Optimization of temperature, sugar concentration, and inoculum size to maximize ethanol production without significant decrease in yeast cell viability

Optimizing Ethanol Production in Saccharomyces cerevisiae at Ambient and Elevated Temperatures through Machine Learning-Guided Combinatorial Promoter Modifications

Bioethanol has gained popularity in recent decades as an ecofriendly alternative to fossil fuels due to increasing concerns about global climate change. However, economically viable ethanol fermentation remains a challenge. High-temperature fermentation can reduce production costs, but Saccharomyces cerevisiae yeast strains normally ferment poorly under high temperatures. In this study, we present a machine learning (ML) approach to optimize bioethanol production in S. cerevisiae by fine-tuning the promoter activities of three endogenous genes. We created 216 combinatorial strains of S. cerevisiae by replacing native promoters with five promoters of varying strengths to regulate ethanol production. Promoter replacement resulted in a 63% improvement in ethanol production at 30 °C. We created an ML-guided workflow by utilizing XGBoost to train high-performance models based on promoter strengths and cellular metabolite concentrations obtained from ethanol production of 216 combinatorial strains at 30 °C. This strategy was then applied to optimize ethanol production at 40 °C, where we selected 31 strains for experimental fermentation. This reduced experimental load led to a 7.4% increase in ethanol production in the second round of the ML-guided workflow. Our study offers a comprehensive library of promoter strength modifications for key ethanol production enzymes, showcasing how machine learning can guide yeast strain optimization and make bioethanol production more cost-effective and efficient. Furthermore, we demonstrate that metabolic engineering processes can be accelerated and optimized through this approach.

Development of two devices for high-throughput screening of ethanol-producing microorganisms by real-time CO2 production monitoring

Bioethanol's importance as a renewable energy carrier led to the development of new devices for the high-throughput screening (HTS) of ethanol-producing microorganisms, monitoring ethanol production, and process optimization. This study developed two devices based on measuring CO₂ evolution (an equimolar byproduct of microbial ethanol fermentation) to allow for a fast and robust HTS of ethanol-producing microorganisms for industrial purposes. First, a pH-based system for identifying ethanol producers (Ethanol-HTS) was established in a 96-well plate format where CO₂ emission is captured by a 3D-printed silicone lid and transferred from the fermentation well to a reagent containing bromothymol blue as a pH indicator. Second, a self-made CO₂ flow meter (CFM) was developed as a lab-scale tool for real-time quantification of ethanol production. This CFM contains four chambers to simultaneously apply different fermentation treatments while LCD and serial ports allow fast and easy data transfer. Applying ethanol-HTS with various yeast concentrations and yeast strains displayed different colors, from dark blue to dark and light green, based on the amount of carbonic acid formed. The results of the CFM device revealed a fermentation profile. The curve of CO₂ production flow among six replications showed the same pattern in all batches. The comparison of final ethanol concentrations calculated based on CO₂ flow by the CFM device with the GC analysis showed 3% difference which is not significant. Data validation of both devices demonstrated their applicability for screening novel bioethanol-producer strains, determining carbohydrate fermentation profiles, and monitoring ethanol production in real time.

Mathematical Modeling of Fed-Batch Ethanol Fermentation Under Very High Gravity and High Cell Density at Different Temperatures

The use of more appropriate kinetic models can assist in improving ethanol fermentation under conditions of very high gravity (VHG) and high cell density (HCD), in order to obtain higher amounts of ethanol in the broth combined with high productivity. The aim of this study was to model fed-batch ethanol fermentation under VHG/HCD conditions, at different temperatures, considering three types of inhibition (substrate, ethanol, and cells). Fermentations were carried out using different temperatures (28 ≤ [Formula: see text] (°C) ≤ 34), inoculum sizes (50 ≤ [Formula: see text] (g L^-1) ≤ 125), and substrate concentrations in the must (258 ≤ [Formula: see text] (g L^-1) ≤ 436). In the proposed model, the cell inhibition power parameter varied with the temperature and inoculum size, while the cell yield coefficient varied with inoculum size and substrate concentration in the must. Hence, it was possible to propose correlations for the cell inhibition power parameter ([Formula: see text]) and for the cell yield coefficient ([Formula: see text]), as functions of the fermentation conditions. Simulations of fed-batch ethanol fermentations at different temperatures, under VHG/HCD conditions, were performed using the proposed correlations. Experimental validation showed that the model was able to accurately predict the dynamic behavior of the fermentations in terms of the concentrations of viable cells, total cells, ethanol, and substrate.

