Determination of cell mass and polymyxin using multi-wavelength fluorescence

Multi-wavelength fluorescence was applied for on-line monitoring of cell mass and the antibiotic polymyxin B in Bacillus polymyxa cultivations. By varying the phosphate and nitrogen content of the medium different polymyxin-cell mass ratios could be obtained. Using this strategy, it was possible to investigate if multi-wavelength fluorescence is able to give independent prediction of the two parameters. Partial least square (PLS) regression was applied to establish mathematical relationships between off-line determined cell mass and polymyxin concentrations and on-line collected fluorescence data. For polymyxin one universal PLS model, with a correlation of 0.95 and a root mean square error of cross validation (RMSECV) of 35 mgl(-1), could be constructed. However, correlation between fluorescence and cell mass dry weight could not be established including data from all three types of cultivations. For data from each type of cultivation, separate models with high correlation and low RMSECV values were built. A large variation in cellular composition as a result of the different levels of nitrogen and phosphorus in the cultivations was the probable reason to the necessity of building three models. The results of the present investigation indicate that production of polymyxin is concomitantly regulated by phosphate and nitrogen as the highest polymyxin yield on cell mass, 0.17+/-0.01 gg(-1), was reached in the cultivations where both nitrogen and phosphate concentrations were kept low.     

Soft sensor based on 2D‐fluorescence and process data enabling real‐time estimation of biomass in Escherichia coli cultivations

In bioprocesses, specific process responses such as the biomass cannot typically be measured directly on‐line, since analytical sampling is associated with unavoidable time delays. Accessing those responses in real‐time is essential for Quality by Design and process analytical technology concepts. Soft sensors overcome these limitations by indirectly measuring the variables of interest using a previously derived model and actual process data in real time. In this study, a biomass soft sensor based on 2D‐fluorescence data and process data, was developed for a comprehensive study with a 20‐L experimental design, for Escherichia coli fed‐batch cultivations. A multivariate adaptive regression splines algorithm was applied to 2D‐fluorescence spectra and process data, to estimate the biomass concentration at any time during the process. Prediction errors of 4.9% (0.99 g/L) for validation and 3.8% (0.69 g/L) for new data (external validation), were obtained. Using principal component and parallel factor analyses on the 2D‐fluorescence data, two potential chemical compounds were identified and directly linked to cell metabolism. The same wavelength pairs were also important predictors for the regression‐model performance. Overall, the proposed soft sensor is a valuable tool for monitoring the process performance on‐line, enabling Quality by Design.     

Chemometric analysis of in-line multi-wavelength fluorescence measurements obtained during cultivations with a lipase producing Aspergillus oryzae strain

The filamentous fungus, Aspergillus oryzae, was cultivated in batch and fed-batch cultivations in order to investigate the use of multi-wavelength fluorescence for monitoring course of events during filamentous fungi cultivations. The A. oryzae strain applied expressed a fungal lipase from Thermomyces lanuginosus. Spectra of multi-wavelength fluorescence were collected every 5 min with the BioView system (DELTA, Denmark) and both explorative and predictive models, correlating the fluorescence data with cell mass and lipase activity, were built. During the cultivations, A. oryzae displayed dispersed hyphal growth and under these conditions no fouling of the multi-wavelength fluorescence sensor was observed. The scores of a parallel factor analysis (PARAFAC) model, based on the fluorescence spectra, gave clear evidence of, for example, the on-set of the feeding phase. The predictive models, estimating the cell mass, showed correlations between 0.73 and 0.97 with root mean square error of cross validation (RMSECV) values between 1.48 and 0.77 g . kg(-1). A model estimating the lipase activity was also constructed for the fed-batch cultivations with a correlation of 0.93. The results presented here clearly show that multi-wavelength fluorescence is a useful tool for monitoring fed-batch cultivations of filamentous fungi.     

