Browsing by Person "Berg, Christoph"

Now showing 1 - 4 of 4

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.
Assessing the capabilities of 2D fluorescence monitoring in microtiter plates with data-driven modeling for secondary substrate limitation experiments of Hansenula polymorpha
(2023) Berg, Christoph; Herbst, Laura; Gremm, Lisa; Ihling, Nina; Paquet-Durand, Olivier; Hitzmann, Bernd; Büchs, Jochen; Berg, Christoph; AVT - Aachener Verfahrenstechnik, Biochemical Engineering, RWTH Aachen University, Aachen, Germany; Herbst, Laura; AVT - Aachener Verfahrenstechnik, Biochemical Engineering, RWTH Aachen University, Aachen, Germany; Gremm, Lisa; AVT - Aachener Verfahrenstechnik, Biochemical Engineering, RWTH Aachen University, Aachen, Germany; Ihling, Nina; AVT - Aachener Verfahrenstechnik, Biochemical Engineering, RWTH Aachen University, Aachen, Germany; Paquet-Durand, Olivier; Department of Process Analytics & Cereal Science, Institute for Food Science and Biotechnology, University of Hohenheim, Stuttgart, Germany; Hitzmann, Bernd; Department of Process Analytics & Cereal Science, Institute for Food Science and Biotechnology, University of Hohenheim, Stuttgart, Germany; Büchs, Jochen; AVT - Aachener Verfahrenstechnik, Biochemical Engineering, RWTH Aachen University, Aachen, Germany
Background: Non-invasive online fluorescence monitoring in high-throughput microbioreactors is a well-established method to accelerate early-stage bioprocess development. Recently, single-wavelength fluorescence monitoring in microtiter plates was extended to measurements of highly resolved 2D fluorescence spectra, by introducing charge-coupled device (CCD) detectors. Although introductory experiments demonstrated a high potential of the new monitoring technology, an assessment of the capabilities and limits for practical applications is yet to be provided. Results: In this study, three experimental sets introducing secondary substrate limitations of magnesium, potassium, and phosphate to cultivations of a GFP-expressing H. polymorpha strain were conducted. This increased the complexity of the spectral dynamics, which were determined by 2D fluorescence measurements. The metabolic responses upon growth limiting conditions were assessed by monitoring of the oxygen transfer rate and extensive offline sampling. Using only the spectral data, subsequently, partial least-square (PLS) regression models for the key parameters of glycerol, cell dry weight, and pH value were generated. For model calibration, spectral data of only two cultivation conditions were combined with sparse offline sampling data. Applying the models to spectral data of six cultures not used for calibration, resulted in an average relative root-mean-square error (RMSE) of prediction between 6.8 and 6.0%. Thus, while demanding only sparse offline data, the models allowed the estimation of biomass accumulation and glycerol consumption, even in the presence of more or less pronounced secondary substrate limitation. Conclusion: For the secondary substrate limitation experiments of this study, the generation of data-driven models allowed a considerable reduction in sampling efforts while also providing process information for unsampled cultures. Therefore, the practical experiments of this study strongly affirm the previously claimed advantages of 2D fluorescence spectroscopy in microtiter plates.
Online 2D fluorescence monitoring in microtiter plates allows prediction of cultivation parameters and considerable reduction in sampling efforts for parallel cultivations of Hansenula polymorpha
(2022) Berg, Christoph; Ihling, Nina; Finger, Maurice; Paquet-Durand, Olivier; Hitzmann, Bernd; Büchs, Jochen
Multi-wavelength (2D) fluorescence spectroscopy represents an important step towards exploiting the monitoring potential of microtiter plates (MTPs) during early-stage bioprocess development. In combination with multivariate data analysis (MVDA), important process information can be obtained, while repetitive, cost-intensive sample analytics can be reduced. This study provides a comprehensive experimental dataset of online and offline measurements for batch cultures of Hansenula polymorpha. In the first step, principal component analysis (PCA) was used to assess spectral data quality. Secondly, partial least-squares (PLS) regression models were generated, based on spectral data of two cultivation conditions and offline samples for glycerol, cell dry weight, and pH value. Thereby, the time-wise resolution increased 12-fold compared to the offline sampling interval of 6 h. The PLS models were validated using offline samples of a shorter sampling interval. Very good model transferability was shown during the PLS model application to the spectral data of cultures with six varying initial cultivation conditions. For all the predicted variables, a relative root-mean-square error (RMSE) below 6% was obtained. Based on the findings, the initial experimental strategy was re-evaluated and a more practical approach with minimised sampling effort and elevated experimental throughput was proposed. In conclusion, the study underlines the high potential of multi-wavelength (2D) fluorescence spectroscopy and provides an evaluation workflow for PLS modelling in microtiter plates.
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.