Two-dimensional fluorescence spectroscopy: a novel approach for controlling fed-batch cultivations

In industrial fed-batch cultivations it is often necessary to control substrate concentrations at a low level to prevent the production of overflow metabolites and thus optimize the biomass yield. A new method for on-line monitoring and fed-batch control based on fluorescence measurements has been developed. Via instantaneous in situ measurements and multivariate data analysis a chemometric model has been established, which enables the rapid detection of ethanol production at aerobic Saccharomyces cerevisiae fed-batch cultivations. The glucose feed rate is controlled by predicting the metabolic state directly from the fluorescence intensities. Thus, ethanol production could be avoided completely while increasing the biomass yield accordingly. The robust instrumentation is suitable for industrial applications.     

Rapid determination of sugar content in biomass hydrolysates using nuclear magnetic resonance spectroscopy

Large populations of potential cellulosic biomass feedstocks are currently being screened for fuel and chemical applications. The monomeric sugar content, released through hydrolysis, is of particular importance and is currently measured with time‐consuming HPLC methods. A method for sugar detection is presented here that employs ¹H NMR spectra regressed against primary HPLC sugar concentration data to build partial least squares (PLS) models. The PLS2 model is able to predict concentrations of both major sugar components, like glucose and xylose, and minor sugars, such as arabinose and mannose, in biomass hydrolysates. The model was built with 65 samples from a variety of different biomass species and covers a wide range of sugar concentrations. Model predictions were validated with a set of 15 samples which were all within error of both HPLC and NMR integration measurements. The data collection time for these NMR measurements is less than 20 min, offering a significant improvement to the 1 h acquisition time that is required for HPLC. Biotechnol. Bioeng. 2013; 110: 721–728. © 2012 Wiley Periodicals, Inc.     

On-line monitoring of recombinant bacterial cultures using multi-wavelength fluorescence spectroscopy

Multi-wavelength fluorescence spectroscopy was evaluated as a tool for on-line monitoring of recombinant Escherichia coli cultivations expressing human basic fibroblast growth factor (hFGF-2). The data sets for the various combinations of the excitation and emission spectra from batch cultivations were analyzed using principal component analysis. Chemometric models (the partial least squares method) were developed for correlating the fluorescence data and the experimentally measured variables such as the biomass and glucose concentrations as well as the carbon dioxide production rate. Excellent correlations were obtained for these variables for the calibration cultivations. The predictability of these models was further tested in batch and fed-batch cultivations. The batch cultivations were well predicted by the PLS models for biomass, glucose concentrations and carbon dioxide production rate (RMSEPs were respectively 5%, 7%, 9%). However, when tested for biomass concentrations in fed-batch cultivations (with final biomass three times higher than the highest calibration data) the models had good predictability at high growth rates (RMSEPs were 3% and 4%, respectively for uninduced and induced fed-batch cultivations), which was as good as for the batch cultivations used for developing the models (RMSEPs were 3% and 5%, respectively for uninduced and induced batch cultivations). The fed-batch cultivations performed at low growth rates exhibited much higher fluorescence for fluorophores such as flavin and NAD(P)H as compared to fed-batch cultivations at high growth rate. Therefore, the PLS models tended to over-predict the biomass concentrations at low growth rates. Obviously the cells changed their concentration of biogenic fluorophores depending on the growth rate. Although multi-wavelength fluorescence spectroscopy is a valuable tool for on-line monitoring of bioprocess, care must be taken to re-calibrate the PLS models at different growth rates to improve the accuracy of predictions.     

Real‐time monitoring of high‐gravity corn mash fermentation using in situ raman spectroscopy