On-line monitoring of recombinant bacterial cultures using multi-wavelength fluorescence spectroscopy

Multi-wavelength fluorescence spectroscopy was evaluated as a tool for on-line monitoring of recombinant Escherichia coli cultivations expressing human basic fibroblast growth factor (hFGF-2). The data sets for the various combinations of the excitation and emission spectra from batch cultivations were analyzed using principal component analysis. Chemometric models (the partial least squares method) were developed for correlating the fluorescence data and the experimentally measured variables such as the biomass and glucose concentrations as well as the carbon dioxide production rate. Excellent correlations were obtained for these variables for the calibration cultivations. The predictability of these models was further tested in batch and fed-batch cultivations. The batch cultivations were well predicted by the PLS models for biomass, glucose concentrations and carbon dioxide production rate (RMSEPs were respectively 5%, 7%, 9%). However, when tested for biomass concentrations in fed-batch cultivations (with final biomass three times higher than the highest calibration data) the models had good predictability at high growth rates (RMSEPs were 3% and 4%, respectively for uninduced and induced fed-batch cultivations), which was as good as for the batch cultivations used for developing the models (RMSEPs were 3% and 5%, respectively for uninduced and induced batch cultivations). The fed-batch cultivations performed at low growth rates exhibited much higher fluorescence for fluorophores such as flavin and NAD(P)H as compared to fed-batch cultivations at high growth rate. Therefore, the PLS models tended to over-predict the biomass concentrations at low growth rates. Obviously the cells changed their concentration of biogenic fluorophores depending on the growth rate. Although multi-wavelength fluorescence spectroscopy is a valuable tool for on-line monitoring of bioprocess, care must be taken to re-calibrate the PLS models at different growth rates to improve the accuracy of predictions.     

On-line monitoring of marine cyanobacterial cultivation based on phycocyanin fluorescence.

A novel on-line fluorescence monitoring system for marine cyanobacterial cultivation was developed. This method is based on the measurement of intracellular phycocyanin content, which is the major light harvesting protein. A fluorescence spectrophotometer, equipped with a flow cell connected with a culture liquid recycling tube was used. Experiments were carried out using a marine unicellular cyanobacteria Synechococcus sp. NKBG 042902 isolated from Japanese coastal sea water. We have optimized excitation wavelength to avoid the light scattering, using non-pigmented old cells which no longer contained phycocyanin. At an excitation wavelength of 590 nm, light scattering was minimized. Viable cell concentration could be measured in the range of 2 x 10(6) to 2 x 10(8) cells per ml, without pronounced light scattering. Continuous monitoring of marine cyanobacteria cultivation was performed. Cell concentrations were determined by both culture fluorescence and by using a hemacytometer. A good linear correlation was obtained. We conclude that on-line monitoring of cyanobacterial culture fluorescence based on phycocyanin is a rapid, efficient and also versatile method for determining viable cell concentration.     

A novel LED‐based 2D‐fluorescence spectroscopy system for in‐line bioprocess monitoring of Chinese hamster ovary cell cultivations—Part II

This study was performed in order to evaluate a new LED‐based 2D‐fluorescence spectrometer for in‐line bioprocess monitoring of Chinese hamster ovary (CHO) cell culture processes. The new spectrometer used selected excitation wavelengths of 280, 365, and 455 nm to collect spectral data from six 10‐L fed‐batch processes. The technique provides data on various fluorescent compounds from the cultivation medium as well as from cell metabolism. In addition, scattered light offers information about the cultivation status. Multivariate data analysis tools were applied to analyze the large data sets of the collected fluorescence spectra. First, principal component analysis was used to accomplish an overview of all spectral data from all six CHO cultivations. Partial least square regression models were developed to correlate 2D‐fluorescence spectral data with selected critical process variables as offline reference values. A separate independent fed‐batch process was used for model validation and prediction. An almost continuous in‐line bioprocess monitoring was realized because 2D‐fluorescence spectra were collected every 10 min during the whole cultivation. The new 2D‐fluorescence device demonstrates the significant potential for accurate prediction of the total cell count, viable cell count, and the cell viability. The results strongly indicated that the technique is particularly capable to distinguish between different cell statuses inside the bioreactor. In addition, spectral data provided information about the lactate metabolism shift and cellular respiration during the cultivation process. Overall, the 2D‐fluorescence device is a highly sensitive tool for process analytical technology applications in mammalian cell cultures.     

