Monitoring of recombinant protein production using bioluminescence in a semiautomated fermentation process

On-line optimization of fermentation processes can be greatly aided by the availability of information on the physiological state of the cell. The goal of our "BioLux" research project was to design a recombinant cell capable of intracellular monitoring of product synthesis and to use it as part of an automated fermentation system. A recombinant plasmid was constructed containing an inducible promoter that controls the gene coding for a model protein and the genes necessary for bioluminescence. The cells were cultured in microfermenters equipped with an on-line turbidity sensor and a specially designed on-line light sensor capable of continuous measurement of bioluminescence. Initial studies were done under simple culture conditions, and a linear correlation between luminescence and protein production was obtained. Such specially designed recombinant bioluminescent cells can potentially be applied for model-based inference of intracellular product formation, as well as for optimization and control of recombinant fermentation processes.     

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.     

Critical importance of moisture content of the medium in alpha-amylase production by Bacillus licheniformis M27 in a solid-state fermentation system

Summary A large reduction (about 30%–78%) is observed in the production of alpha-amylase by Bacillus licheniformis M27 in standardized wheat bran medium under solid-state fermentation when the moisture content of the medium is higher than the standardized value (65%). However, a surge in enzyme production in the first 24 h of fermentation is observed in media with 75% and 85% moisture. The role of decreased oxygen transfer in reducing enzyme tires by about 78% in the medium containing 95% moisture is evident, since the enzyme tire can be effectively increased by agitating the medium during fermentation. No such limitation in oxygen transfer is evident in medium containing 65% moisture even where incubated under static conditions or when the flask is capped by aluminum foil. The data indicate the critical importance of the moisture content of the medium in -amylase production by B. licheniformis M27 in solid-state fermentation systems. The results also have several implications of scientific and techno-economic importance and are useful in explaining some of the advantages of a solid-state fermentation system over the submerged fermentation process. Offprint requests to: B. K. Lonsane     

Analysis of single-chain antibody production in Pichia pastoris using on-line methanol control in fed-batch and mixed-feed fermentations.

In the last few years the Pichia pastoris expression system has been gaining more and more interest for the expression of recombinant proteins. Many groups have employed fermentation technology in their investigations because the system is fairly easy to scale up and suitable for the production in the milligram to gram range. A large number of heterologous proteins from different sources has been expressed, but the fermentation process technology has been investigated to a lesser extent. A large number of fermentations are carried out in standard bioreactors that may be insufficiently equipped to meet the demands of high-cell-density fermentations of methylotrophic yeasts. In particular, the lack of on-line methanol analysis leads to fermentation protocols that may impair the optimal expression of the desired products. We have used a commercially available methanol sensor to investigate in detail the effects of supplementary glycerol feeding while maintaining a constant methanol concentration during the induction of a Mut(+) strain of Pichia pastoris. Specific glycerol feed rates in the range of 38-4.2 mg. g(-1). h(-1) (mg glycerol per gram fresh weight per hour) were investigated. Expression of the recombinant scFv antibody fragment was only observed at specific feed rates below 6 mg. g(-1). h(-1). At low specific feed rates, growth was even lower than with methanol as the sole carbon source and the harvest expression level of the scFv was only half of that found in the control fermentation. These results show that glycerol inhibits expression driven by the AOX1 promoter even at extremely limited availability and demonstrate the benefits of on-line methanol control in Pichia fermentation research.     

Enhanced production of L-(+)-lactic acid in chemostat by Lactobacillus casei DSM 20011 using ion-exchange resins and cross-flow filtration in a fully automated pilot plant controlled via NIR

