Kenics Static Mixer Combined with Gas Sparging for the Improvement of Cross-Flow Microfiltration: Modeling and Optimization.

The use of membrane filtration as a downstream process for microbial biomass harvesting is hampered due to the low permeate flux values achieved during the microfiltration of fermentation broths. Several hydrodynamic methods for increasing permeate flux by creating turbulent flow patterns inside the membrane module are used to overcome this problem. The main goal of this study was to investigate the combined use of a Kenics static mixer and gas sparging during cross-flow microfiltration of Bacillus velezensis IP22 cultivation broth. Optimization of the microfiltration process was performed by using the response surface methodology. It was found that the combined use of a static mixer and gas sparging leads to a considerable increase in the permeate flux, up to the optimum steady-state permeate flux value of 183.42 L·m-2·h-1 and specific energy consumption of 0.844 kW·h·m-3. The optimum steady-state permeate flux is almost four times higher, whilst, at the same time, the specific energy consumption is almost three times lower compared to the optimum results achieved using gas sparging alone. The combination of Kenics static mixer and gas sparging during cross-flow microfiltration is a promising technique for the enhancement of steady-state permeate flux with simultaneously decreasing specific energy consumption.

Best-performing Bacillus strains for microbiologically induced CaCO3 precipitation: Screening of relative influence of operational and environmental factors.

The microbiologically induced calcite precipitation (MICP) can be an emerging approach that could tap onto soil bacterial diversity and use as a bioremediation technique. Based on the concept that bacteria with biomineralization capacity could be effective CaCO3 inductance agents, this study aimed to evaluate the simultaneous influence of 11 operational and environmental factors on the MICP process, for the first time. Therefore, Bacillus muralis, B. lentus, B. simplex, B. firmus, and B. licheniformis, isolated from alkaline soils, were used in the selection of the best performing bacterium compared with a well-known MICP bioagent Sporosarcina pasteurii DSM 33. Plackett-Burman's experimental design was labouring to screen all independent variables for their significances on five outputs (pH value, number of viable cells and spores, amount of urea and CaCO3 precipitate). According to experimentally obtained data, an artificial neural network model based on the Broyden-Fletcher-Goldfarb-Shanno algorithm showed good prediction capabilities, while differences in the relative influences were observed at the bacterial strain level. B. licheniformis turn out to be the most potent bioagent, with a maximum amount of CaCO3 precipitate of 3.14 g/100 mL in the optimal conditions.

Optimization of glycerol-based medium composition for antifungal metabolites production by Bacillus subtilis

Abstract Bacillus species are promising producers of various compounds that have pronounced antimicrobial, antiviral and antitumor activities. Due to its GRAS status, Bacillus subtilis represents an excellent candidate for the usage in plant pathogens biocontrol. In this research, evaluation of antifungal metabolites biosynthesis by Bacillus subtilis ATCC 6633 and optimization of glycerol-based medium composition, using response surface methodology, for the production of compounds effective against Neurospora crassa were investigated. The results of disc-diffusion method indicate that applied Bacillus strain produces compounds with antifungal activity against tested fungus. In order to find optimal cultivation medium composition, the experiments were carried out in accordance with Box-Behnken design, and optimization was performed using the concept of desirability function combined with previously defined mathematical equation, which describes examined bioprocess. The optimization model predicts that maximum inhibition zone diameter against Neurospora crassa of 32.24 mm is achieved when initial content of glycerol, NaNO2 and K2HPO4 were 49.68 g/L, 2.90 g/L and 6.49 g/L, respectively. Additionally, the second optimization set was made to minimize the consumption of medium components and costs of medium preparation. The obtained results are the basis for further research aimed to develop medium appropriate for economically justified production of bioactive compounds at industrial scale.

Modeling and Optimization of Gas Sparging-Assisted Bacterial Cultivation Broth Microfiltration by Response Surface Methodology and Genetic Algorithm.

Production of highly efficient biomass-based microbial biopesticides significantly depends on downstream processing in terms of obtaining as high concentration of viable cells as possible. Microfiltration is one of the recommended operations for microbial biomass separation, but its main limitation is permeate flux decrease due to the membrane fouling. The effect of air sparging as a hydrodynamic technique for improvement of permeate flux during microfiltration of Bacillus velezensis cultivation broth was investigated. Modeling of the microfiltration was performed using the response surface methodology, while desirability function approach and genetic algorithm were applied for optimization, i.e., maximization of permeate flux and minimization of specific energy consumption. The results have revealed antagonistic relationship between the investigated dependent variables. The optimized values of superficial feed velocity and transmembrane pressure were close to the mean values of the investigated value ranges (0.68 bar and 0.96 m/s, respectively), while the optimized value of superficial air velocity had a more narrow distribution around 0.25 m/s. The results of this study have revealed a significant improvement of microfiltration performance by applying air sparging, thus this flux improvement method should be further investigated in downstream processing of different bacterial cultivation broths.