On-line bioprocess monitoring with a multi-wavelength fluorescence sensor using multivariate calibration

Cultivations of Pseudomonas fluorescens were monitored with a multi-wavelength on-line fluorescence sensor. The multi-wavelength fluorometer used excitation light from 270 to 550 nm with 20 nm steps and measured fluorescence emission from 310 to 590 nm. The fluorescence, on-line exhaust gas measurements and off-line analysis of nitrate, succinate, optical density and protein were compared chemometrically by multivariate calibration, i.e. computing partial least square (PLS) regression models. Based on the multivariate regression models, it was possible to determine CO2 and O2 composition in the exhaust gas (the correlation coefficients, R2 between the predicted values by the PLS model and the measured values was 0.97 for CO(2) and 0.97 for O2, respectively). Also to make quantitative determinations of succinate (R(2) = 0.97), protein (R(2) = 0.94), optical density (R(2) = 1.0) and nitrate (R(2) = 0.98) in the medium based on the fluorescence spectra. Only a limited data set was available but the results indicated that the sensor could indirectly determine non-fluorescent compounds, i.e. nitrate and succinate, which probably is due to the stoichiometric relationship between fluorescent cellular components and non-fluorescent compounds. Consequently multi-wavelength fluorescence is an interesting technique for a wide range of applications.     

In situ 2D fluorometry and chemometric monitoring of mammalian cell cultures

The main objective of the present study was to investigate the use of in situ 2D fluorometry for monitoring key bioprocess variables in mammalian cell cultures, namely the concentration of viable cells and the concentration of recombinant proteins. All studies were conducted using a recombinant Baby Hamster Kidney (BHK) cell line expressing a fusion glycoprotein IgG1-IL2 cultured in batch and fed-batch modes. It was observed that the intensity of fluorescence signals in the excitation/emission wavelength range of amino acids, vitamins and NAD(P)H changed along culture time, although the dynamics of single fluorophors could not be correlated with the dynamics of the target state variables. Therefore, multivariate chemometric modeling was adopted as a calibration methodology. 2D fluorometry produced large volumes of redundant spectral data, which were first filtered by principal components analysis (PCA). Then, a partial least squares (PLS) regression was applied to correlate the reduced fluorescence maps with the target state variables. Two validation strategies were used to evaluate the predictive capacity of the developed PLS models. Accurate estimations of viable cells density (r(2) = 0.95; 99.2% of variance captured in the training set; r(2) = 0.91; 97.7% of variance captured in the validation set) and of glycoprotein concentration (r(2) = 0.99 and 99.7% of variance captured in the training set; r(2) = 0.99 and 99.3% of variance captured in the validation set) were obtained over a wide range of reactor operation conditions. The results presented herein confirm that 2D fluorometry constitutes a reliable methodology for on-line monitoring of viable cells and recombinant protein concentrations in mammalian cell cultures.     

In-situ near infrared spectroscopy to monitor key analytes in mammalian cell cultivation

The use of in-situ near infrared spectroscopy (NIRS) as a tool for monitoring four key analytes in a CHO-K1 animal cell culture was investigated. Previous work using on-line NIRS to monitor bioprocesses has involved its application ex-situ where the analyzer is physically outside the fermentor, or to microbial bioprocesses. This novel application of NIRS to monitor analytes within an animal cell culture using a steam sterilizable in-situ fiber optic probe is very important for furthering the use of NIRS within the bioprocessing industry. The method of calibration used to develop the models involved the use of large data sets so that all likely variation in stoichiometry was incorporated within the models. Successful models for glucose, lactate, glutamine, and ammonia were built with Standard Error of Predictions (SEP's) of 0.072 (g/L), 0.0144 (g/L), 0.308 (mM), and 0.036 (mM), respectively of the total concentration range.     