Due to the lack of suitable in-process sensors, on-line monitoring of fermentation processes is restricted almost exclusively to the measurement of physical parameters only indirectly related to key process variables, i.e., substrate, product, and biomass concentration. This obstacle can be overcome by near infrared (NIR) spectroscopy, which allows not only real-time process monitoring, but also automated process control, provided that NIR-generated information is fed to a suitable computerized bioreactor control system. Once the relevant calibrations have been obtained, substrate, biomass and product concentration can be evaluated on-line and used by the bioreactor control system to manage the fermentation. In this work, an NIR-based control system allowed the full automation of a small-scale pilot plant for lactic acid production and provided an excellent tool for process optimization. The growth-inhibiting effect of lactic acid present in the culture broth is enhanced when the growth-limiting substrate, glucose, is also present at relatively high concentrations. Both combined factors can result in a severe reduction of the performance of the lactate production process. A dedicated software enabling on-line NIR data acquisition and reduction, and automated process management through feed addition, culture removal and/or product recovery by microfiltration was developed in order to allow the implementation of continuous fermentation processes with recycling of culture medium and cell recycling. Both operation modes were tested at different dilution rates and the respective cultivation parameters observed were compared with those obtained in a conventional continuous fermentation. Steady states were obtained in both modes with high performance on lactate production. The highest lactate volumetric productivity, 138 g L(-1) h(-1), was obtained in continuous fermentation with cell recycling.     

Monitoring of complex industrial bioprocesses for metabolite concentrations using modern spectroscopies and machine learning: application to gibberellic acid production

Two rapid vibrational spectroscopic approaches (diffuse reflectance-absorbance Fourier transform infrared [FT-IR] and dispersive Raman spectroscopy), and one mass spectrometric method based on in vacuo Curie-point pyrolysis (PyMS), were investigated in this study. A diverse range of unprocessed, industrial fed-batch fermentation broths containing the fungus Gibberella fujikuroi producing the natural product gibberellic acid, were analyzed directly without a priori chromatographic separation. Partial least squares regression (PLSR) and artificial neural networks (ANNs) were applied to all of the information-rich spectra obtained by each of the methods to obtain quantitative information on the gibberellic acid titer. These estimates were of good precision, and the typical root-mean-square error for predictions of concentrations in an independent test set was <10% over a very wide titer range from 0 to 4925 ppm. However, although PLSR and ANNs are very powerful techniques they are often described as "black box" methods because the information they use to construct the calibration model is largely inaccessible. Therefore, a variety of novel evolutionary computation-based methods, including genetic algorithms and genetic programming, were used to produce models that allowed the determination of those input variables that contributed most to the models formed, and to observe that these models were predominantly based on the concentration of gibberellic acid itself. This is the first time that these three modern analytical spectroscopies, in combination with advanced chemometric data analysis, have been compared for their ability to analyze a real commercial bioprocess. The results demonstrate unequivocally that all methods provide very rapid and accurate estimates of the progress of industrial fermentations, and indicate that, of the three methods studied, Raman spectroscopy is the ideal bioprocess monitoring method because it can be adapted for on-line analysis.     

On-line monitoring and controlling system for fermentation processes

A personal computer-based on-line monitoring and controlling system was developed for the fermentation of microorganism. The on-line HPLC system for the analysis of glucose and ethanol in the fermentation broth was connected to the fermenter via an auto-sampling equipment, which could perform the pipetting, filtration and dilution of the sample and final injection onto the HPLC through automation based on a programmed procedure. The A/D and D/A interfaces were equipped in order to process the signals from electrodes and from the detector of HPLC, and to direct the feed pumps, the motor of stirrer and gas flow-rate controller. The software that supervised the control of the stirring speed, gas flow-rate, pH value, feed flow-rate of medium, and the on-line measurement of glucose and ethanol concentration was programmed by using Microsoft Visual Basic under Microsoft Windows. The signal for chromatographic peaks from on-line HPLC was well captured and processed using an RC filter and a smoothing algorithm. This monitoring and control system was demonstrated to be effective in the ethanol fermentation of Zymomonas mobilis operated in both batch and fed-batch modes. In addition to substrate and product concentrations determined by on-line HPLC, the biomass concentration in Z. mobilis fermentation could also be on-line estimated by using the pH control and an implemented software sensor. The substrate concentration profile in the fed-back fermentation followed well the set point profile due to the fed-back action of feed flow-rate control.     

