Cecília R. C. Calado

Integration of production and aqueous two-phase systems extraction of extracellular Fusarium solani pisi cutinase fusion proteins

Genetic engineering was integrated with the production and purification of Fusarium solani pisi cutinases, in order to obtain the highest amount of enzyme activity units, after purification. An aqueous two-phase system (ATPS) of polyethylene glycol 3350, dipotassium phosphate and whole broth was used for the extraction of three extracellular cutinases expressed in Saccharomyces cerevisiae. The production/extraction process was evaluated regarding cutinases secretion in the medium, partition behaviour and extraction yields in the ATPS. The proteins studied were cutinase wild type and two fusion proteins of cutinase with the tryptophane-proline (WP) fusion tags, namely (WP)(2) and (WP)(4). The (WP)(4) fusion protein enabled a 300-fold increase of the cutinase partition coefficient when comparing to the wild type. However, the secretion of the fusion proteins was lower than of the wild type cutinase secretion. A batch extraction strategy was compared with a continuous extraction in a perforated rotating disc contactor (PRDC). The batch and continuous systems were loaded with as much as 60% (w/w) whole cultivation broth. The continuous extraction strategy provided a 2.5 higher separation capacity than the batch extraction strategy. Considering the integrated process, the cutinase-(WP)(2) proved to lead to the highest product activity, enabling five and six times more product activity than the wild type and the (WP)(4) fusion proteins, respectively.

Effect of pre-fermentation on the production of cutinase by a recombinant Saccharomyces cerevisiae

The importance of controlling the expression of heterologous cutinase in a recombinant Saccharomyces cerevisiae SU50 strain was investigated. Maximum specific growth rate and the biomass yield increased 1.91 and 1.16 fold, respectively, when cutinase production was induced by galactose in a pre-fermentation step. However, only 19% of specific cell activity was obtained in comparison to other fermentations following a pre-fermentation step without induction of cutinase expression. Thus, the pre-fermentation step was performed using a selective medium not containing galactose, and the fermentation was performed with a cheaper and complex non-selective medium containing galactose. Under these conditions, and with the aim of maximising the specific cutinase activity, a pre-fermentation with low volume and high density of viable cells must be used. However, due to the low pre-fermentation volume, low yeast cell concentrations and low specific cell activities were obtained after 96 h of fermentation. Otherwise, when the aim was to maximise cutinase yield and productivity, a pre-fermentation volume of 10% (v/v) in relation to fermentation and in the exponential growth phase with a cell concentration between 1.1 and 1.8 g dcw/l should be used. A higher pre-fermentation volume, such as 20% (v/v), would still be economical in the case of a pre-fermentation with low cell density or low cell viability.

Development of a fed-batch cultivation strategy for the enhanced production and secretion of cutinase by a recombinant Saccharomyces cerevisiae SU50 strain

Saccharomyces cerevisiae SU50 strain was cultivated with different concentrations of glucose and galactose with the aim of increasing cutinase activity, cutinase yield on the carbon source, and bioreactor productivity. Cultivations in shake flasks with galactose as the sole carbon source, with sugar concentrations between 10 and 40 g/l, exhibited growth-associated cutinase production and a constant specificity of cutinase secretion. Furthermore, as the galactose concentration increased to values higher than 15 g/l, a progressively higher maximum specific galactose consumption rate and a consequent higher alcoholic fermentation occurred, resulting in progressively lower biomass yields on the carbon source and cutinase yields on biomass. Using high glucose and galactose concentrations in a well-aerated bioreactor resulted in a high biomass productivity (0.5 g dcw/l/h), a high cutinase yield on biomass (21.5 U/mg dew), a final high cutinase secretion efficiency (97%), and plasmid stability (99%). Based on these studies, a two phase fed-batch cultivation strategy was developed. A batch phase with high glucose and galactose concentrations, followed by a fed-batch with a constant feed rate with galactose as the sole carbon source in order to minimize the repression of the GAL 7 promoter, were established. The feed rate was estimated to maintain a pre-determined concentration of galactose (20 g/l) on the culture medium in order to maximize the efficiency of cutinase secretion and minimize the galactose alcoholic fermentation. By this cultivation strategy, enhancements of 3.6-fold in cutinase activity, 1.2-fold in cutinase yield on the carbon source, and 8.7-fold culture productivity were obtained in relation to a batch cultivation performed in shake flasks with 20 g/l of galactose.

