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Saccharomyces cerevisiae, a well-known industrial yeast for alcoholic fermentation, is not historically known to accumulate lipids. Four S. cerevisiae strains used in industrial applications were screened for their ability to accumulate neutral lipids. Only one, D5A, was found to accumulate up to 20% dry cell weight (dcw) lipids. This strain was further engineered by knocking out ADP-activated serine/threonine kinase (SNF1) which increased lipid accumulation to 35% dcw lipids. In addition, we engineered D5A to utilize xylose and found that D5A accumulates up to 37% dcw lipids from xylose as the sole carbon source. Further we over-expressed different diacylglycerol acyltransferase (DGA1) genes and boosted lipid accumulation to 50%. Fatty acid speciation showed that 94% of the extracted lipids consisted of 5 fatty acid species, C16:0 (palmitic), C16:1n7 (palmitoleic), C18:0 (stearic), C18:1n7 (vaccenic), and C18:1n9 (oleic), while the relative distributions changed depending on growth conditions. In addition, this strain accumulated lipids concurrently with ethanol production.

The green microalga Chlorella vulgaris has been widely recognized as a promising candidate for biofuel production due to its ability to store high lipid content and its natural metabolic versatility. Compartmentalized genome-scale metabolic models constructed from genome sequences enable quantitative insight into the transport and metabolism of compounds within a target organism. These metabolic models have long been utilized to generate optimized design strategies for an improved production process. Here, we describe the reconstruction, validation, and application of a genome-scale metabolic model for C. vulgaris UTEX 395, iCZ843. The reconstruction represents the most comprehensive model for any eukaryotic photosynthetic organism to date, based on the genome size and number of genes in the reconstruction. The highly curated model accurately predicts phenotypes under photoautotrophic, heterotrophic, and mixotrophic conditions. The model was validated against experimental data and lays the foundation for model-driven strain design and medium alteration to improve yield. Calculated flux distributions under different trophic conditions show that a number of key pathways are affected by nitrogen starvation conditions, including central carbon metabolism and amino acid, nucleotide, and pigment biosynthetic pathways. Furthermore, model prediction of growth rates under various medium compositions and subsequent experimental validation showed an increased growth rate with the addition of tryptophan and methionine.

AbstractNational scale agronomic projections are an important input for assessing potential benefits of algae cultivation on the future of innovative agriculture. The Algae Testbed Public-Private Partnership was established with the goal of investigating open pond algae cultivation across different geographic, climatic, seasonal, and operational conditions while setting the benchmark for quality data collection, analysis, and dissemination. Identical algae cultivation systems and data analysis methodologies were established at testbed sites across the continental United States and Hawaii. Within this framework, the Unified Field Studies were designed for algae cultivation during all 4 seasons across the testbed network. With increasingly diverse algae research and development, and field deployment strategies, the challenges associated with data collection, quality, and dissemination increase dramatically. The dataset presented here is the complete, curated, climatic, cultivation, harvest, and biomass composition data for each season at each site. These data enable others to do in-depth cultivation, harvest, techno-economic, life cycle, resource, and predictive growth modelling analysis, as well as development of crop protection strategies throughout the algae cultivation industry.

High-protein algae bioproduct system boundaries for environmental sustainability risk analysis.

An effective method for the production of fuels and chemicals from microalgae is to ferment the carbohydrate fraction, extract the lipids and convert the resulting solids through hydrothermal liquefaction (HTL).

ATP3 Unified Field Study DataThe Algae Testbed Public-Private Partnership ATP3 was established with the goal of investigating open pond algae cultivation across different geographic climatic seasonal and operational conditions while setting the benchmark for quality data collection analysis and dissemination. Identical algae cultivation systems and data analysis methodologies were established at testbed sites across the continental United States and Hawaii. Within this framework the Unified Field Studies UFS were designed to characterize the cultivation of different algal strains during all 4 seasons across this testbed network. The dataset presented here is the complete curated climatic cultivation harvest and biomass composition data for each season at each site. These data enable others to do in-depth cultivation harvest techno-economic life cycle resource and predictive growth modeling analysis as well as develop crop protection strategies for the nascent algae industry.NREL Sub award Number DE-AC36-08-GO28308