Impact of sodium chloride and carbon dioxide on conidial germination and radial growth of Penicillium camemberti.

Penicillium camemberti is a domesticated species adapted to the dairy environment, which is used as adjunct cultures to ripen soft cheeses. A recent population genomics analysis on P. camemberti revealed that P. camemberti is a clonal lineage with two varieties almost identical genetically but with contrasting phenotypes in terms of growth, color, mycotoxin production and inhibition of contaminants. P. camemberti variety camemberti is found on Camembert and Brie cheeses, and P. camemberti variety caseifulvum is mainly found on other cheeses like Saint-Marcellin and Rigotte de Condrieu. This study aimed to evaluate the impact of water activity (aw) reduced by sodium chloride (NaCl) and the increase of carbon dioxide (CO2) partial pressure, on conidial germination and growth of two varieties of P. camemberti: var. Camemberti and var. Caseifulvum. Mathematical models were used to describe the responses of P. camemberti strains to both abiotic factors. The results showed that these genetically distant strains had similar responses to increase in NaCl and CO2 partial pressure. The estimated cardinal values were very close between the strains although all estimated cardinal values were significantly different (Likelihood ratio tests, pvalue = 0.05%). These results suggest that intraspecific variability could be more exacerbated during fungal growth compared with conidial germination, especially in terms of macroscopic morphology. Indeed, var. Caseifulvum seemed to be more sensitive to an increase of CO2 partial pressure, as shown by the fungal morphology, with the occurrence of irregular outgrowths, while the morphology of var. Camemberti remains circular. These data could make it possible to improve the control of fungal development as a function of salt and carbon dioxide partial pressure. These abiotic factors could serve as technological barriers to prevent spoilage and increase the shelf life of cheeses. The present data will allow more precise predictions of fungal proliferation as a function of salt and carbon dioxide partial pressure, which are significant technological hurdles in cheese production.

Impact of carbon dioxide on the radial growth of fungi isolated from dairy environment.

In dairy industry, filamentous fungi are used as adjunct cultures in fermented products for their technological properties but they could also be responsible for food spoilage and mycotoxin production. The consumer demands about free-preservative products has increased in recent years and lead to develop alternative methods for food preservation. Modified Atmosphere Packaging (MAP) can inhibit fungal growth and therefore increase the food product shelf-life. This study aimed to evaluate radial growth as a function of CO2 and more particularly carbonic acid for fourteen adjuncts and/or fungal spoiler isolated from dairy products or dairy environment by using predictive mycology tools. The impact of the different chemical species linked to CO2 (notably carbonic acid) were study because it was reported previously that undissociated carbonic acid impacted bacterial growth and bicarbonates ions were involved in modifications of physiological process of fungal cells. A significant diversity in the responses of selected strains was observed. Mucor circinelloides had the fastest growth rates (µ > 11 mm. day-1) while Bisifusarium domesticum, Cladosporium herbarum and Penicillium bialowiezense had the slowest growth rates (µ < 1 mm. day-1). Independently of the medium pH, the majority of strains were sensitive to total carbonic acid. In this case, it was not possible to conclude if CO2 active form was gaseous or aqueous so modeling were performed as a function of CO2 percentage. Only Geotrichum candidum and M. circinelloides strains were sensitive to undissociated carbonic acid. Among the fourteen strains, P. bialowiezense was the less sensitive strain to CO2, no growth was observed at 50% of CO2 only for this strain. M. lanceolatus was the less sensitive strain to CO2, the CO250 which reduce the growth rates by 50% was estimated at 138% of CO2. Low CO2 percentage improved the growth of Penicillium expansum, Penicillium roqueforti and Paecilomyces niveus. Mathematical models (without and with optimum) were suggested to describe the impact of CO2 percentage or undissociated carbonic acid concentration on fungal growth rate.

Effects of carbon dioxide and oxygen on the growth rate of various food spoilage bacteria.

The growth of six bacterial species (Carnobacterium maltaromaticum, Bacillus weihenstephanensis, Bacillus cereus, Paenibacillus spp., Leuconostoc mesenteroides and Pseudomonas fragi) was studied in various gas compositions. Growth curves were obtained at various oxygen concentrations (between 0.1 and 21%), or various carbon dioxide concentrations (between 0 and 100%). Decreasing the O2 concentration from 21% to about 3-5% has no effect on the bacterial growth rates, which are only affected by low oxygen levels. For each strain studied, the growth rate decreased linearly with carbon dioxide concentration, except for L. mesenteroides which remained insensible to this gas. Conversely, the most sensitive strain was totally inhibited by 50% of carbon dioxide in the gas phase at 8 °C. Predictive models were fitted, and the parameters characterizing the inhibitory effect of these two gases were estimated. This study provides new tools to help the food industry design suitable packaging for MAP storage.

