Browsing by Subject "2D fluorescence spectroscopy"

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Advancing 2D fluorescence online monitoring in microtiter plates by separating scattered light and fluorescence measurement, using a tunable emission monochromator
(2023) Berg, Christoph; Busch, Selma; Alawiyah, Muthia Dewi; Finger, Maurice; Ihling, Nina; Paquet-Durand, Olivier; Hitzmann, Bernd; Büchs, Jochen
Online fluorescence monitoring has become a key technology in modern bioprocess development, as it provides in‐depth process knowledge at comparably low costs. In particular, the technology is widely established for high‐throughput microbioreactor cultivation systems, due to its noninvasive character. For microtiter plates, previously also multi‐wavelength 2D fluorescence monitoring was developed. To overcome an observed limitation of fluorescence sensitivity, this study presents a modified spectroscopic setup, including a tunable emission monochromator. The new optical component enables the separation of the scattered and fluorescent light measurements, which allows for the adjustment of integration times of the charge‐coupled device detector. The resulting increased fluorescence sensitivity positively affected the performance of principal component analysis for spectral data of Escherichia coli batch cultivation experiments with varying sorbitol concentration supplementation. In direct comparison with spectral data recorded at short integration times, more biologically consistent signal dynamics were calculated. Furthermore, during partial least square regression for E. coli cultivation experiments with varying glucose concentrations, improved modeling performance was observed. Especially, for the growth‐uncoupled acetate concentration, a considerable improvement of the root‐mean‐square error from 0.25 to 0.17 g/L was achieved. In conclusion, the modified setup represents another important step in advancing 2D fluorescence monitoring in microtiter plates.
Application of two-dimensional fluorescence spectroscopy for the on-line monitoring of teff-based substrate fermentation inoculated with certain probiotic bacteria
(2022) Alemneh, Sendeku Takele; Emire, Shimelis Admassu; Jekle, Mario; Paquet-Durand, Olivier; von Wrochem, Almut; Hitzmann, Bernd
There is increasing demand for cereal-based probiotic fermented beverages as an alternative to dairy-based products due to their limitations. However, analyzing and monitoring the fermentation process is usually time consuming, costly, and labor intensive. This research therefore aims to apply two-dimensional (2D)-fluorescence spectroscopy coupled with partial least-squares regression (PLSR) and artificial neural networks (ANN) for the on-line quantitative analysis of cell growth and concentrations of lactic acid and glucose during the fermentation of a teff-based substrate. This substrate was inoculated with mixed strains of Lactiplantibacillus plantarum A6 (LPA6) and Lacticaseibacillus rhamnosus GG (LCGG). The fermentation was performed under two different conditions: condition 1 (7 g/100 mL substrate inoculated with 6 log cfu/mL) and condition 2 (4 g/100 mL substrate inoculated with 6 log cfu/mL). For the prediction of LPA6 and LCGG cell growth, the relative root mean square error of prediction (pRMSEP) was measured between 2.5 and 4.5%. The highest pRMSEP (4.5%) was observed for the prediction of LPA6 cell growth under condition 2 using ANN, but the lowest pRMSEP (2.5%) was observed for the prediction of LCGG cell growth under condition 1 with ANN. A slightly more accurate prediction was found with ANN under condition 1. However, under condition 2, a superior prediction was observed with PLSR as compared to ANN. Moreover, for the prediction of lactic acid concentration, the observed values of pRMSEP were 7.6 and 7.7% using PLSR and ANN, respectively. The highest error rates of 13 and 14% were observed for the prediction of glucose concentration using PLSR and ANN, respectively. Most of the predicted values had a coefficient of determination (R2) of more than 0.85. In conclusion, a 2D-fluorescence spectroscopy combined with PLSR and ANN can be used to accurately monitor LPA6 and LCGG cell counts and lactic acid concentration in the fermentation process of a teff-based substrate. The prediction of glucose concentration, however, showed a rather high error rate.
