Biodegradation of phenol at high initial concentrations in two-phase partitioning batch and fed-batch bioreactors

A two-phase organic-aqueous system was used to degrade phenol in both batch and fed-batch culture. The solvent, which contained the phenol and partitioned it into the aqueous phase, was systematically selected based on volatility, solubility in the aqueous phase, partition coefficient for phenol, biocompatibility, and cost. The two-phase partitioning bioreactor used 500 mL of 2-undecanone loaded with high concentrations of phenol to deliver the xenobiotic to Pseudomonas putida ATCC 11172 in the 1-L aqueous phase, at subinhibitory levels. The initial concentrations of phenol selected for the aqueous phase were predicted using the experimentally determined partition coefficient for this ternary system of 47.6. This system was initially observed to degrade 4 g of phenol in just over 48 h in batch culture. Further loading of the organic phase in subsequent experiments demonstrated that the system was capable of degrading 10 g of phenol to completion in approximately 72 h. The higher levels of phenol in the system caused a modest increase in the duration of the lag phase, but did not lead to complete inhibition or cell death. The use of a fed-batch approach allowed the system to ultimately consume 28 g of phenol in approximately 165 h, without experiencing substrate toxicity. In this system, phenol delivery to the aqueous phase is demand based, and is directly related to the metabolic activity of the cells. This system permits high loading of phenol without the corresponding substrate inhibition commonly seen in conventional bioreactors. (c) 1997 John Wiley & Sons, Inc. Biotechnol Bioeng 55: 155-162, 1997.     

Dynamic optimization of fed-batch bioreactors using the ant algorithm

The ant colony algorithm, mimicking the cooperative search behavior of ants in real life, has been employed for the dynamic optimization of fed-batch bioreactors. To test the capability of this new heuristic algorithm, two well-known and extensively studied systems have been chosen. The algorithm rapidly converges to optimal feed rate profiles, which maximize the overall production of the desired product and the profits in a computationally efficient and robust manner. The optimal profiles evolved are easy to implement in plant operation. The algorithm compares favorably with the other known techniques.     

Process intensification in fed-batch production bioreactors using non-perfusion seed cultures

ABSTRACT

Although process intensification by continuous operation has been successfully applied in the chemical industry, the biopharmaceutical industry primarily uses fed-batch, rather than continuous or perfusion methods, to produce stable monoclonal antibodies (mAbs) from Chinese hamster ovary (CHO) cells. Conventional fed-batch bioreactors may start with an inoculation viable cell density (VCD) of ~0.5 × 10⁶ cells/mL. Increasing the inoculation VCD in the fed-batch production bioreactor (referred to as N stage bioreactor) to 2–10 × 10⁶ cells/mL by introducing perfusion operation or process intensification at the seed step (N-1 step) prior to the production bioreactor has recently been used because it increases manufacturing output by shortening cell culture production duration. In this study, we report that increasing the inoculation VCD significantly improved the final titer in fed-batch production within the same 14-day duration for 3 mAbs produced by 3 CHO GS cell lines. We also report that other non-perfusion methods at the N-1 step using either fed batch or batch mode with enriched culture medium can similarly achieve high N-1 final VCD of 22–34 × 10⁶ cells/mL. These non-perfusion N-1 seeds supported inoculation of subsequent production fed-batch production bioreactors at increased inoculation VCD of 3–6 × 10⁶ cells/mL, where these achieved titer and product quality attributes comparable to those inoculated using the perfusion N-1 seeds demonstrated in both 5-L bioreactors, as well as scaled up to 500-L and 1000-L N-stage bioreactors. To operate the N-1 step using batch mode, enrichment of the basal medium was critical at both the N-1 and subsequent intensified fed-batch production steps. The non-perfusion N-1 methodologies reported here are much simpler alternatives in operation for process development, process characterization, and large-scale commercial manufacturing compared to perfusion N-1 seeds that require perfusion equipment, as well as preparation and storage vessels to accommodate large volumes of perfusion media. Although only 3 stable mAbs produced by CHO cell cultures are used in this study, the basic principles of the non-perfusion N-1 seed strategies for shortening seed train and production culture duration or improving titer should be applicable to other protein production by different mammalian cells and other hosts at any scale biologics facilities.     

