Enhancement of Electricity Production in Microbial Fuel Cells Using a Biosurfactant-Producing Co-Culture

Microbial fuel cells are bio-electrochemical devices that enable the conversion of chemical energy into bioelectricity. In this manuscript, the use of biosurfactants (Tween 80 and surfactin) and the effect of coculturing E. coli and L. plantarum were used to investigate the generation of bioelectricity coming from an H-type microbial fuel cell. In this setup, E. coli acts as an electron donor while L. plantarum acts as an in situ biosurfactant producer. It was observed that the use of exogenous surfactants enhanced electricity production compared to conventional E. coli cultures. The utilization of Tween 80 and surfactin increased the power generation from 204 µW m-2 to 506 µW m-2 and 577 µW m-2, respectively. Furthermore, co-culturing E. coli and L. plantarum also resulted in a higher power output compared to pure cultures (132.8% more when compared to using E. coli alone and 68.1% more when compared to using L. plantarum alone). Due to the presence of surfactants, the internal resistance of the cell was reduced. The experimental evidence collected here clearly indicates that the production of endogenous surfactants, as well as the addition of exogenous surfactants, will enhance MFC electricity production.

A Study and Modeling of Bifidobacterium and Bacillus Coculture Continuous Fermentation under Distal Intestine Simulated Conditions

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.

Probabilistic modelling of Escherichia coli concentration in raw milk under hot weather conditions

Climate change is one of the threats to the dairy supply chain as it may affect the microbiological quality of raw milk. In this context, a probabilistic model was developed to quantify the concentration of Escherichia coli in raw milk and explore what may happen to France under climate change conditions. It included four modules: initial contamination, packaging, retailing, and consumer refrigeration. The model was built in R using the 2nd order Monte Carlo mc2d package to propagate the uncertainty and analysed its impact independently of the variability. The initial microbial counts were obtained from a dairy farm located in Saudi Arabia to reflect the impact of hot weather conditions. This country was taken as representative of what might happen in Europe and therefore in France in the future due to climate change. A large dataset containing 622 data points was analysed. They were fitted by a Normal probability distribution using the fitdistrplus package. The microbial growth was determined across various scenarios of time and temperature storage reflecting the raw milk supply-chain in France. Existing growth rate data from literature and ComBase were analysed by the Ratkowsky secondary model. Results were interpreted using the nlstools package. The mean E. coli initial concentration in raw milk was estimated to be 1.31 [1.27; 1.35] log CFU/ mL and was found to increase at the end of the supply chain as a function of various time and temperature conditions. The estimations varied from 1.73 [1.42; 2.28] log CFU/mL after 12 h, 2.11 [1.46; 3.22] log CFU/mL after 36 h, and 2.41 [1.69;3.86] log CFU/mL after 60 h of consumer storage. The number of milk packages exceeding the 2-log French hygiene criterion for E. coli increased from 10% [8;12%] to 53% [27;77%] during consumer storage. In addition, the most significant factors contributing to the uncertainty of the model outputs were identified by running a sensitivity analysis. The results showed that the uncertainty around the Ratkowsky model parameters contributed the most to the uncertainty of E. coli concentration estimates. Overall, the model and its outputs provide an insight on the possible microbial raw milk quality in the future in France due to higher temperatures conditions driven by climate change.

One- and Two-Step Kinetic Data Analysis Applied for Single and Co-Culture Growth of Staphylococcus aureus, Escherichia coli, and Lactic Acid Bacteria in Milk

The objective of this study was to compare one- and two-step kinetic data analysis approaches to describe the growth of Staphylococcus aureus, Escherichia coli, and lactic acid bacteria Fresco 1010 starter culture in milk under isothermal conditions between 10 and 37 °C. The primary Huang model (HM) and secondary square root model were applied to lag times and growth rates of each of the population. The one-step approach for single cultures data enabled the direct construction of a tertiary model combining primary and secondary models to determine parameters from all growth data, thus minimizing the transfer of errors from one model to another. The statistical indices showed a significant improvement in the prediction capability provided by this approach. Then, a one-step approach combining the primary Huang, Giménez, and Dalgaard model (H-GD) with the secondary square root model was used to simultaneously model the growth of the populations mentioned above in co-culture under the same conditions. Independent isothermal data sets were chosen for validation of the growth description of single cultures (HM) and co-culture (H-GD) using validation factors, including the bias (Bf) and accuracy (Af). For example, the values of Af for the one-step approach range from 1.17 to 1.20 and 1.04 to 1.08 for single cultures and co-culture, respectively, demonstrating high accuracy. Thus, this approach may be used for co-culture growth description in general or specifically, e.g., in various types of lactic acid fermentation, including artisanal cheese-making technology.

