Abstract
Microalgae such as Euglena gracilis (E. gracilis) are capable of energy-rich lipid production, and have been shown to be a promising source of biofuel. Identifying and selecting E. gracilis strains with higher lipid production per biomass at a single cell level can increase the organism's value for biofuel generation. We propose a high-throughput method to identify E. gracilis cells with varied levels of lipid yield via fluorescence imaging flow cytometry based on radiofrequency-tagged emission (FIRE). By utilizing this imaging method and image post-processing techniques, we are able to extract useful information, such as individual shape metrics, and lipid production per cell.
Original language | English |
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Title of host publication | 20th International Conference on Miniaturized Systems for Chemistry and Life Sciences (MicroTAS 2016) |
Place of Publication | San Diego, California |
Publisher | Chemical and Biological Microsystems Society |
Pages | 307-308 |
Number of pages | 2 |
ISBN (Print) | 9781510834163 |
Publication status | Published - 2016 |
Externally published | Yes |
Event | 20th International Conference on Miniaturized Systems for Chemistry and Life Sciences, MicroTAS 2016 - Dublin, Ireland Duration: 9 Oct 2016 → 13 Oct 2016 |
Conference
Conference | 20th International Conference on Miniaturized Systems for Chemistry and Life Sciences, MicroTAS 2016 |
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Country/Territory | Ireland |
City | Dublin |
Period | 9/10/16 → 13/10/16 |
Keywords
- Biofuel
- Image processing
- Microalgae
- Fluorescence imaging flow cytometry