Cole–Cole, linear and multivariate modeling of capacitance data for on-line monitoring of biomass

This work evaluates three techniques of calibrating capacitance (dielectric) spectrometers used for on-line monitoring of biomass: modeling of cell properties using the theoretical Cole–Cole equation, linear regression of dual-frequency capacitance measurements on biomass concentration, and multivariate (PLS) modeling of scanning dielectric spectra. The performance and robustness of each technique is assessed during a sequence of validation batches in two experimental settings of differing signal noise. In more noisy conditions, the Cole–Cole model had significantly higher biomass concentration prediction errors than the linear and multivariate models. The PLS model was the most robust in handling signal noise. In less noisy conditions, the three models performed similarly. Estimates of the mean cell size were done additionally using the Cole–Cole and PLS models, the latter technique giving more satisfactory results.     

Estimation of microbial mass concentration based on fluorometric measurement of cell protein

To develop a convenient method for the estimation of microbial cell mass, the fluorescence intensity of protein (F₂₉₀) was measured in cell extracts from Escherichia coli, Ruminococcus albus, and Aspergillus niger. Cell extracts obtained by sodium dodecyl sulfate (SDS)-boiling treatment after sonication had high F₂₉₀ intensities under an excitation wavelength (EXW) of 290 nm and an emission wavelength (EMW) of 340 nm. On the basis of the fluorescence spectra, we confirmed that the fluorescence of the extract was caused by protein in the cell, especially by tryptophan residues in the proteins. Carbohydrate, lipids, nucleic acids, and vitamins from the cells did not inerfere significantly with the F₂₉₀ intensity. The intensity and cell mass concentration were related linearly below 0.15 g-cell/l, and the ratio of the intensity to the cell concentration was evaluated as a constant for each microorganism. It was thus possible to monitor the microbial cultures using the F₂₉₀ intensity as an indicator, even in culture systems where optical and gravimetric measurements of cell mass were not effective.     

Fluorescence-based soft-sensor for monitoring beta-lactoglobulin and alpha-lactalbumin solubility during thermal aggregation

A soft-sensor for monitoring solubility of native-like alpha-lactalbumin (alpha-LA) and beta-lactoglobulin (beta-LG) and their aggregation behavior following heat treatment of mixtures under different treatment conditions was developed using fluorescence spectroscopy data regressed with a multivariate Partial Least Squares (PLS) regression algorithm. PLS regression was used to correlate the concentrations of alpha-LA and beta-LG to the fluorescence spectra obtained for their mixtures. Data for the calibration and validation of the soft sensor was derived from fluorescence spectra. The process of thermal induced aggregation of beta-LG and alpha-LA protein in mixtures, which involves the disappearance of native-like proteins, was studied under various treatment conditions including different temperatures, pH, total initial protein concentration and proportions of alpha-LA and beta-LG. It was demonstrated that the multivariate regression models used could effectively deconvolute multi-wavelength fluorescence spectra collected under a variety of process conditions and provide a fairly accurate quantification of respective native-like proteins despite the significant overlapping between their emission profiles. It was also demonstrated that a PLS model can be used as a black-box prediction tool for estimating protein aggregation when combined with simple mass balances.     

On-line culture fluorescence measurement during the batch cultivation of poly-β-hydroxybutyrate producing Alcaligenes eutrophus

Estimation of biomass concentration by on-line fluorimetry was examined during batch cultivations of Alcaligenes eutrophus ATCC 17697, a poly-β-hydroxybutyric acid (PHB) producer. The results obtained revealed a linear correlation between total culture fluorescence and total biomass concentration. The total fluorescence level was attributed to cellular fluorescence and to the fluorescence of compounds presumably produced by the cells and secreted into the culture medium. An increase in the specific cellular fluorescence during the course of the experiments indicated a shift in metabolism that favored the production of PHB.     