Optimization of a stochastically simulated gene network model via simulated annealing

By rearranging naturally occurring genetic components, gene networks can be created that display novel functions. When designing these networks, the kinetic parameters describing DNA/protein binding are of great importance, as these parameters strongly influence the behavior of the resulting gene network. This article presents an optimization method based on simulated annealing to locate combinations of kinetic parameters that produce a desired behavior in a genetic network. Since gene expression is an inherently stochastic process, the simulation component of simulated annealing optimization is conducted using an accurate multiscale simulation algorithm to calculate an ensemble of network trajectories at each iteration of the simulated annealing algorithm. Using the three-gene repressilator of Elowitz and Leibler as an example, we show that gene network optimizations can be conducted using a mechanistically realistic model integrated stochastically. The repressilator is optimized to give oscillations of an arbitrary specified period. These optimized designs may then provide a starting-point for the selection of genetic components needed to realize an in vivo system.     

Optimization of fed-batch bioreactor using neural network model

An algorithm using feedforward neural network model for determining optimal substrate feeding policies for fed-batch fermentation process is presented in this work. The algorithm involves developing the neural network model of the process using the sampled data. The trained neural network model in turn is used for optimization purposes. The advantages of this technique is that optimization can be achieved without detailed kinetic model of the process and the computation of gradient of objective function with respect to control variables is straightforward. The application of the technique is demonstrated with two examples, namely, production of secreted protein and invertase. The simulation results show that the discrete-time dynamics of fed-batch bioreactor can be satisfactorily approximated using a feedforward sigmoidal neural network. The optimal policies obtained with the neural network model agree reasonably well with the previously reported results.     

Computer programs for modeling mammalian cell batch and fed-batch cultures using logistic equations

A MATLAB^® toolbox was developed for applying the logistic modeling approach to mammalian cell batch and fed-batch cultures. The programs in the toolbox encompass sensitivity analyses and simulations of the logistic equations in addition to cell specific rate estimation. The toolbox was first used to generate time courses of the sensitivity equations for characterizing the relationship between the logistic variable and the model parameters. Subsequently, the toolbox was used to describe CHO cell data from batch and fed-batch mammalian cell cultures. Cell density, product, glucose, lactate, glutamine, and ammonia data were analyzed for the batch culture while fed-batch analysis included cell density and product concentration. In all instances, experimental data were well described by the logistic equations and the resulting specific rate profiles were representative of the underlying cell physiology. The 6-variable batch culture data set was also used to compare the logistic specific rates with those from polynomial fitting and discrete derivative methods. The polynomial specific rates grossly misrepresented cell behavior in the initial and final stages of culture while those based on discrete derivatives had high variability due to computational artifacts. The utility of logistic specific rates to guide process development activities was demonstrated using specific protein productivity versus growth rate trajectories for the 3 cultures examined in this study. Overall, the computer programs developed in this study enable rapid and robust analysis of data from mammalian cell batch and fed-batch cultures which can help process development and metabolic flux estimation.     

Mixing-models applied to industrial batch bioreactors

Mixing models for bioreactors on the basis of the tanks-in-series concept are presented and a suitable parameter-estimation method is introduced. The Monte-Carlo-optimization procedure with the inhomogeneity-curve included in the objective function is used. Results of the parameter optimization procedure are given for stirred-tank-bioreactors equipped with one and three Rushton turbines under aerated conditions. The model designed for the stirredtank with three Rushton turbines is capable to describe the mixing properties, while in case of the stirred-tank with one Rushton turbine the simulated radial circulation time does not correlate with the measured one.List of Symbols a ₀₀...a _XY coefficients in Eq. (9) - d _i m stirrer diameter - D m tank diameter - E relative error - F _AX m³/s axial liquid flow rate - F _G m³/s aeration flow rate - F _RAD m³/s radial liquid flow rate - g m/s² acceleration of gravity - h _l m height of fluid in the tank - i _s(t) simulated inhomogeneity-curve - i _m(t) measured inhomogeneity-curve - k number of sensors - n 1/s stirrer revolutions - N number of tanks in the tanks-of-series-cascade - p number of measured time intervalls - t s time - t _c.AX s axial circulation time - t _c,RAD s radial circulation time - T _i °C temperature of sensors - T °C temperature at the end of the experiment - T ₀ °C temperature before pulse injection - V _tot m³ total liquid volume - V _C m³ liquid volume of circulation cascade, additional index specifications describe the cascade elements (Figs.1 and 2) - V _M m³ liquid volume of well mixed stirrer compartment - w ₀ m/s superficial gas velocity - X, Y exponents in eq. (9) - kg/m³ density - Pas dynamic viscosity - m²/s kinematic viscosity - s time constant (time for 63,2% of T ) of the signal Dimensionless Numbers stirrer Froude number - aeration Froude number     

