Comparison of spectroscopy technologies for improved monitoring of cell culture processes in miniature bioreactors

Cell culture process development requires the screening of large numbers of cell lines and process conditions. The development of miniature bioreactor systems has increased the throughput of such studies; however, there are limitations with their use. One important constraint is the limited number of offline samples that can be taken compared to those taken for monitoring cultures in large‐scale bioreactors. The small volume of miniature bioreactor cultures (15 mL) is incompatible with the large sample volume (600 µL) required for bioanalysers routinely used. Spectroscopy technologies may be used to resolve this limitation. The purpose of this study was to compare the use of NIR, Raman, and 2D‐fluorescence to measure multiple analytes simultaneously in volumes suitable for daily monitoring of a miniature bioreactor system. A novel design‐of‐experiment approach is described that utilizes previously analyzed cell culture supernatant to assess metabolite concentrations under various conditions while providing optimal coverage of the desired design space. Multivariate data analysis techniques were used to develop predictive models. Model performance was compared to determine which technology is more suitable for this application. 2D‐fluorescence could more accurately measure ammonium concentration (RMSE_CV 0.031 g L^?1) than Raman and NIR. Raman spectroscopy, however, was more robust at measuring lactate and glucose concentrations (RMSE_CV 1.11 and 0.92 g L^?1, respectively) than the other two techniques. The findings suggest that Raman spectroscopy is more suited for this application than NIR and 2D‐fluorescence. The implementation of Raman spectroscopy increases at‐line measuring capabilities, enabling daily monitoring of key cell culture components within miniature bioreactor cultures. © 2017 American Institute of Chemical Engineers Biotechnol. Prog., 33:337–346, 2017     

Raman spectroscopy and chemometrics for on‐line control of glucose fermentation by Saccharomyces cerevisiae

This work presents the use of Raman spectroscopy and chemometrics for on‐line control of the fermentation process of glucose by Saccharomyces cerevisiae. In a first approach, an on‐line determination of glucose, ethanol, glycerol, and cells was accomplished using multivariate calibration based on partial least squares (PLS). The PLS models presented values of root mean square error of prediction (RMSEP) of 0.53, 0.25, and 0.02% for glucose, ethanol and glycerol, respectively, and RMSEP of 1.02 g L^?1 for cells. In a second approach, multivariate control charts based on multiway principal component analysis (MPCA) were developed for detection of fermentation fault‐batch. Two multivariate control charts were developed, based on the squared prediction error (Q) and Hotelling's T². The use of the Q control chart in on‐line monitoring was efficient for detection of the faults caused by temperature, type of substrate and contamination, but the T² control chart was not able to monitor these faults. On‐line monitoring by Raman spectroscopy in conjunction with chemometric procedures allows control of the fermentative process with advantages in relation to reference methods, which require pretreatment, manipulation of samples and are time consuming. Also, the use of multivariate control charts made possible the detection of faults in a simple way, based only on the spectra of the system. © 2012 American Institute of Chemical Engineers Biotechnol. Prog., 2012     

Rapid monitoring of recombinant antibody production by mammalian cell cultures using fourier transform infrared spectroscopy and chemometrics

Fourier transform infrared (FT‐IR) spectroscopy combined with multivariate statistical analyses was investigated as a physicochemical tool for monitoring secreted recombinant antibody production in cultures of Chinese hamster ovary (CHO) and murine myeloma non‐secreting 0 (NS0) cell lines. Medium samples were taken during culture of CHO and NS0 cells lines, which included both antibody‐producing and non‐producing cell lines, and analyzed by FT‐IR spectroscopy. Principal components analysis (PCA) alone, and combined with discriminant function analysis (PC‐DFA), were applied to normalized FT‐IR spectroscopy datasets and showed a linear trend with respect to recombinant protein production. Loadings plots of the most significant spectral components showed a decrease in the C–O stretch from polysaccharides and an increase in the amide I band during culture, respectively, indicating a decrease in sugar concentration and an increase in protein concentration in the medium. Partial least squares regression (PLSR) analysis was used to predict antibody titers, and these regression models were able to predict antibody titers accurately with low error when compared to ELISA data. PLSR was also able to predict glucose and lactate amounts in the medium samples accurately. This work demonstrates that FT‐IR spectroscopy has great potential as a tool for monitoring cell cultures for recombinant protein production and offers a starting point for the application of spectroscopic techniques for the on‐line measurement of antibody production in industrial scale bioreactors. Biotechnol. Bioeng. 2010; 106: 432–442. © 2010 Wiley Periodicals, Inc.     

