MIM: Deciphering and Optimizing Cross-Domain Interactions to Increase Productivity in High pH-High Alkalinity Microalgae Communities

Microalgae are responsible for more than half of the carbon dioxide fixation worldwide and often have greater photosynthetic efficiencies than terrestrial plants. Microalgae can use this fixed carbon to produce compounds like lipids that have value as an alternative to crude oil for biofuel and chemical production. Furthermore, microalgae can be cultivated on marginal lands using waste water; thus, they their commercial cultivation does not compete directly with existing food and feed crops.

A major challenge for the large-scale cultivation of microalgae is the lack of understanding about how microbial communities affect algae growth. This interdisciplinary research and training project will use microbiology and molecular biology approaches, combined with engineering and computer modeling approaches, to bridge gaps in the understanding of algal microbiome interactions to achieve maximum productivity and culture stability.

The research approaches and results will be transferrable to other natural and industrial systems relevant to society such as wastewater treatment, nutrient cycling, and nutraceutical production. Broader societal outcomes will include improved algal cultivation strategies, the training of graduate and undergraduate students with an emphasis on integrating students from tribal colleges in Montana, and the development of educational outreach modules for K-12 classrooms.

This research project will focus on understanding and ultimately controlling the microbiome of highly productive, high pH/high alkalinity algal cultures for stable and robust primary productivity. Physical and metabolic interactions will be identified and quantified in the algae’s natural habitat and in enrichment cultures. Mathematical models of organismal and community metabolisms will be developed and used to predict possible improvements in the microbiome and in interspecies interactions.

These predictions will be tested using well-defined experiments including next generation sequencing and physiology studies enabling observation of carbon and nitrogen exchange at both the culture and single-cell levels. Iterative refinement of modeling and experiments will lead to an in-depth understanding and ultimately optimization of community productivity, robustness, and stability.

On a broader, ecological level, this work will decipher interactions of organisms in high pH, high alkalinity environments, which are among the most productive ecosystems in the world. The results and approaches to be developed will be readily transferrable to other phototrophic-driven environments as well as to other multi-domain microbial communities such as fungal-bacterial co-cultures.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.