Initial Glucose Concentration Research Articles

Ethanol production by Kluyveromyces marxianus ATCC 36907: Fermentation features and mathematical modeling

The effects of different temperatures (30 °C, 35 °C, 40 °C, and 45 °C) and initial glucose concentrations (50 g/L, 120 g/L, and 190 g/L) on the fermentative metabolism of Kluyveromyces marxianus ATCC 36907 were evaluated to optimize ethanol production. Mathematical models were developed based on experimental data to describe cell growth, substrate consumption, and ethanol production. Various kinetic models integrated with material balances were examined. The Akaike information criterion (AIC) was employed to identify the most accurate model representing the experimental behavior. Interestingly, the ethanol production rate was independent of the growth rate of K. marxianus. The growth kinetics indicated that the growth rate could be controlled by the oxygen concentration, which was influenced by cell concentration rather than glucose consumption. A desirability function was utilized to optimize ethanol productivity, substrate conversion efficiency and temperature, considering the conditions for future applications in simultaneous saccharification and fermentation (SSF) processes. The optimized experimental conditions obtained were validated, resulting in a new model specific to these conditions. This new model analysis confirmed the achievement of the objective to prioritize ethanol production. The optimized conditions for maximum ethanol production were initial glucose concentration of 91 g/L and temperature of 40 °C. Under these conditions, the ethanol concentration reached 12 g/L, with glucose conversion efficiency into ethanol of 0.13 g/g and productivity of 1.09 g/L/h after 11 h. This approach provided valuable insights into the fermentative behavior of K. marxianus, serving as a foundation for the design, optimization, and process control in biorefineries.

Bioproduction of succinic acid from potato waste. Kinetic modeling

Succinic acid is a key chemical platform for the implementation of biorefineries and, therefore, for the development of a sustainable bioeconomy. In this work, succinic acid anaerobic production by Actinobacillus succinogenes from potato waste and glucose was carried out. Firstly, a simple kinetic model was developed to accurately predict the evolution of succinic acid, substrate, by-products, and biomass based on bottle experiments performed at different initial glucose concentrations. Secondly, experiments with an acid hydrolysate of potato waste as carbon source were performed in orbitally shaken bottles and bioreactor to compare the fermentation performance of the potato waste with the pure glucose. Using this hydrolysate, 32.2 g‧L-1 of succinic acid were obtained with a productivity of 0.64 g‧L-1‧h-1, improving SA yield by 37% compared to results with pure glucose. This is one of the highest values to date for succinic acid bioproduction from food residues (0.92 g‧g-1). Finally, the proposed kinetic model was successfully applied to the fermentation data obtained from potato waste fermentation, being this type of models a highly valuable tool for future techno-economic analysis of the bioprocess.

Production and Characterization of Poly(3-hydroxybutyrate) from Halomonas boliviensis LC1 Cultivated in Hydrolysates of Quinoa Stalks

