Bacteriophages, viruses that can infect bacteria, are promising alternatives for antibiotic treatment caused by antibiotic-resistant bacteria strains. For that reason, the production of bacteriophages is extensively studied. Mathematical modelling can lead to the improvement of bioprocess by identification of critical process parameters and their impact on the demanded product. Dynamic modelling considers a system (i.e. bioreactor or bioprocess) as a dynamic object focusing on changes in the initial and final parameters (such as biomass concentration and product formation) in time, so-called signals and treats the studied system as a “black box” that processes signals. This work aimed to develop a mathematical model that describes bacteriophage production process. As result, we created a dynamic model that can estimate the number of bacteriophages released from cells as plaque-forming units at specific time points based on the changes in the bacteria host-cell concentration. Moreover, the proposed model allowed us to analyze the impact of the initial virus concentration given by multiplicity of infection (MOI) on the amount of produced bacteriophages.
In this study, batch fermentation of glucose to ethanol by Saccharomyces cerevisiae (ATCC 7754) was carried out using 2.5 dm3 BioFlo®115 bioreactor. The main objective of this study was to investigate the kinetics of ethanol fermentation by means of the non-structured model. The fermentation process was carried out for 72 h. Samples were collected every 4 h and then yeast growth concentration of ethanol and glucose were measured. The mathematical model was composed of three equations, which represented the changes of biomass, substrate and ethanol concentrations. The mathematical model of bioprocess was solved by means of Matlab/SimulinkTM environment. The obtained results from the proposed model showed good agreement with the experimental data, thus it was concluded that this model can be used for the mathematical modeling of ethanol production.
New development trends of conventional bioprocess and bioreactor engineering were presented taking into account new achievements of molecular biology and genetic engineering. One can notice the dusk of a so-called 'black box' approach, which was up to now the main concept of macro- analysis of bioreactor processes. In other levels of bioreactor analysis (micro- and macroscopic) the progress is also observed. Therefore, it does not mean a complete change of approach to the analysis of bioprocess but rather its complementation on the molecular level and further development of macroscopic approach. As a result, one can expect higher efficiency of bioproducts, particularly of secondary metabolites.
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