In situ Raman spectroscopy for simultaneous monitoring of multiple process parameters in mammalian cell culture bioreactors

In this study, the application of Raman spectroscopy to the simultaneous quantitative determination of glucose, glutamine, lactate, ammonia, glutamate, total cell density (TCD), and viable cell density (VCD) in a CHO fed‐batch process was demonstrated in situ in 3 L and 15 L bioreactors. Spectral preprocessing and partial least squares (PLS) regression were used to correlate spectral data with off‐line reference data. Separate PLS calibration models were developed for each analyte at the 3 L laboratory bioreactor scale before assessing its transferability to the same bioprocess conducted at the 15 L pilot scale. PLS calibration models were successfully developed for all analytes bar VCD and transferred to the 15 L scale. © 2012 American Institute of Chemical Engineers Biotechnol. Prog., 2012     

Hybridoma growth and antibody production as a function of cell density and specific growth rate in perfusion culture

Steady state metabolic parameters for hybridoma cell line H22 were determined over a wide range of cell densities and specific growth rates in a filtration based homogeneous perfusion reactor. Operating the reactor at perfusion rates of 0.75, 2.0, and 2.9 day(-1)(each at four different specific growth rates), viable cell densities as high as 2 x 10(7) cells/mL were obtained. For the cell line under investigation, the specific monoclonal antibody production rate was found to be a strong function of the viable cell density, increasing with increasing cell density. In contrast, most of the substrate consumption and product formation rates were strong functions of the specific growth rate. Substrate metabolism became more efficient at high cell densities and low specific growth rates. The Specific rates of metabolite formation and the apparent yields of lactate from glucose and ammonia from glutamine decreased at low specific growth rates and high cell densities. While the specific oxygen consumption rate was independent of the specific growth rate and cell density, ATP production was more oxidative at lower specific growth rate and higher cell density. These observed shifts are strong indications of the production potential of high-density perfusion culture. (c) 1995 John Wiley & Sons, Inc.     

Reducing dimensionality for prediction of genome-wide breeding values

Partial least square regression (PLSR) and principal component regression (PCR) are methods designed for situations where the number of predictors is larger than the number of records. The aim was to compare the accuracy of genome-wide breeding values (EBV) produced using PLSR and PCR with a Bayesian method, ''BayesB''. Marker densities of 1, 2, 4 and 8 N_e markers/Morgan were evaluated when the effective population size (N_e) was 100. The correlation between true breeding value and estimated breeding value increased with density from 0.611 to 0.681 and 0.604 to 0.658 using PLSR and PCR respectively, with an overall advantage to PLSR of 0.016 (s.e = 0.008). Both methods gave a lower accuracy compared to the ''BayesB'', for which accuracy increased from 0.690 to 0.860. PLSR and PCR appeared less responsive to increased marker density with the advantage of ''BayesB'' increasing by 17% from a marker density of 1 to 8N_e/M. PCR and PLSR showed greater bias than ''BayesB'' in predicting breeding values at all densities. Although, the PLSR and PCR were computationally faster and simpler, these advantages do not outweigh the reduction in accuracy, and there is a benefit in obtaining relevant prior information from the distribution of gene effects.     

Monitoring a bioprocess for ethanol production using FT-MIR and FT-Raman spectroscopy

