Optimization of a chromatographic stationary phase based on gellan gum using central composite design.

To develop a new stationary phase of easy production, low cost, biocompatible, biodegradable and low unspecific adsorption, a three-dimensional network was prepared by combining the natural polysaccharide of gellan with divalent cations. The stability of this cation exchange chromatographic matrix was optimized by using an experimental design tool. The optimal conditions proposed for the gellan gel formulation were 48mM ZnSO4, 0% DMF, 25°C, 0.75% gellan and 0.5h. The applicability of gellan matrix was tested by chromatographic assays with three model proteins (bovine serum albumin (BSA), α-chymotripsin and lysozyme). The results showed that the retention occurred in function of the net charge of each protein in MES buffer pH 6.2 and the elution was performed by increase of ionic strength to 750mM NaCl in MES buffer pH 6.2. Lysozyme was the more retained protein due to its positive charge more effective than α-chymotripsin, while BSA did not interact with the matrix due to its negative charge at these conditions. Dynamic binding capacity assays were accomplished to characterize this matrix and to compare with commercial resins. The values of dynamic binding capacity from gellan gel were 3.9mg/mL and 17.4mg/mL, at 10% and 50% of breakthrough, respectively. In this way, gellan gel might be a promising chromatographic matrix to explore ionic interactions and to be applied in different purification strategies, getting the best benefit from its use at low cost.

Fast development of Pichia pastoris GS115 Mut(+) cultures employing batch-to-batch control and hybrid semi-parametric modeling.

In this paper, we implemented a model-based optimization platform for fast development of Pichia pastoris cultures employing batch-to-batch control and hybrid semi-parametric modeling. We illustrate the methodology with a P. pastoris GS115 strain expressing a single-chain antibody fragment (scFv) by determining the optimal time profiles of temperature, pH, glycerol feeding and methanol feeding that maximize the endpoint scFv titer. The first hybrid model was identified from data of six exploratory experiments carried out in a pilot 50-L reactor. This model was subsequently used to maximize the final scFv titer of the proceeding batch employing a dynamic optimization program. Thereupon, the optimized time profiles of control variables were implemented in the pilot reactor and the resulting new data set was used to re-identify the hybrid model and to re-optimize the next batch. The iterative batch-to-batch optimization was stopped after 4 complete optimized batches with the final scFv titer stabilizing at 49.5 mg/L. In relation to the baseline batch (executed according to the Pichia fermentation guidelines by Invitrogen) a more than fourfold increase in scFv titer was achieved. The biomass concentration at induction and the methanol feeding rate profile were found to be the most critical control degrees of freedom to maximize scFv titer.

Segregated flux balance analysis constrained by population structure/function data: the case of PHA production by mixed microbial cultures.

In this study we developed a segregated flux balance analysis (FBA) method to calculate metabolic flux distributions of the individual populations present in a mixed microbial culture (MMC). Population specific flux data constraints were derived from the raw data typically obtained by the fluorescence in situ hybridization (FISH) and microautoradiography (MAR)-FISH techniques. This method was applied to study the metabolic heterogeneity of a MMC that produces polyhydroxyalkanoates (PHA) from fermented sugar cane molasses. Three populations were identified by FISH, namely Paracoccus sp., Thauera sp., and Azoarcus sp. The segregated FBA method predicts a flux distribution for each of the identified populations. The method is shown to predict with high accuracy the average PHA storage flux and the respective monomeric composition for 16 independent experiments. Moreover, flux predictions by segregated FBA were slightly better than those obtained by nonsegregated FBA, and also highly concordant with metabolic flux analysis (MFA) estimated fluxes. The segregated FBA method can be of high value to assess metabolic heterogeneity in MMC systems and to derive more efficient eco-engineering strategies. For the case of PHA-producing MMC considered in this work, it becomes apparent that the PHA average monomeric composition might be controlled not only by the volatile fatty acids (VFA) feeding profile but also by the population composition present in the MMC.

Application of adaptive DO-stat feeding control to Pichia pastoris X33 cultures expressing a single chain antibody fragment (scFv).

In this study, fed-batch cultures of a Pichia pastoris strain constitutively expressing a single chain antibody fragment (scFv) under the control of the glyceraldehyde-3-phosphate dehydrogenase (GAP) promoter were performed in a pilot 50 L bioreactor. Due to the very high cell density achieved within the first 75 h, typically between 140 and 160 g-DCW/L of dry cell weight (DCW), most of the scFv is produced under hard oxygen transfer limitation. To improve scFv productivity, a direct adaptive dissolved oxygen (DO)-stat feeding controller that maximizes glycerol feeding under the constraint of available oxygen transfer capacity was developed and applied to this process. The developed adaptive controller enabled to maximize glycerol feeding through the regulation of DO concentration between 3 and 5 % of saturation, thereby improving process productivity. Set-point convergence dynamics are characterized by a fast response upon large perturbations to DO, followed by a slower but very robust convergence in the vicinity of the boundary with almost imperceptible overshoot. Such control performance enabled operating closer to the 0 % boundary for longer periods of time when compared to a traditional proportional-integral-derivative algorithm, which tends to destabilize with increasing cell density.

Optimization of fermentation conditions for the production of human soluble catechol-O-methyltransferase by Escherichia coli using artificial neural network.

The aim of this work was to optimize the temperature, pH and stirring rate of the production of human soluble catechol-O-methyltransferase (hSCOMT) in a batch Escherichia coli culture process. A central composite design (CCD) was firstly employed to design the experimental assays used in the evaluation of these operational parameters on the hSCOMT activity for a semi-defined and complex medium. Predictive artificial neural network (ANN) models of the hSCOMT activity as function of the combined effects of these variables was proposed based on this exploratory experiments performed for the two culture media. The regression coefficients (R(2)) for the final models were 0.980 and 0.983 for the semi-defined and complex medium, respectively. The ANN models predicted a maximum hSCOMT activity of 183.73 nmol/h, at 40 °C, pH 6.5 and stirring rate of 351 rpm, and 132.90 nmol/h, at 35 °C, pH 6.2 and stirring rate of 351 rpm, for semi-defined and complex medium, respectively. These results represent a 4-fold increase in total hSCOMT activity by comparison to the standard operational conditions used for this bioprocess at slight scale.