The design of controllers for batch bioreactors

The implementation of control algorithms to batch bioreactors is often complicated by variations in process dynamics that occur during the course of fermentation. Such a wide operating range often renders the performance of fixed gain proportional-integral-differential (PID) controllers unsatisfactory. In this work, detailed studies on the control of batch fermentations are per formed. Two simple controller designs are presented with the intent to compensate for changing process dynamics. One design incorporates the concepts of static feedforward-feedback control. While this technique produces tighter control than feedback alone, it is not as successful as a controller based on gain scheduling. The gain-scheduling controller, a subclass of adaptive controllers, uses the oxygen uptake rate as an auxiliary variable to fine-tune the PID controller parameters. The control of oxygen tension in the bioreactor is used as a vehicle to convey the proposed ideas, analyses, and results. Simulation experiments indicate significant improvement in controller performance can be achieved by both of the proposed approaches even in the presence of measurement noise.     

Feedback stabilization of fed-batch bioreactors: non-monotonic growth kinetics

This paper deals with the design of a feedback controller for fed-batch microbial conversion processes that forces the substrate concentration C(S) to a desired setpoint, starting from an arbitrary (initial) substrate concentration when non-monotonic growth kinetics apply. This problem is representative for a lot of industrial fermentation processes, with the baker's yeast fermentation as a well-known example. It is assumed that the specific growth rate mu is function of the substrate concentration only. A first approach exploits the availability of on-line measurements of both the substrate and biomass concentration. A second approach is merely based on on-line measurements of the biomass concentration, which provide an estimate for the specific growth rate. After a reformulation of the substrate concentration setpoint into a specific growth rate setpoint, it is demonstrated that the fed-batch process can still be stabilized around any desired operating point along the non-monotonic kinetics.     

Constructing linkage maps in autotetraploid species using simulated annealing

In this paper we demonstrate how molecular markers segregating in a full-sib autotetraploid mapping population can be ordered to form a linkage map using simulated annealing. This approach facilitates the examination of orders close to the optimum to see which marker placings are fixed and identify the markers whose position is less certain. A simulation study investigates the effects of population size, marker spacing, ratio of dominant to codominant markers, typing errors and missing values. The method is applied to map 30 amplified fragment length polymorphism and microsatellite markers on linkage group IV of potato.     

Use of surface-immobilized Trichoderma in batch and fed-batch fermentations

Needle-punch polyester was shown to be an effective support material for the immobilization of Trichoderma reesei Rut C30. When used as a resident inoculum for a batch process, the immobilized Trichoderma was very stable and resulted in a reduced rate of biomass generation in the bulk liquid phase as compared to cultures inoculated with free mycelium. Fed-batch fermentations with the immobilized Trichoderma produced ca. 80% of the activity of those using free cells; however, the activity was more stable and the crude enzyme broth produced had a greatly reduced biomass concentration.     

Constructing circular phylogenetic networks from weighted quartets using simulated annealing

In this paper, we present a heuristic algorithm based on the simulated annealing, SAQ-Net, as a method for constructing phylogenetic networks from weighted quartets. Similar to QNet algorithm, SAQ-Net constructs a collection of circular weighted splits of the taxa set. This collection is represented by a split network. In order to show that SAQ-Net performs better than QNet, we apply these algorithm to both the simulated and actual data sets containing salmonella, Bees, Primates and Rubber data sets. Then we draw phylogenetic networks corresponding to outputs of these algorithms using SplitsTree4 and compare the results. We find that SAQ-Net produces a better circular ordering and phylogenetic networks than QNet in most cases. SAQ-Net has been implemented in Matlab and is available for download at http://bioinf.cs.ipm.ac.ir/softwares/saq.net.     

Ethanol effect on batch and fed-batch Arthrospira platensis growth

The ability of Arthrospira platensis to use ethanol as a carbon and energy source was investigated by batch process and fed-batch process. A. platensis was cultivated under the effect of a single addition (batch process) and a daily pulse feeding (fed-batch process) of pure ethanol, at different concentrations, to evaluate cell concentration (X) and specific growth rate (μ). A marked increase was observed in the cell concentration of A. platensis in runs with ethanol addition when compared to control cultures without ethanol addition. The fed-batch process using an ethanol concentration of 38 mg L^?1 days^?1 reached the maximum cell concentration of 2,393 ± 241 mg L^?1, about 1.5-fold that obtained in the control culture. In all experiments, the maximum specific growth rate was observed in the early exponential phase of cell growth. In the fed-batch process, μ decreased more slowly than in the batch process and control culture, resulting in the highest final cell concentration. Ethanol can be used as a feasible carbon and energy source for A. platensis growth via a fed-batch process.     