The application of Fourier transform mid-infrared (FT-MIR) spectroscopy and Fourier transform Raman (FT-Raman) spectroscopy for process and quality control of fermentative production of ethanol was investigated. FT-MIR and FT-Raman spectroscopy along with multivariate techniques were used to determine simultaneously glucose, ethanol, and optical cell density of Saccharomyces cerevisiae during ethanol fermentation. Spectroscopic measurement of glucose and ethanol were compared and validated with the high-performance liquid chromatography (HPLC) method. Spectral wave number regions were selected for partial least-squares (PLS) regression and principal component regression (PCR) and calibration models for glucose, ethanol, and optical cell density were developed for culture samples. Correlation coefficient (R ²) value for the prediction for glucose and ethanol was more than 0.9 using various calibration methods. The standard error of prediction for the PLS first-derivative calibration models for glucose, ethanol, and optical cell density were 1.938 g/l, 1.150 g/l, and 0.507, respectively. Prediction errors were high with FT-Raman because the Raman scattering of the cultures was weak. Results indicated that FT-MIR spectroscopy could be used for rapid detection of glucose, ethanol, and optical cell density in S. cerevisiae culture during ethanol fermentation. Journal of Industrial Microbiology & Biotechnology (2001) 26, 185–190. Received 16 November 2000/ Accepted in revised form 12 January 2001     

The interaction of ammonia and xenon with the imidazole glycerol phosphate synthase from Thermotoga maritima as detected by NMR spectroscopy

The imidazole glycerol phosphate (ImGP) synthase from the hyperthermophilic bacterium Thermotoga maritima is a 1:1 complex of the glutaminase subunit HisH and the cyclase subunit HisF. It has been proposed that ammonia generated by HisH is transported through a channel to the active site of HisF, which generates intermediates of histidine (ImGP) and de novo biosynthesis of 5‐aminoimidazole‐4‐carboxamideribotide. Solution NMR spectroscopy of ammonium chloride‐titrated samples was used to study the interaction of NH₃ with amino acids inside this channel. Although numerous residues showed ¹⁵N chemical shift changes, most of these changes were caused by nonspecific ionic strength effects. However, several interactions appeared to be specific. Remarkably, the amino acid residue Thr 78—which is located in the central channel—shows a large chemical shift change upon titration with ammonium chloride. This result and the reduced catalytic activity of the Thr78Met mutant indicate a special role of this residue in ammonia channeling. To detect and further characterize internal cavities in HisF, which might for example contribute to ammonia channeling, the interaction of HisF with the noble gas xenon was analyzed by solution NMR spectroscopy using ¹H‐¹⁵N HSQC experiments. The results indicate that HisF contains three distinct internal cavities, which could be identified by xenon‐induced chemical shift changes of the neighboring amino acid residues. Two of these cavities are located at the active site at opposite ends of the substrate N′‐[(5′‐phosphoribulosyl)formimino]‐5‐aminoimidazole‐4‐carboxamide‐ribonucleotide (PRFAR) binding groove. The third cavity is located in the interior of the central β‐barrel of HisF and overlaps with the putative ammonia transport channel.     

Quick generation of Raman spectroscopy based in‐process glucose control to influence biopharmaceutical protein product quality during mammalian cell culture

Mitigating risks to biotherapeutic protein production processes and products has driven the development of targeted process analytical technology (PAT); however implementing PAT during development without significantly increasing program timelines can be difficult. The development of a monoclonal antibody expressed in a Chinese hamster ovary (CHO) cell line via fed‐batch processing presented an opportunity to demonstrate capabilities of altering percent glycated protein product. Glycation is caused by pseudo‐first order, non‐enzymatic reaction of a reducing sugar with an amino group. Glucose is the highest concentration reducing sugar in the chemically defined media (CDM), thus a strategy controlling glucose in the production bioreactor was developed utilizing Raman spectroscopy for feedback control. Raman regions for glucose were determined by spiking studies in water and CDM. Calibration spectra were collected during 8 bench scale batches designed to capture a wide glucose concentration space. Finally, a PLS model capable of translating Raman spectra to glucose concentration was built using the calibration spectra and spiking study regions. Bolus feeding in mammalian cell culture results in wide glucose concentration ranges. Here we describe the development of process automation enabling glucose setpoint control. Glucose‐free nutrient feed was fed daily, however glucose stock solution was fed as needed according to online Raman measurements. Two feedback control conditions were executed where glucose was controlled at constant low concentration or decreased stepwise throughout. Glycation was reduced from ～9% to 4% using a low target concentration but was not reduced in the stepwise condition as compared to the historical bolus glucose feeding regimen. © 2015 American Institute of Chemical Engineers Biotechnol. Prog., 32:224–234, 2016     