The global production of fossil-based plastics has reached critical levels, and their substitution with bio-based polymers is an urgent requirement. Poly(3-hydroxybutyrate) (PHB) is a biopolymer that can be produced via microbial cultivation, but efficient microorganisms and low-cost substrates are required. Halomonas boliviensis LC1, a moderately halophilic bacterium, is an effective PHB producer, and hydrolysates of the residual stalks of quinoa (Chenopodium quinoa Willd.) can be considered a cheap source of sugars for microbial fermentation processes in quinoa-producing countries. In this study, H. boliviensis LC1 was adapted to a cellulosic hydrolysate of quinoa stalks obtained via acid-catalyzed hydrothermal pretreatment and enzymatic saccharification. The adapted strain was cultivated in hydrolysates and synthetic media, each of them with two different initial concentrations of glucose. Cell growth, glucose consumption, and PHB formation during cultivation were assessed. The cultivation results showed an initial lag in microbial growth and glucose consumption in the quinoa hydrolysates compared to cultivation in synthetic medium, but after 33 h, the values were comparable for all media. Cultivation in hydrolysates with an initial glucose concentration of 15 g/L resulted in a higher glucose consumption rate (0.15 g/(L h) vs. 0.14 g/(L h)) and volumetric productivity of PHB (14.02 mg/(L h) vs. 10.89 mg/(L h)) than cultivation in hydrolysates with 20 g/L as the initial glucose concentration. During most of the cultivation time, the PHB yield on initial glucose was higher for cultivation in synthetic medium than in hydrolysates. The produced PHBs were characterized using advanced analytical techniques, such as high-performance size-exclusion chromatography (HPSEC), Fourier transform infrared (FTIR) spectroscopy, 1H nuclear magnetic resonance (NMR) spectroscopy, scanning electron microscopy (SEM), X-ray diffraction (XRD), and thermogravimetric analysis (TGA). HPSEC revealed that the molecular weight of PHB produced in the cellulosic hydrolysate was lower than that of PHB produced in synthetic medium. TGA showed higher thermal stability for PHB produced in synthetic medium than for that produced in the hydrolysate. The results of the other characterization techniques displayed comparable features for both PHB samples. The presented results show the feasibility of producing PHB from quinoa stalks with H. boliviensis.

Optimization of fermentation conditions as a metabolic strategy for the high-yield and high-selectivity bio-based 2,3-butanediol production

Optimization of culture conditions can be used as an alternative metabolic control strategy to genetic engineering to improve bio-based 2,3-butanediol (2,3-BDO) production, especially its yield and optical purity. In this study, a first-order model was determined to predict the 2,3-BDO yield, which reached about 90% in batch cultures at 32° C, pH = 5, and kLa ∼ 5.0 ± 2.7 h−1, using a new and safe Paenibacillus peoriae NRRL BD-62. No acetoin accumulation and an absolute levo-2,3-BDO optical purity were also verified. About 39.4 g/L of 2,3-BDO, with a yield of 0.43 g/g, and a levo-:meso-2,3-BDO ratio of 1.9:1, was obtained at the expense of acetoin, lactic acid, and ethanol in fed-batch fermentation at kLa adjusted within its optimized range (∼7.5 h−1) to overcome operational limitations using high initial glucose concentrations. The low pH contributed to the carbon flux shift toward the levo-isomer synthesis, possibly due to the preferential butanediol dehydrogenase activation, while the highly oxygen-limited environment favored the complete acetoin conversion, enhancing the 2,3-BDO yield. These results provide significant contributions to the high-yield, acetoin-free, and safe bio-based 2,3-BDO production of particular interest in large-scale fermentations.

Thermotolerance improvement of engineered Saccharomyces cerevisiae ERG5 Delta ERG4 Delta ERG3 Delta, molecular mechanism, and its application in corn ethanol production

BackgroundThe thermotolerant yeast is beneficial in terms of efficiency improvement of processes and reduction of costs, while Saccharomyces cerevisiae does not efficiently grow and ferment at high-temperature conditions. The sterol composition alteration from ergosterol to fecosterol in the cell membrane of S. cerevisiae affects the thermotolerant capability.ResultsIn this study, S. cerevisiae ERG5, ERG4, and ERG3 were knocked out using the CRISPR–Cas9 approach to impact the gene expression involved in ergosterol synthesis. The highest thermotolerant strain was S. cerevisiae ERG5ΔERG4ΔERG3Δ, which produced 22.1 g/L ethanol at 37 °C using the initial glucose concentration of 50 g/L with an increase by 9.4% compared with the wild type (20.2 g/L). The ethanol concentration of 9.4 g/L was produced at 42 ℃, which was 2.85-fold of the wild-type strain (3.3 g/L). The molecular mechanism of engineered S. cerevisiae at the RNA level was analyzed using the transcriptomics method. The simultaneous deletion of S. cerevisiae ERG5, ERG4, and ERG3 caused 278 up-regulated genes and 1892 down-regulated genes in comparison with the wild-type strain. KEGG pathway analysis indicated that the up-regulated genes relevant to ergosterol metabolism were ERG1, ERG11, and ERG5, while the down-regulated genes were ERG9 and ERG26. S. cerevisiae ERG5ΔERG4ΔERG3Δ produced 41.6 g/L of ethanol at 37 °C with 107.7 g/L of corn liquefied glucose as carbon source.ConclusionSimultaneous deletion of ERG5, ERG4, and ERG3 resulted in the thermotolerance improvement of S. cerevisiae ERG5ΔERG4ΔERG3Δ with cell viability improvement by 1.19-fold at 42 °C via modification of steroid metabolic pathway. S. cerevisiae ERG5ΔERG4ΔERG3Δ could effectively produce ethanol at 37 °C using corn liquefied glucose as carbon source. Therefore, S. cerevisiae ERG5ΔERG4ΔERG3Δ had potential in ethanol production at a large scale under supra-optimal temperature.

