Genome-scale analysis of Saccharomyces cerevisiae metabolism and ethanol production in fed-batch culture

A dynamic flux balance model based on a genome-scale metabolic network reconstruction is developed for in silico analysis of Saccharomyces cerevisiae metabolism and ethanol production in fed-batch culture. Metabolic engineering strategies previously identified for their enhanced steady-state biomass and/or ethanol yields are evaluated for fed-batch performance in glucose and glucose/xylose media. Dynamic analysis is shown to provide a single quantitative measure of fed-batch ethanol productivity that explicitly handles the possible tradeoff between the biomass and ethanol yields. Productivity optimization conducted to rank achievable fed-batch performance demonstrates that the genetic manipulation strategy and the fed-batch operating policy should be considered simultaneously. A library of candidate gene insertions is assembled and directly screened for their achievable ethanol productivity in fed-batch culture. A number of novel gene insertions with ethanol productivities identical to the best metabolic engineering strategies reported in previous studies are identified, thereby providing additional targets for experimental evaluation. The top performing gene insertions were substrate dependent, with the highest ranked insertions for glucose media yielding suboptimal performance in glucose/xylose media. The analysis results suggest that enhancements in biomass yield are most beneficial for the enhancement of fed-batch ethanol productivity by recombinant xylose utilizing yeast strains. We conclude that steady-state flux balance analysis is not sufficient to predict fed-batch performance and that the media, genetic manipulations, and fed-batch operating policy should be considered simultaneously to achieve optimal metabolite productivity.     

Dynamic optimization of hybridoma growth in a fed-batch bioreactor

This study addressed the problem of maximizing cell mass and monoclonal antibody production from a fed-batch hybridoma cell culture. We hypothesized that inaccuracies in the process model limited the mathematical optimization. On the basis of shaker flask data, we established a simple phenomenological model with cell mass and lactate production as the controlled variables. We then formulated an optimal control algorithm, which calculated the process-model mismatch at each sampling time, updated the model parameters, and re-optimized the substrate concentrations dynamically throughout the time course of the batch. Manipulated variables were feed rates of glucose and glutamine. Dynamic parameter adjustment was done using a fuzzy logic technique, while a heuristic random optimizer (HRO) optimized the feed rates. The parameters selected for updating were specific growth rate and the yield coefficient of lactate from glucose. These were chosen by a sensitivity analysis. The cell mass produced using dynamic optimization was compared to the cell mass produced for an unoptimized case, and for a one-time optimization at the beginning of the batch. Substantial improvements in reactor productivity resulted from dynamic re-optimization and parameter adjustment. We demonstrated first that a single offline optimization of substrate concentration at the start of the batch significantly increased the yield of cell mass by 27% over an unoptimized fermentation. Periodic optimization online increased yield of cell mass per batch by 44% over the single offline optimization. Concomitantly, the yield of monoclonal antibody increased by 31% over the off-line optimization case. For batch and fed-batch processes, this appears to be a suitable arrangement to account for inaccuracies in process models. This suggests that implementation of advanced yet inexpensive techniques can improve performance of fed-batch reactors employed in hybridoma cell culture.     

Multi-stage high cell continuous fermentation for high productivity and titer

We carried out the first simulation on multi-stage continuous high cell density culture (MSC-HCDC) to show that the MSC-HCDC can achieve batch/fed-batch product titer with much higher productivity to the fed-batch productivity using published fermentation kinetics of lactic acid, penicillin and ethanol. The system under consideration consists of n-serially connected continuous stirred-tank reactors (CSTRs) with either hollow fiber cell recycling or cell immobilization for high cell-density culture. In each CSTR substrate supply and product removal are possible. Penicillin production is severely limited by glucose metabolite repression that requires multi-CSTR glucose feeding. An 8-stage C-HCDC lactic acid fermentation resulted in 212.9 g/L of titer and 10.6 g/L/h of productivity, corresponding to 101 and 429% of the comparable lactic acid fed-batch, respectively. The penicillin production model predicted 149% (0.085 g/L/h) of productivity in 8-stage C-HCDC with 40 g/L of cell density and 289% of productivity (0.165 g/L/h) in 7-stage C-HCDC with 60 g/L of cell density compared with referring batch cultivations. A 2-stage C-HCDC ethanol experimental run showed 107% titer and 257% productivity of the batch system having 88.8 g/L of titer and 3.7 g/L/h of productivity. MSC-HCDC can give much higher productivity than batch/fed-batch system, and yield a several percentage higher titer as well. The productivity ratio of MSC-HCDC over batch/fed-batch system is given as a multiplication of system dilution rate of MSC-HCDC and cycle time of batch/fed-batch system. We suggest MSC-HCDC as a new production platform for various fermentation products including monoclonal antibody.     

