RESUMEN
The diversity and the stability of the microbial community are associated with microecological interactions between its members. Antagonism is one type of interaction, which particularly determines the benefits that probiotics bring to host health by suppressing opportunistic pathogens and microbial contaminants in food. Mathematical models allow for quantitatively predicting intrapopulation relationships. The aim of this study was to create predictive models for bacterial contamination outcomes depending on the probiotic antagonism and prebiotic concentration. This should allow an improvement in the screening of synbiotic composition for preventing gut microbial infections. The functional model (fermentation) was based on a three-stage continuous system, and the distal colon section (N2, pH 6.8, flow rate 0.04 h-1) was simulated. The strains Bifidobacterium adolescentis ATCC 15703 and Bacillus cereus ATCC 9634 were chosen as the model probiotic and pathogen. Oligofructose Orafti P95 (OF) was used as the prebiotic at concentrations of 2, 5, 7, 10, 12, and 15 g/L of the medium. In the first stage, the system was inoculated with Bifidobacterium, and a dynamic equilibrium (Bifidobacterium count, lactic, and acetic acids) was achieved. Then, the system was contaminated with a 3-day Bacillus suspension (spores). The microbial count, as well as the concentration of acids and residual carbohydrates, was measured. A Bacillus monoculture was studied as a control. The stationary count of Bacillus in monoculture was markedly higher. An increase (up to 8 h) in the lag phase was observed for higher prebiotic concentrations. The specific growth rate in the exponential phase varied at different OF concentrations. Thus, the OF concentration influenced two key events of bacterial infection, which together determine when the maximal pathogen count will be reached. The mathematical models were developed, and their accuracies were acceptable for Bifidobacterium (relative errors ranging from 1.00% to 2.58%) and Bacillus (relative errors ranging from 0.74% to 2.78%) count prediction.
RESUMEN
A number of mechanisms have been proposed explaining probiotics and prebiotics benefit human health, in particular, probiotics have a suppression effect on pathogen growth that can be enhanced with the introduction of prebiotics. In vitro models enhanced with computational biology can be useful for selecting a composition with prebiotics from new plant sources with the greatest synergism. Water extracts from burdock root and Jerusalem artichoke tubers were purified by ultrafiltration and activated charcoal and concentrated on a rotary evaporator. Fructans were precipitated with various concentrations of ethanol. Bifidobacterium bifidum 8 VKPM AC-2136 and Staphylococcus aureus ATCC 43300 strains were applied to estimate the synbiotic effect. The growth of bifidobacteria and staphylococci in monocultures and cocultures in broths with glucose, commercial prebiotics, as well as isolated fructans were studied. The minimum inhibitory concentrations (MICs) of lactic and acetic acids for the Staphylococcus strain were determined. A quantitative model joining the formation of organic acids by probiotics as antagonism factors and the MICs of pathogens (as the measure of their inhibition) was tested in cocultures and showed a high predictive value (R2 ≥ 0.86). The synbiotic factor obtained from the model was calculated based on the experimental data and obtained constants. Fructans precipitated with 20% ethanol and Bifidobacterium bifidum have the greater synergism against Staphylococcus.
RESUMEN
The hollow fiber membrane bioreactor (HFMB) has been investigated for the cultivation of mammalian Chinese hamster ovary cell expansion. The experiments were carried out in Petri's dishes and in the hollow fiber membrane bioreactor having 20 fibers (S2025 from FiberCell Systems). The approach to HFMB modelling which combines the model of cell growth kinetics and hydrodynamics has been proposed. The hydrodynamic model is made using ANSYS Fluent software. The mathematical model of HFMB was developed, allowing the study of the hydrodynamics into the lumen and the extracapillary spaces, the filtration through the membrane fiber with the cell expansion on outer membrane surface. The direct nutrient medium flow variant into the extracapillary space was suggested. Based on the numerical simulations, the optimal parameters were selected for daily changes in the medium flow-rate into the lumen space. The HFMB scaling up was performed for the larger size HFMB (60 fibers).
Asunto(s)
Reactores Biológicos , Técnicas de Cultivo de Célula , Membranas Artificiales , Modelos Teóricos , Animales , Células CHO , Cricetinae , CricetulusRESUMEN
The present study is dedicated to the development of novel criteria for assessing the synbiotic effect of prebiotic and probiotic composition against a specific pathogen. These criteria were obtained from the quantitative model of Bifidobacterium adolescentis ATCC 15703 and Bacillus cereus ATCC 9634 (as a model food contaminant) competition in co-culture fermentation. The model is based on the hypothesis that probiotics can reduce the specific growth rate of non-probiotics by producing short-chain fatty acids. To define the relationship between the specific growth rate of non-probiotics and short-chain fatty acid yields, the inhibition constants were determined separately for each inhibitor produced by bifidobacteria (lactic, acetic and propionic acids) in a pure culture of bacilli. Two different equations based on the minimum inhibitor concentration (MIC) and inhibition constant (Ki) were used to connect the specific growth rate and concentrations of inhibitors. The yields of the inhibitors mentioned above were obtained from co-culture experiments. The experimental values and the values predicted by the model of Bacillus count did not differ significantly (R2 not less than 0.83) in the competition experiments. Therefore, the general criterion of the synbiotic effect was derived from the model and presents the coefficient of non-probiotic specific growth rate reduction as a result of probiotic growth and inhibitor formation in the final co-culture fermentation. This criterion has been examined for different commercial prebiotics coupled with the Bifidobacterium adolescentis strain. The synergistic combination of inulin GR with bifidobacteria had the best effect against Bacillus cereus ATCC 9634.
