Carla A.M. Portugal

In situ 2D fluorometry and chemometric monitoring of mammalian cell cultures

The main objective of the present study was to investigate the use of in situ 2D fluorometry for monitoring key bioprocess variables in mammalian cell cultures, namely the concentration of viable cells and the concentration of recombinant proteins. All studies were conducted using a recombinant Baby Hamster Kidney (BHK) cell line expressing a fusion glycoprotein IgG1‐IL2 cultured in batch and fed‐batch modes. It was observed that the intensity of fluorescence signals in the excitation/emission wavelength range of amino acids, vitamins and NAD(P)H changed along culture time, although the dynamics of single fluorophors could not be correlated with the dynamics of the target state variables. Therefore, multivariate chemometric modeling was adopted as a calibration methodology. 2D fluorometry produced large volumes of redundant spectral data, which were first filtered by principal components analysis (PCA). Then, a partial least squares (PLS) regression was applied to correlate the reduced fluorescence maps with the target state variables. Two validation strategies were used to evaluate the predictive capacity of the developed PLS models. Accurate estimations of viable cells density (r2 = 0.95; 99.2% of variance captured in the training set; r2 = 0.91; 97.7% of variance captured in the validation set) and of glycoprotein concentration (r2 = 0.99 and 99.7% of variance captured in the training set; r2 = 0.99 and 99.3% of variance captured in the validation set) were obtained over a wide range of reactor operation conditions. The results presented herein confirm that 2D fluorometry constitutes a reliable methodology for on‐line monitoring of viable cells and recombinant protein concentrations in mammalian cell cultures. Biotechnol. Bioeng. 2009;102: 1098–1106.

Multivariate statistically-based modelling of a membrane bioreactor for wastewater treatment using 2D fluorescence monitoring data

This work presents the development of multivariate statistically-based models for monitoring several key performance parameters of membrane bioreactors (MBR) for wastewater treatment. This non-mechanistic approach enabled the deconvolution of 2D fluorescence spectroscopy data, a powerful technique that has previously been shown to capture important information regarding MBR performance. Projection to latent structure (PLS) modelling was used to integrate 2D fluorescence data, after compression through parallel factor analysis (PARAFAC), with operation and analytical data to describe an MBR fouling indicator (transmembrane pressure, TMP), five descriptors of the effluent quality (total COD, soluble COD, concentration of nitrite and nitrate, total nitrogen and total phosphorus in the permeate) and the biomass concentration in the bioreactor (MLSS). A multilinear correlation was successfully established for TMP, CODtp and CODsp, whereas the optimised models for the remaining outputs included quadratic and interaction terms of the compressed 2D fluorescence matrices. Additionally, the coefficients of the optimised models revealed important contributions of some of the input parameters to the modelled outputs. This work demonstrates the applicability of 2D fluorescence and statistically-based models to simultaneously monitor multiple key MBR performance parameters with minimal analytical effort. This is a promising approach to facilitate the implementation of MBR technology for wastewater treatment.

Real-time monitoring of membrane bioreactors with 2D-fluorescence data and statistically based models

The application of membrane bioreactors (MBR) for wastewater treatment is growing worldwide due to their compactness and high effluent quality. However, membrane fouling, mostly associated to biological products, can reduce MBR performance. Therefore, it is important to monitor MBRs as close to real-time as possible to accelerate control actions for maximal biological and membrane performance. 2D-fluorescence spectroscopy is a promising on-line tool to simultaneously monitor wastewater treatment efficiency and the formation of potential biological fouling agents. In this study, 2D-fluorescence data obtained from the wastewater and the permeate of a MBR was successfully modelled using projection to latent structures (PLS) to monitor variations in the influent and effluent total chemical oxygen demand (COD). Analysis of the results also indicated that humic acids and proteins highly contributed to the measured COD in both streams. Nevertheless, this approach was not valid for other performance parameters of the MBR system (such as influent and effluent ammonia and phosphorus), which is usually characterised through a high number of analytical and operating parameters. Principal component analysis (PCA) was thus used to find possible correlations between these parameters, in an attempt to reduce the analytical effort required for full MBR characterisation and to reduce the time frame necessary to obtain monitoring results. The 3 first principal components, capturing 57% of the variance, indicated and confirmed expected relationships between the assessed parameters. However, this approach alone could not provide robust enough correlations to enable the elimination of parameters for process description (PCA loadings ≤ 0.5). Nevertheless, it is possible that the information captured by 2D-fluorescence spectroscopy could replace some of the analytical and operating parameters, since this technique was able to successfully describe influent and effluent total COD. It is thus proposed that combined modelling of 2D-fluorescence data and selected performance/operating parameters should be further explored for efficient MBR monitoring aiming at rapid process control.

