Effect of incorrectly estimated parameters on the control of specific growth rate inE. coli fed-batch fermentation

An exponential feeding strategy has been frequently used in fed-batch fermentation of recombinantE. coli. In this feeding scheme, growth yield and initial cell concentration, which can be erroneously determined, are needed to calculate the feed rate for controlling specific growth rate at the set point. The effect of the incorrect growth yield and initial cell concentration on the control of the specific growth rate was theoretically analyzed. Insignificance of the correctness of those parameters for the control of the specific growth rate was shown theoretically and experimentally.     

Immobilized cell biocatalyst activation and pseudo-steady-state behavior: model and experiment

An intrinsic, unstructured model has been utilized to describethe startup dynamics of a continuous Caalginate-immobilized Zymomonas mobilis (ATCC 10988) fermentation. This model predicts, at least qualitatively, transients in the fermenter effluent glucose, ethanol, and biomass concentrations as well as radial gradients in immobilized-cell concentration and activity within the gelbiocatalysts. Predicted intrabiocatalyst gradients in immobilized-cell specific growth rate were used to calculate the corresponding gradients in intracellular RNA level based on a reported linear relationship between the two. Mathematical simulations of immobilized biomass concentration profiles and RNA content were verified using a novel, scanning microfluorimetry technique.     

On-line analysis of avermectin fermentation cell growth kinetics in an industrial pilot plant

Experimental data are presented which show that on-line calculation of oxygen uptake rate can be used to estimate the cell concentration of Streptomyces avermitilis during the active growth phase of this fermentation. Moreover, by dividing the oxygen uptake rate by the total oxygen consumed, an on-line estimate of specific growth rate of this culture can be generated. A theoretical basis is provided for this model. Use of a mass spectrometer for vent gas analysis coupled with computer data acquisition has made this information both very accurate and readily available. Examples are given which illustrate the kinetics of the avermectin fermentation as well as the effect of a temperature shift on the specific growth rate.     

Dialysis Continuous Process for Ammonium-Lactate Fermentation of Whey: Mathematical Model and Computer Simulation

A mathematical model was developed to describe a dialysis process for the continuous fermentation of whey lactose to lactic acid, with neutralization to a constant pH by ammonia. In the process, whey of a relatively high concentration is fed into the fermentor circuit at a relatively low rate so that the residual concentration of lactose is low. The fermentor effluent contains ammonium lactate, bacterial cells, and residual whey solids and could be used as a nitrogen-enriched feedstuff for ruminant animals. Only water is fed into the dialysate circuit at a relatively high rate. The dialysate effluent contains purified ammonium lactate and could be converted to lactic acid and ammonium sulfate for industry. The fermentation was specifically modeled as a set of equations representing material balances and rate relationships in the two circuits. Dialysis continuous fermentations, in general, were modeled by combining these equations and by using dimensionless parameters. The generalized model was then solved for the steady state and used to simulate the specific fermentation on a digital computer. The results showed the effects of various material and operational and kinetic parameters on the process and predicted that it could be operated efficiently.     

Modelling oscillatory behavior in batch fermentations

A batch fermentation is modelled with constant and variable yeild terms. It is shown that the model cannot exhibit oscillations if a constant yield term is used. Oscillations in the cell concentration, but not in the limiting substrate concentration, can be simulated if a variable yield function of the limiting substrate is used. Conditions, for which the variable yield needs to satisfy in order to generate oscillations in the cell concentration, are discussed. The primary condition is that the yield must become zero at the same time that the specific growth rate does. Experimental results exhibiting oscillatory behavior are presented and compared with the proposed model.     

Modeling enzyme production with Aspergillus oryzae in pilot scale vessels with different agitation, aeration, and agitator types

The purpose of this article is to demonstrate how a model can be constructed such that the progress of a submerged fed-batch fermentation of a filamentous fungus can be predicted with acceptable accuracy. The studied process was enzyme production with Aspergillus oryzae in 550 L pilot plant stirred tank reactors. Different conditions of agitation and aeration were employed as well as two different impeller geometries. The limiting factor for the productivity was oxygen supply to the fermentation broth, and the carbon substrate feed flow rate was controlled by the dissolved oxygen tension. In order to predict the available oxygen transfer in the system, the stoichiometry of the reaction equation including maintenance substrate consumption was first determined. Mainly based on the biomass concentration a viscosity prediction model was constructed, because rising viscosity of the fermentation broth due to hyphal growth of the fungus leads to significant lower mass transfer towards the end of the fermentation process. Each compartment of the model was shown to predict the experimental results well. The overall model can be used to predict key process parameters at varying fermentation conditions.     