Reliable estimation of the key variables and of their rates of change in alcoholic fermentation

The paper establishes a rigorous probabilistic framework for the reconciliation of apparently conflicting data from various physical and chemical measurements related to the key biological variables of alcoholic fermentation: the ethanol and the residual sugar concentrations. The analysis is carried out on a database consisting of 15 beer fermentation experiments, for which off-line determinations of ethanol concentration, fermentable sugar concentration, wort density and refractive index are available, as well as on-line records of evolved CO₂. The basic reconciliation method uses mass balance and monotonicity constraints derived from the biological knowledge of the fermentation process. In order to provide interpolated values and rate estimates, smoothness requirements are added. The reconciliation procedure gives more reliable estimates than any given measurement, detects outliers, helps fixing problems in the experimental setting and is also applicable on line.     

Knowledge based control applied to fixed bed pulsed bioreactors

In this work, an expert system was developed and applied for on-line control and supervision of ethanolic fermentation by immobilized Saccharomyces cerevisiae in a fixed-bed pulsed bioreactor of 1.2 l of working volume. A number of experiments with different substrate concentrations (75, 100, 150 and 200 g/l) and hydraulic residence times (2.4, 1.2 and 0.8 h) were carried out. Knowledge-based computer-aided supervision of this process involves accurate on-line measurement of the relevant process variables (temperature, pH, flow rate, carbon dioxide production, etc.). Carbon dioxide production was used for the estimation of the ethanol productivity. The analysis of the measured data allowed to detect states or trends that may be indicative of process or system failures, providing advices and/or alarms. The results showed the reliability of the control system. In previous works, it was proven that pulsing the feed stream highly improves the productivity of fermentation processes carried out in fixed-bed bioreactors [14, 15, 16]. The amplitude and frequency of the pulsation, which is a key factor in the performance of a pulsed feed bioreactor [13], was selected by the control system by using an algorithm allowing the ethanol productivity to be optimized. The pulsation frequency which maximizes the ethanol productivity, presents a high dependency on the hydraulic residence time and the feeding substrate concentration. When increasing the substrate concentration the optimum pulsation frequency also increases; when increasing the hydraulic residence time the optimum pulsation frequency decreases.     

Improving the monitoring of methanol concentration during high cell density fermentation of Pichia pastoris

The Pichia pastoris expression system is widely used for the production of recombinant proteins. A simple and efficient experimental set-up allowing on-line monitoring of the methanol concentration during the fermentation of P. pastoris based on the detection of the methanol vapor concentration in the exhaust air from fermenter by a tin dioxide (SnO2) semiconductor sensor is described. An experimental procedure to allow precise calibration of the system and to reduce methanol sensor's interferences (>95% reduction) are also presented and discussed. Accuracy and measurement error were estimated about 0.05 g x l(-1) and 6%, respectively. The efficient monitoring of methanol will help to advanced control of recombinant protein production and process optimization.     

Monitoring of Lactobacillus fermentation process by using ion chromatography with a series piezoelectric quartz crystal detector

A new method monitoring Lactobacillus fermentation process, which combines ion chromatography (IC) with a series piezoelectric quartz crystal (SPQC) technique, is presented in this paper. Monitoring of the fermentation process was realized by examining the rate of production of lactic acid. An automatic membrane dialyser was used for the pretreatment of the sample in on-line monitoring. A mixture of p-hydroxybenzoic acid and N,N-diethylethanolamine was adopted as mobile phase and its flow rate was 0.8 ml/min. The effects of some fermentation conditions were also discussed in detail. Accordingly, the optimal fermentation conditions were obtained. This method is simple and convenient while the results obtained are accurate and reliable.     

Measuring kLa with randomly pulsed dynamic method

This reports on the determination of the overall oxygen transfer coefficient in a mechanically agitated vessel using a randomly pulsed dynamic method. This method consists in exciting the system by randomly switching the inlet gas stream with air or nitrogen with an identical volumetric flow rate. A pseudo-random binary sequence was used. This procedure is routinely used in process control for the identification of system's transfer function. The pulsed dynamic method gives good reliability (as compared with the traditional gassing-out method) and reproducibility in water. However, further improvement is needed before it can be used to monitor on-line the k(L)a during a fermentation.     