In situ Raman spectroscopy was employed for real‐time monitoring of simultaneous saccharification and fermentation (SSF) of corn mash by an industrial strain of Saccharomyces cerevisiae. An accurate univariate calibration model for ethanol was developed based on the very strong 883 cm^?1 C–C stretching band. Multivariate partial least squares (PLS) calibration models for total starch, dextrins, maltotriose, maltose, glucose, and ethanol were developed using data from eight batch fermentations and validated using predictions for a separate batch. The starch, ethanol, and dextrins models showed significant prediction improvement when the calibration data were divided into separate high‐ and low‐concentration sets. Collinearity between the ethanol and starch models was avoided by excluding regions containing strong ethanol peaks from the starch model and, conversely, excluding regions containing strong saccharide peaks from the ethanol model. The two‐set calibration models for starch (R² = 0.998, percent error = 2.5%) and ethanol (R² = 0.999, percent error = 2.1%) provide more accurate predictions than any previously published spectroscopic models. Glucose, maltose, and maltotriose are modeled to accuracy comparable to previous work on less complex fermentation processes. Our results demonstrate that Raman spectroscopy is capable of real time in situ monitoring of a complex industrial biomass fermentation. To our knowledge, this is the first PLS‐based chemometric modeling of corn mash fermentation under typical industrial conditions, and the first Raman‐based monitoring of a fermentation process with glucose, oligosaccharides and polysaccharides present. Biotechnol. Bioeng. 2013; 110: 1654–1662. © 2013 Wiley Periodicals, Inc.     

On-line multi-analyzer monitoring of biomass, glucose and acetate for growth rate control of a Vibrio cholerae fed-batch cultivation

In situ near-infrared (NIR) spectroscopy and in-line electronic nose (EN) mapping were used to monitor and control a cholera-toxin producing Vibrio cholerae fed-batch cultivation carried out with a laboratory method as well as with a production method. Prediction models for biomass, glucose and acetate using NIR spectroscopy were developed based on spectral identification and partial-least squares (PLS) regression resulting in high correlation to reference data (standard errors of prediction for biomass, glucose and acetate were 0.20 gl(-1), 0.26 gl(-1) and 0.28 gl(-1)). A compensation algorithm for aerated bioreactor disturbances was integrated in the model computation, which in particular improved the prediction by the biomass model. First, the NIR data were applied together with EN in-line data selected by principal component analysis (PCA) for generating a trajectory representation of the fed-batch cultivation. A correlation between the culture progression and EN signals was demonstrated, which proved to be beneficial in monitoring the culture quality. It was shown that a deviation from a normal cultivation behavior could easily be recognized and that the trajectory was able to alarm a bacterial contamination. Second, the NIR data indicated the potential of predicting the concentration of formed cholera toxin with a model prediction error of 0.020 gl(-1). Third, the on-line biomass prediction based on the NIR model was used to control the overflow metabolism acetate formation of the V. cholerae culture. The controller compared actual specific growth rate as estimated from the prediction with the critical acetate formation growth rate, and from that difference adjusted the glucose feed rate.     

Demonstration of the Crabtree effect in Phaffia rhodozyma during continuous and fed-batch cultivation

By monitoring cell yield and fermentation products during fed-batch and continuous growth, Pfaffia rhodozyma was shown to exhibit the Crabtree effect. In fed-batch culture at feed concentrations of 27 and 55 g glucose/l there was good agreement between the observed biomass formation and that predicted by a mass balance model. At 125 g glucose/l in the feed, biomass formation was less than predicted and fermentation products such as ethanol and acetic acid accumulated in the culture medium. In continuous culture with a feed concentration of 10 g glucose/l, the Crabtree effect became apparent at a dilution rate of 0.1 h -1 . Aerobic fermentation did not occur provided the sugar substrate was maintained at a concentration of less than 0.5 g/l. Although the cell yield coefficient was reduced from 0.5 g/g to 0.16 g/g during aerobic fermentation, the carotenoid content of the cells was unaffected.     

On-line estimation of sugar concentration for control of fed-batch fermentation of lignocellulosic hydrolyzates by Saccharomyces cerevisiae