A multivariate calibration procedure for UV/VIS spectrometric monitoring of BHK‐21 cell metabolism and growth

Monitoring mammalian cell culture with UV–vis spectroscopy has not been widely explored. The aim of this work was to calibrate Partial Least Squares (PLS) models from off‐line UV–vis spectral data in order to predict some nutrients and metabolites, as well as viable cell concentrations for mammalian cell bioprocess using phenol red in culture medium. The BHK‐21 cell line was used as a mammalian cell model. Spectra of samples taken from batches performed at different dissolved oxygen concentrations (10, 30, 50, and 70% air saturation), in two bioreactor configurations and with two strategies to control pH were used to calibrate and validate PLS models. Glutamine, glutamate, glucose, and lactate concentrations were suitably predicted by means of this strategy. Especially for glutamine and glucose concentrations, the prediction error averages were lower than 0.50 ± 0.10 mM and 2.21 ± 0.16 mM, respectively. These values are comparable with those previously reported using near infrared and Raman spectroscopy in conjunction with PLS. However, viable cell concentration models need to be improved. The present work allows for UV–vis at‐line sensor development, decrease cost related to nutrients and metabolite quantifications and establishment of fed‐batch feeding schemes. © 2013 American Institute of Chemical Engineers Biotechnol. Prog., 30:241–248, 2014     

Adaptation of hybridoma cells to higher ammonia concentration

Using two mouse-mouse hybridoma cell lines, the response to ammonia step and serial changes was investigated in batch and continuous cultures with serum-free medium. The inhibitory effect of ammonia on cell growth depended on the cultivation mode, and differed markedly between cell lines. The cell line, 4C10B6 producing IgG monoclonal antibody against Pseudomonas, showed a high adaptation ability to ammonia. The 4C10B6 cells could grow under ammonia concentration as high as 21 mmol/l NH₄Cl with a viability of 80% in the continuous culture with serial increase in ammonia concentration. Whereas, in the batch culture with ammonia step change the cell growth completely ceased at 12 mmol/l NH₄Cl. The other cell line, TO-405 producing IgG monoclonal antibody against hepatitis B surface antigen, could not adapt to ammonia, and the cell growth did not occur at 9 mmol/l NH₄Cl even under the ammonia serial change.List of symbols D_Feed d^-1 Dilution rate of fresh feed medium (=F_o/V) - D_Out d^-1 Dilution rate of cell suspension (=F₁/V) - F₁ ml·d^-1 Volumetric discharge rate of cell suspension - F₀ ml·d^-1 Volumetric flow rate of fresh feed medium - k_D h^-1 Specific death rate - P mmol·l^-1 Product concentration - S mmol·l^-1 Substrate concentration in culture broth - S₀ mmol·l^-1 Substrate concentration in feed medium - t d Cultivation time - V ml Working volume of reactor - X₀ cells·ml^-1 Total cell density - X_V cells·ml^-1 Viable cell density - Y_P/S mmol·mmol^-1 Yield of product from substrate - Y_X/S cells·mmol^-1 Yield of cells from substrate - mmol·cell^-1·h^-1 Specific production rate - h^-1 Specific growth rate - mmol·cell^-1·h^-1 Specific consumption rate of substrate     

Investigating antibacterial effects of garlic (Allium sativum) concentrate and garlic-derived organosulfur compounds on Campylobacter jejuni by using Fourier transform infrared spectroscopy, Raman spectroscopy, and electron microscopy