In silico analysis of bioethanol production from glucose/xylose mixtures during fed-batch fermentation of co-culture and mono-culture systems

This study presents a detailed in silico analysis of bioethanol production from glucose/xylose mixtures of various compositions by fed-batch co-culture and mono-culture fermentation of specialized microbes. The mono-culture consists of recombinant Saccharomyces cerevisise that can metabolize both hexose and pentose sugars while the co-culture system consists of substrate-selective microbes. Dynamic flux balance models based on available genome-scale reconstructions of the microorganisms have been used to analyze bioethanol production in fed-batch culture with constant feed rates and the maximization of ethanol productivity is addressed by computing optimal aerobic-anaerobic switching times. The simulation results clearly point to the superior performance of fed-batch fermentation of microbial co-culture against fed-batch fermentation of mono-culture for bioethanol production from glucose/xylose mixtures. A set of potential genetic engineering strategies for enhancement of S. cerevisiae and Escherichia coli strains performance have been identified. Such in silico predictions using genome-scale models provide valuable guidance for conducting in vivo metabolic engineering experiments.     

Bioethanol from fermentation of cassava pulp in a fibrous-bed bioreactor using immobilized Δldh, a genetically engineered Thermoanaerobacterium aotearoense

There is an increasing worldwide interest in bioethanol production from agricultural, industrial, and urban residues for both ecological and economic reasons. The acid hydrolysis of cassava pulp to reducing sugars and their fermentation to ethanol were evaluated in a fibrousbed bioreactor with immobilized Δldh, a genetically engineered Thermoanaerobacterium aotearoense. A maximum yield of total reducing sugars of 53.5% was obtained after 8 h of hydrolysis at 85oC in 0.4 mol/L hydrochloric acid with a solid-to-liquid ratio of 1:20, which was optimized by using an orthogonal design based on preliminary experiments. In the FBB, the fed-batch fermentation, using glucose as the sole carbon source, gave a maximum ethanol production of 38.3 g/L with a yield of 0.364 g/g in 100 h; whereas the fed-batch fermentation, using xylose as the sole carbon source, gave 34.1 g/L ethanol with a yield of 0.342 g/g in 135 h. When cassava pulp hydrolysate was used as a carbon source, 39.1 g/L ethanol with a yield of 0.123 g/g cassava pulp in185 h was observed, using the fed-batch fermentation model. In addition, for repeated batch fermentation of cassava pulp hydrolysate carried out in the fibrous-bed bioreactor, long-term operation with high ethanol yield and volumetric productivity were achieved. The above results show that the acid hydrolysate of cassava pulp can be used for ethanol production in a fibrous-bed bioreactor, although some inhibition phenomena were observed during the process of fermentation.     

Calorimetric control of fed-batch cultures of Saccharomyces cerevisiae

Calorimetry has been used to control the glucose feeding in fed-batch cultures of S. cerevisiae in order to avoid ethanol formation and maintain a fully respiratory metabolism. Comparisons between batch and fed-batch cultivations showed that the former had a much lower growth yield. The growth yields for fed-batch cultivations were more than 30% higher than for batch cultures. However, energy balance calculations showed that a large part of the increase could be explained by the evaporation of ethanol during batch cultivations. When the growth yields obtained from the batch cultures were corrected for the evaporation of ethanol, the increase in growth yield for fed-batch cultures was about 10%.     