1)H NMR Relaxation Study of a Magnetic Ionic Liquid as a Potential Contrast Agent.

A proton nuclear magnetic relaxation dispersion (1)H NMRD study of the molecular dynamics in mixtures of magnetic ionic liquid [P66614][FeCl4] with [P66614][Cl] ionic liquid and mixtures of [P66614][FeCl4] with dimethyl sulfoxide (DMSO) is presented. The proton spin-lattice relaxation rate, R1, was measured in the frequency range of 8 kHz-300 MHz. The viscosity of the binary mixtures was measured as a function of an applied magnetic field, B, in the range of 0-2 T. In the case of DMSO/[P66614][FeCl4] the viscosity was found to be independent from the magnetic field, while in the case of the [P66614][Cl]/[P66614][FeCl4] system viscosity decreased with the increase of the magnetic field strength. The spin-lattice relaxation results were analyzed for all systems taking into account the relaxation mechanisms associated with the molecular motions with correlation times in a range between 10(-11) and 10(-7)s, usually observed by NMRD, and the paramagnetic relaxation contributions associated with the presence of the magnetic ions in the systems. In the case of the DMSO/[P66614][FeCl4] system the R1 dispersion shows the relaxation enhancement due to the presence of the magnetic ions, similar to that reported for contrast agents. For the [P66614][Cl]/[P66614][FeCl4] system, the R1 dispersion presents a much larger paramagnetic relaxation contribution, in comparison with that observed for the DMSO/[P66614][FeCl4] mixtures but different from that reported for other magnetic ionic liquid system. In the [P66614][Cl]/[P66614][FeCl4] system the relaxation enhancement associated with the paramagnetic ions is clearly not proportional to the concentration of magnetic ions, in contrast with what is observed for the DMSO/[P66614][FeCl4] system.

Nano-structured magneto-responsive membranes from block copolymers and iron oxide nanoparticles

Mixed matrix membranes (MMMs) provide an exciting alternative to traditional membranes due to their favorable properties from both building blocks which are essential for certain separation applications. Block copolymer directed synthesis of MMMs is an innovative approach for the preparation of porous materials. In the current work the syntheses of mixed matrix membranes from a PMAA-b-PMMA block copolymer and functionalized iron oxide magnetic nanoparticles are demonstrated. The block copolymers were synthesized using a RAFT polymerization technique, along with three different types of magnetic nanoparticles with various surface properties. The thin film membranes were prepared by mixing different ratios of diblock copolymer in THF and iron oxide nanoparticles in water followed by tape casting or spin coating. The particles and the membranes were characterized using TEM, DLS, and SEM. The permeation behavior of the membranes was assessed using filtration tests in the presence and absence of a magnetic field.

Effect of tissue scaffold topography on protein structure monitored by fluorescence spectroscopy

The impact of surface topography on the structure of proteins upon adhesion was assessed through non-invasive fluorescence monitoring. This study aimed at obtaining a better understanding about the role of protein structural status on cell-scaffold interactions. The changes induced upon adsorption of two model proteins with different geometries, trypsin (globular conformation) and fibrinogen (rod-shaped conformation) on poly-l-lactic acid (PLLA) scaffolds with different surface topographies, flat, fibrous and surfaces with aligned nanogrooves, were assessed by fluorescence spectroscopy monitoring, using tryptophan as structural probe. Hence, the maximum emission blue shift and the increase of fluorescence anisotropy observed after adsorption of globular and rod-like shaped proteins on surfaces with parallel nanogrooves were ascribed to more intense protein-surface interactions. Furthermore, the decrease of fluorescence anisotropy observed upon adsorption of proteins to scaffolds with fibrous morphology was more significant for rod-shaped proteins. This effect was associated to the ability of these proteins to adjust to curved surfaces. The additional unfolding of proteins induced upon adsorption on scaffolds with a fibrous morphology may be the reason for better cell attachment there, promoting an easier access of cell receptors to initially hidden protein regions (e.g. RGDS sequence), which are known to have a determinant role in cell attaching processes.

Fluorescence monitoring of trypsin adsorption in layer-by-layer membrane systems.

