INSPIRE: Unraveling Factors that Determine Fast Growth of a Photoautotroph

This INSPIRE award is partially funded by the Systems and Synthetic Biology program in the Division of Molecular and Cellular Biosciences in the Directorate for Biological Sciences; the Biotechnology and Biochemical Engineering program and the Environmental Engineering program in the Division of Chemical, Bioengineering, Environmental, and Transport Systems in the Directorate for Engineering; the Office of Integrated Activities, and the Office of International Science & Engineering. This award is aimed at generating systems level insights into the processes and dynamics that influence growth in model photosynthetic organisms. As such, this project has important implications for fundamental understanding of a complex and essential biological process, and has significant implications for biotechnology applications. Photosynthesis is the engine of life on our planet, and organisms that live off of photosynthesis, such as cyanobacteria, algae, and plants, are primarily responsible for carbon sequestration in the biosphere. On the planet today, such oxygen-producing photosynthetic organisms assimilate 100 petagrams (100 gigatons) of carbon per year. In contrast, organisms that need chemical nutrients as sources of energy assimilate only 0.3 petagrams (0.3 gigatons) per year. This INSPIRE project is aimed at unraveling the most important factors that control growth rates of cyanobacteria, a model photosynthetic organism. It brings together two different fields, cyanobacteria physiology and mathematical modeling, to abstract fundamental rules of growth parameters and dynamics. It will help design tool kits for engineering cyanobacteria and other photosynthetic microorganisms to enable increased biomass production, an essential requirement for biotechnology applications for sunlight driven carbon-neutral production of food, feed and fuel. The project will also provide training for international undergraduates and engage students under the iGEM training program.

The team of researchers identified recently a unicellular cyanobacterium, Synechococcus elongatus strain, UTEX 2973, with the fastest growth rate among all cyanobacterial strains studied to date. Surprisingly, this strain is a close relative of Synechococcus elongatus PCC 7942, a well-studied model cyanobacterial strain. The two share greater than 99% genome sequence identity. However, the growth potential of Synechococcus 2973 is nearly three-fold better than Synechococcus 7942. The investigators will determine the key factors that are responsible for fast growth of cyanobacteria by applying experimental molecular approaches to compare Synechococcus 7942 with Synechococcus 2973, using adaptive evolution, and developing metabolic and expression (ME) models. They will compare the transcriptome of the two strains under different light intensities, CO2 levels and growth phases. The integrating of ME models for Synechococcus 2973 and Synechococcus 7942 with the transcriptomic data generated are expected to uncover metabolic and expression differences that contribute to the increased biomass production of Synechococcus 2973. The photosynthetic and carbon fixation efficiencies will also be measured to better elucidate mechanistic differences between these strains. In addition, a subset of mutations identified by genome comparison will be analyzed in an effort to recapitulate the fast-growth phenotype.