Increased heterologous protein production by Saccharomyces cerevisiae growing on ethanol as sole carbon source

Saccharomyces cerevisiae is a widely used host organism for the production of heterologous proteins, often cultivated in glucose-based fed-batch processes. This production system however has many factors limiting the productivity, mainly towards the end of the fermentation. For the optimised production of a Camelid antibody fragment this process was evaluated. In shake flask cultivations, it was found that ethanol has a strong effect on productivity increase and therefore glucose and ethanol fed-batch fermentations were compared. It appeared that specific heterologous protein production was up to five times higher in the ethanol cultivation and could be further optimised. Then the key characteristics of ethanol fed-batch fermentations such as growth rate and specific production were determined under ethanol limitation and accumulation and growth limiting conditions in the final phase of the process. It appeared that an optimal production process should have an ethanol accumulation throughout the feed phase of approximately 1% v/v in the broth and that production remains very efficient even in the last phase of the process. This productivity increase on ethanol versus glucose was also proven for several other Camelid antibody fragments some of which were heavily impaired in secretion on glucose, but very well produced on ethanol. This leads to the suggestion that the ethanol effect on improved heterologous protein production is linked to a stress response and folding and secretion efficiency.     

产PCA基因工程菌M18G反复补料分批培养研究

吩嗪-1-羧酸(PCA)是一种广谱、高效的微生物源农药,采用反复补料分批培养工艺可提高PCA合成速率,为实现PCA的商业化生产打下了良好的基础。本试验针对高产PCA的基因工程菌M18G,首先在摇瓶培养条件下,用正交试验法研究了培养基中各主要营养因子葡萄糖、黄豆粉、甘油、95%乙醇等对PCA产量的影响,并确定了适合PCA分泌的最佳培养基(1L)为:葡萄糖6g,黄豆粉40g,甘油6mL,95%乙醇5.9mL;然后确定了反复补料分批培养时更换新鲜培养基的最佳时间为每次培养进行48h后、体积比例为90%。在此条件下,培养进行五个周期后,PCA的合成速率可达到2.27mg/h,是优化后分批培养的1.34倍,同时延长了培养周期,有利于提高设备使用率,降低生产成本。     

Dynamic model-based evaluation of process configurations for integrated operation of hydrolysis and co-fermentation for bioethanol production from lignocellulose

In this study a number of different process flowsheets were generated and their feasibility evaluated using simulations of dynamic models. A dynamic modeling framework was used for the assessment of operational scenarios such as, fed-batch, continuous and continuous with recycle configurations. Each configuration was evaluated against the following benchmark criteria, yield (kg ethanol/kg dry-biomass), final product concentration and number of unit operations required in the different process configurations. The results show that simultaneous saccharification and co-fermentation (SSCF) operating in continuous mode with a recycle of the SSCF reactor effluent, results in the best productivity of bioethanol among the proposed process configurations, with a yield of 0.18 kg ethanol/kgdry-biomass.     

Inline noninvasive Raman monitoring and feedback control of glucose concentration during ethanol fermentation

Raman spectroscopy as a process analytical technology tool was implemented for the monitoring and control of ethanol fermentation carried out with Saccharomyces cerevisiae. The need for the optimization of bioprocesses such as ethanol production, to increase product yield, enhanced the development of control strategies. The control system developed by the authors utilized noninvasive Raman measurements to avoid possible sterilization problems. Real-time data analysis was applied using partial least squares regression (PLS) method. With the aid of spectral pretreatment and multivariate data analysis, the monitoring of glucose and ethanol concentration was successful during yeast fermentation with the prediction error of 4.42 g/L for glucose and 2.40 g/L for ethanol. By Raman spectroscopy-based feedback control, the glucose concentration was maintained at 100 g/L by the automatic feeding of concentrated glucose solution. The control of glucose concentration during fed-batch fermentation resulted in increased ethanol production. Ethanol yield of 86% was achieved compared to the batch fermentation when 75 % yield was obtained. The results show that the use of Raman spectroscopy for the monitoring and control of yeast fermentation is a promising way to enhance process understanding and achieve consistently high production yield.     

Aeration alleviates ethanol inhibition and glycerol production during fed-batch ethanol fermentation

In this study, we investigated the effects of aeration on ethanol inhibition and glycerol production during fed-batch ethanol fermentation. When aeration was conducted at 0.13, 0.33, and 0.8 vvm, the ethanol productivity, specific ethanol production rate, and ethanol yield in the presence of greater than 100 g/L of ethanol were higher than when aeration was not conducted. In addition, estimation of the parameters (α and β) in a model equation of ethanol inhibition kinetics indicated that aeration alleviated ethanol inhibition against the specific growth rate and the specific ethanol production rate. Specifically, when aeration was conducted, the glycerol yield and specific glycerol production rate decreased approximately 50 and 70%, respectively. Finally, the results of this study indicated that aeration during fed-batch ethanol fermentation may improve the ethanol concentration in the final culture broth, as well as the ethanol productivity.     