Fourier transform infrared (FT-IR) spectroscopy and Raman spectroscopy were used to study the cell injury and inactivation of Campylobacter jejuni from exposure to antioxidants from garlic. C. jejuni was treated with various concentrations of garlic concentrate and garlic-derived organosulfur compounds in growth media and saline at 4, 22, and 35°C. The antimicrobial activities of the diallyl sulfides increased with the number of sulfur atoms (diallyl sulfide < diallyl disulfide < diallyl trisulfide). FT-IR spectroscopy confirmed that organosulfur compounds are responsible for the substantial antimicrobial activity of garlic, much greater than those of garlic phenolic compounds, as indicated by changes in the spectral features of proteins, lipids, and polysaccharides in the bacterial cell membranes. Confocal Raman microscopy (532-nm-gold-particle substrate) and Raman mapping of a single bacterium confirmed the intracellular uptake of sulfur and phenolic components. Scanning electron microscopy (SEM) and transmission electron microscopy (TEM) were employed to verify cell damage. Principal-component analysis (PCA), discriminant function analysis (DFA), and soft independent modeling of class analogs (SIMCA) were performed, and results were cross validated to differentiate bacteria based upon the degree of cell injury. Partial least-squares regression (PLSR) was employed to quantify and predict actual numbers of healthy and injured bacterial cells remaining following treatment. PLSR-based loading plots were investigated to further verify the changes in the cell membrane of C. jejuni treated with organosulfur compounds. We demonstrated that bacterial injury and inactivation could be accurately investigated by complementary infrared and Raman spectroscopies using a chemical-based, "whole-organism fingerprint" with the aid of chemometrics and electron microscopy.     

Analysis of chemometric models applied to Raman spectroscopy for monitoring key metabolites of cell culture

The Food and Drug Administration (FDA) initiative of Process Analytical Technology (PAT) encourages the monitoring of biopharmaceutical manufacturing processes by innovative solutions. Raman spectroscopy and the chemometric modeling tool partial least squares (PLS) have been applied to this aim for monitoring cell culture process variables. This study compares the chemometric modeling methods of Support Vector Machine radial (SVMr), Random Forests (RF), and Cubist to the commonly used linear PLS model for predicting cell culture components—glucose, lactate, and ammonia. This research is performed to assess whether the use of PLS as standard practice is justified for chemometric modeling of Raman spectroscopy and cell culture data. Model development data from five small-scale bioreactors (2 × 1 L and 3 × 5 L) using two Chinese hamster ovary (CHO) cell lines were used to predict against a manufacturing scale bioreactor (2,000 L). Analysis demonstrated that Cubist predictive models were better for average performance over PLS, SVMr, and RF for glucose, lactate, and ammonia. The root mean square error of prediction (RMSEP) of Cubist modeling was acceptable for the process concentration ranges of glucose (1.437 mM), lactate (2.0 mM), and ammonia (0.819 mM). Interpretation of variable importance (VI) results theorizes the potential advantages of Cubist modeling in avoiding interference of Raman spectral peaks. Predictors/Raman wavenumbers (cm⁻¹) of interest for individual variables are X1139–X1141 for glucose, X846–X849 for lactate, and X2941–X2943 for ammonia. These results demonstrate that other beneficial chemometric models are available for use in monitoring cell culture with Raman spectroscopy.     

Effect of NH3 on the cell growth of a hybridoma cell line

Ammonia often has been reported to inhibit cell growth. The aqueous ammonia equilibrium between the un-ionized form (NH₃) and the ammonium ion (NH₄ ⁺) depends on the pH of the solution. Extensive studies in batch and continuous cultivation by varying pH and total ammonia concentration were carried out to investigate whether a kinetic model describing growth inhibition by ammonia has to be based on the total ammonia concentration, or the concentration of NH₃. A significant relationship between the specific growth rate and death rate, respectively, and the NH₃ concentration but not the total ammonia concentration, was detected. An adaptation of the cells to high ammonia levels was not observed. Based on these results a new kinetic model for ammonia mediated growth inhibition is suggested. For high density cultivation it is recommended to control the pH at the lower limit of the growth optimum to keep the NH₃ level low.     

Screening of bacterial strains capable of converting biodiesel‐derived raw glycerol into 1,3‐propanediol, 2,3‐butanediol and ethanol

