A mathematical model based on a dynamic metabolic flux balance (DMFB) is developed for a process of fed-batch fermentation of Bordetella pertussis. The model is based on the maximization of growth rate at each time interval subject to stoichiometric constraints. The model is calibrated and verified with experimental data obtained in two different bioreactor experimental systems. It was found that the model calibration was mostly sensitive to the consumption or production rates of tyrosine and, for high supplementation rates, to the consumption rate of glutamate. Following this calibration the model correctly predicts biomass and by-products concentrations for different supplementation rates. Comparisons of model predictions to oxygen uptake and carbon emission rates measurements indicate that the TCA cycle is fully functional.
Stirred bioreactors are commonly used unit operations in the pharmaceutical industry. In this study, computational fluid dynamics (CFD) was used in order to analyze the influence of the impeller configuration (Segment–Segment and Segment–Rushton impeller configurations) and the impeller rotational speed (an operational parameter) on the hydrodynamic behaviour and mixing performance of a bioreactor equipped with a double impeller. A relatively close agreement between the power values obtained from the CFD model and those measured experimentally was observed. Various parameters such as velocity profiles, stress generated by impellers due to the turbulence and velocity gradient, flow number, and mixing time were used to compare the CFD simulations. It was observed that the impeller’s RPM could change the intensity of the interaction between the impellers when a Segment–Rushton impeller was used. In general, increasing the RPM led to an increase in total power and the stress acting on the cells and to a shorter mixing time. At a constant RPM, the Segment–Rushton impeller configuration had higher total power and stress acting on cells compared to the Segment–Segment impeller configuration. At lower RPM values (i.e., 50 and 100), the Segment–Segment impeller provided a shorter mixing time. Conversely, at the highest RPM (i.e., 150) the Segment–Rushton impeller had a shorter mixing time compared to the Segment–Segment impeller; this was attributed to the high level of turbulence generated with the former impeller configuration at high RPM.
Fluorescence spectroscopy in combination with multivariate statistical methods was employed as a tool for monitoring the manufacturing process of pertactin (PRN), one of the virulence factors of Bordetella pertussis utilized in whopping cough vaccines. Fluorophores such as amino acids and co-enzymes were detected throughout the process. The fluorescence data collected at different stages of the fermentation and purification process were treated employing principal component analysis (PCA). Through PCA, it was feasible to identify sources of variability in PRN production. Then, partial least square (PLS) was employed to correlate the fluorescence spectra obtained from pure PRN samples and the final protein content measured by a Kjeldahl test from these samples. In view that a statistically significant correlation was found between fluorescence and PRN levels, this approach could be further used as a method to predict the final protein content.
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