Abstract 3171: Detecting ploidy specific vulnerability to resource restriction: An integrated in vitro and in silico approach

Abstract Changes in the number of copies of the genome, i.e. changes in ploidy are widespread among cancer cells. Increased ploidy is thought to benefit cancer cells by conferring robustness against deleterious consequences of genomic instability. However, whether there are any potential costs associated with increased ploidy has not been sufficiently investigated. One hypothesis holds that high ploidy cells may exhibit increased sensitivity to limitations in resources, due to the extra energy required for the replication of a larger genome. To address this hypothesis, we developed an integrated in vitro and in silico system to investigate the response to glucose restriction in diploid and tetraploid cells. Near diploid (2N) SUM159 breast cancer cells were fused to generate an isogenic tetraploid (4N) cell line. 2N or 4N cells were plated with varying initial concentrations of glucose. Cells grew for five days and media was not refreshed, so cells depleted the glucose in the media until they eventually died. Throughout the experiments, glucose concentration was measured at 24 hour intervals, and images were taken at 8 hour intervals allowing quantification of the number of alive or dead cells over time. These in vitro data were then used as inputs to the in silico portion of our system, which consists of an Ordinary Differential Equation (ODE) model of cancer cell growth. ODE model parameters were estimated using the measured outputs from the in vitro experiments. Parameters estimated from the ODE model gave insight into differences between the 2N and 4N cell lines. We found that 4N cells outcompeted 2N cells at high glucose concentrations, due to their ability to divide more rapidly when glucose was abundant. However, 2N cells were able to outcompete 4N cells at lower glucose concentrations. The advantage of 2N cells at low glucose was not due to an increased proliferative capacity. Instead, 2N cells were more resistant to cell death when glucose was limited. Our next steps will be to expand our system to assess ploidy specific sensitivity to other resources, such as phosphate or oxygen. The ODE model we have developed allows us to identify resource conditions that will select for tumor cells based on ploidy. In future this knowledge can be used to suggest therapeutics that can modulate resource availability within tumors, in order to steer tumor evolution towards less aggressive phenotypes. Citation Format: Richard J. Beck, Didem Ilter, Ana P. Gomes, Noemi Andor. Detecting ploidy specific vulnerability to resource restriction: An integrated in vitro and in silico approach [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3171.

Dynamic hybrid modeling of fuel ethanol fermentation process by integrating biomass concentration XGBoost model and kinetic parameter artificial neural network model into mechanism model

Fuel ethanol has drawn extensive attention as renewable energy. However, modeling the fuel ethanol batch fermentation process is still a critical task. The unstructured kinetic model (UKM) is often utilized to model the process, but it encounters two problems due to the large differences in initial glucose concentrations. First, the UKM has poor predictions of the yeast growth, which is a crucial production index. Second, the kinetic parameters of the UKM are time-varying because of the changing environmental conditions. The constant manually set kinetic parameters affect the prediction accuracy. To tackle the problems, we propose a dynamic hybrid model of the fuel ethanol fermentation process. First, a biomass concentration prediction model based on extreme gradient boosting is developed. It predicts the values of biomass concentrations and mycelium growth rate as supplementary mechanism knowledge. Then, we present an artificial neural network-based model to determine the time-varying kinetic parameters. Our model can accurately predict the time series of biomass, ethanol, and glucose concentrations, with RMSEs reaching 0.3323, 1.9295, and 3.0540. Experimental results show that the dynamic hybrid model performs with satisfactory accuracy in modeling the fuel ethanol fermentation process.