A new expanded modelling approach for investigating the bioprotective capacity of Latilactobacillus sakei CTC494 against Listeria monocytogenes in ready-to-eat fish products

Understanding the role of food-related factors on the efficacy of protective cultures is essential to attain optimal results for developing biopreservation-based strategies. The aim of this work was to assess and model growth of Latilactobacillus sakei CTC494 and Listeria monocytogenes CTC1034, and their interaction, in two different ready-to-eat fish products (i.e., surimi-based product and tuna pâté) at 2 and 12 °C. The existing expanded Jameson-effect and a new expanded Jameson-effect model proposed in this study were evaluated to quantitatively describe the effect of microbial interaction. The inhibiting effect of the selected lactic acid bacteria strain on the pathogen growth was product dependent. In surimi product, a reduction of lag time of both strains was observed when growing in coculture at 2 °C, followed by the inhibition of the pathogen when the bioprotective L. sakei CTC494 reached the maximum population density, suggesting a mutualism-antagonism continuum phenomenon between populations. In tuna pâté, L. sakei CTC494 exerted a strong inhibition of L. monocytogenes at 2 °C (<0.5 log increase) and limited the growth at 12 °C (<2 log increase). The goodness-of-fit indexes indicated that the new expanded Jameson-effect model performed better and appropriately described the different competition patterns observed in the tested fish products. The proposed expanded competition model allowed for description of not only antagonistic but also mutualism-based interactions based on their influence on lag time.

Evaluation of Scenarios for Improving the Collection System for a Milk Factory in Ethiopia

The milk for a factory in Sululta (Ethiopia) is currently collected at ambient temperature. To increase milk production, the sourcing must be extended. This requires the collection of not only the morning milk but also the evening milk from smallholder farms. To accomplish this, the collection of milk from small farmers has to be improved, whereby the milk quality has to be assured with reasonable cost and environmental impact. A model predicting milk rejection was developed based on initial contamination and time and temperature profiles. With this model, different cooling scenarios we reevaluated regarding the expected effectiveness of reducing the rejection rate during collection. Second, cost estimations were made to implement the scenarios to collect morning and evening milk from smallholder farms. A third criterion was greenhouse gas (GHG) emissions per litre of collected milk. Finally, the feasibility of the scenarios was assessed in terms of technical, practical, and economic aspects. Including both quality and economics, the best scenario can be expected from a cooling centre where farmers bring their milk twice a day, except there are signals that the farmers would not be willing to deliver the evening milk to the centre at night. In that case, an additional collecting system would be needed to increase the milk supply. This would result in higher collection costs and an increased risk of milk rejection at the factory gate. Furthermore, this would reduce the value of the chilling centre, as in that case it would be better to deliver the milk directly to the factory. Both scenarios would increase GHG emissions compared with the current situation. Only the use of an off-grid solar power-driven cooling system at the farms would reduce the GHG emissions. However, this solution is less feasible economically. The applied combination of a simple model, economic analysis and the effect on GHG emissions gives valuable information on the effectiveness and limitations of different cooling scenarios for the milk factory. It can help to successfully apply a scenario for increasing the milk supply.

Effect of Lactic Acid Bacteria Addition on the Microbiological Safety of Pasta-Filata Types of Cheeses

In this work, the effects of different combinations of lactic acid bacteria (LAB) on the growth of coagulase-positive staphylococci (CPS) and Escherichia coli were evaluated during ripening of 23 curd cheeses, and their subsequent behavior during the manufacture and storage of pasta-filata cheeses was characterized. Three groups of cheeses were prepared in total: first, control cheeses from raw milk without LAB addition; further pasteurized milk cheeses with LAB, CPS and E. coli intentional inoculation; and finally, raw milk cheeses with LAB added. The aim was to compare the effect of LAB from starter culture, and also in combination with native LAB, and to evaluate the LAB effect as a group, and further to suggest the culture with the best inhibitory potential. Based on the results, counts of CPS increased over 24 h in control curd cheese by 1.76 ± 0.56 log CFU/g. On the other hand, in raw milk cheeses with the addition of starter culture, the increase in CPS counts by 0.76 ± 0.87 log CFU/g was noticed. Counts of E. coli increased during the first 24 h of curd manufacture by 3.56 ± 0.41 log CFU/g in cheeses without LAB addition. Contrary to this, using of LAB cultures resulted in an increase in E. coli counts by only 1.40 ± 1.07 log CFU/g. After steaming at 63.6 ± 1.9°C for 7.2 ± 2.1 min (temperature of heated acidified curd was 54.9 ± 1.7°C), CPS decreased by 0.58 ± 1.12 log CFU/g, and E. coli decreased by 1.23 ± 0.97 log CFU/g in all cheeses, regardless of LAB addition. Finally, during storage of cheeses at 6 ± 0.5°C for 28 days, the levels of E. coli in control cheeses and in raw milk LAB-enriched cheeses reached levels of 2.07 ± 2.28 log CFU/g and 1.20 ± 0.85 log CFU/g, respectively. In addition, the counts of CPS at the end of storage met the criteria of EU Commission Regulation (EC) No. 1441/2007 (2007) (less than 4 log CFU/g) in all manufactured cheeses with added LAB culture, while in the control raw milk cheeses, a level of 3.80 ± 1.22 log CFU/g was observed. Regarding the culture used, the best microbiological inhibitory effect in 28-day-old cheeses was reached by the combination of Fresco culture with Lacticaseibacillus rhamnosus GG, and the best sensory properties were judged to be those for cheeses manufactured with Culture A. A moderate negative effect of storage on overall sensory acceptance was noted, according to the final evaluation of overall acceptability of pasta-filata cheeses. The most satisfactory overall acceptability after 28 days of storage at 6°C was reached for cheese with the addition of culture A.

