At-line monitoring of a submerged filamentous bacterial cultivation using near-infrared spectroscopy

The use of near infra-red spectroscopy (NIRS) to monitor a submerged filamentous bacterial bioprocess was investigated. An industrial strain of the filamentous bacterium Streptomyces fradiae was cultured in a 12 litre stirred tank reactor (STR) using a complex medium. This mycelial 4 phase (oil, water, gas and solid) system produced highly complex and variable matrices, therefore monitoring such a complex fluid with NIRS represented a considerable challenge. Nevertheless, successful models for four key analytes (methyl oleate, glucose, glutamate and ammonium) were built at-line (rapid off-line) using NIRS. In the present study, the methods used to formulate, select and validate the models for the key analytes are discussed, with particular emphasis on how the model performance can be critically evaluated. Since previous reports on NIRS in monitoring bioprocesses have either involved simpler matrices, or, in filamentous systems, have not discussed how NIRS models can be critically assessed, the emphasis in the present study on providing an insight into the modelling process in such a complex matrix, may be particularly important to the applicability of NIRS to such industrial bioprocesses.     

Assessment of in-line near-infrared spectroscopy for continuous monitoring of fermentation processes

The application of NIR in-line to monitor and control fermentation processes was investigated. Determination of biomass, glucose, and lactic and acetic acids during fermentations of Staphylococcus xylosus ES13 was performed by an interactance fiber optic probe immersed into the culture broth and connected to a NIR instrument. Partial least squares regression (PLSR) calibration models of second derivative NIR spectra in the 700-1800 nm region gave satisfactory predictive models for all parameters of interest: biomass, glucose, and lactic and acetic acids. Batch, repeated batch, and continuous fermentations were monitored and automatically controlled by interfacing the NIR to the bioreactor control unit. The high frequency of data collection permitted an accurate study of the kinetics, supplying lots of data that describe the cultural broth composition and strengthen statistical analysis. Comparison of spectra collected throughout fermentation runs of S. xylosus ES13, Lactobacillus fermentum ES15, and Streptococcus thermophylus ES17 demonstrated the successful extension of a unique calibration model, developed for S. xylosus ES13, to other strains that were differently shaped but growing in the same medium and fermentation conditions. NIR in-line was so versatile as to measure several biochemical parameters of different bacteria by means of slightly adapted models, avoiding a separate calibration for each strain.     

At-line monitoring of key parameters of nisin fermentation by near infrared spectroscopy,chemometric modeling and model improvement

An analytical procedure has been developed for at-line (fast off-line) monitoring of 4 key parameters including nisin titer (NT), the concentration of reducing sugars, cell concentration and pH during a nisin fermentation process. This procedure is based on near infrared (NIR) spectroscopy and Partial Least Squares (PLS). Samples without any preprocessing were collected at intervals of 1 h during fifteen batch of fermentations. These fermentation processes were implemented in 3 different 5 l fermentors at various conditions. NIR spectra of the samples were collected in 10 min. And then, PLS was used for modeling the relationship between NIR spectra and the key parameters which were determined by reference methods. Monte Carlo Partial Least Squares (MCPLS) was applied to identify the outliers and select the most efficacious methods for preprocessing spectra, wavelengths and the suitable number of latent variables (n _LV). Then, the optimum models for determining NT, concentration of reducing sugars, cell concentration and pH were established. The correlation coefficients of calibration set (R _c) were 0.8255, 0.9000, 0.9883 and 0.9581, respectively. These results demonstrated that this method can be successfully applied to at-line monitor of NT, concentration of reducing sugars, cell concentration and pH during nisin fermentation processes.     

基于近红外光谱实时监测乙醇发酵过程多组分参数

生物量、葡萄糖浓度和乙醇浓度是乙醇发酵过程的重要参数,传统的方法通常对发酵液取样作离线测量,不仅需要采用多种仪器进行测试分析,而且耗时耗力,成为实时过程调控和优化的障碍。文中针对这些重要过程参数提出了一个基于近红外光谱技术的原位实时检测方法。通过采用浸入式近红外光谱仪对发酵溶液进行原位测量,基于多输出最小二乘支持向量机回归(MLS-SVR)方法建立了利用近红外光谱同时分析葡萄糖浓度、生物量和乙醇浓度的多输出预测模型。实验结果表明,该方法能实时准确地检测乙醇发酵过程中的葡萄糖浓度、生物量和乙醇浓度,而且相对于现有的偏最小二乘法(PLS)分别对各组分建模和预测,能明显提高测量准确性和可靠性。     