Intracellular pH-based controlled cultivation of yeast cells: II. cultivation methodology

Intracellular pH (pH(i)) was measured on-line in a bioreactor using a fluorescent pH(i) indicator, 9-aminoacridine, and controlled fed-batch cultivations of yeast cells based on pH(i) (FB-pH(i)) were performed. In FB-pH(i) cultivations, automated glucose additions were made to the culture in response to culture pH(i). The average ethanol (an-aerobic product) yield was significantly lower [0.12 g g(-1) glucose in fed-batch pH(i) cultivations with 100 ppm glucose additions (FB-pH(i)-100 cultivation) vs. 0.48 g g(-1) glucose in batch] and cell yield was higher (0.54 g g(-1) glucose in FB-pH(i)-100 cultivation vs. 0.3 g g(-1) glucose in batch) compared to batch cultivation. An expression has been derived to calculate changes in pH(i) from measured fluorescence values when the cell concentration increases during growth. Cultivations based on pH(i), performed with different magnitudes of glucose addition (100, 50, and 10 ppm additions), showed that lower magnitudes of glucose addition resulted in lower ethanol yields while cell yield remained unaffected. The ratio of specific oxygen uptake rate to specific glucose uptake rate (OUR/GUR) increased with decreased in magnitude of glucose additions in FB-pH(i) cultivations, suggesting that the culture aerobic state was higher when the magnitude of glucose addition was lower. The average cell productivity in FB-pH(i) cultivations was 29% higher than in batch cultivation. Cells were also cultivated at high OUR conditions, and the results are compared with other cultivations. (c) 1993 John Wiley & Sons, Inc.     

Optimized prodigiosin production with Pseudomonas putida KT2440 using parallelized noninvasive online monitoring

The red pigment prodigiosin is of high pharmaceutical interest, due to its potential applications as an antitumor drug and antibiotic agent. As previously demonstrated, Pseudomonas putida KT2440 is a suitable host for prodigiosin production, as it exhibits high tolerance toward the antimicrobial properties of prodigiosin. So far, prodigiosin concentrations of up to 94 mg/L have been achieved in shake flask cultivations. For the characterization and optimization of the prodigiosin production process, the scattered light of P. putida and fluorescence of prodigiosin was measured. The excitation and emission wavelengths for prodigiosin measurement were analyzed by recording 2D fluorescence spectra. The strongest prodigiosin fluorescence was obtained at a wavelength combination of 535/560 nm. By reducing the temperature to 18 °C and using 16 g/L glucose, the prodigiosin concentration was more than doubled compared with the initial cultivation conditions. The obtained results demonstrate the capabilities of parallelized microscale cultivations combined with noninvasive online monitoring of fluorescence for rapid bioprocess development, using prodigiosin as a molecule of current biotechnological interest.     

Synchronous fluorescence spectroscopy as a novel tool to enable PAT applications in bioprocesses

In this work, synchronous fluorescence spectroscopy (SFS) is evaluated as a new tool for real-time bioprocess monitoring of animal cell cultures. This technique presents several advantages over the traditional two-dimensional (2D) fluorometry since it provides data on various fluorescent compounds in a single spectrum, showing improved peak resolution and recording speed. Bioreactor cultures of three monoclonal antibody-producing CHO cell lines were followed in situ by both 2D and synchronous fluorometry techniques. The time profiles of the main spectral features in each data type present some differences, but principal component analysis indicated both as containing enough information to distinguish the cultures. Partial least squares regression models were then independently developed for viable cell density and antibody levels on the basis of the different fluorescence signals recorded, hiding half of the dataset for subsequent validation purposes. Regardless of the signal used, model predictions fit very well the off-line measurements; still, the synchronous spectra collected at a wavelength difference of 20 nm allowed comparable and superior performances for cell density and antibody titer, respectively, with validation accuracies higher than 91%. Therefore, SFS compares favorably with the traditional 2D approach, becoming an improved, faster option for real-time monitoring of cells and product titer over culture time. The readiness in data acquisition facilitates the design of process control strategies meeting the requirements of a PAT application.     

