Evaluation of spectrofluorometry as a tool for estimation in fed-batch fermentations

Native culture fluorescence was investigated as an additional source of information for predicting biomass and glucose concentrations in a fed-batch fermentation of Alcaligenes eutrophus. Partial least squares (PLS) regression and a feed forward neural network (FFNN) coupled with principle component analysis (PCA) were each used to model the kinetics of the fermentation. Data from three fermentations was combined to form a training set for model calibration and data from a fourth fermentation was used as the testing set. The fluorescent soft-sensors were compared with a previously developed feed forward neural network soft-sensor model which used oxygen uptake rate (OUR), carbon dioxide evolution rate (CER), aeration rate, feed rate, and fermentor volume to estimate biomass and glucose concentrations. The best model performance for predicting both biomass and glucose concentrations was achieved using the native fluorescence-based models. Real data predictions of the biomass concentration in the testing set were obtained using both the PLS and FFNN PCA modeling utilizing fluorescence measurements plus the rate of change of the fluorescence measurements. Accurate predictions of the glucose concentration in the testing set were obtained using the FFNN PCA modeling technique utilizing the rate of change of the fluorescence measurements. Substrate exhaustion was indicated qualitatively by a first-order PLS model utilizing the rate of change of fluorescence measurements. These results indicate that native culture fluorescence shows promise for providing additional valuable information to enhance predictive modeling which cannot be extracted from other easily acquired measurements.     

Determination of in vivo oxygen uptake and carbon dioxide evolution rates from off-gas measurements under highly dynamic conditions

In vivo kinetics of Saccharomyces cerevisiae are studied, in a time window of 150 s, by analyzing the response of O(2) and CO(2) in the fermentor off-gas after perturbation of chemostat cultures by metabolite pulses. Here, a new mathematical method is presented for the estimation of the in vivo oxygen uptake rate (OUR) and carbon dioxide evolution rate (CER) directly from the off-gas data in such perturbation experiments. The mathematical construction allows effective elimination of delay and distortion in the off-gas measurement signal under highly dynamic conditions. A black box model for the fermentor off-gas system is first obtained by system identification, followed by the construction of an optimal linear filter, based on the identified off-gas model. The method is applied to glucose and ethanol pulses performed on chemostat cultures of S. cerevisiae. The estimated OUR is shown to be consistent with the independent dissolved oxygen measurement. The estimated in vivo OUR and CER provide valuable insights into the complex dynamic behavior of yeast and are essential for the establishment and validation of in vivo kinetic models of primary metabolism.     

基于活细胞量测量的利福霉素发酵过程氮源优化策略

在发酵生产利福霉素SV的过程中,其菌丝体的生长代谢情况及产物发酵合成都与有活力的菌丝量密切相关.介绍了在线活细胞传感仪测定活细胞量的方法,它利用细胞的介电特性,能够排除发酵液中固含物的干扰,测得的电容值与活细胞浓度呈线性相关,可以作为工艺优化过程中的关键参数.通过电容变化反映的前期生长出现的二次生长现象,进行了通过使用迟效氮源豆饼粉代替了原培养基中价格昂贵的速效氮源蛋白胨,成功消除了发酵前期由于氮源利用转换造成的生长停滞期,利用豆饼粉情况下培养前期的OUR和CER达到了14.8和15.3 mmol/L/h,明显高于利用速效氮源蛋白胨A组的8.6和11.3 mmol/L/h,保证了持续较高的比生长速率,对于促进菌体的氧消耗速率的增加和维持有着重要的作用,明显有利于利福霉素的合成与速率的维持,氮源替代组的发酵效价达到了5969±19 U/ml,与对照组(5030±17U/ml)相比显著提升发酵单位18.7%以上.     