干扰素基因工程菌产物表达数学模型的研究

根据阻遏蛋白,辅阻遏因子与启动基因之间的相互作用,建立了采用色氨酸启动子的基因工程重组徽生物的产物表达数学模型。提出了mRNA最大转录速率常数和产物表达速率常数与比生长速率呈线性关系的假设,用干扰素基因工程菌培养过程中的实验数据估计了mR—NA转录速率常数,干扰素表达速率常数和干扰素降解速率常数。推导出了发酵过程中干扰素表达量和细胞内干扰素比活计算公式。运用这些公式可以通过检测色氨酸浓度和细胞比生长速率来计算预测干扰紊表达量。确定最佳的终止培养时间。     

Multiblock PLS analysis of an industrial pharmaceutical process

The performance of an industrial pharmaceutical process (production of an active pharmaceutical ingredient by fermentation, API) was modeled by multiblock partial least squares (MBPLS). The most important process stages are inoculum production and API production fermentation. Thirty batches (runs) were produced according to an experimental planning. Rather than merging all these data into a single block of independent variables (as in ordinary PLS), four data blocks were used separately (manipulated and quality variables for each process stage). With the multiblock approach it was possible to calculate weights and scores for each independent block. It was found that the inoculum quality variables were highly correlated with API production for nominal fermentations. For the nonnominal fermentations, the manipulations of the fermentation stage explained the amount of API obtained (especially the pH and biomass concentration). Based on the above process analysis it was possible to select a smaller set of variables with which a new model was built. The amount of variance predicted of the final API concentration (cross-validation) for this model was 82.4%. The advantage of the multiblock model over the standard PLS model is that the contributions of the two main process stages to the API volumetric productivity were determined.     

Reactive extraction of penicillin G in a pilot plant Karr-column III. Modelling and simulation of the extraction process

Summary The longitudinal concentration profiles of penicillin the continuous aqueous phase of a pilot plant Karr-column of 7.6 m height was calculated by a mathematic model consisting of reaction rate and cascase models. Satisfactory agreements between calculated and measured profiles were found. The identified mass transfer coefficients are identical in the bench-scale and pilot plant columns, in the model medium and fermentation medium as well as at different stroke frequencies. The specific interfacial area are strongly influenced by these parameters. The model can be used for calculation of penicillin extraction columns of different sizes. For the layout of the columns, hydrodynamic data are needed, which, however, cannot yet be calculated on a theoretical basis.     

Monitoring cell concentration and activity by multiple excitation fluorometry.

Four key cellular metabolic fluorophores--tryptophan, pyridoxine, NAD(P)H, and riboflavin--were monitored on-line by a multiple excitation fluorometric system (MEFS) and a modified SLM 8000C scanning spectrofluorometer in three model yeast fermentation systems--bakers' yeast growing on glucose, Candida utilis growing on ethanol, and Saccharomyces cerevisiae RTY110/pRB58 growing on glucose. The measured fluorescence signals were compared with cell concentration, protein concentration, and cellular activity. The results indicate that the behavior and fluorescence intensity of various fluorophores differ in the various fermentation systems. Tryptophan fluorescence is the best signal for the monitoring of cell concentration in bakers' yeast and C. utilis fermentations. Pyridoxine fluoresce is the best signal for the monitoring of cell concentration in the S. cerevisiae RTY110/pRB58 fermentation. In bakers' yeast fermentations the pyridoxine fluorescence signal can be used to monitor cellular activity. The NAD(P)H fluorescence signal is a good indicator of cellular activity in the C. utilis fermentation. For this fermentation NAD(P)H fluorescence can be used to control ethanol feeding in a fed-batch process.     

A phenomenological model to represent the kinetics of growth by <Emphasis Type="Italic">Corynebacterium glutamicum</Emphasis> for lysine production

Corynebacterium glutamicum is commonly used for lysine production. In the last decade, several metabolic engineering approaches have been successfully applied to C. glutamicum. However, only few studies have been focused on the kinetics of growth and lysine production. Here, we present a phenomenological model that captures the growth and lysine production during different phases of fermentation at various initial dextrose concentrations. The model invokes control coefficients to capture the dynamics of lysine and trehalose synthesis. The analysis indicated that maximum lysine productivity can be obtained using 72 g/L of initial dextrose concentration in the media, while growth was optimum at 27 g/L of dextrose concentration. The predictive capability was demonstrated through a two-stage fermentation strategy to enhance the productivity of lysine by 1.5 times of the maximum obtained in the batch fermentation. Two-stage fermentation indicated that the kinetic model could be further extended to predict the optimal feeding strategy for fed-batch fermentation.     