High‐throughput analysis of the plasmid bioproduction process in Escherichia coli by FTIR spectroscopy

Monitoring plasmid production systems is a lab intensive task. This article proposes a methodology based on FTIR spectroscopy and the use of chemometrics for the high‐throughput analysis of the plasmid bioproduction process in E. coli. For this study, five batch cultures with different initial medium compositions are designed to represent different biomass and plasmid production behavior, with the maximum plasmid and biomass concentrations varying from 11 to 95 mg L−1 and 6.8 to 12.8 g L−1, respectively, and the plasmid production per biomass varying from 0.4 to 5.1 mg g−1. After a short sample processing consisting of centrifugation and dehydration, the FTIR spectra are recorded from the collected cellular biomass using microtiter plates with 96 wells. After spectral pre‐processing, the predictive FTIR spectra models are derived by using partial least squares (PLS) regression with the wavenumber selection performed by a Monte‐Carlo strategy. Results show that it is possible to improve the PLS models by selecting specific spectral ranges. For the plasmid model, the spectral regions between 590–1,130, 1,670–2,025, and 2,565–3,280 cm−1 are found to be highly relevant. Whereas for the biomass, the best wavenumber selections are between 900–1,200, 1,500–1,800, and 2,850–3,200 cm−1. The optimized PLS models show a high coefficient of determination of 0.91 and 0.89 for the plasmid and biomass concentration, respectively. Additional PLS models for the prediction of the carbon sources glucose and glycerol and the by‐product acetic acid, based on metabolism‐induced correlations between the nutrients and the cellular biomass are also established. Biotechnol. Bioeng. 2012;109: 2279–2285.

Antigenic diversity among Portuguese clinical isolates of Helicobacter pylori

Background:  The human gastroduodenal pathogen, Helicobacter pylori, is characterized by an unusual extent of genetic heterogeneity. This dictates differences in the antigenic pattern of strains resulting in heterogeneous human humoral immune responses. Here, we examined the antigenic variability among a group of 10 strains isolated from Portuguese patients differing in age, gender, and H. pylori‐associated gastric diseases.

In situ near infrared spectroscopy monitoring of cyprosin production by recombinant Saccharomyces cerevisiae strains

Near infrared (NIR) spectroscopy was used to in situ monitoring the cultivation of two recombinant Saccharomyces cerevisiae strains producing heterologous cyprosin B. NIR spectroscopy is a fast and non-destructive technique, that by being based on overtones and combinations of molecular vibrations requires chemometrics tools, such as partial least squares (PLS) regression models, to extract quantitative information concerning the variables of interest from the spectral data. In the present work, good PLS calibration models based on specific regions of the NIR spectral data were built for estimating the critical variables of the cyprosin production process: biomass concentration, cyprosin activity, cyprosin specific activity, the carbon sources glucose and galactose concentration and the by-products acetic acid and ethanol concentration. The PLS models developed are valid for both recombinant S. cerevisiae strains, presenting distinct cyprosin production capacities, and therefore can be used, not only for the real-time control of both processes, but also in optimization protocols. The PLS model for biomass yielded a R(2)=0.98 and a RMSEP=0.46 g dcw l(-1), representing an error of 4% for a calibration range between 0.44 and 13.75 g dcw l(-1). A R(2)=0.94 and a RMSEP=167 Um l(-1) were obtained for the cyprosin activity, corresponding to an error of 6.7% of the experimental data range (0-2509 Um l(-1)), whereas a R(2)=0.93 and RMSEP=672 U mg(-1) were obtained for the cyprosin specific activity, corresponding to an error of 7% of the experimental data range (0-11,690 Um g(-1)). For the carbon sources glucose and galactose, a R(2)=0.96 and a RMSECV of 1.26 and 0.55 g l(-1), respectively, were obtained, showing high predictive capabilities within the range of 0-20 g l(-1). For the metabolites resulting from the cell growth, the PLS model for acetate was characterized by a R(2)=0.92 and a RMSEP=0.06 g l (-1), which corresponds to a 6.1% error within the range of 0.41-1.23 g l(-1); for the ethanol, a high accuracy PLS model with a R(2)=0.97 and a RMSEP=1.08 g l(-1) was obtained, representing an error of 9% within the range of 0.18-21.76 g l(-1). The present study shows that it is possible the in situ monitoring and prediction of the critical variables of the recombinant cyprosin B production process by NIR spectroscopy, which can be applied in process control in real-time and in optimization protocols. From the above, NIR spectroscopy appears as a valuable analytical tool for online monitoring of cultivation processes, in a fast, accurate and reproducible operation mode.

In Situ Near-Infrared (NIR) versus High-Throughput Mid-Infrared (MIR) Spectroscopy to Monitor Biopharmaceutical Production