重组毕赤酵母表达工程植酸酶发酵过渡相参数相关分析

微生物发酵是一个涉及不同尺度的互相关联的复杂生物系统的过程 ,将重组毕赤酵母表达工程植酸酶过渡相的在线和离线参数进行了相关分析研究。通过对发酵过程的在线细胞代谢生理参数 (OUR)和环境参数 (DO)的变化进行相关分析表明 :甘油和葡萄糖碳源对AOX合成的阻遏强度不同 ,葡萄糖的阻遏性明显强于甘油 ,相对于醇氧化酶启动子 ,葡萄糖为强阻遏性底物。根据甲醇代谢途径关键酶酶活性变化 ,推测出各代谢途径流量分布的变化 ,即甲醇诱导后糖酵解途径和三羧酸循环途径代谢流比例下降 ,而磷酸戊糖途径中代谢流通量上升 ,甲醇完全氧化代谢流成为主要代谢流 ,与过渡相在线参数pH、OUR(CER)和RQ等相关分析的甲醇代谢途径的变化结果一致。此外 ,建立了生产过程在线控制与分析的标准 :当OUR和CER逐渐增大 ,则可判断甲醇已被利用和启动子已被甲醇成功诱导 ,即工程植酸酶开始启动表达.     

A kinetic model for lutein production by the green microalga Chlorella protothecoides in heterotrophic culture

Production of lutein by the green microalga Chlorella protothecoides grown heterotrophically in a fermentor using glucose as the carbon source and urea as the nitrogen source was investigated. An unstructured kinetic model was proposed to describe the microalgal culture system including cell growth, lutein formation, as well as glucose and nitrogen consumption. The inhibition potentials of biomass, product and substrates on growth and lutein formation were examined and incorporated into the kinetic model. Values of the kinetic model parameters were estimated. The resulting model predictions were in good agreement with the experimental results. The model can be helpful in scale-up, optimization and control of the C. protothecoides culture process, and can also be used as a guideline for similar microalgal cultivation systems. Received 28 January 1999/ Accepted in revised form 27 August 1999     

Optimization of microalgal photobioreactor system using model predictive control with experimental validation

To maximize biomass and lipid concentrations, various optimization methods were investigated in microalgal photobioreactor systems under mixotrophic conditions. Lipid concentration was estimated using unscented Kalman filter (UKF) with other measurable sources and subsequently used as lipid data for performing model predictive control (MPC). In addition, the maximized biomass and lipid trajectory obtained by open-loop optimization were used as target trajectory for tracking by MPC. Simulation studies and experimental validation were performed and significant improvements in biomass and lipid productivity were achieved in the case where MPC was applied. However, occurence of a lag phase was observed while manipulating the feed flow rates, which is induced by large amount of inputs. This is an important phenomenon that can lead to model–plant mismatch and requires further study for the optimization of microalgal photobioreactors.     

On-line monitoring of respiration in recombinant-baculovirus infected and uninfected insect cell bioreactor cultures

Respiration rates in Spodoptera frugiperda (Sf-9) cell bioreactor cultures were successfully measured on-line using two methods: The O(2) uptake rate (OUR) was determined using gas phase pO(2) values imposed by a dissolved oxygen controller and the CO(2) evolution rate (CER) was measured using an infrared detector. The measurement methods were accurate, reliable, and relatively inexpensive. The CER was routinely determined in bioreactor cultures used for the production of several recombinant proteins. Simple linear relationships between viable cell densities and both OUR and CER in exponentially growing cultures were used to predict viable cell density. Respiration measurements were also used to follow the progress of baculoviral infections in Sf-9 cultures. Infection led to increases in volumetric and per-cell respiration rates. The relationships between respiration and several other culture parameters, including viable cell density, cell protein, cell volume, glucose consumption, lactate production, viral titer, and recombinant beta-galactosidase accumulation, were examined. The extent of the increase in CER following infection and the time postinfection at which maximum CER was attained were negatively correlated with the multiplicity of infection (MOI) at multiplicities below the level required to infect all the cells in a culture. Delays in the respiration peak related to the MOI employed were correlated with delays in the peak in recombinant protein accumulation. DO levels in the range 5-100% did not exert any major effects on viable cell densities, CER, or product titer in cultures infected with a baculovirus expressing recombinant beta-galactosidase. (c) 1996 John Wiley & Sons, Inc.     

A macrokinetic modelling of the biosynthesis of lovastatin by Aspergillus terreus

In this work a simple kinetic model to describe the biosynthesis of lovastatin by Aspergillus terreus ATCC 20542 was proposed. Several series of experiments were conducted at different media compositions. The concentrations of C- and N-sources were changed over a wide range and so were the initial biomass concentrations. From these runs the relationships ruling the substrates uptake, biomass and product formation were learnt. Lovastatin biosynthesis appeared to be partly growth associated. The inhibitive effect of organic nitrogen on lovastatin biosynthesis was found and lactose appeared to be an important limiting substrate in the formation of lovastatin. The parameters of the model were evaluated on the basis of the kinetic data obtained in the separate experiments made in triplicate at two chosen media compositions. Other results obtained at different media compositions were independent of the ones mentioned above and used for the verification of the model. The validity of the model was also examined for the lactose-fed fed-batch run. Finally, a sensitivity analysis of the model parameters was performed. The formulated model, although relatively simplified, described the experimental data quite well and could be regarded as the background for further attempts to mathematically describe the process of lovastatin biosynthesis.     

