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

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 2 3 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.

A Lignocellulolytic Colletotrichum sp. OH with Broad-Spectrum Tolerance to Lignocellulosic Pretreatment Compounds and Derivatives and the Efficiency to Produce Hydrogen Peroxide and 5-Hydroxymethylfurfural Tolerant Cellulases

“…Evidently, no literature is available regarding the synergistic effect of pretreatment-derived inhibitors with H 2 O 2 on fungal growth and metabolism. However, using statistical methods, a mixed concentration of 3.3 mmol/L formic acid, 21.6 mmol/L levulinic acid, and 6.6 mmol/L furfural inhibitors was optimized to increase the growth and ethanol yield of Saccharomyces cerevisiae [110]. Similarly, the fungus T. versicolor was reported to grow on mixed inhibitors of phenol, levulinic acid, HMF, and furfural at 0.4, 0.3, 0.2, and 0.6 g/L, respectively, by detoxification of the inhibitors [92].…”

Optimization of oxalic acid pre-treatment and enzymatic saccharification in Typha latifolia for production of reducing sugar

“…Higher biomass causes mechanical delay, uneven mix up of substrate and availability of water molecule to disintegrate lignin, hemicellulose and cellulose [ 17 ]. Lower temperatures and short reaction time (using concentrated sulphuric acid) have known to degrade sugars and release levulinic acid which inhibits ethanol production during fermentation [ 8 , 12 , 26 ].…”

Identifying Variables Influencing Traditional Food Solid-State Fermentation by Statistical Modeling

“…One approach is to use statistical analysis of process data to identify variables that affect yield. A practical solution is to extract information by statistical modelling of historical process data [10][11][12]. This practice has already been applied in several fermentation systems.…”