Economic feasibility of biosynthetic fuel and chemical production hinges upon harnessing metabolism to achieve high titre and yield. Here we report a thorough genotypic and phenotypic optimization of an oleaginous organism to create a strain with significant lipogenesis capability. Specifically, we rewire Yarrowia lipolytica's native metabolism for superior de novo lipogenesis by coupling combinatorial multiplexing of lipogenesis targets with phenotypic induction. We further complete direct conversion of lipid content into biodiesel. Tri-level metabolic control results in saturated cells containing upwards of 90% lipid content and titres exceeding 25 g l À 1 lipids, which represents a 60-fold improvement over parental strain and conditions. Through this rewiring effort, we advance fundamental understanding of lipogenesis, demonstrate non-canonical environmental and intracellular stimuli and uncouple lipogenesis from nitrogen starvation. The high titres and carbon-source independent nature of this lipogenesis in Y. lipolytica highlight the potential of this organism as a platform for efficient oleochemical production.

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Abstract. Exogenous disturbances are critical agents of change in temperate forests capable of damaging trees and influencing forest structure, composition, demography, and ecosystem processes. Forest disturbances of intermediate magnitude and intensity receive relatively sparse attention, particularly at landscape scales, despite influencing most forests at least once per generation. Contextualizing the spatial extent and heterogeneity of such damage is of paramount importance to increasing our understanding of forested ecosystems. We investigated patterns of intermediate wind disturbance across a forested landscape in the northern Great Lakes, USA. A vegetation change tracker (VCT) algorithm was utilized for processing near-biennial Landsat data stacks ) spanning forests sustaining damage from four recent windstorms. VCT predominantly maps stand-clearing disturbance and regrowth patterns, which were used to identify forest boundaries, young stands, and disturbance patterns across space and time. To map wind damage severity, we compared satellite-derived normalized difference vegetation index (NDVI) values calculated from pre-and post-storm Landsat imagery. A geographic information system (GIS) was used to derive wind damage predictor variables from VCT, digital terrain, soils/landform, land cover, and storm tracking data. Hierarchical and random forests regressions were applied to rank the relative importance of predictor variables in influencing wind damage.A conservative estimate of aggregate damage from the intermediate windstorms (extrapolated to ;150,000 ha, ;25,500 severe) rivaled individual large, infrequent disturbances in the region. Damage patterns were relatively congruent among storms and became more spatially heterogeneous with increasing disturbance intensity. Proximity to forest-nonforest edge, stand age, and soils/landform were consistently important damage predictors. The spatial extent and distribution of the first two damage predictors are extremely sensitive to anthropogenic modifications of forested landscapes, the most important disturbance agent in the northern Great Lakes. This provides circumstantial evidence suggesting anthropogenic activities are augmenting and/or diminishing the ecological effects of the natural wind disturbance regime. Natural disturbances of intermediate size and intensity are significant agents of change in this region, and likely in other regions, deserving more attention from ecologists and biogeographers.