Simultaneous determination of L- and D-methotrexate using a sequential injection analysis/amperometric biosensors system

A sequential injection analysis (SIA) is proposed for the simultaneous determination of L- and D-methotrexate (Mtx) using amperometric biosensors as detectors. A SIA system is proposed due to the highest precision and accuracy and lower consumption of sample and buffer. The amperometric biosensors used as detectors in SIA system were based on L-amino acid oxidase (L-AAOD) or/and L-glutamate oxidase (L-Glox) and horseradish peroxidase (HRP) for the assay of L-Mtx and D-amino acid oxidase (D-AAOD) and HRP for the assay of D-Mtx were selected. The linear concentration ranges are of pmol/l to nmol/l magnitude order, with very low limits of detection. The SIA/biosensors system can be used reliably on-line in synthesis process control, for the simultaneous assay of L- and D-Mtx with a frequency of 34 samples per hour.     

Adaptive on-line model for aerobic Saccharomyces cerevisiae fermentation

In order to study and control fermentation processes, indirect on-tine measurements and mathematical models can be used. In this article we present a mathematical on-line model for fermentation processes. The model is based on atom and partial mass balances as well as on equations describing the acid-base system. The model is brought into an adaptive form by including transport equations for mass transfer and unstructured expressions for the fermentation kinetics. The state of the process, i.e., the concentrations of biomass, substrate, and products, can be estimated on-line using the balance part of the model completed with measurement equations for the input and output flows of the process. Adaptivity is realized by means of on-line estimation of parameters in the transport and kinetic expressions using recursive regression analysis. These expressions can thus be used in the model as valid equations enabling prediction of the process. This makes model-based automation of the process and testing of the validity of the measurement variables possible. The model and the on-line principles are applied to a 3.5-L laboratory tormentor in which Saccharomyces cerevisiae is cultivated. The experimental results show that the model-based estimation of the state and the predictions of the process correlate closely with high-performance liquid chromatography (HPLC) analyses. (c) 1995 John Wiley & Sons, Inc.     

A knowledge based system for diagnosing microbial activities during a fermentation process

A knowledge based system, LAexpert, was developed to diagnose microbial activities during a fermentation process on the basis of specific rates determined on-line. The LAexpert is a supervisor for a process control system and assists operators in fault diagnosis. The LAexpert was implemented using a fuzzy expert system shell based on the object oriented programming tool Smalltalk V/Mac running in a Macintosh II computer. The shell can handle uncertainties both in the measurements and knowledge by fuzzy reasoning.List of Symbols X g/l biomass dry weight (g/l) - S g/l substrate concentration (g/l) - P g/l product concentration (g/l) - _c, _c, _c 1/h specific rates calculated from on-line measured data of X, S and P (1/h) - _d, _d, _d 1/h specific rates read from database of BIOACS (1/h)     

A near-infrarod spectroscopy technique for the control of fermentation processes: An application to lactic acid fermentation

A near-infrared (NIR) spectroscopy technique for the control of lactic acid fermentation process has been proposed. Lactic acid, glucose, and biomass concentrations were determined by the NIR spectroscopy method. The three parameters examined were closely correlated to the results obtained with classical laboratory procedures. Moreover, the conditions for the on-line utilization of the NIR spectroscopy measurement system were pointed out. The great versatility of the NIR spectroscopy should permit its use for other fermentation processes. (c) 1994 John Wiley & Sons, Inc.     

