Leveraging Genetic-Background Effects in Saccharomyces cerevisiae To Improve Lignocellulosic Hydrolysate Tolerance

A major obstacle to sustainable lignocellulosic biofuel production is microbe inhibition by the combinatorial stresses in pretreated plant hydrolysate. Chemical biomass pretreatment releases a suite of toxins that interact with other stressors, including high osmolarity and temperature, which together can have poorly understood synergistic effects on cells. Improving tolerance in industrial strains has been hindered, in part because the mechanisms of tolerance reported in the literature often fail to recapitulate in other strain backgrounds. Here, we explored and then exploited variations in stress tolerance, toxin-induced transcriptomic responses, and fitness effects of gene overexpression in different Saccharomyces cerevisiae (yeast) strains to identify genes and processes linked to tolerance of hydrolysate stressors. Using six different S. cerevisiae strains that together maximized phenotypic and genetic diversity, first we explored transcriptomic differences between resistant and sensitive strains to identify common and strain-specific responses. This comparative analysis implicated primary cellular targets of hydrolysate toxins, secondary effects of defective defense strategies, and mechanisms of tolerance. Dissecting the responses to individual hydrolysate components across strains pointed to synergistic interactions between osmolarity, pH, hydrolysate toxins, and nutrient composition. By characterizing the effects of high-copy gene overexpression in three different strains, we revealed the breadth of the background-specific effects of gene fitness contributions in synthetic hydrolysate. Our approach identified new genes for engineering improved stress tolerance in diverse strains while illuminating the effects of genetic background on molecular mechanisms.

Recent studies on natural variation within Saccharomyces cerevisiae have uncovered substantial phenotypic diversity. Here, we took advantage of this diversity, using it as a tool to infer the effects of combinatorial stress found in lignocellulosic hydrolysate. By comparing sensitive and tolerant strains, we implicated primary cellular targets of hydrolysate toxins and elucidated the physiological states of cells when exposed to this stress. We also explored the strain-specific effects of gene overexpression to further identify strain-specific responses to hydrolysate stresses and to identify genes that improve hydrolysate tolerance independent of strain background. This study underscores the importance of studying multiple strains to understand the effects of hydrolysate stress and provides a method to find genes that improve tolerance across strain backgrounds.