Very High Gravity Bioethanol Revisited: Main Challenges and Advances

Over the last decades, the constant growth of the world-wide industry has been leading to more and more concerns with its direct impact on greenhouse gas (GHG) emissions. Resulting from that, rising efforts have been dedicated to a global transition from an oil-based industry to cleaner biotechnological processes. A specific example refers to the production of bioethanol to substitute the traditional transportation fuels. Bioethanol has been produced for decades now, mainly from energy crops, but more recently, also from lignocellulosic materials. Aiming to improve process economics, the fermentation of very high gravity (VHG) mediums has for long received considerable attention. Nowadays, with the growth of multi-waste valorization frameworks, VHG fermentation could be crucial for bioeconomy development. However, numerous obstacles remain. This work initially presents the main aspects of a VHG process, giving then special emphasis to some of the most important factors that traditionally affect the fermentation organism, such as nutrients depletion, osmotic stress, and ethanol toxicity. Afterwards, some factors that could possibly enable critical improvements in the future on VHG technologies are discussed. Special attention was given to the potential of the development of new fermentation organisms, nutritionally complete culture media, but also on alternative process conditions and configurations.

Screening of the five different wild, traditional and industrial Saccharomyces cerevisiae strains to overproduce bioethanol in the batch submerged fermentation

Efforts to produce bioethanol with higher productivity in a batch submerged fermentation were made by evaluating the bioethanol production of the five different strains of Saccharomyces cerevisiae, namely, NCYC 4109 (traditional bakery yeast), SFO6 (industrial yeast), TTCC 2956 (hybrid baking yeast) and two wild yeasts, PTCC 5052 and BY 4743. The bioethanol productivity and kinetic parameters for all five yeasts at constant fermentation conditions, during 72 h, were evaluated and monitored. The obtained results indicated that compared to the wild yeasts, both traditional bakery (NCYC 4109) and industrial (SFO6) yeasts had higher bioethanol productivity (0.9 g/L h). Significant (p<0.05) differences between biomass concentration of NCYC 4109 yeast and those of other yeasts 30 h after start of fermentation, and its high bioethanol concentration (59.19 g/L) and yield over consumed sugars (77.25%) were highlighted among all the studied yeasts. Minimum bioethanol productivity was obtained using yeasts PTCC 5052 (0.7 g/L h) and TTCC 2956 (0.86 g/L h). However, maximum yield over consumed sugar was obtained using the yeast TTCC 2956 (79.41%).

A sequential pretreatment of lignocelluloses in bamboo biomass to fermentable sugars by acid/enzymatic hydrolysis

A sequential pretreatment method for hydrolyzing rigid hemicelluloses and cellulose content in the bamboo biomass was investigated in this study. The effects of different parameters, such as nature of biomass, type of acid, acid and biomass concentration, were studied. Under the optimum condition of 5% (v/v) HCl-treated biomass and biomass concentration (8%, w/v), the maximum yield of sugar (619 mg/g of biomass) was obtained. The enzymatic hydrolysis parameter conditions were further optimized by response surface methodology-based central composite method. According to the results, the highest yield of sugar (515 mg/g of biomass) was obtained at hydrolysis temperature 50 °C, biomass concentration 8.9%, w/v, enzyme concentration (199.8 mg/g of biomass) and time 60 h, respectively. The effects of untreated, pretreated and enzymatically hydrolyzed biomass structure and complexity were investigated by field emission scanning electron microscopy and X-ray diffraction techniques.