Fermentation kinetics of recombinant yeast in batch and fed-batch cultures

Fed-batch cultures of recombinant microorganisms have attracted attention as they can separate cell growth stage from cloned-gene expression phase during fermentations. In this work, the effect of different glucose feeding strategies on cell growth and cloned gene expression was studied during aerobic fed-batch fermentations of recombinant yeast, containing the plasmid pRB58. The plasmid contains the yeast SUC2 gene, which codes for the enzyme invertase. Some feeding policies resulted in a constant glucose concentration inside the fermentor, while others deliberately introduced a cyclic variation. The cell mass yield was found to be higher at low glucose concentrations, thus indicating a shift to the more energy-efficient respiratory pathway. The SUC2 gene expression was derepressed at glucose levels below 2 g/L. The response of specific invertase activity to changes in the medium glucose concentration was found to be almost immediate.     

Growth of Photorhabdus luminescens in batch and glucose fed-batch culture

Photorhabdus luminescens, a bacterial symbiont of entomopathogenic biocontrol nematodes, was grown in batch and glucose fed-batch culture. The cell density, bioluminescence, production of antibiotic substances, number of cells with inclusion bodies, glucose concentration and oxygen uptake rate were recorded. The addition of 12.4 g l⁻¹ glucose prolonged the growth, and the yield almost doubled, from 6.85 g l⁻¹ to 12.45 g l⁻¹ dry mass. The production of antibiotic substances increased by 140%. Bioluminescence was higher in the batch culture. A shift of P. luminescens to phase II variants was not detected. Received: 21 January 2000 / Received revision: 3 April 2000 / Accepted: 7 April 2000     

Optimization of cyclodextrin glycosyltransferase production from Klebsiella pneumoniae AS-22 in batch, fed-batch, and continuous cultures

Production of a novel cyclodextrin glycosyltransferase (CGTase) from Klebsiella pneumoniae AS-22 strain, which converts starch predominantly to alpha-CD at high conversion yields, in batch, fed-batch, and continuous cultures, is presented. In batch fermentations, optimization of different operating parameters such as temperature, pH, agitation speed, and carbon-source concentration resulted in more than 6-fold increase in CGTase activity. The enzyme production was further improved by two fed-batch approaches. First, using glucose-based feed to increase cell density, followed by starch-based feed to induce enzyme production, resulted in high cell density of 76 g dry cell weight/L, although the CGTase production was low. Using the second approach of a single dextrin-based feed, 20-fold higher CGTase was produced compared to that in batch fermentations with media containing tapioca starch. In continuous operation, more than 8-fold increase in volumetric CGTase productivity was obtained using dextrin-based media compared to that in batch culture using starch-based media.     

用遗传算法优化流加培养的底物流加轨迹

遗传算法（Genetic Algorithm,GA)j是把生物进化论和遗传学原理应用于工程优化而创造出来的新的优化算法,在复杂问题的优化方面显示出了优良性能。近年来GA开始应用于发酵工程领域,本文介绍了应用GA优化流加培养流加轨迹的原理和方法。     

MASTR: multiple alignment and structure prediction of non-coding RNAs using simulated annealing

MOTIVATION: As more non-coding RNAs are discovered, the importance of methods for RNA analysis increases. Since the structure of ncRNA is intimately tied to the function of the molecule, programs for RNA structure prediction are necessary tools in this growing field of research. Furthermore, it is known that RNA structure is often evolutionarily more conserved than sequence. However, few existing methods are capable of simultaneously considering multiple sequence alignment and structure prediction. RESULT: We present a novel solution to the problem of simultaneous structure prediction and multiple alignment of RNA sequences. Using Markov chain Monte Carlo in a simulated annealing framework, the algorithm MASTR (Multiple Alignment of STructural RNAs) iteratively improves both sequence alignment and structure prediction for a set of RNA sequences. This is done by minimizing a combined cost function that considers sequence conservation, covariation and basepairing probabilities. The results show that the method is very competitive to similar programs available today, both in terms of accuracy and computational efficiency. AVAILABILITY: Source code available from http://mastr.binf.ku.dk/