About the project – University of Copenhagen

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The PHOTO.COMM project

PHOTO.COMM aims to establish key factors that underpin stable microalgal communities in

Main focus and participants in the project. Please click the photo for a higher resolution

nature and use these as a template to design synthetic communities with superior robustness and productivity as a primary trait. By designing communities bottom up, we have the opportunity to incorporate strains that deliver the desired end-products, either directly or in combination with multiple metabolic partners.

The PHOTO.COMM research training programme involves four interlinked research work packages (shown in the figure below).



WP-R1 will analyse microalgal communities as used by the industrial partners. The species composition will be determined by a combination of traditional and molecular methods, and the growth and characteristics of the cultures will be characterised in detail using metagenomics approaches.

WP-R2 will characterize the cultures in WP-R1 in detail using metagenomics and apply systems biology methodologies to obtain whole-systems understanding of the factors that influence the robustness and performance of mixed cultures.

WP-R3 will engineer new strains of cyanobacteria and eukaryotic algae, to improve their photosynthetic efficiency, their CO2 fixation rates and their nutrient uptake characteristics. These will then be fed into the work in WP-R1 to generate new synthetic communities, whose performance will be compared with natural cultures. The data will also be fed into the mathematical models in WP-R2 and this iterative process will enable PHOTO.COMM programme to build a knowledge base that offers novel mixed cultures with superior abilities for industrial use.

WP-R4 will involve the rigorous testing of these new, synthetic microalgae communities by the 3 industrial partners. The results will be compared with those from laboratory-scale studies by the academic partners, and these data will be used to further refine the mathematical modelling.