Bioethanol production from taro waste using thermo-tolerant yeast Kluyveromyces marxianus K21

In the present study, evaluation and optimization of taro waste (TW), which was mainly composed of taro peels that contain many starch residues, as the main carbon source in medium were studied. The flask studies showed the optimal medium was using 170g/L of TW which is about 100g/L of glucose and 9g/L of CGM as alternative nitrogen source. Simultaneous saccharification and fermentation (SSF) exhibited higher bioethanol productivity toward separation hydrolysis and fermentation (SHF). The optimal condition of SSF was 5% of Kluyveromyces marxianus K21 inoculum at 40°C resulting in the maximum ethanol concentration (48.98g/L) and productivity (2.23g/L/h) after 22h of cultivation. The scaling up experiment in a 5L bioreactor demonstrated that K21 can still maintain its capability. After 20h of cultivation, 43.78g/L of ethanol (2.19g/L/h of productivity) was achieved corresponding to a 94.2% theoretical ethanol yield.

Quantifying second generation ethanol inhibition: Design of Experiments approach and kinetic model development

While softwoods represent a potential feedstock for second generation ethanol production, compounds present in their hydrolysates can inhibit fermentation. In this study, a novel Design of Experiments (DoE) approach was used to identify significant inhibitory effects on Saccharomyces cerevisiae D5A for the purpose of guiding kinetic model development. Although acetic acid, furfural and 5-hydroxymethyl furfural (HMF) were present at potentially inhibitory levels, initial factorial experiments only identified ethanol as a significant rate inhibitor. It was hypothesized that high ethanol levels masked the effects of other inhibitors, and a subsequent factorial design without ethanol found significant effects for all other compounds. When these non-ethanol effects were accounted for in the kinetic model, R¯(2) was significantly improved over an ethanol-inhibition only model (R¯(2)=0.80 vs. 0.76). In conclusion, when ethanol masking effects are removed, DoE is a valuable tool to identify significant non-ethanol inhibitors and guide kinetic model development.

Current Trends in Bioethanol Production by Saccharomyces cerevisiae: Substrate, Inhibitor Reduction, Growth Variables, Coculture, and Immobilization

Bioethanol is one of the most commonly used biofuels in transportation sector to reduce greenhouse gases. S. cerevisiae is the most employed yeast for ethanol production at industrial level though ethanol is produced by an array of other yeasts, bacteria, and fungi. This paper reviews the current and nonmolecular trends in ethanol production using S. cerevisiae. Ethanol has been produced from wide range of substrates such as molasses, starch based substrate, sweet sorghum cane extract, lignocellulose, and other wastes. The inhibitors in lignocellulosic hydrolysates can be reduced by repeated sequential fermentation, treatment with reducing agents and activated charcoal, overliming, anion exchanger, evaporation, enzymatic treatment with peroxidase and laccase, in situ detoxification by fermenting microbes, and different extraction methods. Coculturing S. cerevisiae with other yeasts or microbes is targeted to optimize ethanol production, shorten fermentation time, and reduce process cost. Immobilization of yeast cells has been considered as potential alternative for enhancing ethanol productivity, because immobilizing yeasts reduce risk of contamination, make the separation of cell mass from the bulk liquid easy, retain stability of cell activities, minimize production costs, enable biocatalyst recycling, reduce fermentation time, and protect the cells from inhibitors. The effects of growth variables of the yeast and supplementation of external nitrogen sources on ethanol optimization are also reviewed.

Simultaneous saccharification and co-fermentation of aqueous ammonia pretreated corn stover with an engineered Saccharomyces cerevisiae SyBE005

Co-fermentation of glucose and xylose from lignocelluloses is an efficient approach to increasing ethanol production. Simultaneous saccharification and co-fermentation (SSCF) of corn stover pretreated with aqueous ammonia was performed using engineered yeast with xylose utilization pathway. Thus far, the effect of the several key factors on SSCF was investigated, including temperature, inoculation size, pre-hydrolysis and pH. Ethanol concentration was achieved to 36.5 g/L during SSCF process with 6% glucan loading. The addition of Tween 20 reduced enzyme loading, i.e., from 15 to 7.5 FPU/gglucan with the same final ethanol concentration. The ethanol concentration was achieved to 70.1g/L at 12% glucan loading. Yeast feeding, combined with substrate and enzyme feeding, was proved to be an efficient approach for SSCF with high solid loading.

