Attenuated total reflectance Fourier transform mid-infrared spectroscopic quantification of sorbitol and sorbose during a Gluconobacter biotransformation process

Mid-infrared spectroscopy (MIRS) was used to simultaneously detect and predict concentrations of d-sorbitol and l-sorbose during a Gluconobacter suboxydans biotransformation. Quantitative models for both these compounds were developed for the entire time-course of the process and validated externally using samples not included in the original modelling exercise, giving standard errors of prediction of 3.29 and 3.3% for sorbitol and sorbose, respectively, and a correlation coefficient close to 1.     

Data reconciliation of concentration estimates from mid‐infrared and dielectric spectral measurements for improved on‐line monitoring of bioprocesses

Real‐time data reconciliation of concentration estimates of process analytes and biomass in microbial fermentations is investigated. A Fourier‐transform mid‐infrared spectrometer predicting the concentrations of process metabolites is used in parallel with a dielectric spectrometer predicting the biomass concentration during a batch fermentation of the yeast Saccharomyces cerevisiae. Calibration models developed off‐line for both spectrometers suffer from poor predictive capability due to instrumental and process drifts unseen during calibration. To address this problem, the predicted metabolite and biomass concentrations, along with off‐gas analysis and base addition measurements, are reconciled in real‐time based on the closure of mass and elemental balances. A statistical test is used to confirm the integrity of the balances, and a non‐negativity constraint is used to guide the data reconciliation algorithm toward positive concentrations. It is verified experimentally that the proposed approach reduces the standard error of prediction without the need for additional off‐line analysis. © 2009 American Institute of Chemical Engineers Biotechnol. Prog., 2009     

Mid‐infrared spectroscopy‐based analysis of mammalian cell culture Parameters

Within the framework of process analytical technology, infrared spectroscopy (IR) has been used for characterization of biopharmaceutical production processes. Although noninvasive attenuated total reflection (ATR) spectroscopy can be regarded as gold standard within IR‐based process analytics, simpler and more cost‐effective mid‐infrared (MIR) instruments might improve acceptability of this technique for high‐level monitoring of small scale experiments as well as for academia where financial restraints impede the use of costly equipment. A simple and straightforward at‐line mid‐IR instrument was used to monitor cell viability parameters, activity of lactate dehydrogenase (LDH), amount of secreted antibody, and concentration of glutamate and lactate in a Chinese hamster ovary cell culture process, applying multivariate prediction models, including only 25–28 calibration samples per model. Glutamate amount could be predicted with high accuracy (R² 0.91 for independent test‐set) while antibody concentration achieved good prediction for concentrations >0.4 mg L^?1. Prediction of LDH activity was accurate except for the low activity regime. The model for lactate monitoring was only moderately good and requires improvements. Relative cell viability between 20 and 95% could be predicted with low error (8.82%) in comparison to reference methods. An initial model for determining the number of nonviable cells displayed only acceptable accuracy and requires further improvement. In contrast, monitoring of viable cell number showed better accuracy than previously published ATR‐based results. These results prove the principal suitability of less sophisticated MIR instruments to monitor multiple parameters in biopharmaceutical production with relatively low investments and rather fast calibration procedures. © 2015 American Institute of Chemical Engineers Biotechnol. Prog., 31:578–584, 2015     

In situ near infrared spectroscopy for analyte‐specific monitoring of glucose and ammonium in streptomyces coelicolor fermentations

There are many challenges associated with in situ collection of near infrared (NIR) spectra in a fermentation broth, particularly for highly aerated and agitated fermentations with filamentous organisms. In this study, antibiotic fermentation by the filamentous bacterium Streptomyces coelicolor was used as a model process. Partial least squares (PLS) regression models were calibrated for glucose and ammonium based on NIR spectra collected in situ. To ensure that the models were calibrated based on analyte‐specific information, semisynthetic samples were used for model calibration in addition to data from standard batches. Thereby, part of the inherent correlation between the analytes could be eliminated. The set of semisynthetic samples were generated from fermentation broth from five separate fermentations to which different amounts of glucose, ammonium, and biomass were added. This method has previously been used off line but never before in situ. The use of semisynthetic samples along with validation on an independent batch provided a critical and realistic evaluation of analyte‐specific models based on in situ NIR spectroscopy. The prediction of glucose was highly satisfactory resulting in a RMSEP of 1.1 g/L. The prediction of ammonium based on NIR spectra collected in situ was not satisfactory. A comparison with models calibrated based on NIR spectra collected off line suggested that this is caused by signal attenuation in the optical fibers in the region above 2,000 nm; a region which contains important absorption bands for ammonium. For improved predictions of ammonium in situ, it is suggested to focus efforts on enhancing the signal in that particular region. © 2009 American Institute of Chemical Engineers Biotechnol. Prog., 2010     

傅立叶变换红外光谱技术对两株大肠杆菌的鉴别

【目的】应用傅立叶变换红外光谱(Fourier transform infrared spectroscopy,FT-IR)技术对两株不同来源的大肠杆菌进行鉴别。【方法】用FT-IR技术对两株不同来源的大肠杆菌进行指纹图谱数据采集,用化学计量学分析方法对光谱进行分析。【结果】建立了基于主成分分析(Principal component analysis,PCA)和分级聚类分析(Hierarchical cluster analysis,HCA)两种聚类分析模型,均可将两株大肠杆菌进行成功区分。【结论】傅立叶变换红外光谱分析方法简便、快速、易操作,结果重现性好,可用于区分不同来源的同种细菌。     

Real-time compensation of the inner filter effect in high-density bioluminescent cultures

Bioluminescence has recently become a popular research tool in several fields, including medicine, pharmacology, biochemistry, bioprocessing, and environmental engineering. Beginning with purely qualitative goals, scientists are now targeting more demanding applications where accurate, quantitative interpretation of bioluminescence is necessary. Using the recent advances in fiber-optic technology, bioluminescence is easily monitored in vivo and in real time. However, the convenience of this measurement is often concealing an unsuspected problem: the bioluminescence signal might be corrupted by a large error caused by the extinction of light by biological cells. Since bioluminescent cultures not only emit light but also absorb and scatter it, the measured signal is related in a complex, nonlinear, and cell-concentration-dependent manner to the "true" bioluminescence. This light extinction effect, known as the "inner filter effect," is significant in high-density cultures. Adequate interpretation of the bioluminescence signal can be difficult without its correction. Here, we propose a real-time algorithm for elimination of the inner filter effect in a bioreactor. The algorithm yields the bioluminescence which would be measured if the glowing culture was completely transparent. This technique has been successfully applied to batch and continuous cultivation of recombinant bioluminescent Escherichia coli. (c) 1993 John Wiley & Sons, Inc.