 2016
PDF: 10 pages
Proc. SPIE 10026, Real-time Photonic Measurements, Data Management, and Processing II, 100260L (4 November 2016); doi: 10.1117/12.2245836
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)
Yiyue Jiang, The Univ. of Tokyo (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. 10026:
Real-time Photonic Measurements, Data Management, and Processing II
Ming Li; Bahram Jalali; Keisuke Goda; Kevin K. Tsia, Editor(s)

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