Production of ethanol by Clostridium thermosaccharolyticum: II. A quantitative model describing product distributions

The study of the continuous culture of Clostridium thermosaccharolyticum on xylose showed multiple steady states and hysteresis. A quantitative model based on the biochemistry and physiology of xylose fermentation by C. thermosaccharolyticum was developed. The objective in developing this model was to bring together the observations both of this study and of other researchers on the fermentation of xylose. The model equations were written based on the metabolic pathway for xylose utilization by C. thermosaccharolyticum and the requirement that the carbon, ATP, and NADH within the cell be balanced. Given the specific growth rate mu and the specific xylose utilization rate q(s), a set of product distributions (ethanol, acetate, and lactate) satisfying these balances was obtained. This set was plotted on a triangular plot and named the permitted region. The product distributions within this permitted region were shown to be affected by the environmental parameters such as iron concentration and hydrogen partial pressure. The model predicted trends in product distribution which correlate with experimentally observed phenomena. The model was also used to analyze the continuous-culture data from our experimental work.     

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.     

A maximum production strategy of lysine based on a simplified model derived from a metabolic reaction network

The aim of this study is to develop a strategy for maximum production of a target product with a simplified model derived from a metabolic reaction network through an example of lysine production. Based on the model, a search for the optimal specific growth rate profile was conducted among the available conditions of batch fermentation based on the derived model, when the total fermentation time was fixed. The optimal specific growth rate was obtained as a boundary control: initially, the specific growth rate was maintained at a maximum value and was subsequently switched to a critical value giving the maximum specific production rate. To make the specific growth rate follow this optimal profile as accurately as possible in batch mode, first, an appropriate initial concentration of leucine was employed in the experiment. Second, the feeding strategy of leucine was further studied. The specific growth rate profile with feeding was closer to the optimal one and the amount of lysine produced at the final stage of fermentation was increased about twofold, compared to that in the batch fermentation. Finally, the strategy was summarized as an algorithm for general use of this method.     

Effects of pH and acetic acid on homoacetic fermentation of lactate by Clostridium formicoaceticum

Clostridium formicoaceticum homofermentatively converts lactate to acetate at 37 degrees C and pH 6.6-9.6. However, this fermentation is strongly inhibited by acetic acid at acidic pH. The specific growth rate of this organism decreased from a maximum at pH 7.6 to zero at pH 6.6. This inhibition effect was found to be attributed to both H(+) and undissociated acetic acid. At pH values below 7.6, the H(+) inhibited the fermentation following non-competitive inhibition kinetics. The acetic acid inhibition was found to be stronger at a lower medium pH. At pH 6.45-6.8, cell growth was found to be primarily limited by a maximum undissociated acetic acid concentration of 0.358 g/L (6mM). This indicates that the undissociated acid, not the dissociated acid, is the major acid inhibitor. At pH 7.6 or higher, this organism could tolerate acetate concentrations of higher than 0.8M, but salt (Na(+)) became a strong inhibitor at concentrations of higher than 0.4M. Acetic acid inhibition also can be represented by noncompetitive inhibition kinetics. A mathematical model for this homoacetic fermentation was also developed. This model can be used to simulate batch fermentation at any pH between 6.9 and 7.6.     

电子嗅在线反馈控制毕赤酵母糖化酶发酵过程中甲醇浓度新方法的应用

探索了电子嗅传感仪直接通过发酵尾气进行发酵液中甲醇浓度在线检测的方法,建立了毕赤酵母表达糖化酶过程中甲醇浓度的自动化反馈补料控制模型,可准确实现发酵过程中甲醇浓度的精确控制;研究表明,当利用电子嗅将培养液中甲醇浓度稳定控制在(890±35)ppm水平下,发酵诱导培养到128h时目的蛋白糖化酶酶活达到了8 153U/ml,与甲醇浓度控制在(350±26)ppm时的发酵水平相比提升了48.8%。该方法具有无需前处理、与发酵液非接触、快速和准确性的优点,为提升工程酵母在工业发酵培养过程工艺的优化控制具有重要的指导作用。     

A kinetic model for the quantitative analysis of complement

A simple model has been developed which accurately predicts the time course of complement mediated lysis of sensitized red cells. The model assumes that the one hit theory of immune hemolysis is applicable and that the rate of lysis is directly proportional to the concentration of a complement component present in rate limiting amounts. It also assumes that the rate of lysis is dependent on the fraction of cells lysed. The model can be related to the classical von Krogh equation for end point complement analyses and can be used to estimate the rate constant for the critical step in hemolysis, as well as the efficiency of the critical complement component in the rate limiting step. Parameters derived from the model can be quantitatively related to complement concentration and can be used as the basis for a quantitative assay of complement activity. The model can also be used to calculate, for a particular sample, the concentration at which complement activity becomes undectable, the complement activity of the pure, undiluted sample, and the time required for the sample to produce complete lysis of the available cells.     