Applicability of near-infrared spectroscopy for process monitoring in bioethanol production

The applicability of near-infrared (NIR) spectroscopy to bioethanol production is investigated. The NIR technique can provide assistance for rapid process monitoring, because organic compounds absorb radiation in the wavelength range 1100–2300 nm. For quantification of a sample's chemical composition, a calibration model is required that relates the measured spectral NIR absorbances to concentrations. For calibration, the concentrations in g/l are determined by the analytical reference method high performance liquid chromatography (HPLC). The calibration models are built and validated for moisture, protein, and starch in the feedstock material, and for glucose, ethanol, glycerol, lactic acid, acetic acid, maltose, fructose, and arabinose in the processed broths. These broths are prepared in laboratory experiments: The ground cereal samples are fermented to alcoholic broths (‘mash’), which are divided into an ethanol fraction and the residual fraction ‘stillage’ by distillation. The NIR technology together with chemometrics proved itself beneficial for fast monitoring of the current state of the bioethanol process, primarily for higher concentrated substances (>1 g/l).     

At-line raman spectroscopy and design of experiments for robust monitoring and control of miniature bioreactor cultures

The biopharmaceutical industry is moving toward a more quality by design (QbD) approach that seeks to increase product and process understanding and process control. Miniature bioreactor systems offer a high-throughput method enabling the assessment of numerous process variables in a controlled environment. However, the number of off/at-line samples that can be taken is restricted due to the small working volume of each vessel. This limitation may be resolved through the use of Raman spectroscopy due to its ability to obtain multianalyte data from small sample volumes fast. It can, however, be challenging to implement this technique for this application due to the complexity of the sample matrix and that analytes are often present in low concentration. Here, we present a design of experiments (DOE) approach to generate samples for calibrating robust multivariate predictive models measuring glucose, lactate, ammonium, viable cell concentration (VCC) and product concentration, for unclarified cell culture that improves the daily monitoring of each miniature bioreactor vessel. Furthermore, we demonstrate how the output of the glucose and VCC models can be used to control the glucose and main nutrient feed rate within miniature bioreactor cultures to within qualified critical limits set for larger scale vessels. The DOE approach used to generate the calibration sample set is shown to result in models more robust to process changes than by simply using samples taken from the “typical” process. © 2018 American Institute of Chemical Engineers Biotechnol. Prog., 35: e2740, 2019.     

Monitoring biomass and glycerol in an Escherichia coli fermentation using near-infrared spectroscopy

Summary Near-infrared spectroscopy was used to determine biomass and glycerol concentrations in E.coli whole broth fermentation samples. For dry cell weight, a standard error of prediction (SEP) of 0.2 g/L and correlation coefficient (r) of 0.991 were obtained. The SEP and r for glycerol, carbon nutrient, were 0.3 g/L and 0.979. respectively. Off-line analysis was accomplished within 2 minutes of sampling and therefore provides the opportunity to monitor fermentations quickly enough to permit in-process development and troubleshooting.     

Analytical monitoring of alcoholic fermentation using NIR spectroscopy

Alcoholic fermentation under Saccharomyces cerevisiae yeasts is governed largely by glucose uptake, biomass formation, ethanol and glycerin production, and acidification. In this work, PLS calibration models were developed with a view to determining these analytical parameters from near infrared spectra and analytical data provided by the corresponding reference methods. The models were applied to a set of samples obtained from various fermentation processes. The glucose, ethanol, and biomass values predicted by the models exhibited a high correlation with those provided by the reference method.     

Applying near-infrared spectroscopy in downstream processing: one calibration for multiple clarification processes of fermentation media

The use of near-infrared spectroscopy (NIRS) is demonstrated in the first downstream processing (DSP) steps of an active pharmaceutical ingredient (API) manufacturing process. The first method developed was designed to assess the API content in the filtrate stream (aqueous) of a rotary drum vacuum filter. The PLS method, built after spectral preprocessing and variable selection, had an accuracy of 0.01% (w/w) for an API operational range between 0.20 and 0.45% (w/w). The robustness and extrapolation ability of the calibration was proved when samples from ultrafiltration and nanofiltration processes, ranging from 0 to 2% (w/w), were linearly predicted (R2=0.99). The development of a robust calibration model is generally a very time-consuming task, and once established it is imperative that it can be useful for a long period of time. This work demonstrates that NIR procedures, when carefully developed, can be used in different process conditions and even in different process steps of similar unit operations.     