Mo-modified MnOx for the efficient oxidation of high-concentration glucose to formic acid in water

Severe Mo-modified MnOx binary oxide catalysts were synthesized and served as highly active catalysts for the oxidation of glucose to formic acid in water. A maximum formic acid yield of 79% was achieved from glucose (10 g/L) over Mo(1)-MnOx at 160 °C after 90 min of reaction time. Even when the initial glucose concentration was 110 g/L, 54% of formic acid yield could be obtained with Mo(1)-MnOx, which was almost twice the yield obtained with pristine MnOx as the catalyst. Characterization results showed that the low valence Mn (Mn2+ and Mn3+) ions were the active sites and played key roles in the oxidation of glucose to formic acid. The introduction of Mo could increase the content of low valence Mn (Mn2+ and Mn3+) ions and the adsorbed oxygen (Oads) ratio. A mechanism study indicated that arabinose and glyoxylic acid were the dominant intermediates. Various carbohydrates (xylose, fructose, maltose, sucrose, cellobiose) with high initial concentration afforded formic acid yields >45% demonstrating the potential of Mo(1)-MnOx for transforming lignocellulosic biomass to formic acid.

Optimization of feather degradation by a Bacillus thuringiensis isolate using response surface methodology and investigation of the feather protein hydrolysate structure.

Valorization of chicken feather is a long-sought approach for its sustainable disposal. Being protein rich, hydrolyzed chicken feather has a wide range of applications, not limited to formulation of microbiological culture media, animal feed, and biofertilizers, but extends to synthesis of bioplastic films, cosmetics, and biomedicals. In this study, a potent keratinolytic isolate was recovered from soil and identified by 16S rRNA as Bacillus thuringiensis. Feather degradation by the isolate was optimized through response surface methodology. First, one-variable-at-a-time technique to assign the factors that affect feather degradation, then Box-Behnken central composite design model were employed. The model, involving three independent variables (initial pH, inoculum size, and concentration of supplementary glucose), was significant (R2 =0.9716). According to the model, complete feather degradation is obtained at an inoculum size of B. thuringiensis B4 equal to 1×1010 CFU/ml, when feather meal broth is supplemented with 1.5% (w/v) glucose and pH adjusted to 8.5. Protein content of the lysate was 327.8±25μg/ml, and no carbohydrates were detected. SEM/EDX analysis has shown that the hydrolysate consisted mainly of O, P, S, and Se in addition to carbon, while FTIR images assured the presence of carboxyl and amino groups characteristic of peptides and amino acids.

Critical Parameters in an Enzymatic Way to Obtain the Unsweet Lactose-Free Milk Using Catalase and Glucose Oxidase Co-Encapsulated into Hydrogel with Chemical Cross-Linking.

The presented work involves obtaining and characterising a two-enzymatic one-pot bioreactor, including encapsulated (co-immobilised) glucose oxidase and catalase. The enzymatic capsules were applied to produce unsweet, lactose-free milk during low-temperature catalysis. Furthermore, operational conditions, like pH and aeration, were selected in the paper, which sorts out discrepancies in literature reports. All experiments were carried out at 12 °C, corresponding to milk storage and transportation temperature. Preliminary studies (for reasons of analytical accuracy) were carried out in a buffer (pH, concentration of sugars mimicking conditions in the lactose-free milk, the initial glucose concentration 27.5 g/L) verified by processes carried out in milk in the final stage of the study. The presented results showed the need for regulating pH and the aeration of the reaction mixture in the continuous mode during the process. The procedure of co-immobilisation was performed in an alginate matrix with the cross-linking of glutaraldehyde or carbodiimide while carbodiimide showed better enzymes retention inside alginate capsules. Co-encapsulated enzymes could be used for nine cycles, preserving finally about 40% of the initial activity.