Use of Artificial Neural Networks and a Gamma-Concept-Based Approach To Model Growth of and Bacteriocin Production by Streptococcus macedonicus ACA-DC 198 under Simulated Conditions of Kasseri Cheese Production

Growth of and bacteriocin production by Streptococcus macedonicus ACA-DC 198 were assessed and modeled under conditions simulating Kasseri cheese production. Controlled fermentations were performed in milk supplemented with yeast extract at different combinations of temperature (25, 40, and 55°C), constant pH (pHs 5 and 6), and added NaCl (at concentrations of 0, 2, and 4%, wt/vol). The data obtained were used to construct two types of predictive models, namely, a modeling approach based on the gamma concept, as well as a model based on artificial neural networks (ANNs). The latter computational methods were used on 36 control fermentations to quantify the complex relationships between the conditions applied (temperature, pH, and NaCl) and population behavior and to calculate the associated biokinetic parameters, i.e., maximum specific growth and cell count decrease rates and specific bacteriocin production. The functions obtained were able to estimate these biokinetic parameters for four validation fermentation experiments and obtained good agreement between modeled and experimental values. Overall, these experiments show that both methods can be successfully used to unravel complex kinetic patterns within biological data of this kind and to predict population kinetics. Whereas ANNs yield a better correlation between experimental and predicted results, the gamma-concept-based model is more suitable for biological interpretation. Also, while the gamma-concept-based model has not been designed for modeling of other biokinetic parameters than the specific growth rate, ANNs are able to deal with any parameter of relevance, including specific bacteriocin production.     

Computer control of the penicillin fermentation using the filtration probe in conjunction with a structured process model

A structured model for the penicillin fermentation is presented. This model includes three different cell types: (1) hyphae tips, (2) penicillin-producing cells, and (3) degenerated, metabolically inactive cells. Cell degeneration has been described previously as a gradual loss of cytoplasmic material by endogenous metabolism. The rate at which such loss of cytoplasm (and activity) proceeds can be expressed as a linear function of the specific growth rate. At growth rates above some minimum value (0.0115 h(-1)) cell degeneration can be prevented. This model served as the control basis during open-loop as well as closed-loop computer control of the fermentation. Closed-loop control was achieved through feedback information of biomass concentration using a filtration probe and was required when complex nutrients contributed significantly to the overall biomass production.     

A novel feeding strategy for enhanced plasmid stability and protein production in recombinant yeast fedbatch fermentation

A novel feeding strategy in fedbatch recombinant yeast fermentation was developed to achieve high plasmid stability and protein productivity for fermentation using low-cost rich (non-selective) media. In batch fermentations with a recombinant yeast, Saccharomyces cerevisiae, which carried the plasmid pSXR125 for the production of beta-galactosidase, it was found that the fraction of plasmid-carrying cells decreased during the exponential growth phase but increased during the stationary phase. This fraction increase in the stationary phase was attributed to the death rate difference between the plasmid-free and plasmid-carrying cells caused by glucose starvation in the stationary phase. Plasmid-free cells grew faster than plasmid-carrying cells when there were plenty of growth substrate, but they also lysed or died faster upon the depletion of the growth substrate. Thus, pulse additions of the growth substrate (glucose) at appropriate time intervals allowing for significant starvation period between two consecutive feedings during fedbatch fermentation should have positive effects on stabilizing plasmid and enhancing protein production. A selective medium was used to grow cells in the initial batch fermentation, which was then followed with pulse feeding of concentrated non-selective media in fedbatch fermentation. Both experimental data and model simulation show that the periodic glucose starvation feeding strategy can maintain a stable plasmid-carrying cell fraction and a stable specific productivity of the recombinant protein, even with a non-selective medium feed for a long operation period. On the contrary, without glucose starvation, the fraction of plasmid-carrying cells and the specific productivity continue to drop during the fedbatch fermentation, which would greatly reduce the product yield and limit the duration that the fermentation can be effectively operated. The new feeding strategy would allow the economic use of a rich, non-selective medium in high cell density recombinant fedbatch fermentation. This new feeding strategy can be easily implemented with a simple IBM-PC based control system, which monitors either glucose or cell concentration in the fermentation broth.