The ability of bacterial strains to assimilate glycerol derived from biodiesel facilities to produce metabolic compounds of importance for the food, textile and chemical industry, such as 1,3‐propanediol (PD), 2,3‐butanediol (BD) and ethanol (EtOH), was assessed. The screening of 84 bacterial strains was performed using glycerol as carbon source. After initial trials, 12 strains were identified capable of consuming raw glycerol under anaerobic conditions, whereas 5 strains consumed glycerol under aerobiosis. A plethora of metabolic compounds was synthesized; in anaerobic batch‐bioreactor cultures PD in quantities up to 11.3 g/L was produced by Clostridium butyricum NRRL B‐23495, while the respective value was 10.1 g/L for a newly isolated Citrobacter freundii. Adaptation of Cl. butyricum at higher initial glycerol concentration resulted in a PD_max concentration of ～32 g/L. BD was produced by a new Enterobacter aerogenes isolate in shake‐flask experiments, under fully aerobic conditions, with a maximum concentration of ～22 g/L which was achieved at an initial glycerol quantity of 55 g/L. A new Klebsiella oxytoca isolate converted waste glycerol into mixtures of PD, BD and EtOH at various ratios. Finally, another new C. freundii isolate converted waste glycerol into EtOH in anaerobic batch‐bioreactor cultures with constant pH, achieving a final EtOH concentration of 14.5 g/L, a conversion yield of 0.45 g/g and a volumetric productivity of ～0.7 g/L/h. As a conclusion, the current study confirmed the utilization of biodiesel‐derived raw glycerol as an appropriate substrate for the production of PD, BD and EtOH by several newly isolated bacterial strains under different experimental conditions.     

Estimating photosynthetic traits from reflectance spectra: A synthesis of spectral indices,numerical inversion,and partial least square regression

The lack of efficient means to accurately infer photosynthetic traits constrains understanding global land carbon fluxes and improving photosynthetic pathways to increase crop yield. Here, we investigated whether a hyperspectral imaging camera mounted on a mobile platform could provide the capability to help resolve these challenges, focusing on three main approaches, that is, reflectance spectra-, spectral indices-, and numerical model inversions-based partial least square regression (PLSR) to estimate photosynthetic traits from canopy hyperspectral reflectance for 11 tobacco cultivars. Results showed that PLSR with inputs of reflectance spectra or spectral indices yielded an R² of ~0.8 for predicting V _cmax and J _max, higher than an R² of ~0.6 provided by PLSR of numerical inversions. Compared with PLSR of reflectance spectra, PLSR with spectral indices exhibited a better performance for predicting V _cmax (R² = 0.84 ± 0.02, RMSE = 33.8 ± 2.2 μmol m⁻² s⁻¹) while a similar performance for J _max (R² = 0.80 ± 0.03, RMSE = 22.6 ± 1.6 μmol m⁻² s⁻¹). Further analysis on spectral resampling revealed that V _cmax and J _max could be predicted with ~10 spectral bands at a spectral resolution of less than 14.7 nm. These results have important implications for improving photosynthetic pathways and mapping of photosynthesis across scales.     

Survey of cytotoxic and UV protection effects of biosynthesized cerium oxide nanoparticles

Cerium oxide nanoparticles (CeO₂ NPs) are among the important nanoparticles that are extensively utilized in cosmetics, automotive industries, ultraviolet (UV) filtration, gas sensors, and pharmaceutical products. In this study, CeO₂ NPs were synthesized using an aqueous extract of Ziziphus jujube fruit. The synthesized nanoparticles were characterized using UV‐visible spectroscopy, powder X‐ray diffraction, Fourier transform infrared spectroscopy, energy‐dispersive spectroscopy, field energy scanning electron microscopy, and Raman methods. The results indicated that the size of synthesized nanoparticles is between 18 and 25 nm, and they have a spherical shape. UV absorbance of the synthesized nanoparticles was measured through spectrophotometric method in the range of 290 to 320 nm. The cytotoxic activity of synthesized CeO₂ NPs against colon (HT‐29) cancer cell line was surveyed through 3‐(4,5‐dimethylthiazol‐2‐yl)‐2,5‐diphenyltetrazolium bromide assay. The results showed that synthesized nanoparticles are nontoxic on HT‐29 cells under 400 μg/mL concentrations after 24 hours of treatment time periods. The increase in treatment time cases increases cytotoxic activity of synthesized nanoparticles. Sun protection factor of CeO₂ NPs, as a criterion for amount of sunlight radiation protection, was determined by applying Mansur equation. The results demonstrated that synthesized CeO₂ NPs have excellent UV protection and sunscreen physical absorption properties.     