A robust soft sensor based on artificial neural network for monitoring microbial lipid fermentation processes using Yarrowia lipolytica.

Microbial oils produced by Yarrowia lipolytica offer an environmentally friendly and sustainable alternative to petroleum as well as traditional lipids from animals and plants. The accurate measurement of fermentation parameters, including the substrate concentration, dry cell weight, and lipid accumulation, is the foundation of process control, which is indispensable for industrial lipid production. However, it remains a great challenge to measure the complex parameters online during the lipid fermentation process, which is nonlinear, multivariate, and characterized by strong coupling. As a type of AI technology, the artificial neural network model is a powerful tool for handling extremely complex problems, and it can be employed to develop a soft sensor to monitor the microbial lipid fermentation process of Y. lipolytica. In this study, we first analyzed and emphasized the volume of sodium hydroxide and dissolved oxygen concentration as central parameters of the fermentation process. Then, a soft sensor based on a four-input artificial neural network model was developed, in which the input variables were fermentation time, dissolved oxygen concentration, initial glucose concentration, and additional volume of sodium hydroxide. This provides the possibility of online monitoring of dry cell weight, glucose concentration, and lipid production with high accuracy, which can be extended to similar fermentation processes characterized by the addition of bases or acids, as well as changes of the dissolved oxygen concentration.

Co-Fermentation of Glucose-Xylose Mixtures from Agroindustrial Residues by Ethanologenic Escherichia coli: A Study on the Lack of Carbon Catabolite Repression in Strain MS04.

The production of biofuels, such as bioethanol from lignocellulosic biomass, is an important task within the sustainable energy concept. Understanding the metabolism of ethanologenic microorganisms for the consumption of sugar mixtures contained in lignocellulosic hydrolysates could allow the improvement of the fermentation process. In this study, the ethanologenic strain Escherichia coli MS04 was used to ferment hydrolysates from five different lignocellulosic agroindustrial wastes, which contained different glucose and xylose concentrations. The volumetric rates of glucose and xylose consumption and ethanol production depend on the initial concentration of glucose and xylose, concentrations of inhibitors, and the positive effect of acetate in the fermentation to ethanol. Ethanol yields above 80% and productivities up to 1.85 gEtOH/Lh were obtained. Furthermore, in all evaluations, a simultaneous co-consumption of glucose and xylose was observed. The effect of deleting the xyIR regulator was studied, concluding that it plays an important role in the metabolism of monosaccharides and in xylose consumption. Moreover, the importance of acetate was confirmed for the ethanologenic strain, showing the positive effect of acetate on the co-consumption rates of glucose and xylose in cultivation media and hydrolysates containing sugar mixtures.

Citric Acid Production by Yarrowia lipolytica NRRL Y-1094: Optimization of pH, Fermentation Time and Glucose Concentration Using Response Surface Methodology

In this study, three Yarrowia lipolytica strains (Y. lipolytica NRRL Y-1094, Y. lipolytica NRRL YB-423 and Y. lipolytica IFP29) were screened for acid-production capacity and the maximum zone-area was formed by Y. lipolytica NRRL Y-1094. The strain was then selected as a potential citric-acid (CA) producer for further studies. The CA production by Y. lipolytica NRRL Y-1094 was optimized using response surface methodology (RSM) and considering three factors, comprising initial pH-value, fermentation time, and initial glucose-concentration. The highest CA-concentration was 30.31 g/L under optimum conditions (pH 5.5, 6 days, and 125 g/L glucose) in shake flasks. It has been reported that this result gives better results than many productions with shake flasks. According to estimated regression-coefficients for CA concentration, the fermentation time had the greatest impact on CA production, followed by the substrate concentration and initial pH-level, respectively. On the other hand, this study is a fundamental step in solving and optimizing the production mechanism of Y. lipolytica NRRL Y-1094, a microorganism that has not yet been used in CA production with a glucose-based medium. The results suggest that future studies can perform higher yields by optimizing other medium constituents and environmental factors.