At-line monitoring of bioreactor protein production by Surface Plasmon Resonance

An innovative and automated method for the at-line monitoring of secreted protein was developed by harnessing a Surface Plasmon Resonance-based biosensor to a bioreactor. The proof of concept was performed by following at-line the relative concentration of a secreted protein produced by transient transfection of mammalian cells in a bioreactor. Our results suggest that our approach can be readily applied to the at-line determination of both protein concentration and bioactivity. Our experimental setup and strategy can thus satisfy the needs related to the development of novel bioprocess control protocols in the context of the new process analytical technology that arises in the biopharmaceutical industry.     

Instability of glutamate production by Corynebacterium glutamicum 2262 in continuous culture using the temperature-triggered process

Kinetics and physiology of Corynebacterium glutamicum 2262 cultured for extended periods in continuous mode were investigated at 33, 39 and 41 degrees C. At 33 degrees C no glutamate production occurred whatever the dilution rates tested (ranging between 0.05 and 0.5 h(-1)). When the continuous culture was performed at 39 degrees C and D=0.05 h(-1), the glutamate was actively produced, while the activities of 2-oxoglutarate dehydrogenase complex (ODHC) and pyruvate dehydrogenase (PDH) were, respectively completely inhibited and 35% decreased. Simultaneously, the intracellular glutamate was 62% reduced compared to the level found at 33 degrees C and the co-metabolites lactate and trehalose were excreted. The decrease in PDH activity during the glutamate production was suggested to be responsible for the accumulation of by-products and for limiting the carbon flux required for glutamate synthesis. When the culture was prolonged for more than 100 h, a cell selection occurred, in favor of growth and to the detriment of glutamate production. In fact, these selected cells presented high levels of ODHC and PDH activities even at 39 degrees C, resulting in a complete inhibition of the glutamate production after 150 h of culture. A further temperature increase till 41 degrees C restored the glutamate production and abolished the ODHC activity of these selected cells.     

基于傅里叶变换近红外光谱实时分析1,3-丙二醇发酵过程生物量的在线监测方法

生物量是反映生物发酵过程进展的重要参数,对生物量进行实时监测可用于对发酵过程的调控优化。为克服目前主要采用的离线方法检测生物量时间滞后和人工测量误差较大等缺点,本研究针对1,3-丙二醇发酵过程设计了一个基于傅里叶变换近红外光谱实时分析技术的生物量在线监测实验平台,通过对实时采集光谱预处理以及敏感光谱段分析,应用偏最小二乘算法,建立了1,3-丙二醇发酵过程生物量变化的动态预测模型。以底物甘油浓度为60 g/L和40 g/L的发酵过程作为外部验证实验,分析得到模型的预测均方根误差分别为0.341 6和0.274 3,结果表明所建立的模型具有较好的实时预测能力,能够实现对1,3-丙二醇发酵过程中生物量的有效在线监测。     

Critical evaluation of models developed for monitoring an industrial submerged bioprocess for antibiotic production using near-infrared spectroscopy

Near-infrared spectroscopy (NIRS) is known to have potential for cost-effective monitoring of bioprocesses. Although this has been demonstrated in many instances and several models have been reported, information regarding the complexity of models required and their utility over extended periods of time is lacking. In the present study, the complexity of the models required for the NIRS prediction of substrate (oil) and product (tylosin) concentration in an industrial bioprocess that employs a physicochemically heterogeneous medium for antibiotic production was assessed. Measurements made by both the diffuse reflectance and transmittance modes were investigated. SEP values for the prediction of the analytes averaged 5% or less, for the successful models, when evaluated using an external validation set, 2 years after the initial model development exercise. Diffuse reflectance measurements showed poorer results, compared to transmittance measurements, especially for monitoring tylosin. In general, this investigation provides evidence to support the fact that models built for the prediction of analytes in a commercial bioprocess that employs a physicochemically complex production medium can be robust in performance over an extended period of time and that simple models based on fewer terms or latent variables can perform well, even in the context of matrices that are relatively complex. It also indicates that sample presentation is likely to be a critical factor in the successful application of NIRS in bioprocess monitoring, which merits further detailed investigation.     