Fluorescence-based real time monitoring and diagnostics of recombinant Pichia pastoris cultivations in a bioreactor

This study describes the application of the multivariate curve resolution (MCR) analysis technique for real-time analysis of culture fluorescence during recombinant Pichia pastoris cultivation in a bioreactor. Fluorescence spectra were acquired with an on-line dual excitation wavelength fluorometer and then used to develop a real time MCR-based bioprocess monitoring and diagnostics tool. Initial bioreactor experiments using two similar recombinant antibody secreting P. pastoris cell lines showed significant differences in protein production. To distinguish between the contributions of operating conditions and the specific cell line's genetic composition to the observed differences in protein production, the bioreactor experiments were repeated and accompanied by real time MCR analysis. The tests demonstrated high sensitivity of MCR-derived “pure concentration” profiles to growth as well as to initial conditions, thus enabling real-time cultivation process trend diagnostics and fault detection. © 2018 Her Majesty the Queen in Right of Canada © 2018 American Institute of Chemical Engineers Biotechnol. Prog., 35: e2761, 2019.     

Chemometric modeling and two-dimensional fluorescence analysis of bioprocess with a new strain of <Emphasis Type="Italic">Klebsiella pneumoniae</Emphasis> to convert residual glycerol into 1,3-propanediol

The goal of this study was to show that the metabolism of Klebsiella pneumoniae under different aeration strategies could be monitored and predicted by the application of chemometric models and fluorescence spectroscopy. Multi-wavelength fluorescence was applied to the on-line monitoring of process parameters for K. pneumoniae cultivations. Differences observed in spectra collected under aerobiosis and anaerobiosis can be explained by the different metabolic states of the cells. To predict process variables such as biomass, glycerol, and 1,3-propanediol (1,3-PD), chemometric models were developed on the basis of the acquired fluorescence spectra, which were measured continuously. Although glycerol and 1,3-PD are not fluorescent compounds, the results showed that this technique could be successfully applied to the on-line monitoring of variables in order to understand the process and thus improve 1,3-PD production. The root mean square errors of predictions were 0.78 units, 10 g/L, and 2.6 g/L for optical density, glycerol, and 1,3-PD, respectively.     

Electronic nose for estimation of product concentration in mammalian cell cultivation

The off-gas composition from perfusion cultivation of a CHO-cell line producing recombinant human blood coagulation Factor VIII is monitored with an electronic nose. It is shown that the electronic nose in combination with an artificial neural network can be used for on-line estimation of the Factor VIII concentration in production-scale cultivations. The obtained prediction error (1†) for the Factor VIII concentration was 1.1 IU/ml. The potential of the electronic nose for estimation of viable cell count is outlined in laboratory-scale Factor VIII cultivations. The obtained prediction error (1†) for the viable cell count was 0.4᎒⁶ cells/ml. The results show that this non-invasive method is potentially useful for on-line bioprocess monitoring.     

Comparison of viable cell concentration estimation methods for a mammalian cell cultivation process

Various mechanistic and black-box models were applied for on-line estimations of viable cell concentrations in fed-batch cultivation processes for CHO cells. Data from six fed-batch cultivation experiments were used to identify the underlying models and further six independent data sets were used to determine the performance of the estimators. The performances were quantified by means of the root mean square error (RMSE) between the estimates and the corresponding off-line measured validation data sets. It is shown that even simple techniques based on empirical and linear model approaches provide a fairly good on-line estimation performance. Best results with respect to the validation data sets were obtained with hybrid models, multivariate linear regression technique and support vector regression. Hybrid models provide additional important information about the specific cellular growth rates during the cultivation.