Development of an on-line process monitoring for yeast cultivations via 2D-fluorescence spectroscopy
(2019) Assawajaruwan, Supasuda; Hitzmann, Bernd
An optimum process is required in the field of food, pharmaceutical and biotechnological industry with the ultimate goal of achieving high productivity and high-quality products. In order to achieve this goal, there are many different parameters to be realized and controlled, e.g., physical, chemical and biological aspects of microbial bioprocesses. Microbial cultivations are a very complex process, therefore, reliable and efficient tools are required to receive as much real-time information for an on-line monitoring as possible, so that the processes can be controlled in time. The primary objective of this research was to apply a two-dimensional (2D) fluorescence spectroscopy to monitor glucose, ethanol and biomass concentrations of yeast cultivations. The measurement of one spectrum has 120 fluorescence intensity variables of excitation and emission wavelength combinations (WLCs) without consideration of the scattered light. To investigate which WLCs carry important and relevant information regarding the analyte concentrations, the three wavelength selection methods were implemented: a method based on loadings, variable importance in projection (VIP) and ant colony optimization. The five selected WLCs from each method for a particular analyte were evaluated by multiple linear regression (MLR) models. The selected WLCs, which showed the best predictive performance of the MLR models, were relevant to the analyte concentrations. Regarding the results of the MLR models, the most significant WLCs contained seven different excitation and emission wavelengths. They can be combined to have 38 WLCs for one spectrum based on the principle of fluorescence. They were in the area of NADH, tryptophan, pyridoxine, riboflavin and FAD/FMN. The 38 WLCs were used to predict the glucose, ethanol and biomass concentrations via partial least squares (PLS) regression. The best prediction from the PLS models with 38 WLCs had the percentage of root mean square error of prediction (pRMSEP) in the range of 3.1-6.3 %, which was not significantly different from the PLS models with the 120 variables. Therefore, the specific fluorescence sensor for yeast cultivations could be built with less filters, which would make it a low-cost device. The following plan of the research goal was to investigate the attribute of fluorophores inside cells in real time using a 2D fluorescence spectrometer. The considered intracellular fluorophores, such as NADH, tryptophan, pyridoxine, riboflavin and FAD/FMN were observed during the yeast cultivations under three different conditions: batch, fed-batch with the glucose pulse during a glucose growth phase (GP) and fed-batch with the glucose pulse during an ethanol growth phase (EP) after a diauxic shift. With the help of principal component analysis, the different states of the yeast cultivations, particularly the glucose pulse during EP, can be recognized and identified from the on-line fluorescence spectra. On the other hand, the change of the fluorescence spectra in the fed-batch process with the glucose pulse during GP was not recognizable. Remarkably, the intensities of the fluorophores due to the glucose pulse during EP did not change in the same direction. The fluorescence intensities of NADH and riboflavin increased, but the intensity of tryptophan, pyridoxine and FAD/FMN decreased. The conversion between tryptophan and NADH intensities was quantified as a proportional factor. It was calculated from the ratio of the area of NADH and tryptophan fluorescence intensity after the glucose addition until depletion. The proportional factor was independent on various glucose concentrations with the coefficient of determination, R2 = 0.999. The correlative intensity changes of these fluorophores demonstrate a metabolic switch from ethanol to glucose growth phase. Based on the previous experiments, a closed-loop control has been implemented for yeast cultivations. 2D fluorescence spectroscopy was applied for an on-line monitoring and control of yeast cultivations to attain pure oxidative metabolism. A glucose concentration is an important factor in a fed-batch process of Saccharomyces cerevisiae. Therefore, it has to be controlled under a critical concentration to avoid overflow metabolism and to gain high productivity of biomass. The characteristic of the NADH intensity can effectively identify the metabolic switch between oxidative and oxidoreductive states. Consequently, the feed rates were regulated using the NADH intensity as a metabolic signal. With this closed-loop control of the glucose concentration, a biomass yield was obtained at 0.5 gbiomass/gglucose. Additionally, ethanol production could be avoided during the controlled feeding phase. The fluorescence sensor with the signal of the NADH intensity has potential to control a glucose concentration under the critical value in real time. The experiments carried out show that 2D fluorescence spectroscopy has great potential in on-line monitoring and process control of the yeast cultivations. Consequently, it is promising to build up a compact and economical fluorescence sensor with the specific wavelengths using light-emitting diodes and photodiodes. The sensor would be a cost-effective and miniaturized device for routine analysis, which could be advantageous to real-time bioprocess monitoring.
Online process state estimation for Hansenula polymorpha cultivation with 2D fluorescence spectra-based chemometric model calibrated from a theoretical model in place of offline measurements
(2023) Babor, Majharulislam; Paquet-Durand, Olivier; Berg, Christoph; Büchs, Jochen; Hitzmann, Bernd
The use of 2D fluorescence spectra is a powerful, instantaneous, and highly accurate method to estimate the state of bioprocesses. The conventional approach for calibrating a chemometric model from raw spectra needs a large number of offline measurements from numerous runs, which is tedious, time-consuming, and error-prone. In addition, many process variables lack direct signal responses, which forces chemometric models to make predictions based on indirect responses. In order to predict glycerol and biomass concentrations online in batch cultivation of Hansenula polymorpha, this study substituted offline measurements with simulated values. The only data from cultivations needed to generate the chemometric model were the 2D fluorescence spectra, with the presumption that they contain sufficient information to characterize the process state at a measurement point. The remainder of the evaluation was carried out with the aid of a mathematical process model that describes the theoretical interferences between process variables in the system. It is shown that the process model parameters, including microbial growth rate, the yield of biomass from glycerol, and lag time can be determined from only the spectra by employing a model-based calibration (MBC) approach. The prediction errors for glycerol and biomass concentrations were 8.6% and 5.7%, respectively. An improved model-based calibration (IMBC) approach is presented that calibrates a chemometric model for only biomass. Biomass was predicted from a 2D fluorescence spectrum in new cultivations, and glycerol concentration was estimated from the process model utilizing predicted biomass as an input. By using this method, the prediction errors for glycerol and biomass were reduced to 5.2% and 4.7%, respectively. The findings indicate that model-based calibration, which can be carried out with only 2D fluorescence spectra gathered from prior runs, is an effective method for estimating the process state online.