The development of biopharmaceutical manufacturing processes presents critical constraints, with the major constraint being that living cells synthesize these molecules, presenting inherent behavior variability due to their high sensitivity to small fluctuations in the cultivation environment. To speed up the development process and to control this critical manufacturing step, it is relevant to develop high-throughput and in situ monitoring techniques, respectively. Here, high-throughput mid-infrared (MIR) spectral analysis of dehydrated cell pellets and in situ near-infrared (NIR) spectral analysis of the whole culture broth were compared to monitor plasmid production in recombinant Escherichia coli cultures. Good partial least squares (PLS) regression models were built, either based on MIR or NIR spectral data, yielding high coefficients of determination (R2) and low predictive errors (root mean square error, or RMSE) to estimate host cell growth, plasmid production, carbon source consumption (glucose and glycerol), and by-product acetate production and consumption. The predictive errors for biomass, plasmid, glucose, glycerol, and acetate based on MIR data were 0.7 g/L, 9 mg/L, 0.3 g/L, 0.4 g/L, and 0.4 g/L, respectively, whereas for NIR data the predictive errors obtained were 0.4 g/L, 8 mg/L, 0.3 g/L, 0.2 g/L, and 0.4 g/L, respectively. The models obtained are robust as they are valid for cultivations conducted with different media compositions and with different cultivation strategies (batch and fed-batch). Besides being conducted in situ with a sterilized fiber optic probe, NIR spectroscopy allows building PLS models for estimating plasmid, glucose, and acetate that are as accurate as those obtained from the high-throughput MIR setup, and better models for estimating biomass and glycerol, yielding a decrease in 57 and 50% of the RMSE, respectively, compared to the MIR setup. However, MIR spectroscopy could be a valid alternative in the case of optimization protocols, due to possible space constraints or high costs associated with the use of multi-fiber optic probes for multi-bioreactors. In this case, MIR could be conducted in a high-throughput manner, analyzing hundreds of culture samples in a rapid and automatic mode.

Direct product sequestration of a recombinant cutinase from batch fermentations of Saccharomyces cerevisiae.

The recovery of cutinase of Fusarium solani pisi produced by the yeast Saccharomyces cerevisiae was studied in a fluidised bed adsorption system directly integrated with a productive fermenter (so-called direct product sequestration; DPS). The relative efficiency of this system was compared with the one of a conventional purification process by discrete sequences of fermentation, broth clarification, ultrafiltration and fixed bed anion exchange chromatography. By direct product sequestration of the extracellular heterologous cutinase it was possible, through only one unit operation: (i) to perform broth clarification, (ii) to obtain a high cutinase concentration factor, and (iii) to recover cutinase with a specific activity that equalled that obtained with the conventional purification process. It was also possible (iv) to substantially reduce the total process time, (v) to improve the overall yield, and (vi) to increase cutinase productivity. Furthermore, the procedure outlined is suitable for large scale bioprocess exploitation.

Kinetic modeling of plasmid bioproduction in Escherichia coli DH5α cultures over different carbon-source compositions.

The need for the development of economic high plasmid production in Escherichia coli cultures is emerging, as a result of the latest advances in DNA vaccination and gene therapy. In order to contribute to achieve that, a model describing the kinetics involved in the bioproduction of plasmid by recombinant E. coli DH5α is presented, as an attempt to understand the complex and non-linear metabolic relationships and the plasmid production occurring in dynamic batch culture environments, run under different media compositions of glucose and glycerol, that result in distinct maximum biomass growths (between 8.2 and 12.8 g DCW/L) and specific plasmid productions (between 1.1 and 7.4 mg/g DCW). The model based on mass balance equations for biomass, glucose, glycerol, acetate and plasmid accurately described different culture behaviors, using either glucose or glycerol as carbon source, or mixtures of both. From the 17 parameters obtained after model simplification, the following 10 parameters were found to be independent of the carbon source composition: the substrate affinity constants, the inhibitory constants of biomass growth on glycerol by glucose, of biomass growth on acetate by glycerol and the global biomass growth by acetate, and the yields of biomass on acetate, acetate on glucose and glycerol, and plasmid on glucose. The parameters that depend on the culture composition, and that might explain the differences found between cultures, were: maximum specific growth rates on glucose, glycerol and acetate; biomass yield on glucose and glycerol; and plasmid yield on glycerol and acetate. Moreover, a crucial role of acetate in the plasmid production was revealed by the model, with most of plasmid production being associated to the acetate consumption. The model provides meaningful insight on the E. coli dynamic cell behavior concerning the plasmid bioproduction, which might lead to important guidelines for culture optimization and process scale-up and control.

Use of chemometrics in the selection of a Saccharomyces cerevisiae expression system for recombinant cyprosin B production

Two multivariate statistical methods, factor analysis (FA) and hierarchical cluster analysis (HCA), were applied to experimental data set to evaluate their usefulness in selecting the adequate expression system and optimal growth parameters for recombinant cyprosin B production. Using FA, the large data set was reduced to two factors representing 73.4% of variability. Factor 1, with 53.5% of variability, corresponds to recombinant cyprosin B expression and efficient secretion, while factor 2, accounting for 19.9% of variability, represents cell growth and physiological characteristics. FA and HCA allowed the establishment of correlations among different variables and the clusters obtained providing clear identification of the experimental parameters related to cyprosin B production, which results on more accurate scientific output and time saving when selection of an adequate expression system is concerned.