Model-based control of feed rate and illuminance in a photosynthetic fed-batch reactor for H2S removal

Traditional application of computer to fermentation processes has focused on the measurement and control of parameters such as temperature, pH, vessel pressure, sparge rate, dissolved oxygen, substrate concentration, and product concentration. In a fed-batch reactor with the photosynthetic green sulfur bacterium Chlorobium thiosulfatophilum which converts hydrogen sulfide to elementary sulfur or sulfate, separate measurement of cell mass concentration and sulfur particle concentration turbidimetrically was difficult due to their combined contributions to the total turbidity. Instead of on-line measurement of many process variables, a model-based control of feed rate and illuminance was designed. Optimal operation condition relating feed rate vs. light intensity was obtained to suppress the accumulation of sulfate and sulfide, and to save light energy in a 4-1 photosynthetic fed-batch reactor. This relation was correlated with the inreasing cell mass concentration. A model which describes the cell growth by considering the light attenuation effects due to scattering and absorption, and to crowding effect of the cells, was established beforehand with the results from the experiments. Based on these optimal operating conditions and the cell growth model, automatic controls of feed rate and illuminance were carried out alternatively to the traditional application of computer to fermentation with on-line measurement, realtime response and adjustment of process variables.List of Symbols F ml/min Flow rate of gas mixture - hV lux Average illuminance - Q mmol/(l h) Removal rate of hydrogen sulfide - X mg protein/l Cell mass concentration as protein - X ₀ mg protein/l Initial cell mass concentration - X _m mg protein/l Maximum cell mass concentration - _a h^–1 Apparent specific growth rate     

On-line near infrared monitoring of glycerol-boosted anaerobic digestion processes: evaluation of process analytical technologies

A study of NIR as a tool for process monitoring of thermophilic anaerobic digestion boosted by glycerol has been carried out, aiming at developing simple and robust Process Analytical Technology modalities for on-line surveillance in full scale biogas plants. Three 5 L laboratory fermenters equipped with on-line NIR sensor and special sampling stations were used as a basis for chemometric multivariate calibration. NIR characterisation using Transflexive Embedded Near Infra-Red Sensor (TENIRS) equipment integrated into an external recurrent loop on the fermentation reactors, allows for representative sampling, of the highly heterogeneous fermentation bio slurries. Glycerol is an important by-product from the increasing European bio-diesel production. Glycerol addition can boost biogas yields, if not exceeding a limiting 5-7 g L(-1) concentration inside the fermenter-further increase can cause strong imbalance in the anaerobic digestion process. A secondary objective was to evaluate the effect of addition of glycerol, in a spiking experiment which introduced increasing organic overloading as monitored by volatile fatty acids (VFA) levels. High correlation between on-line NIR determinations of glycerol and VFA contents has been documented. Chemometric regression models (PLS) between glycerol and NIR spectra needed no outlier removals and only one PLS-component was required. Test set validation resulted in excellent measures of prediction performance, precision: r(2) = 0.96 and accuracy = 1.04, slope of predicted versus reference fitting. Similar prediction statistics for acetic acid, iso-butanoic acid and total VFA proves that process NIR spectroscopy is able to quantify all pertinent levels of both volatile fatty acids and glycerol.     

Two-stage culture process for improved production of ganoderic acid by liquid fermentation of higher fungus Ganoderma lucidum

Investigations on the impact of pellet size on the cellular oxygen uptake and accumulation of ganoderic acid (GA) suggested the favorable effect of oxygen limitation on GA formation by the higher fungus Ganoderma lucidum. A two-stage fermentation process was thus proposed for enhanced GA production by combining conventional shake-flask fermentation with static culture. A high cell density of 20.9 g of DW/L (DW = dry cell weight) was achieved through a 4-day shake-flask fermentation followed by a 12-day static culture. A change in the cell morphology and a decrease in the sugar consumption rate were observed during the static culture. The GA production in the new two-stage process was considerably enhanced with its content increased from 1.36 (control) to 3.19 mg/100 mg of DW, which was much higher than previously observed.     

Yeast killer activity: A quantitative study

Summary A method, based on the reaction of a sensitive strain being transferred to medium prefermented by a killer strain, is proposed for the quantitative determination of the killer activity in fermentation media by Saccharomyces cerevisiae K1. This technique enables killer activity to be closely followed throughout the duration of batch fermentation. The killer activity in the culture medium is represented by the percentage decrease in viable biomass in comparison with the viable biomass of a reference culture.