Dynamics of glutamate synthesis and excretion fluxes in batch and continuous cultures of temperature-triggered Corynebacterium glutamicum

Corynebacterium glutamicum 2262 strain, when triggered for glutamate excretion, experiences a rapid decrease in growth rate and increase in glutamate efflux. In order to gain a better quantitative understanding of the factors controlling the metabolic transition, the fermentation dynamics was investigated for a temperature-sensitive strain cultivated in batch and glucose-limited continuous cultures. For non-excreting cells at 33°C, increasing the growth rate resulted in strong increases in the central metabolic fluxes, but the intracellular glutamate level, the oxoglutarate dehydrogenase complex (ODHC) activity and the flux distribution at the oxoglutarate node remained essentially constant. When subjected to a temperature rise to 39°C, at both high- and low-metabolic activities, the bacteria showed a rapid attenuation in ODHC activity and an increase from 28% to more than 90% of the isocitrate dehydrogenase flux split towards glutamate synthesis. Simultaneously to the reduction in growth rate, the cells activated a high capacity export system capable of expelling the surplus of synthesized glutamate.     

Functional near-infrared spectroscopy studies in children

Psychosomatic and developmental behavioral medicine in pediatrics has been the subject of significant recent attention, with infants, school-age children, and adolescents frequently presenting with psychosomatic, behavioral, and psychiatric symptoms. These may be a consequence of insecurity of attachment, reduced self-confidence, and peer -relationship conflicts during their developmental stages. Developmental cognitive neuroscience has revealed significant associations between specific brain lesions and particular cognitive dysfunctions. Thus, identifying the biological deficits underlying such cognitive dysfunction may provide new insights into therapeutic prospects for the management of those symptoms in children. Recent advances in noninvasive neuroimaging techniques, and especially functional near-infrared spectroscopy (NIRS), have contributed significant findings to the field of developmental cognitive neuroscience in pediatrics. We present here a comprehensive review of functional NIRS studies of children who have developed normally and of children with psychosomatic and behavioral disorders.     

Investigation of the effect of clinically relevant interferents on glucose monitoring using near-infrared spectroscopy

Near infrared spectroscopy (NIR) is a promising technique for continuous blood glucose monitoring for diabetic patients. Four interferents, at physiological concentrations, were introduced to study how the glucose predictions varied with a standard multivariate calibration model. Lactate and ethanol were found to interfere strongly with the glucose predictions unless they were included in the calibration models. Lactate was mistaken for glucose and gave erroneously high glucose predictions, with a dose response of 0.46 mM/mM. The presence of ethanol resulted in too low glucose predictions, with a dose response of −0.43 mM/mM. Acetaminophen, a known interferent in the glucose monitoring devices used for diabetes management today, was not found to be an interferent in NIR spectroscopy, nor was caffeine. Thus, interferents that may appear in high concentrations, such as ethanol and lactate, must be included in the calibration or model building of future NIR-based glucose measurement devices for diabetes monitoring.     

On-line monitoring of human prostate cancer cells in a perfusion rotating wall vessel by near-infrared spectroscopy

PC-3 human prostate cancer cells have been cultivated in a rotating wall vessel in which glucose, lactate, and glutamine profiles were monitored noninvasively and in real time by near-infrared (NIR) spectroscopy. The calibration models were based on off-line spectra from tissue culture experiments described previously (Rhiel et al., Biotechnol Bioeng 77:73-82). Monitoring performance was improved by Fourier filtering of the spectra and initial off-set adjustment. The resulting standard errors of predictions were 0.95, 0.74, and 0.39 mM for glucose, lactate, and glutamine, respectively. The concentration of ammonia could not be accurately measured from the same spectra. In addition, metabolite uptake and production rates were determined for PC-3 prostate cancer cells during exponential growth in batch-mode cultivation. Cells grew with a doubling time of 21 h and consumed glucose and glutamine at rates of 6.8 and 1.8 x 10(-17) mol/cell.s, respectively. This resulted in lactate and ammonia production rates of 11.9 and 1.3 x 10(-17) mol/cell.s, respectively. Compared with other monitoring technologies, this technology has many advantages for spaceflights and stand-alone units; for instance, calibration can be performed at one time and then applied in a reagentless, low-maintenance way at a later time. The resulting concentration information can be incorporated into closed-loop control schemes, thereby leading to better in vitro models of in vivo behavior.     

Membrane gas sensors for fermentation monitoring

Results from studies of membrane gas sensors are presented to show their general applicability to fermentation monitoring of volatiles, such as alcohols, organic acids, and aldehydes under various process and reactor conditions. Mainly the silicone tubing methods is described, with examples from ethanolic fermentation. The influences of temperature, pH, membrane, and other factors as well as performance in fermentation liquids are investigated.