Growth prediction of two bacterial populations in co-culture with lactic acid bacteria

The co-culture growth of Staphylococcus aureus, Escherichia coli and lactic acid bacteria starter culture in milk was quantitatively evaluated and modelled with a set of coupled differential equations originally proposed by Baranyi and Roberts and by Gimenez and Dalgaard (BR–GD model). The lactic acid bacteria starter culture showed the ability to induce an early stationary phase of both E. coli and S. aureus populations at different combination of temperature (ranging from 12 to 37 ℃) and lactic acid bacteria inocula (from approx. 103 to 106 CFU/ml). First, the prediction ability was performed only with parameters estimated from individual growth curves of E. coli, S. aureus and the lactic acid bacteria in milk (Dataset 1, 21 experiments). Subsequently, the model was extended with the average competition coefficients (E-BR–GD model) that represented quantitative relations among the populations. The prediction ability of this model was validated with the second dataset consisting of seven experiments. Results and also their statistical indices (accuracy and bias factors) showed that the E-BR–GD model improved growth prediction of all involved populations. Thus, the total root mean square error decreased from 0.457, 0.840 and 0.322 log CFU/ml (BR–GD model) to 0.290, 0.245 and 0.333 log CFU/ml (E-BR–GD) for S. aureus, E. coli and lactic acid bacteria, respectively. This approach in growth prediction of multiple competing microbial populations can be used in assessment of S. aureus and E. coli exposure from raw milk cheeses consumption and contribute to decision making in prevention of staphylococcal enterotoxin production.

The Effect of Salt and Temperature on the Growth of Fresco Culture

The effect of environmental factors, including temperature and water activity, has a considerable impact on the growth dynamics of each microbial species, and it is complicated in the case of mixed cultures. Therefore, the aim of this study was to describe and analyze the growth dynamics of Fresco culture (consisting of 3 different bacterial species) using predictive microbiology tools. The growth parameters from primary fitting were modelled against temperature using two different secondary models. The intensity of Fresco culture growth in milk was significantly affected by incubation temperature described by Gibson’s model, from which the optimal temperature for growth of 38.6 °C in milk was calculated. This cardinal temperature was verified with the Topt = 38.3 °C calculated by the CTMI model (cardinal temperature model with inflection), providing other cardinal temperatures, i.e., minimal Tmin = 4.0 °C and maximal Tmax = 49.6 °C for Fresco culture growth. The specific growth rate of the culture under optimal temperature was 1.56 h−1. The addition of 1% w/v salt stimulated the culture growth dynamics under temperatures down to 33 °C but not the rate of milk acidification. The prediction data were validated and can be used in dairy practice during manufacture of fermented dairy products.

Occurence of antibiotic resistant bacteria in raw cow milk from vending machines

The prevalence of antibiotic resistant coliform bacteria and enterococci in fresh raw cow milk obtained from four vending machines in Slovakia was assessed. Also, differences in the number of antibiotic-resistant bacteria in milk according to season (winter and summer) were compared. Number of total coliform bacteria ranged from 2.45 to 4.18 log CFU/mL. Majority of them were resistant to ampicillin. This was expected due to their intrinsic resistance apart from Escherichia coli which is sensitive to ampicillin. In addition, we observed also tetracycline and gentamicin resistance. Each of our samples contained E.coli. Number of total enterococci ranged from 1.95 to 3.78 log CFU/mL. We have observed predominantly vancomycin resistance in all tested samples. In samples taken during winter we have found higher number of total and resistant coliforms as well as total enterococci compared to those taken during summer.

Adjacent-possible ecological niche: growth of Lactobacillus species co-cultured with Escherichia coli in a synthetic minimal medium

In certain conditions, members of the Lactobacillus genus are auxotrophs that have fastidious requirements for growth. Notably, Lactobacillus cannot grow in M9 medium, a minimal synthetic medium used for Escherichia coli. However, we found that some Lactobacillus strains can be grown in M9 when co-cultured with E. coli K-12. In the co-culture, L. casei proliferates exponentially, reaching cell densities of 108 CFU (colony-forming unit) ml-1 in 6 h and dominating E. coli in the late growth phase. Spent medium from E. coli grown overnight lacked this growth-promoting effect on L. casei. Similarly, the effect was not observed when the species were separated by a 0.4-µm membrane. Microscopic observations showed that L. casei are embedded in the micro-scale clusters of E. coli in the early growth phase. This study describes for the first time the ability of a Lactobacillus species to grow in minimal medium when in close proximity with co-cultured bacteria.