A feed control strategy, based on estimated sugar concentrations, was developed with the purpose of avoiding severe inhibition of the yeast Saccharomyces cerevisiae during fermentation of spruce hydrolyzate. The sum of the fermentable hexose sugars, glucose and mannose, was estimated from on-line measurements of carbon dioxide evolution rate and biomass concentration by use of a simple stoichiometric model. The feed rate of the hydrolyzate was controlled to maintain constant sugar concentration during fed-batch fermentation, and the effect of different set-point concentrations was investigated using both untreated and detoxified hydrolyzates. The fed-batch cultivations were evaluated with respect to cellular physiology in terms of the specific ethanol productivities, ethanol yields, and viability of the yeast. The simple stoichiometric model used resulted in a good agreement between estimated sugar concentrations and off-line determinations of sugar concentrations. Furthermore, the control strategy used made it possible to maintain a constant sugar concentration without major oscillations in the feed rate or the sugar concentration. For untreated hydrolyzates the average ethanol productivity could be increased by more than 130% compared to batch fermentation. The average ethanol productivity was increased from 0.12 to 0.28 g/g h. The productivity also increased for detoxified hydrolyzates, where an increase of 16% was found (from 0.50 to 0.58 g/g h).     

Analytical monitoring of alcoholic fermentation using NIR spectroscopy

Alcoholic fermentation under Saccharomyces cerevisiae yeasts is governed largely by glucose uptake, biomass formation, ethanol and glycerin production, and acidification. In this work, PLS calibration models were developed with a view to determining these analytical parameters from near infrared spectra and analytical data provided by the corresponding reference methods. The models were applied to a set of samples obtained from various fermentation processes. The glucose, ethanol, and biomass values predicted by the models exhibited a high correlation with those provided by the reference method.     

A model of xylitol production by the yeast Candida mogii

Production of xylitol from xylose in batch fermentations of Candida mogii ATCC 18364 is discussed in the presence of glucose as the cosubstrate. Various initial ratios of glucose and xylose concentrations are assessed for their impact on yield and rate of production of xylitol. Supplementation with glucose at the beginning of the fermentation increased the specific growth rate, biomass yield and volumetric productivity of xylitol compared with fermentation that used xylose as the sole carbon source. A mathematical model is developed for eventual use in predicting the product formation rate and yield. The model parameters were estimated from experimental observations, using a genetic algorithm. Batch fermentations, which were carried out with xylose alone and a mixture of xylose and glucose, were used to validate the model. The model fitted well with the experimental data of cell growth, substrate consumption and xylitol production.     

On-line process monitoring and chemometric modeling with 2D fluorescence spectra obtained in recombinant E. coli fermentations

2D spectrofluorometry produces a large volume of spectral data during fermentation processes with recombinant E. coli, which can be analyzed using chemometric methods such as principal component analysis (PCA), principal component regression (PCR) and partial least square regression (PLS). An analysis of the spectral data by PCA results in scores and loadings that are not only visualized in the score-loading plots but are also used to monitor the fermentation processes on-line. The score plots provided useful qualitative information on four fermentation processes for the production of extracellular 5-aminolevulinic acid (ALA). Two chemometric models (PCR and PLS) were used to examine the correlation between the 2D fluorescence spectra and a few parameters of the fermentation processes. The results showed that PLS had slightly better calibration and prediction performance than PCR.     

High-cell-density fed-batch cultivation of the docosahexaenoic acid producing marine alga Crypthecodinium cohnii

The heterotrophic marine alga Crypthecodinium cohnii is known to produce docosahexaenoic acid (DHA), a polyunsaturated fatty acid with food and pharmaceutical applications, during batch cultivation on complex media containing sea salt, yeast extract, and glucose. In the present study, fed-batch cultivation was studied as an alternative fermentation strategy for DHA production. Glucose and acetic acid were compared as carbon sources. For both substrates, the feed rate was adapted to the maximum specific consumption rate of C. cohnii. In glucose-grown cultures, this was done by maintaining a significant glucose concentration (between 5 and 20 g/L) throughout fermentation. In acetic acid-grown cultures, the medium feed was automatically controlled via the culture pH. A feed consisting of acetic acid (50% w/w) resulted in a higher overall volumetric productivity of DHA (r(DHA)) than a feed consisting of 50% (w/v) glucose (38 and 14 mg/L/h, respectively). The r(DHA) was further increased to 48 mg/L/h using a feed consisting of pure acetic acid. The latter fermentation strategy resulted in final concentrations of 109 g/L dry biomass, 61 g/L lipid, and 19 g/L DHA. These are the highest biomass, lipid, and DHA concentrations reported to date for a heterotrophic alga. Vigorous mixing was required to sustain aerobic conditions during high-cell-density cultivation. This was complicated by culture viscosity, which resulted from the production of viscous extracellular polysaccharides. These may present a problem for large-scale industrial production of DHA. Addition of a commercial polysaccharide-hydrolase preparation could decrease the viscosity of the culture and the required stirring.     