A closed-loop artificial pancreas based on model predictive control: Human-friendly identification and automatic meal disturbance rejection

Type 1 diabetes is characterized by a lack of insulin production by the pancreas, causing high blood glucose concentrations and requiring external insulin infusion to regulate blood glucose. Continuous glucose sensors can be coupled with continuous insulin infusion pumps to create a closed-loop artificial pancreas. A novel procedure of “human-friendly” identification testing using multisine inputs is developed to estimate suitable models for use in an artificial pancreas. A constrained model predictive control (MPC) strategy is developed to reduce risks of hypo- and hyperglycemia (low and high blood glucose concentration). Meal detection and meal size estimation algorithms are developed to improve meal glucose disturbance rejection when incoming meals are not announced. Closed-loop performance is evaluated through simulation studies of a type 1 diabetic individual, illustrating the ability of the MPC-based artificial pancreas control strategy to handle announced and unannounced meal disturbances.     

杂交瘤细胞培养中摄氧速率(OUR)的在线检测及其与细胞生长及代谢的关系

在批式及灌流培养条件下研究了杂交瘤细胞在无血清培养基中的生长、代谢情况与氧消耗的关系。应用动力学方法在线进行OUR的检测,同时离线取样检测其他参数。结果发现OUR与谷氨酰胺的消耗、抗体的生成及活细胞密度间有明显的相关关系,进一步的分析还发现在对数生长期,OUR与活细胞密度间具有良好的线性关系,qOUR(0.103±0.028)×10^-12mol/cell/h,可以通过它来进行细胞密度的在线检测。并通过以ΔOUR=0时刻作为灌流调整点进行连续灌流培养的初步实验验证了OUR作为培养过程反馈控制参数的可能性。     

A simple and modified manometric method for measuring oxygen uptake rate of plant cells in flask cultures

Summary A simple and convenient technique was developed based on the principle of Warburg manometric method to measure O₂ uptake rate (OUR) and CO₂ evolution rate (CER) of suspended cells in a shake flask culture. It was successfully applied to suspension cultures of rice (Oryza sativa) and Panax notoginseng cells, and some important bioprocess parameters, such as OUR, CER, respiratory quotient (RQ), specific OUR (SOUR) and specific CER (SCER), were quantitatively obtained. The measuring system is easy to operate, able to treat many samples simultaneously and is economical.     

Kinetics of biodegradation of p-xylene and naphthalene and oxygen transfer in a novel airlift immobilized bioreactor

The scope of this study included the biodegradation performance and the rate of oxygen transfer in a pilot-scale immobilized soil bioreactor system (ISBR) of 10-L working volume. The ISBR was inoculated with an acclimatized population of contaminant degrading microorganisms. Immobilization of microorganisms on a non-woven polyester textile developed the active biofilm, thereby obtaining biodegradation rates of 81 mg/L x h and 40 mg/L x h for p-xylene and naphthalene, respectively. Monod kinetic model was found to be suitable to correlate the experimental data obtained during the course of batch and continuous operations. Oxygen uptake and transfer rates were determined during the batch biodegradation process. The dynamic gassing-out method was used to determine the oxygen uptake rate (OUR) and volumetric oxygen mass transfer, K(L) a. The maximum volumetric OUR of 255 mg O(2)/L x h occurred approximately at 720-722 h after inoculation, when the dry weight of biomass concentration was 0.67 g/L.     

