(4ct) Algal Derived Biofuels: A Systems Biology Approach to Increasing TAG Accumulation in C. Reinhardtii

Although algal derived biofuels have recently gained widespread attention for their potential as a source of renewable energy, the idea is not new. The aquatic species program (ASP), a federally funded program in the eighties, was charged with determining the feasibility of producing biodiesel from high-lipid accumulating algae (1). One unfortunate conclusion drawn from the program was that Chlamydomonas reinhardtii, a reference green algal species, was not capable of accumulating high levels of lipids and was therefore excluded from further study. While this conclusion may have been true for normal growth conditions, it has recently been shown that C. reinhardtii does accumulate lipids under certain nutrient limitations, such as nitrogen (2-4), sulfur (5), and phosphorous (2). The response to these nutrient limitations in C. reinhardtii is an increase in storage product accumulation, both starch and triacylglycerols (TAGs), but the exact distribution of carbon fluxes and the regulatory control behind the switch from balanced growth to accumulation of storage products is not yet known. Understanding how and why C. reinhardtii directs its carbon away from biomass production toward carbon storage may provide useful information on how to engineer the cell to accumulate higher amounts of lipids during normal growth and provide insights into the metabolism of other green algae.

Two approaches were taken to gain further insight into the control of carbon partitioning in C. reinhardtii. First, a large scale metabolic reconstruction was performed in order to formulate a flux balance analysis model (6), which is capable of predicting intracellular fluxes using linear programming. This model was then used to predict the effect of nitrogen deprivation on the intracellular fluxes of C. reinhardtii and how these predictions match reported lipid contents (3, 4). Temporal transcriptome analysis was also performed on nitrogen starved cells using RNAseq to eluciadate both transcription factors and potential gene targets to increase TAG yields and the results will be presented.

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6. N. R. Boyle, J. A. Morgan, BMC Systems Biology 3, 4 (2009).