A Mathematical model for ethanol production by extractive fermentation in a continuous stirred tank fermentor

Extractive fermentation is a technique that can be used to reduce the effect of end product inhibition through the use of a water-immiscible phase that removes fermentation products in situ. This has the beneficial effect of not only removing inhibitory products as they are formed (thus keeping reaction rates high) but also has the potential for reducing product recovery costs. We have chosen to examine the ethanol fermentation as a model system for end product inhibition and extractive fermentation and have developed a computer model predicting the productivity enhancement possible with this technique together with other key parameters such as extraction efficiency and residual glucose concentration. The model accommodates variable liquid flowrates entering and leaving the system, since it was found that the aqueous outlet flowrate could be up to 35% lower than the inlet flowrate during extractive fermentation of concentrated glucose feeds due to the continuous removal of ethanol from the fermentation broth by solvent extraction. The model predicts a total ethanol productivity of 82.6 g/L h if a glucose feed of 750 g/L is fermented with a solvent having a distribution coefficient of 0.5 at a solvent dilution rate of 5.0 h(-1). This is more than 10 times higher than for a conventional chemostat fermentation of a 250 g/L glucose feed. The model has furthermore illustrated the possible trade-offs that exist between obtaining a high extraction efficiency and a low residual glucose concentration.     

Optimization and robustness analysis of hybridoma cell fed-batch cultures using the overflow metabolism model

The maximization of biomass productivity in fed-batch cultures of hybridoma cells is analyzed based on the overflow metabolism model. Due to overflow metabolism, often attributed to limited oxygen capacity, lactate and ammonia are formed when the substrate concentrations (glucose and glutamine) are above a critical value, which results in a decrease in biomass productivity. Optimal feeding rate, on the one hand, for a single feed stream containing both glucose and glutamine and, on the other hand, for two separate feed streams of glucose and glutamine are determined using a Nelder–Mead simplex optimization algorithm. The optimal multi exponential feed rate trajectory improves the biomass productivity by 10 % as compared to the optimal single exponential feed rate. Moreover, this result is validated by the one obtained with the analytical approach in which glucose and glutamine are fed to the culture so as to control the hybridoma cells at the critical metabolic state, which allows maximizing the biomass productivity. The robustness analysis of optimal feeding profiles obtained with different optimization strategies is considered, first, with respect to parameter uncertainties and, finally, to model structure errors.     

Modelling and optimization of fermentation factors for enhancement of alkaline protease production by isolated Bacillus circulans using feed-forward neural network and genetic algorithm

Aim: Modelling and optimization of fermentation factors and evaluation for enhanced alkaline protease production by Bacillus circulans. Methods and Results: A hybrid system of feed‐forward neural network (FFNN) and genetic algorithm (GA) was used to optimize the fermentation conditions to enhance the alkaline protease production by B. circulans. Different microbial metabolism regulating fermentation factors (incubation temperature, medium pH, inoculum level, medium volume, carbon and nitrogen sources) were used to construct a ‘6‐13‐1’ topology of the FFNN for identifying the nonlinear relationship between fermentation factors and enzyme yield. FFNN predicted values were further optimized for alkaline protease production using GA. The overall mean absolute predictive error and the mean square errors were observed to be 0·0048, 27·9, 0·001128 and 22·45 U ml^?1 for training and testing, respectively. The goodness of the neural network prediction (coefficient of R²) was found to be 0·9993. Conclusions: Four different optimum fermentation conditions revealed maximum enzyme production out of 500 simulated data. Concentration‐dependent carbon and nitrogen sources, showed major impact on bacterial metabolism mediated alkaline protease production. Improved enzyme yield could be achieved by this microbial strain in wide nutrient concentration range and each selected factor concentration depends on rest of the factors concentration. The usage of FFNN–GA hybrid methodology has resulted in a significant improvement (>2·5‐fold) in the alkaline protease yield. Significance and Impact of the Study: The present study helps to optimize enzyme production and its regulation pattern by combinatorial influence of different fermentation factors. Further, the information obtained in this study signifies its importance during scale‐up studies.     