外源葡萄糖对山定子生长及根系氮素代谢的影响

以有机质含量仅为0.65%的低碳冲积沙土为栽培基质,以当年生山定子幼苗为试材,分别添加与土壤本体微生物生物量碳(MBC)等量的碳量(2 g·kg^-1)、5倍MBC碳量(10g·kg^-1)的葡萄糖,以不添加葡萄糖为对照,处理后0~30 d内定期采集根系样品,研究外源葡萄糖对低碳土壤中山定子幼苗生长、根系构型及氮素代谢的影响.结果表明:5倍MBC碳源处理后山定子幼苗的株高、总生物量、总根长和根表面积分别显著增加12.3%、26.4%、23.2%和14.6%,而茎粗、根体积和平均直径无显著变化.等量及5倍MBC碳源处理均显著提高了山定子的根系活力,分别在第3和15天达到峰值,高于对照119.1%和75.7%.在整个处理期间,等量及5倍MBC碳源处理显著增加了根中NO_3^-、NO_2^-和NH_4^+含量;整体上,等量及5倍MBC碳源处理均显著增强根系中硝酸还原酶、谷氨酰胺合酶、谷氨酸脱氢酶、谷氨酸合酶、谷草转氨酶和谷丙转氨酶的活性,其中5倍MBC处理的作用最显著.5倍MBC的外源葡萄糖浓度更有利于促进低碳土壤中山定子根系中氮素的吸收代谢过程,诱导植株生长、干物质积累和根系构型改变.     

Forecasting and control of lactate bifurcation in Chinese hamster ovary cell culture processes

Biomanufacturing exhibits inherent variability that can lead to variation in performance attributes and batch failure. To help ensure process consistency and product quality the development of predictive models and integrated control strategies is a promising approach. In this study, a feedback controller was developed to limit excessive lactate production, a widespread metabolic phenomenon that is negatively associated with culture performance and product quality. The controller was developed by applying machine learning strategies to historical process development data, resulting in a forecast model that could identify whether a run would result in lactate consumption or accumulation. In addition, this exercise identified a correlation between increased amino acid consumption and low observed lactate production leading to the mechanistic hypothesis that there is a deficiency in the link between glycolysis and the tricarboxylic acid cycle. Using the correlative process parameters to build mechanistic insight and applying this to predictive models of lactate concentration, a dynamic model predictive controller (MPC) for lactate was designed. This MPC was implemented experimentally on a process known to exhibit high lactate accumulation and successfully drove the cell cultures towards a lactate consuming state. In addition, an increase in specific titer productivity was observed when compared with non-MPC controlled reactors.     

Modelling and dynamic simulation of a moving bed bioreactor using respirometry for the estimation of kinetic parameters

Respirometry was used for the characterization of active autotrophic and heterotrophic biomass in a pilot scale moving bed bioreactor (MBBR). For this purpose biofilm samples attached to the carrier elements of the MBBR were transferred to a static gas/static liquid type respirometer with intermittent aeration. Known amounts of ammonia nitrogen and acetate were added to the respirometer. The dissolved oxygen (DO) decrease during the non-aeration phase was measured and used to calculate the oxygen uptake rate (OUR) of the active biomass. The resulting respirograms featured the typical endogenous and exogenous respiration phases and the shape of the respirogram was as expected from analogous respirometry with activated sludge. The OUR response was modelled with the activated sludge model ASM1 and the relevant kinetic parameter values for autotrophic and heterotrophic growth were adjusted. The adjusted parameter set and data originating from a 4-day long intensive measurement campaign were used for modelling and simulation of the pilot scale MBBR. The parameter estimation resulted in a good dynamic simulation of ammonia and nitrate variations in the effluent of the MBBR. Important MBBR properties including biofilm age, biofilm composition, and both attachment and detachment rate were extracted from the model.     

Oxygen supply controls the onset of pristinamycins production by Streptomyces pristinaespiralis in shaking flasks

Antibiotics are secondary metabolites, generally produced during stationary phase of growth under different nutritional and hydrodynamic stresses. However, the exact mechanisms of the induction of antibiotics production are still not clearly established. In a previous study, the induction of pristinamycins production by Streptomyces pristinaespiralis as well as product concentrations were correlated with power dissipation per unit of volume (P/V) in shaking flasks. In this study, detailed kinetics of growth, substrate consumption, oxygen transfer rate and pristinamycins production under varying P/V conditions have been obtained and analyzed. Our results showed that higher P/V resulted in a higher concentration of biomass and promoted an earlier nutrient limitation and ultimately an earlier induction of pristinamycins production. The maximal specific growth rate, specific oxygen consumption rate and specific consumption rate of glutamate increased with P/V while influence was less marked with specific consumption rate of glucose, arginine, ammonium ions and phosphate. When oxygen uptake rate (OUR) was limited by free-surface oxygen transfer, pristinamycins production was not detected despite the occurrence of nitrogen and/or phosphate sources limitation. The threshold value for OUR observed was around 25 mmol L(-1) h(-1). This suggested that a limitation in nitrogen and/or phosphate alone was not sufficient to induce pristinamycins production by S. pristinaespiralis pr11. To induce this production, the oxygen transfer had to be non-limiting.     