Modeling of Xanthophyllomyces dendrorhous growth on glucose and overflow metabolism in batch and fed-batch cultures for astaxanthin production

An astaxanthin-producing yeast Xanthophyllomyces dendrorhous ENM5 was cultivated in a liquid medium containing 50 g/L glucose as the major carbon source in stirred fermentors (1.5-L working volume) in fully aerobic conditions. Ethanol was produced during the exponential growth phase as a result of overflow metabolism or fermentative catabolism of glucose by yeast cells. After accumulating to a peak of 3.5 g/L, the ethanol was consumed by yeast cells as a carbon source when glucose in the culture was nearly exhausted. High initial glucose concentrations and ethanol accumulation in the culture had inhibitory effects on cell growth. Astaxanthin production was partially associated with cell growth. Based on these culture characteristics, we constructed a modified Monod kinetic model incorporating substrate (glucose) and product (ethanol) inhibition to describe the relationship of cell growth rate with glucose and ethanol concentrations. This kinetic model, coupled with the Luedeking-Piret equation for the astaxanthin production, gave satisfactory prediction of the biomass production, glucose consumption, ethanol formation and consumption, and astaxanthin production in batch cultures over 25-75 g/L glucose concentration ranges. The model was also applied to fed-batch cultures to predict the optimum feeding scheme (feeding glucose and corn steep liquor) for astaxanthin production, leading to a high volumetric yield (28.6 mg/L) and a high productivity (5.36 mg/L/day).     

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.     

Construction of robust dynamic genome-scale metabolic model structures of Saccharomyces cerevisiae through iterative re-parameterization

Dynamic flux balance analysis (dFBA) has been widely employed in metabolic engineering to predict the effect of genetic modifications and environmental conditions in the cell׳s metabolism during dynamic cultures. However, the importance of the model parameters used in these methodologies has not been properly addressed. Here, we present a novel and simple procedure to identify dFBA parameters that are relevant for model calibration. The procedure uses metaheuristic optimization and pre/post-regression diagnostics, fixing iteratively the model parameters that do not have a significant role. We evaluated this protocol in a Saccharomyces cerevisiae dFBA framework calibrated for aerobic fed-batch and anaerobic batch cultivations. The model structures achieved have only significant, sensitive and uncorrelated parameters and are able to calibrate different experimental data. We show that consumption, suboptimal growth and production rates are more useful for calibrating dynamic S. cerevisiae metabolic models than Boolean gene expression rules, biomass requirements and ATP maintenance.     

High-level production of ethanol during fed-batch ethanol fermentation with a controlled aeration rate and non-sterile glucose powder feeding of Saccharomyces cerevisiae

In this study, we utilized a unique strategy for fed-batch fermentation using ethanol-tolerant Saccharomyces cerevisiae to achieve a high-level of ethanol production that could be practically applied on an industrial scale. During this study, the aeration rate was controlled at 0.0, 0.13, 0.33, and 0.8 vvm to determine the optimal aeration conditions for the production of ethanol. Additionally, non-sterile glucose powder was fed during fed-batch ethanol fermentation and corn-steep liquor (CSL) in the medium was used as an organic N-source. When aeration was conducted, the ethanol production and productivity were superior to that when aeration was not conducted. Specifically, the maximum ethanol production reached approximately 160 g/L, when the fermentor was aerated at 0.13 vvm. These findings indicate that the use of a much less expensive C-source may enable the fermentation process to be directed towards the improvement of overall ethanol production and productivity in fermentors that are aerated at 0.13 vvm. Furthermore, if a repeated fed-batch process in which the withdrawal and fill is conducted prior to 36 h can be employed, aeration at a rate of 0.33 and/or 0.8 vvm may improve the overall ethanol productivity     

Engineering Klebsiella oxytoca for efficient 2, 3-butanediol production through insertional inactivation of acetaldehyde dehydrogenase gene

Ethanol was a major byproduct of 2,3-butanediol (2,3-BD) fermentation by Klebsiella oxytoca ME-UD-3. In order to achieve a high efficiency of 2,3-BD production, K. oxytoca mutants deficient in ethanol formation were successfully constructed by replace the aldA gene coding for aldehyde dehydrogenase with a tetracycline resistance cassette. The results suggested that inactivation of aldA led to a significantly improved 2,3-BD production. The carbon flux to 2,3-BD was enhanced by eliminating the byproducing ethanol and at the same time reducing the accumulation of another byproduct acetoin. At last, by fed-batch culturing of the mutant, the final 2,3-BD titer up to 130 g/l with the productivity of 1.63 g/l.h and the 2,3-BD yield relative to glucose of 0.48 g/g was obtained.     

