Byung Jo Yu

Improved galactose fermentation of Saccharomyces cerevisiae through inverse metabolic engineering.

Although Saccharomyces cerevisiae is capable of fermenting galactose into ethanol, ethanol yield and productivity from galactose are significantly lower than those from glucose. An inverse metabolic engineering approach was undertaken to improve ethanol yield and productivity from galactose in S. cerevisiae. A genome‐wide perturbation library was introduced into S. cerevisiae, and then fast galactose‐fermenting transformants were screened using three different enrichment methods. The characterization of genetic perturbations in the isolated transformants revealed three target genes whose overexpression elicited enhanced galactose utilization. One confirmatory (SEC53 coding for phosphomannomutase) and two novel targets (SNR84 coding for a small nuclear RNA and a truncated form of TUP1 coding for a general repressor of transcription) were identified as overexpression targets that potentially improve galactose fermentation. Beneficial effects of overexpression of SEC53 may be similar to the mechanisms exerted by overexpression of PGM2 coding for phosphoglucomutase. While the mechanism is largely unknown, overexpression of SNR84, improved both growth and ethanol production from galactose. The most remarkable improvement of galactose fermentation was achieved by overexpression of the truncated TUP1 (tTUP1) gene, resulting in unrivalled galactose fermentation capability, that is 250% higher in both galactose consumption rate and ethanol productivity compared to the control strain. Moreover, the overexpression of tTUP1 significantly shortened lag periods that occurs when substrate is changed from glucose to galactose. Based on these results we proposed a hypothesis that the mutant Tup1 without C‐terminal repression domain might bring in earlier and higher expression of GAL genes through partial alleviation of glucose repression. mRNA levels of GAL genes (GAL1, GAL4, and GAL80) indeed increased upon overexpression of tTUP. The results presented in this study illustrate that alteration of global regulatory networks through overexpression of the identified targets (SNR84 and tTUP1) is as effective as overexpression of a rate limiting metabolic gene (PGM2) in the galactose assimilation pathway for efficient galactose fermentation in S. cerevisiae. In addition, these results will be industrially useful in the biofuels area as galactose is one of the abundant sugars in marine plant biomass such as red seaweed as well as cheese whey and molasses. Biotechnol. Bioeng. 2011; 108:621–631.

Identification of gene targets eliciting improved alcohol tolerance in Saccharomyces cerevisiae through inverse metabolic engineering.

The economic production of biofuels from renewable biomass using Saccharomyces cerevisiae requires tolerance to high concentrations of sugar and alcohol. Here we applied an inverse metabolic engineering approach to identify endogenous gene targets conferring improved alcohol tolerance in S. cerevisiae. After transformation with a S. cerevisiae genomic library, enrichment of the transformants exhibiting improved tolerance was performed by serial subculture in the presence of iso-butanol (1%). Through sequence analysis of the isolated plasmids from the selected transformants, four endogenous S. cerevisiae genes were identified as overexpression targets eliciting improved tolerance to both iso-butanol and ethanol. Overexpression of INO1, DOG1, HAL1 or a truncated form of MSN2 resulted in remarkably increased tolerance to high concentrations of iso-butanol and ethanol. Overexpression of INO1 elicited the highest ethanol tolerance, resulting in higher titers and volumetric productivities in the fermentation experiments performed with high glucose concentrations. In addition, the INO1-overexpressing strain showed a threefold increase in the specific growth rate as compared to that of the control strain under conditions of high levels of glucose (10%) and ethanol (5%). Although alcohol tolerance in yeast is a complex trait affected by simultaneous interactions of many genes, our results using a genomic library reveal potential target genes for better understanding and possible engineering of metabolic pathways underlying alcohol tolerance phenotypes.