Machine learning-based model predictive controller design for cell culture processes

The biopharmaceutical industry continuously seeks to optimize the critical quality attributes to maintain the reliability and cost-effectiveness of its products. Such optimization demands a scalable and optimal control strategy to meet the process constraints and objectives. This work uses a model predictive controller (MPC) to compute an optimal feeding strategy leading to maximized cell growth and metabolite production in fed-batch cell culture processes. The lack of high-fidelity physics-based models and the high complexity of cell culture processes motivated us to use machine learning algorithms in the forecast model to aid our development. We took advantage of linear regression, the Gaussian process and neural network models in the MPC design to maximize the daily protein production for each batch. The control scheme of the cell culture process solves an optimization problem while maintaining all metabolites and cell culture process variables within the specification. The linear and nonlinear models are developed based on real cell culture process data, and the performance of the designed controllers is evaluated by running several real-time experiments.     

Morphologically structured model for antitumoral retamycin production during batch and fed-batch cultivations of Streptomyces olindensis

A morphologically structured model is proposed to describe trends in biomass growth, substrate consumption, and antitumoral retamycin production during batch and fed-batch cultivations of Streptomyces olindensis. Filamentous biomass is structured into three morphological compartments (apical, subapical, and hyphal), and the production of retamycin, a secondary metabolite, is assumed to take place in the subapical cell compartment. Model accounts for the effect of glucose as well as complex nitrogen source on both the biomass growth and retamycin production. Laboratory data from bench-scale batch and fed-batch fermentations were used to estimate some model parameters by nonlinear regression. The predictive capability of the model was then tested for additional fed-batch and continuous experiments not used in the previous fitting procedure. The model predictions show fair agreement to the experimental data. The proposed model can be useful for further studies on process optimization and control.     

Parametric sensitivity analysis and reduction of a detailed nutritional model of plant cell cultures

A kinetic model of plant nutrition described by Cloutier et al. (Cloutier et al., 2008. Biotechnol Bioeng 99:189-200) is progressively simplified so as to obtain a predictive model that describes the evolution of the biomass and the extracellular and intracellular concentrations of three determining nutrients, that is, free intracellular nitrogen, phosphate, and carbohydrate compounds. Three techniques of global sensitivity analysis are successively applied to assess the model parameter influence and potential correlation. The resulting dynamic model is able to predict plant growth for the two most encountered plant bioprocesses, namely suspension cells and hairy roots.     

Respirometric evaluation and modeling of glucose utilization by Escherichia coli under aerobic and mesophilic cultivation conditions

The study presents a mechanistic model for the evaluation of glucose utilization by Escherichia coli under aerobic and mesophilic growth conditions. In the first step, the experimental data was derived from batch respirometric experiments conducted at 37 degrees C, using two different initial substrate to microorganism (S(0)/X(0)) ratios of 15.0 and 1.3 mgCOD/mgSS. Acetate generation, glycogen formation and oxygen uptake rate profile were monitored together with glucose uptake and biomass increase throughout the experiments. The oxygen uptake rate (OUR) exhibited a typical profile accounting for growth on glucose, acetate and glycogen. No acetate formation (overflow) was detected at low initial S(0)/X(0) ratio. In the second step, the effect of culture history developed under long-term growth limiting conditions on the kinetics of glucose utilization by the same culture was evaluated in a sequencing batch reactor (SBR). The system was operated at cyclic steady state with a constant mean cell residence time of 5 days. The kinetic response of E.coli culture was followed by similar measurements within a complete cycle. Model calibration for the SBR system showed that E. coli culture regulated its growth metabolism by decreasing the maximum growth rate (lower microH) together with an increase of substrate affinity (lower K(S)) as compared to uncontrolled growth conditions. The continuous low rate operation of SBR system induced a significant biochemical substrate storage capability as glycogen in parallel to growth, which persisted throughout the operation. The acetate overflow was observed again as an important mechanism to be accounted for in the evaluation of process kinetics.