Statistical prediction of interactions between low concentrations of inhibitors on yeast cells responses added to the SD-medium at low pH values

Abstract

Abstract Background In the present work, the main inhibitors of the yeast cells (vanillin, furfural, formic, and levulinic acid) were generated by pretreatments or hydrolysis (sulfuric acid or enzymes) to convert reducing sugars into ethanol. Inhibitors were added at increasing concentrations to the SD-medium containing yeast extract while negative effects on yeast cells were observed. Statistical analyses were applied to predict and interpret results related to biomass production. Results Inhibitors affected productivities and yields of biomass and ethanol when added to SD-medium. Based on the 23 full-central-composite design, “predicted” and “observed” values of ethanol and biomass were obtained in presence of the major inhibitors, which were acetic acid, formic acid, and levulinic acids. Increases in biomass and ethanol production are described in the Response surface graphs (RSM graphs) that resulted from multiple interactions between inhibitors. Positive interactions between the inhibitors occurred at low concentrations and pH values. The results were experimentally validated. Conclusions Statistical analysis is an extremely useful tool for predicting data during process monitoring, while re-adjustments of conditions can be performed, whenever necessary. In addition, the development of new strains of yeast with high tolerance to biomass inhibitors will have a major impact on the production of second-generation ethanol. Increases in fermentation activity of the yeast Saccharomyces cerevisiae in a mixture containing low concentrations of inhibitors were observed.

Keywords

• Saccharomyces cerevisiae
• Biomass inhibitors
• Factorial designs
• RMS analysis
• Response optimizer
• Interactions between inhibitors