Multi-Objective Optimal Regulation of Glucose Concentration in Type I Diabetes Mellitus

Abstract Type I, or insulin-dependent diabetes mellitus, is a chronic disease in which insulin is not adequately produced by the pancreatic β-cells, which leads to a high glucose concentration. In practice, external insulin delivery is the only method to deal with this disease. To this end, a multi-objective optimal control for insulin delivery is introduced in this paper. Three conflicting objectives, including minimizing the risk of hypoglycemia and hyperglycemia, and reducing the amount of injected insulin, are considered. These objectives are minimized simultaneously while tuning the closed-loop system parameters that include the design details of the linear-quadratic regulator (LQR) and estimator speed of convergence. The lower and upper bounds of the LQR setup parameters are determined by Bryson’s rule taking into account the nominal glucose range (70−160 mg/dL) and maximum and minimum pump infusion rates (0.0024−15 mU/min). The lower and upper bounds of the estimator convergence speed are chosen such that the estimator is faster than the fastest mode of the closed-loop system. For computer simulations, Bergman’s minimal model, which is one of the commonly used models, is employed to simulate glucose-insulin dynamics in Type-I diabetic patients. The optimization problem is solved by the nondominated sorting genetic algorithm (NSGA-II), one of the widely used algorithms in solving multi-objective optimization problems (MOPs). The optimal solutions in terms of the Pareto set and its image, the Pareto front, are obtained and analyzed. The results show that the MOP solution introduces many optimal options from which the decision-maker can choose to implement. Furthermore, under high initial glucose levels, parametric variations of Bergman’s model, and external disturbance, the optimal control performance are tested to show that the system can bring glucose levels quickly to the desired value regardless of high initial glucose concentrations, can efficiently work for different patients, and is robust against irregular snacks or meals.

Analysis of Hepatic Lipid Metabolism Model: Simulation and Non-Stationary Global Sensitivity Analysis

Lipid metabolism is a complex process and it is extremely helpful to simulate its performance with different models that explain all the biological processes that comprise it, which then enables its better understanding as well as understanding the kinetics of the process itself. Typically, kinetic parameters are obtained from a number of sources under specific experimental conditions, and they are a source of uncertainty. Sensitivity analysis is a useful technique for controlling the uncertainty of model parameters. It evaluates a model's dependence on its input variables. In this work, hepatic lipid metabolism was mathematically simulated and analyzed. Simulations of the model were performed using different initial plasma glucose (GB) and plasma triacylglyceride (TAG) concentrations according to proposed menus for different meals (breakfast, lunch, snack and dinner). A non-stationary Fourier amplitude sensitivity test (FAST) was applied to analyze the effect of 78 kinetic parameters on 24 metabolite concentrations and 45 reaction rates of the biological part of the hepatic lipid metabolism model at five time points (tf = 10, 50, 100, 250 and 500 min). This study examined the total influence of input parameter uncertainty on the variance of metabolic model predictions. The majority of the propagated uncertainty is due to the interactions of numerous factors rather than being linear from one parameter to one result. Obtained results showed differences in the model control regarding the different initial concentrations and also the changes in the model control over time. The aforementioned knowledge enables dietitians and physicians, working with patients who need to regulate fat metabolism due to illness and/or excessive body mass, to better understand the problem.

The characterisation of Wickerhamomyces anomalus M15, a highly tolerant yeast for bioethanol production using seaweed derived medium.