Alcoholic fermentation with flocculant Saccharomyces cerevisiae in fed-batch process

Studies have been conducted on selecting yeast strains for use in fermentation for ethanol production to improve the performance of industrial plants and decrease production costs. In this paper, we study alcoholic fermentation in a fed-batch process using a Saccharomyces cerevisiae yeast strain with flocculant characteristics. Central composite design (CCD) was used to determine the optimal combination of the variables involved, with the sucrose concentration of 170 g/L, a cellular concentration in the inoculum of 40% (v/v), and a filling time of 6 h, which resulted in a 92.20% yield relative to the theoretical maximum yield, a productivity of 6.01 g/L h and a residual sucrose concentration of 44.33 g/L. With some changes in the process such as recirculation of medium during the fermentation process and increase in cellular concentration in the inoculum after use of the CCD was possible to reduce the residual sucrose concentration to 2.8 g/L in 9 h of fermentation and increase yield and productivity for 92.75% and 9.26 g/L h, respectively. A model was developed to describe the inhibition of alcoholic fermentation kinetics by the substrate and the product. The maximum specific growth rate was 0.103 h(-1), with K(I) and K(s) values of 109.86 and 30.24 g/L, respectively. The experimental results from the fed-batch reactor show a good fit with the proposed model, resulting in a maximum growth rate of 0.080 h(-1).

Application of response surface methodology for the optimization of arabinose biotransformation to arabitol by Candida parapsilosis

L-arabitol, a polyol with applications in the food and pharmaceutical industries, is secreted by different yeasts, e.g., Candida spp., Pichia spp., and Debaryomyces spp. The process of its biotechnological production is highly dependent on the physical and chemical conditions of culture. The aim of this study was to use statistical response surface methodology (RSM) to optimize the biotransformation of L-arabinose to arabitol by Candida parapsilosis, a yeast species able to assimilate pentoses. Batch cultures of the yeast were prepared following a Plackett-Burman design for seven variables. Following this, rotation speed, temperature, and L-arabinose concentration were chosen for a central composite design (CCD) experiment, which was carried out to optimize the production L-arabitol. The results showed that the optimal levels for the three factors were: rotation speed 150 rpm, temperature 28°C, and L-arabinose concentration 32.5 g/l. The predicted concentration of arabitol after two days of incubation of C. parapsilosis under the above conditions was 14.3 g/l. The value of R2=0.8323 suggested that this model was well-fitted to the experimental data, and this was confirmed during a verification experiment.

Induction of gene expression in bacteria at optimal growth temperatures

Traditional temperature-sensitive systems use either heat shock (40-42 °C) or cold shock (15-23 °C) to induce gene expression at temperatures that are not the optimal temperature for host cell growth (37 °C). This impacts the overall productivity and yield by disturbing cell growth and cellular metabolism. Here, we have developed a new system which controls gene expression in Escherichia coli at more permissive temperatures. The temperature-sensitive cI857-P L system and the classic lacI-P lacO system were connected in series to control the gene of interest. When the culture temperature was lowered, the thermolabile cI857 repressor was activated and blocked the expression of lacI from P L. Subsequently, the decrease of LacI derepressed the expression of gene of interest from P lacO . Using a green fluorescent protein marker, we demonstrated that (1) gene expression was tightly regulated at 42 °C and strongly induced by lowering temperature to 25-37 °C; (2) different levels of gene expression can be induced by varying culture temperature; and (3) gene expression after induction was sustained until the end of the log phase. We then applied this system in the biosynthesis of acetoin and demonstrated that high yield and production could be achieved using temperature induction. The ability to express proteins at optimal growth temperatures without chemical inducers is advantageous for large-scale and industrial fermentations.