Cole–Cole, linear and multivariate modeling of capacitance data for on-line monitoring of biomass

This work evaluates three techniques of calibrating capacitance (dielectric) spectrometers used for on-line monitoring of biomass: modeling of cell properties using the theoretical Cole–Cole equation, linear regression of dual-frequency capacitance measurements on biomass concentration, and multivariate (PLS) modeling of scanning dielectric spectra. The performance and robustness of each technique is assessed during a sequence of validation batches in two experimental settings of differing signal noise. In more noisy conditions, the Cole–Cole model had significantly higher biomass concentration prediction errors than the linear and multivariate models. The PLS model was the most robust in handling signal noise. In less noisy conditions, the three models performed similarly. Estimates of the mean cell size were done additionally using the Cole–Cole and PLS models, the latter technique giving more satisfactory results.     

Enhanced discrimination and calibration of biomass NIR spectral data using non-linear kernel methods

Rapid methods for the characterization of biomass for energy purpose utilization are fundamental. In this work, near infrared spectroscopy is used to measure ash and char content of various types of biomass. Very strong models were developed, independently of the type of biomass, to predict ash and char content by near infrared spectroscopy and multivariate analysis. Several statistical approaches such as principal component analysis (PCA), orthogonal signal correction (OSC) treated PCA and partial least squares (PLS), Kernel PCA and PLS were tested in order to find the best method to deal with near infrared data to classify and predict these biomass characteristics. The model with the highest coefficient of correlation and the lowest RMSEP was obtained with OSC-treated Kernel PLS method.     

无载体固定化酵母细胞木薯淀粉质原料酒精连续发酵研究

以木薯粉糖化液为发酵底物,在总发酵体积(有效)为15L的悬浮床生物反应器中,对一株粟酒裂殖酵母变异株进行一级和二级连续发酵研究。结果表明,二级连续发酵系统可明显改善一级系统的不足,并取得了平均流加糖液浓度150g/L,发酵强度为97g/L.h,流出液酒精浓度727g/L,残糖浓度374g./L,总糖利用率达90%的较好结果;整个系统在连续一个月的运行中从未发现染菌现象,发酵操作稳定。     

Energetics and kinetics of maltose transport in Saccharomyces cerevisiae: a continuous culture study.

In Saccharomyces cerevisiae, maltose is transported by a proton symport mechanism, whereas glucose transport occurs via facilitated diffusion. The energy requirement for maltose transport was evaluated with a metabolic model based on an experimental value of YATP for growth on glucose and an ATP requirement for maltose transport of 1 mol.mol-1. The predictions of the model were verified experimentally with anaerobic, sugar-limited chemostat cultures growing on a range of maltose-glucose mixtures at a fixed dilution rate of 0.1 h-1. The biomass yield (grams of cells.gram of sugar-1) decreased linearly with increasing amounts of maltose in the mixture. The yield was 25% lower during growth on maltose than during that on glucose, in agreement with the model predictions. During sugar-limited growth, the residual concentrations of maltose and glucose in the culture increased in proportion to their relative concentrations in the medium feed. From the residual maltose concentration, the in situ rates of maltose consumption by cultures, and the Km of the maltose carrier for maltose, it was calculated that the amount of this carrier was proportional to the in situ maltose consumption rate. This was also found for the amount of intracellular maltose. These two maltose-specific enzymes therefore exert high control over the maltose flux in S. cerevisiae in anaerobic, sugar-limited, steady-state cultures.     

Control of nitrate concentration in fermentations of Corynebacterium glutamicum

A nitrate control system has been devised for the maintenance of stable nitrate concentrations throughout fed-batch fermentations of Corynebacterium glutamicum. The feedback control system was based on the use of a nitrate-ion-selective electrode to directly monitor the nitrate levels in the fermentor and an automatic controller to activate a nitrate feed pump. The electrode which was used for controlling the nitrate level was stable through-out the fermentation period. The apparent maximum specific growth rate, biomass production, protein production, biomass yields on glucose and nitrate, and amino acid production were all optimal at approximately 50mM nitrate.