Evaluation of phenotype stability and ecological risk of a genetically engineered alga in open pond production

Genetically engineered (GE) algae offer the promise of producing food, fuel, and other valuable products with reduced requirements for land and fresh water. While the gains in productivity measured in GE terrestrial crops are predicted to be mirrored in GE algae, the stability of phenotypes and ecological risks posed by GE algae in large-scale outdoor cultivation remain unknown. Here, we describe the first US Environmental Protection Agency (EPA)-sanctioned experiment aimed at understanding how GE algae perform in outdoor cultivation. Acutodesmus dimorphus was genetically engineered by the addition of two genes, one for enhanced fatty acid biosynthesis, and one for recombinant green fluorescence protein (GFP) expression; both the genes and their associated phenotypes were maintained during fifty days of outdoor cultivation. We also observed that while the GE algae dispersed from the cultivation ponds, colonization of the trap ponds by the GE strain declined rapidly with increasing distance from the source cultivation ponds. In contrast, many species of indigenous algae were found in every trap pond within a few days of starting the experiment. When inoculated in water from five local lakes, the GE algae's effect on biodiversity, species composition, and biomass of native algae was indiscernible from those of the wild-type (wt) progenitor algae, and neither the GE nor wt algae were able to outcompete native strains. We conclude that GE algae can be successfully cultivated outdoors while maintaining GE traits, and that for the specific GE algal strain tested here they did not outcompete or adversely impact native algae populations when grown in water taken from local lakes. This study provides an initial evaluation of GE algae in outdoor cultivation and a framework to evaluate GE algae risks associated with outdoor GE algae production

Transcriptional program for nitrogen starvation-induced lipid accumulation in Chlamydomonas reinhardtii.

BackgroundAlgae accumulate lipids to endure different kinds of environmental stresses including macronutrient starvation. Although this response has been extensively studied, an in depth understanding of the transcriptional regulatory network (TRN) that controls the transition into lipid accumulation remains elusive. In this study, we used a systems biology approach to elucidate the transcriptional program that coordinates the nitrogen starvation-induced metabolic readjustments that drive lipid accumulation in Chlamydomonas reinhardtii.ResultsWe demonstrate that nitrogen starvation triggered differential regulation of 2147 transcripts, which were co-regulated in 215 distinct modules and temporally ordered as 31 transcriptional waves. An early-stage response was triggered within 12 min that initiated growth arrest through activation of key signaling pathways, while simultaneously preparing the intracellular environment for later stages by modulating transport processes and ubiquitin-mediated protein degradation. Subsequently, central metabolism and carbon fixation were remodeled to trigger the accumulation of triacylglycerols. Further analysis revealed that these waves of genome-wide transcriptional events were coordinated by a regulatory program orchestrated by at least 17 transcriptional regulators, many of which had not been previously implicated in this process. We demonstrate that the TRN coordinates transcriptional downregulation of 57 metabolic enzymes across a period of nearly 4 h to drive an increase in lipid content per unit biomass. Notably, this TRN appears to also drive lipid accumulation during sulfur starvation, while phosphorus starvation induces a different regulatory program. The TRN model described here is available as a community-wide web-resource at http://networks.systemsbiology.net/chlamy-portal.ConclusionsIn this work, we have uncovered a comprehensive mechanistic model of the TRN controlling the transition from N starvation to lipid accumulation. The program coordinates sequentially ordered transcriptional waves that simultaneously arrest growth and lead to lipid accumulation. This study has generated predictive tools that will aid in devising strategies for the rational manipulation of regulatory and metabolic networks for better biofuel and biomass production