Estimation of Potentially Toxic Elements Contamination in Anthropogenic Soils on a Brown Coal Mining Dumpsite by Reflectance Spectroscopy: A Case Study

In order to monitor Potentially Toxic Elements (PTEs) in anthropogenic soils on brown coal mining dumpsites, a large number of samples and cumbersome, time-consuming laboratory measurements are required. Due to its rapidity, convenience and accuracy, reflectance spectroscopy within the Visible-Near Infrared (Vis-NIR) region has been used to predict soil constituents. This study evaluated the suitability of Vis-NIR (350–2500 nm) reflectance spectroscopy for predicting PTEs concentration, using samples collected on large brown coal mining dumpsites in the Czech Republic. Partial Least Square Regression (PLSR) and Support Vector Machine Regression (SVMR) with cross-validation were used to relate PTEs data to the reflectance spectral data by applying different preprocessing strategies. According to the criteria of minimal Root Mean Square Error of Prediction of Cross Validation (RMSEP_cv) and maximal coefficient of determination (R²_cv) and Residual Prediction Deviation (RPD), the SVMR models with the first derivative pretreatment provided the most accurate prediction for As (R²_cv) = 0.89, RMSEP_cv = 1.89, RPD = 2.63). Less accurate, but acceptable prediction for screening purposes for Cd and Cu (0.66 ˂ R²_cv) ˂ 0.81, RMSEP_cv = 0.0.8 and 4.08 respectively, 2.0 ˂ RPD ˂ 2.5) were obtained. The PLSR model for predicting Mn (R²_cv) = 0.44, RMSEP_cv = 116.43, RPD = 1.45) presented an inadequate model. Overall, SVMR models for the Vis-NIR spectra could be used indirectly for an accurate assessment of PTEs’ concentrations.     

Real‐time monitoring of antibody glycosylation site occupancy by in situ Raman spectroscopy during bioreactor CHO cell cultures

The glycosylation of therapeutic monoclonal antibodies (mAbs), a known critical quality attribute, is often greatly modified during the production process by animal cells. It is essential for biopharmaceutical industries to monitor and control this glycosylation. However, current glycosylation characterization techniques involve time‐ and labor‐intensive analyses, often carried out at the end of the culture when the product is already synthesized. This study proposes a novel methodology for real‐time monitoring of antibody glycosylation site occupancy using Raman spectroscopy. It was first observed in CHO cell batch culture that when low nutrient concentrations were reached, a decrease in mAb glycosylation was induced, which made it essential to rapidly detect this loss of product quality. By combining in situ Raman spectroscopy with chemometric tools, efficient prediction models were then developed for both glycosylated and nonglycosylated mAbs. By comparing variable importance in projection profiles of the prediction models, it was confirmed that Raman spectroscopy is a powerful method to distinguish extremely similar molecules, despite the high complexity of the culture medium. Finally, the Raman prediction models were used to monitor batch and feed‐harvest cultures in situ. For the first time, it was demonstrated that the concentrations of glycosylated and nonglycosylated mAbs could be successfully and simultaneously estimated in real time with high accuracy, including their sudden variations due to medium exchanges. Raman spectroscopy can thus be considered as a promising PAT tool for feedback process control dedicated to on‐line optimization of mAb quality. © 2018 American Institute of Chemical Engineers Biotechnol. Prog., 34:486–493, 2018     

Erythrocyte heme‑oxygenation status indicated as a risk factor in prehypertension by Raman spectroscopy

Raman spectroscopy of erythrocytes provides detailed information about the structure and status of heme moiety, which can be used to provide new insights into molecular pathogenesis of several diseases. In this study, we present the first Raman spectroscopy investigations of the effect of hemoglobin oxygenation in the context of hypertensive disease. The experimental data was subjected to Logistic Regression, which indicated heme?oxygenation status as an important risk factor alongside other clinical parameters. The 1605/1621?cm^?1 band ratio was selected as an optimal Raman metric for risk assessment and along with other band ratios (1583, 1639, 1310?cm^?1) related to heme status and when combined with clinical data via logistic regression gave an Area Under the Curve (AUC) >0.95 for prehypertension risk prediction. The work demonstrates the feasibility of Raman spectroscopy to distinguish between prehypertensive and normotensive states. Simultaneously, it is implied that the etiology of the high blood pressure progression may be connected with the changes in hemoglobin oxygenation.