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Real-time non-invasive characterization and selection of oil-producing microalgae at the single-cell level (Fuel making algae)
Date du début: 1 avr. 2010, Date de fin: 31 mars 2013 PROJET  TERMINÉ 

In this proposal we will pursue two main research topics geared towards an efficient preparation of new production-optimized algae cultures in a photobioreactor: - Characterization of the physiological state of individual microalgal cells - the characterization of the nutrient status of microalgae for rapid monitoring of nutrient dynamics and metabolism of algae on the single-cell level (in-vivo, and in real-time) within the photobioreactor The determination of the quantitative information on the degree of unsaturation of the bio-oil of individual microalgal cells. - Identifying and optimizing microalgal species for biofuel production - algae production (optimization of the growth process, cell density, and lipid contents) for selected species and selection of the cells according to the metabolic parameters for cultivation in the photobioreactor. This will lead to the identification and selection of the best possible algal strains - „superior“ algae - for the mass production of commercial biofuel. In order to achieve the above goals, we will exploit an experimental technique based on the combination of optical micromanipulation with Raman microspectroscopy – so-called Raman tweezers. The analyzed cells will be spatially confined in suspension using an optical trap and, simultaneously, their chemical composition corresponding to the cell metabolic state will be studied using the Raman spectroscopy. The studied cells will be sorted according to their metabolic state using microfluidic systems in order to elucidate fundamental questions about intercellular variability and what governs it. Moreover, knowing the metabolic response on a single cell level can significantly contribute to the study and use of microalgae in systems biology and biofuel technology. Raman spectroscopy is capable to measure nutrient dynamics and metabolism in vivo, in real-time, and label free making it possible to monitor/evaluate population variability within the photobioreactor.

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