Analysis of ethanol production from xylose using Pichia stipitis in microaerobic conditions through experimental observations and kinetic modelling

A novel kinetic model for a cocoa waste fermentation to ethanol reaction and its experimental validation

A non-segregated kinetic model is proposed to describe a fermentation process of agro-industrial residues derived via cocoa (mucilage juice) by Pichia kudriavzevii. The novel proposed hybrid model is based on a multiple coupling reaction mechanisms (structured) to describe the kinetics of substrate consumption, biomass, carbon dioxide, and ethanol, coupled to an unstructured model for the activity enzyme. The parameters of the kinetic model are estimated by non-linear least-squares curve fitting using the Marquardt-Levenberg algorithm. In addition, numerical simulations were compared with the experimental data via residual graphs. The effectiveness of the model was statistically evaluated using dimensionless efficiency coefficients under different initial conditions. A global sensitivity analysis was applied (Fisher's information matrix). The experimental results of the batch reactor showed a maximum ethanol concentration of 29 g/L, with a yield of 0.48 g-ethanol/g-glucose and a productivity of 0.30 g/L h. The method determined that the cell formation coefficient and the specific substrate consumption rate (θ1 and θ2) directly influence most of the states of our system. The proposed scheme is particularly suitable to assist in the rational design of cell factory properties or fermentation processes because it can represent the complex biochemistry in more detail and under different initial experimental conditions; the above reveals that the generated model is robust and can be considered for control and optimization purposes.

Analysis of Single-Step Pretreatments for Lignocellulosic Platform Isolation as the Basis of Biorefinery Design

Biorefinery feasibility is highly influenced by the early design of the best feedstock transformation pathway to obtain value-added products. Pretreatment has been identified as the critical stage in biorefinery design since proper pretreatment influences subsequent reaction, separation, and purification processes. However, many pretreatment analyses have focused on preserving and valorizing six-carbon sugars for future use in bioconversion processes, leaving aside fractions such as hemicellulose and lignin. To date, there has been no pretreatment systematization for the removal of lignocellulosic fractions. This work defines pretreatment efficacy through operational, economic, environmental, and social indicators. Thus, using the data reported in the literature, as well as the results of the simulation schemes, a multi-criteria weighting of the best-performing schemes for the isolation or removal of cellulose, hemicellulose, and lignin was carried out. As a main result, it was concluded that dilute acid is the most effective for cellulose isolation and hemicellulose removal for producing platform products based on six- and five-carbon sugars, respectively. Additionally, the kraft process is the best methodology for lignin removal and its future use in biorefineries. The results of this work help to elucidate a methodological systematization of the pretreatment efficacy in the design of biorefineries as an early feasibility stage considering sustainability aspects.

Screening novel genes by a comprehensive strategy to construct multiple stress-tolerant industrial Saccharomyces cerevisiae with prominent bioethanol production

BACKGROUND

Strong multiple stress-tolerance is a desirable characteristic for Saccharomyces cerevisiae when different feedstocks are used for economical industrial ethanol production. Random mutagenesis or genome shuffling has been applied for improving multiple stress-tolerance, however, these techniques are generally time-consuming and labor cost-intensive and their molecular mechanisms are unclear. Genetic engineering, as an efficient technology, is poorly applied to construct multiple stress-tolerant industrial S. cerevisiae due to lack of clear genetic targets. Therefore, constructing multiple stress-tolerant industrial S. cerevisiae is challenging. In this study, some target genes were mined by comparative transcriptomics analysis and applied for the construction of multiple stress-tolerant industrial S. cerevisiae strains with prominent bioethanol production.

RESULTS

Twenty-eight shared differentially expressed genes (DEGs) were identified by comparative analysis of the transcriptomes of a multiple stress-tolerant strain E-158 and its original strain KF-7 under five stress conditions (high ethanol, high temperature, high glucose, high salt, etc.). Six of the shared DEGs which may have strong relationship with multiple stresses, including functional genes (ASP3, ENA5), genes of unknown function (YOL162W, YOR012W), and transcription factors (Crz1p, Tos8p), were selected by a comprehensive strategy from multiple aspects. Through genetic editing based on the CRISPR/Case9 technology, it was demonstrated that expression regulation of each of these six DEGs improved the multiple stress-tolerance and ethanol production of strain KF-7. In particular, the overexpression of ENA5 significantly enhanced the multiple stress-tolerance of not only KF-7 but also E-158. The resulting engineered strain, E-158-ENA5, achieved higher accumulation of ethanol. The ethanol concentrations were 101.67% and 27.31% higher than those of the E-158 when YPD media and industrial feedstocks (straw, molasses, cassava) were fermented, respectively, under stress conditions.

CONCLUSION

Six genes that could be used as the gene targets to improve multiple stress-tolerance and ethanol production capacities of S. cerevisiae were identified for the first time. Compared to the other five DEGs, ENA5 has a more vital function in regulating the multiple stress-tolerance of S. cerevisiae. These findings provide novel insights into the efficient construction of multiple stress-tolerant industrial S. cerevisiae suitable for the fermentation of different raw materials.

Dynamic Modeling of the Impact of Temperature Changes on CO2 Production during Milk Fermentation in Batch Bioreactors

Knowledge of the mathematical models of the fermentation processes is indispensable for their simulation and optimization and for the design and synthesis of the applicable control systems. The paper focuses on determining a dynamic mathematical model of the milk fermentation process taking place in a batch bioreactor. Models in the literature describe milk fermentation in batch bioreactors as an autonomous system. They do not enable the analysis of the effect of temperature changes on the metabolism during fermentation. In the presented extensive multidisciplinary study, we have developed a new mathematical model that considers the impact of temperature changes on the dynamics of the CO₂ produced during fermentation in the batch bioreactor. Based on laboratory tests and theoretical analysis, the appropriate structure of the temperature-considered dynamic model was first determined. Next, the model parameters of the fermentation process in the laboratory bioreactor were identified by means of particle swarm optimization. Finally, the experiments with the laboratory batch bioreactor were compared with the simulations to verify the derived mathematical model. The developed model proved to be very suitable for simulations, and, above all, it enables the design and synthesis of a control system for batch bioreactors.

Treatment of thin stillage by Aspergillus oryzae and its effect on alcoholic fermentation in syrup liquid

The microbial degradation of thin stillage for environment-friendly treatment has been studied extensively in recent years, and useful compounds in the treated-thin stillage are expected to be utilized in the subsequent fermentation. In this study, an Aspergillus oryzae H18, suitable for growing in thin stillage, was isolated from soil and served to degrade the organic matter in thin stillage, with the increase in pH (from 3·75 to 4·8) and decrease in chemical oxygen demand (COD, 81·3% removal rate). The effect of thin stillage as backset water after degradation of the strain H18 on alcohol production in syrup liquid was investigated. Compared with zero addition of thin stillage, the alcohol yield in mixed syrup liquid increased by 8·6% when the concentration of treated-thin stillage was 20%. After the addition of nutrients at proper concentration (0·5% urea, 1% molasses, 0·25% NaCl, 0·2% NaH₂ PO₄ , 0·3% MgSO₄ and 0·25% CaCl₂ ) in thin stillage, the alcohol yield in yeast fermentation was increased by 32·7% when mixed syrup liquid (with 40% thin stillage treated by H18) was employed, in comparison to control group without thin stillage addition. Meanwhile, the fermentation time was shortened, and alcohol production rate was enhanced.