Advanced generation biofuels have potential for replacing fossil fuels as society moves forward into a net-zero carbon future. Marine biomass is a promising source of fermentable sugars for fermentative bioethanol production; however the medium derived from seaweed hydrolysis contains various inhibitors, such as salts that affected ethanol fermentation efficiency. In this study the stress tolerance of a marine yeast, Wickerhamomyces anomalus M15 was characterised. Specific growth rate analysis results showed that Wickerhamomyces anomalus M15 could tolerate up to 600 g/L glucose, 150 g/L xylose and 250 g/L ethanol, respectively. Using simulated concentrated seaweed hydrolysates, W. anomalus M15’s bioethanol production potential using macroalgae derived feedstocks was assessed, in which 5.8, 45.0, and 19.9 g/L ethanol was produced from brown (Laminaria digitata), green (Ulva linza) and red seaweed (Porphyra umbilicalis) based media. The fermentation of actual Ulva spp. hydrolysate harvested from United Kingdom shores resulted in a relatively low ethanol concentration (15.5 g/L) due to challenges that arose from concentrating the seaweed hydrolysate. However, fed-batch fermentation using simulated concentrated green seaweed hydrolysate achieved a concentration of 73 g/L ethanol in fermentations using both seawater and reverse osmosis water. Further fermentations conducted with an adaptive strain W. anomalus M15-500A showed improved bioethanol production of 92.7 g/L ethanol from 200 g/L glucose and reduced lag time from 93 h to 24 h in fermentation with an initial glucose concentration of 500 g/L. The results indicated that strains W. anomalus M15 and W. anomalus M15-500A have great potential for industrial bioethanol production using marine biomass derived feedstocks. It also suggested that if a concentrated high sugar content seaweed hydrolysate could be obtained, the bioethanol concentration could achieve 90 g/L or above, exceeding the minimum industrial production threshold.

Butyric Acid Production by Fermentation: Employing Potential of the Novel Clostridium tyrobutyricum Strain NRRL 67062

In this study, the ability of a novel strain of Clostridium tyrobutyricum NRRL 67062 to produce butyric acid during glucose fermentation was evaluated. The strain was evaluated for substrate and product inhibition in batch experiments using anaerobic tubes. To characterize glucose inhibition, initial glucose concentrations ranging from 60 to 250 g L−1 were used, and it was demonstrated that a glucose concentration of 250 g L−1 exerted strong inhibition on cell growth and fermentation. To evaluate butyric acid inhibition, the culture was challenged with 5–50 g L−1 of butyric acid at an initial pH of 6.5. These experiments were performed without pH control. When challenged with a butyric acid concentration of 50 g L−1, cell growth was slow; however, it produced 8.25 g L−1 of butyric acid. This suggested that the butyric acid tolerance of the culture was 58 g L−1. In a scaled-up batch experiment, which was performed in a 2.5 L fermentor with an initial glucose concentration of 100 g L−1, the pH was controlled at 6.5. In this experiment, the strain produced 57.86 g L−1 of butyric acid and 12.88 g L−1 of acetic acid, thus producing 70.74 g L−1 of total acids with a productivity of 0.69 g·L−1·h−1. A concentration of 70.74 g L−1 of acids equates to a yield of 0.71 g of acid per g consumed glucose. The maximum cell concentration was 3.80 g L−1, which may have been the reason for high productivity in the batch culture. Finally, corn steep liquor (CSL; a commercial nutrient solution) provided greater growth and acid production than the refined medium.

Bioethanol production from microalgae biomass at high-solids loadings

Industrial adoption of microalgae biofuel technology has always been hindered by its economic viability. To increase the feasibility of bioethanol production from microalgae, fermentation was applied to Chlorella vulgaris FSP-E biomass at high-solids loading conditions. First, Chlorella vulgaris FSP-E was cultivated to produce microalgae biomass with high carbohydrate content. Next, different ethanol-producing microorganisms were screened. Saccharomyces cerevisiae FAY-1 showed no inhibition when fermenting high initial glucose concentrations and was selected for the fermentation experiments at high-solids loadings. Optimization of acid hydrolysis at high biomass loading was also performed. The fermentation of microalgal biomass hydrolysate produced a final ethanol concentration and yield higher than most reported literature using microalgae feedstock. In addition, the kinetics of bioethanol fermentation of microalgae hydrolysate under high-solids loading were evaluated. These results showed the potential of fermenting microalgae biomass at high-solids loading in improving the viability of microalgae bioethanol production.