Influence of cultivation procedure for Saccharomyces cerevisiae used as pitching agent in industrial spent sulphite liquor fermentations

The cell viability and fermentation performance often deteriorate in fermentations of spent sulphite liquor (SSL). This investigation therefore addresses the question of how different cultivation conditions for yeast cells influence their ability to survive and boost the ethanol production capacity in an SSL-based fermentation process. The strains used as pitching agents were an industrially harvested Saccharomyces cerevisiae and commercial dry baker's yeast. This study therefore suggests that exposure to SSL in combination with nutrients, prior to the fermentation step, is crucial for the performance of the yeast. Supplying 0.5 g/l fresh yeast cultivated under appropriate cultivation conditions may increase ethanol concentration more than 200%.

Improvement of ethanol production using Saccharomyces cerevisiae by enhancement of biomass and nutrient supplementation

Optimization of ethanol production through addition of substratum and protein-lipid additives was studied. Oilseed meal extract was used as protein lipid supplement, while rice husk was used as substratum. The effect of oil seed meal extract and rice husk was observed at varying concentration of medium sugar from 8% to 20%. Of the three oil seed meal extracts used, viz. groundnut, safflower, and sunflower, safflower was found to be most efficient. The use of oilseed meal extract at 4% was found to enhance ethanol production by almost 50% and enhanced sugar tolerance from 8% to 16%. A further increase of almost 48% ethanol was observed on addition of 2 g of rice husk per 100 ml of medium. An increase in cell mass with better sugar attenuation was observed. Further optimization was sought through use of sugarcane juice as the sugar source. While 8.9% ethanol yield with 75% sugar attenuation was observed at 20% sucrose concentration, it was found to increase to 12% (v/v) with almost complete utilization of medium sugar when sugarcane juice was used. Cell weight was also observed to increase by 26%.

Optimization of process parameters for ethanol production from sugar cane molasses by Zymomonas mobilis using response surface methodology and genetic algorithm

Ethanol is a potential energy source and its production from renewable biomass has gained lot of popularity. There has been worldwide research to produce ethanol from regional inexpensive substrates. The present study deals with the optimization of process parameters (viz. temperature, pH, initial total reducing sugar (TRS) concentration in sugar cane molasses and fermentation time) for ethanol production from sugar cane molasses by Zymomonas mobilis using Box-Behnken experimental design and genetic algorithm (GA). An empirical model was developed through response surface methodology to analyze the effects of the process parameters on ethanol production. The data obtained after performing the experiments based on statistical design was utilized for regression analysis and analysis of variance studies. The regression equation obtained after regression analysis was used as a fitness function for the genetic algorithm. The GA optimization technique predicted a maximum ethanol yield of 59.59 g/L at temperature 31 °C, pH 5.13, initial TRS concentration 216 g/L and fermentation time 44 h. The maximum experimental ethanol yield obtained after applying GA was 58.4 g/L, which was in close agreement with the predicted value.

Optimization of low-cost medium for very high gravity ethanol fermentations by Saccharomyces cerevisiae using statistical experimental designs

Statistical experimental designs were used to develop a medium based on corn steep liquor (CSL) and other low-cost nutrient sources for high-performance very high gravity (VHG) ethanol fermentations by Saccharomyces cerevisiae. The critical nutrients were initially selected according to a Plackett-Burman design and the optimized medium composition (44.3 g/L CSL; 2.3 g/L urea; 3.8 g/L MgSO₄·7H₂O; 0.03 g/L CuSO₄·5H₂O) for maximum ethanol production by the laboratory strain CEN.PK 113-7D was obtained by response surface methodology, based on a three-level four-factor Box-Behnken design. The optimization process resulted in significantly enhanced final ethanol titre, productivity and yeast viability in batch VHG fermentations (up to 330 g/L glucose) with CEN.PK113-7D and with industrial strain PE-2, which is used for bio-ethanol production in Brazil. Strain PE-2 was able to produce 18.6±0.5% (v/v) ethanol with a corresponding productivity of 2.4±0.1g/L/h. This study provides valuable insights into cost-effective nutritional supplementation of industrial fuel ethanol VHG fermentations.