An on-line physiological state recognition system for the lysine fermentation process based on a metabolic reaction model

A metabolic reaction model was developed for the lysine fermentation process by Corynebacterium glutamicum AJ-3462 to estimate the physiological state of the cells-that is, the growth and production activity, and the flux distribution of metabolites-from on-line measurable rates only. First, the extended Kalman filter was applied to eliminate noise in the measured rates. Then, using the metabolic reaction model, the lysine production rate and flux distribution were calculated. The estimation results allowed the physiological state of lysine production to be recognized, and an appropriate measure corresponding to the estimated state, such as intermittent addition of glucose and/or leucine, to be taken to maintain a high level of lysine productivity in batch culture. Finally, application of the recognition system enabled lysine to be produced from glucose at a higher yield than that from glucose- or leucine-limited exponential fed-batch cultures. (c) 1997 John Wiley & Sons, Inc. Biotechnol Bioeng 55: 170-181, 1997.     

Dynamic flux balance modeling of microbial co-cultures for efficient batch fermentation of glucose and xylose mixtures

Sequential uptake of pentose and hexose sugars that compose lignocellulosic biomass limits the ability of pure microbial cultures to efficiently produce value-added bioproducts. In this work, we used dynamic flux balance modeling to examine the capability of mixed cultures of substrate-selective microbes to improve the utilization of glucose/xylose mixtures and to convert these mixed substrates into products. Co-culture simulations of Escherichia coli strains ALS1008 and ZSC113, engineered for glucose and xylose only uptake respectively, indicated that improvements in batch substrate consumption observed in previous experimental studies resulted primarily from an increase in ZSC113 xylose uptake relative to wild-type E. coli. The E. coli strain ZSC113 engineered for the elimination of glucose uptake was computationally co-cultured with wild-type Saccharomyces cerevisiae, which can only metabolize glucose, to determine if the co-culture was capable of enhanced ethanol production compared to pure cultures of wild-type E. coli and the S. cerevisiae strain RWB218 engineered for combined glucose and xylose uptake. Under the simplifying assumption that both microbes grow optimally under common environmental conditions, optimization of the strain inoculum and the aerobic to anaerobic switching time produced an almost twofold increase in ethanol productivity over the pure cultures. To examine the effect of reduced strain growth rates at non-optimal pH and temperature values, a break even analysis was performed to determine possible reductions in individual strain substrate uptake rates that resulted in the same predicted ethanol productivity as the best pure culture.     

Identification of optimal flow rate for culture media,cell density,and oxygen toward maximization of virus production in a fed-batch baculovirus-insect cell system

In recent times, it has been realized that novel vaccines are required to combat emerging disease outbreaks, and faster optimization is required to respond to global vaccine demands. Although, fed-batch operations offer better productivity, experiment-based optimization of a new fed-batch process remains expensive and time-consuming. In this context, we propose a novel computational framework that can be used for process optimization and control of a fed-batch baculovirus-insect cell system. Since the baculovirus expression vector system (BEVS) is known to be widely used platforms for recombinant protein/vaccine production, we chose this system to demonstrate the identification of optimal profile. Toward this, first, we constructed a mathematical model that captures the time course of cell and virus growth in a baculovirus-insect cell system. Second, the proposed model was used for numerical analysis to determine the optimal operating profiles of control variables such as culture media, cell density, and oxygen based on a multiobjective optimal control formulation. Third, a detailed comparison between batch and fed-batch culture was perfromed along with a comparison between various alternatives of fed-batch operation. Finally, we demonstrate that a model-based quantification of controlled feed addition in fed-batch culture is capable of providing better productivity as compared to a batch culture. The proposed framework can be utilized for the estimation of optimal operating regions of different control variables to achieve maximum infected cell density and virus yield while minimizing the substrate/media, uninfected cell, and oxygen consumption.