Different glucose analyzers report different glucose concentration values in term newborns

BackgroundThe American Academy of Pediatrics and Pediatric Endocrine Society neonatal hypoglycemia guidelines based their glucose concentration treatment thresholds on studies that predominantly used Beckman and Yellow Springs Glucose Oxidase Analyzers. Currently, a majority (76%) of U.S. hospital laboratories utilizing glucose oxidase methodology use Vitros® Glucose Analyzers. However, a bias of ~+5% between glucose concentrations from Beckman vs. Vitros Glucose Analyzers has been reported; this could have a clinically significant effect when using published guideline treatment thresholds.MethodsTo determine if there is similar instrument bias between Beckman and Vitros Analyzers in reported glucose concentrations from term newborns, we compared plasma glucose concentrations measured within the first 3 h after birth by Beckman vs. Vitros Analyzers in a total of 1,987 newborns (Beckman n = 904, Vitros n = 1,083). Data were fit using nonlinear cubic spline models between collection time and glucose concentration.ResultsThe non-linear patterns of initial glucose concentrations (during the first 3 h after birth) as measured by Beckman and Vitros Analyzers paralleled each other with no overlap of the fit spline curve 95% confidence intervals, with an approximate +5 mg/dL constant bias. Additionally, in method comparison studies performed in the Chemistry Laboratory on adult samples, there was a +4.2-7.4 mg/dL measured glucose bias for the Beckman vs. Vitros Analyzer.ConclusionGlucose concentrations from term, appropriate size for gestational age newborns were about 5 mg/dL higher when measured by Beckman vs. Vitros Analyzers. Perhaps, concentrations of 45 mg/dL reported from Beckman Analyzers may be equivalent to 40 mg/dL from Vitros Analyzers. When managing neonatal hypoglycemia, it is important to know which analyzer was used and whether adjusting for potential instrument bias is necessary when following published guidelines.

The Effect of Different Substrates on the Morphological Features and Polyols Production of Endomyces magnusii Yeast during Long-Lasting Cultivation.

The study on the influence of different glucose concentrations (2%, 0.5%, and 0.2%) and glycerol (1%) on the morphological and physiological features, as well as the composition of soluble carbohydrates, was performed using Endomyces magnusii yeast. Two-factor analysis of variance with repetitions to process the data of the cell size changes showed that the substrate type affected cell size the most. The cells with 2% glucose were 30–35% larger than those growing on glycerol. The decrease in the initial glucose concentration up to 0.5–0.2% slightly changed the cell length. However, even in the logarithmic growth phase pseudo-mycelium of two to four cells appeared in the cultures when using low glucose, unlike those using glycerol. Throughout the whole experiment, more than 90% of the populations remained viable on all of the substrates tested. The ability for colony formation decreased during aging. Nevertheless, at the three-week stage, upon substrate restriction (0.2% glucose), it was twice higher than those under the other conditions. The respiration rate also decreased and exceeded not more than 10% of that in the logarithmic phase. By the end of the experiment, the cyanide-sensitive respiration share decreased up to 40% for all types of substrates. The study of soluble cytosol carbohydrates showed that the cultures using 2% glucose and 1% glycerol contained mainly arabitol and mannitol, while at low glucose concentrations they were substituted for inositol. The formation of inositol is supposed to be related to pseudo-mycelium formation. The role of calorie restriction in the regulation of carbohydrate synthesis and the composition in the yeast and its biotechnological application is under consideration.