A combined fluorescence analysis, involving the use of steady-state fluorescence and fluorescence anisotropy was used, allowing eliciting information about the structural changes induced on trypsin after exposure to membrane surfaces with diverse chemistry, designed through a layer-by-layer methodology. Using this monitoring strategy it was possible to understand the influence of the surface chemistry on the structural characteristics of the attached proteins and how they relate to changes of their activity resulting from the adsorption process. This knowledge may be used to direct the development of surfaces with suitable chemistry, leading enzymatic-based processes with improved performance. The results obtained show clearly that trypsin exposed to different membrane surfaces, changes its conformation, either if it adsorbs to the membrane or if it remains in solution. A significant loss of enzymatic activity was observed upon the adsorption process, for the adsorbed and non-adsorbed protein. This loss of the trypsin activity was correlated with the presence of molecular unfolding events that mediate trypsin-membrane surface interactions and the decrease of the molecular mobility of the adsorbed trypsin, which was shown to be dependent on the chemical characteristics of the membrane surface. Changes on the selectivity of the adsorbed trypsin were also observed, and may be ruled by the strength of the enzyme-surface interactions established.

Development of fluorescent thermoresponsive nanoparticles for temperature monitoring on membrane surfaces

In this work, tris(phenantroline)ruthenium(II) chloride (Ru(phen)3) was immobilized in silica nanoparticles prepared according to the Stöber method. Efforts were devoted on the optimization of the nano-thermometer in terms of size, polydispersity, intensity of the emission and temperature sensitivity. In particular, the immobilization of the luminophore in an external thin shell made of silica grown in a second step on bare silica nanoparticles allowed producing fluorescent monodisperse silica nanoparticles (420±20nm). A systematic study was addressed to maximize the intensity of the emission of the fluorescent nanoparticles by adjusting the concentration of Ru(phen)32+ in the shell from 0.2 to 24wt.%, whereas the thickness of the shell is affected by the amount of silica precursor employed. The luminescent activity of the doped nanoparticles was found to be sensitive to the temperature. In fact, the intensity of the emission linearly decreased by increasing the temperature from 20°C to 65°C. The thermoresponsive nanoparticles were functionalized with long aliphatic chains in order to obtain hydrophobic nanoparticles. The developed nanoparticles were immobilized via dip-coating procedure on the surface of hydrophobic porous membranes, such as Polyvinylidene fluoride (PVDF) prepared via Non-Solvent Induced Phase Separation (NIPS), providing local information about the membrane surface temperature.

Development of a hybrid model strategy for monitoring membrane bioreactors.

In the present study, the performance of a membrane bioreactor (MBR) was modelled using a hybrid approach based on the activated sludge model number 3 (ASM3) combined with projection to latent structures (PLS) to predict the residuals of the ASM. The application of ASM to MBRs requires frequent re-calibration to adjust the model to variations in influent characteristics, determined through time-consuming analysis and batch tests. Considering this problem, the objective of this study was to improve ASM prediction ability with minimal additional monitoring effort. Hybrid models were developed to predict three MBR performance parameters: mixed liquor suspended solids (MLSS), COD in the permeate (CODp) and nitrite and nitrate concentration in the permeate (NOxp). For PLS modelling of ASM residuals three input strategies were used: (1) analytic and operating data; (2) operating data plus 2D fluorescence spectroscopy; (3) all the data. The first input strategy improved ASM prediction of the three selected outputs, and highlighted the lack of detailed and real-time information from wastewater and operating parameters in the ASM used in this study. In the second input strategy, the incorporation of updated data from 2D fluorescence spectroscopy resulted on better model fitting than in the first input strategy, for all the output parameters studied. Through the hybrid modelling approach it was possible to significantly improve the ASM predictions in real-time using 2D fluorescence measurements and other relevant parameters acquired on-line, without requiring further laboratory analysis. Furthermore, the third input strategy, incorporating all the collected data, did not significantly improve the prediction of the outputs beyond the second strategy. This shows that 2D fluorescence spectroscopy is a comprehensive monitoring tool, able to capture on-line the required information to complement, through hybrid modelling, the mechanistic information described by an ASM.

Influence of Magnetic Nanoparticles on PISA Preparation of Poly(Methacrylic Acid)-b-Poly(Methylmethacrylate) Nano-Objects

This article presents the synthesis of poly(methacrylic acid)-b-poly(methyl methacrylate) diblock copolymer via polymerization-induced self-assembly in the presence of iron-oxide nanoparticles. Detailed phase diagrams with and without inorganic nanoparticles were constructed. Scanning transmission electron microscopy and energy dispersive X-ray photometry studies confirme the decoration of the polymeric nanoparticles with the iron-oxide nanoparticles. These hybrid nanoparticles were used to prepare porous thin film membranes by spin coating. Finally, the magneto-responsive properties of the membranes were assessed using water filtration tests in the presence and absence of a magnetic field.