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利用荧光辅助光流体时间拉伸显微镜对纤细裸藻进行高通量精确单细胞筛选

High-Throughput Accurate Single-Cell Screening of Euglena gracilis with Fluorescence-Assisted Optofluidic Time-Stretch Microscopy.

作者信息

Guo Baoshan, Lei Cheng, Ito Takuro, Jiang Yiyue, Ozeki Yasuyuki, Goda Keisuke

机构信息

Department of Chemistry, University of Tokyo, Tokyo 113-0033, Japan.

Department of Electronic Engineering, Tsinghua University, Beijing 100084, China.

出版信息

PLoS One. 2016 Nov 15;11(11):e0166214. doi: 10.1371/journal.pone.0166214. eCollection 2016.

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, 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 high-throughput, high-accuracy, single-cell screening of E. gracilis with fluorescence-assisted optofluidic time-stretch microscopy-a method that combines the strengths of microfluidic cell focusing, optical time-stretch microscopy, and fluorescence detection used in conventional flow cytometry. Specifically, our fluorescence-assisted optofluidic time-stretch microscope consists of an optical time-stretch microscope and a fluorescence analyzer on top of a hydrodynamically focusing microfluidic device and can detect fluorescence from every E. gracilis cell in a population and simultaneously obtain its image with 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 holds promise for evaluating cultivation techniques and selective breeding for microalgae-based biofuel production.

摘要

开发可靠、可持续且经济的替代燃料来源是一项对全球而言重要但具有挑战性的目标。作为液体化石燃料的替代品,藻类生物燃料有望在缓解全球变暖方面发挥关键作用,因为藻类通过光合作用吸收大气中的二氧化碳。在用于燃料生产的各种藻类中,纤细裸藻是一种有吸引力的微藻物种,因为已知它会在脂质滴内产生蜡酯(对生物柴油和航空燃料有益)。迄今为止,虽然存在许多诱导微藻细胞高效产生和积累脂质的技术,但很少有分析方法可用于同时以高通量、高精度和单细胞分辨率表征包括纤细裸藻在内的此类脂质积累微藻群体。在此,我们展示了利用荧光辅助光流体时间拉伸显微镜对纤细裸藻进行高通量、高精度、单细胞筛选——该方法结合了微流体细胞聚焦、光学时间拉伸显微镜以及传统流式细胞术中使用的荧光检测的优势。具体而言,我们的荧光辅助光流体时间拉伸显微镜由一台光学时间拉伸显微镜和一台荧光分析仪组成,位于流体动力学聚焦微流体装置之上,能够检测群体中每个纤细裸藻细胞的荧光,并同时以每秒10000个细胞的高通量获取其图像。利用该系统获取的多维信息,我们对氮充足(正常)和氮缺乏(脂质积累)的纤细裸藻细胞进行分类,假阳性率低至1.0%。这种方法有望用于评估基于微藻的生物燃料生产的培养技术和选择性育种。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a81e/5112898/3bc3d4015fad/pone.0166214.g001.jpg

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