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 recent years, infections are more often caused by pathogens with high multi-drug resistance, classified as the “ESKAPE” microorganisms. Therefore, investigation of these pathogens, e.g., Klebsiella pneumoniae, often requires biomass production for treatment testing such as antibiotics or bacteriophages. Moreover, K. pneumoniae can be successfully applied as a biocatalyst for other industrial applications, increasing the need for this bacteria biomass. In the current study, we proposed a novel magnetically assisted bioreactor for the cultivation of K. pneumoniae cells in the presence of an external alternating magnetic field (AMF). High efficiency of the production requires optimal bacteria growth conditions, e.g., temperature and field frequency. Therefore, we performed an optimization procedure using a central composite design for these two parameters in a wide range. As an objective function, we utilized a novel, previously described growth factor that considers both biomass and bacteria growth kinetics. Thus, based on the response surface, we could specify the optimal growth conditions. Moreover, we analysed the impact of the AMF on bacteria proliferation, which indicated positive field frequency windows, where the highest stimulatory effect of AMF on bacteria proliferation occurred. Obtained results proved that the magnetically assisted bioreactor could be successfully employed for K. pneumoniae cultivation.