Impact of water activity on the radial growth of fungi in a dairy environment.

Filamentous fungi are used in the dairy industry as adjunct cultures in fermented products, but can also lead to food spoilage, waste and economic losses. The control of filamentous fungi with abiotic factors contributes to longer food shelf life and prevention of fungal spoilage. One of the main abiotic factors for controlling fungal growth in foods is water activity (aw). This study aimed to evaluate radial growth as a function of aw for sixteen fungal adjuncts and/or spoilers isolated from dairy products or a dairy environment. Glycerol (a non-ionic compound) and sodium chloride (NaCl, an ionic compound) were used to adjust the aw of culture media. This study showed significant diversity in the responses of the tested fungal strains as a function of medium aw. The growth response of Penicillium bialowiezense and Sporendonema casei was binary, with no clear decrease of growth rate until the growth limit, when the aw was reduced. For the strains of Bisifusarium domesticum, Mucor circinelloides and Penicillium camemberti, a decrease of aw had the same impact on radial growth rate regardless of the aw belonging to their growth range. For the strains of Aspergillus flavus, Cladosporium herbarum, Geotrichum candidum, Mucor lanceolatus, Penicillium expansum, Penicillium fuscoglaucum, Penicillium nalgiovense, Paecilomyces niveus, Penicillium roqueforti, Penicillium solitum and Scopulariopsis asperula, the impact of a decrease in aw was more pronounced at high aw than at low aw. A mathematical model was suggested to describe this impact on the radial growth rate. For all tested species, radial growth was more sensitive to NaCl than glycerol. The ionic strength of NaCl mainly explains the difference in the effects of the two solutes.

Modelling the thermal inactivation of spores from different phylogenetic groups of Bacillus cereus.

The objective of this work is to match available phylogenetic information for Bacillus cereus strains with published thermal resistance parameters (D90°C, z) and to use this information to develop refined inactivation models for B. cereus sensu lato. To do so, the thermal resistance parameters were retrieved for 57 strains of B. cereus that could be assigned to a phylogenetic group. This information was used to build specific distributions for D90°C and z for the different phylogenetic groups of B. cereus to build refined thermal inactivation models for B. cereus. For validation purposes, thermal parameters were also retrieved for additional strains of unknown groups, but which had been classified as psychrotrophic or mesophilic. Monte Carlo simulations were first performed assuming that the model parameters D90°C and z are independent. However, based on the observation that combinations of very high D90°C and high z-values were not reported, an alternative Monte Carlo simulation set was explored for the phylogenetic Groups with very high z-values (i.e.i.e. Groups IV and VI). With both simulation sets, the predicted lower and upper limits of the D-values are close to the lowest and highest D-values reported in two previous meta-analysis studies. However, a better correspondence between the predicted and observed limits is obtained when using the alternative simulation set.

The effect of pH on the growth rate of Bacillus cereus sensu lato: Quantifying strain variability and modelling the combined effects of temperature and pH.

In this study, the effect of pH, alone or in combination with temperature, on the maximum growth rate (µmax) of B. cereus sensu lato was investigated. In phase 1, the effect of pH at 30 °C was studied for 16 mesophilic strains and 2 psychrotrophic strains of Bacillus cereus sensu lato. The µmax vs. pH relationship was found to show a similar pattern for all the strains. Several pH models from literature were evaluated and the best performing 'growth rate vs. pH' model selected. A stochastic model was then developed to predict the maximum specific growth rate of mesophilic B. cereus at 30 °C as a function of pH, the intra-species variability being incorporated via considering the model parameters (e.g. pHmin) randomly distributed. The predicted maximum specific growth rates were acceptably close to independent published data. In phase 2, the combined effects of temperature and pH were studied. Growth rates were also generated at 15, 20 and 40 °C for a selection of strains and the pH model was fitted at each temperature. Interestingly, the results showed that the estimates for the pHmin parameter for mesophilic strains were lower at 20-30 °C than near the optimum temperature (40 °C), suggesting that experiments for the determination of this parameter should be conducted at lower-than-optimum temperatures. New equations were proposed for the relationship between temperature and the minimum pH-values, which were also consistent with the experimental growth boundaries. The parameters defining this equation quantify the minimum temperature for growth observed experimentally, the temperature of maximum enzyme stability and the maximum temperature for growth. Deviations from the Gamma hypothesis (multiplicative effects of environmental factors on the maximum specific growth rate) were observed near the growth limits, especially at 40 °C. To improve model performance, two approaches, one based on a minimum pH-term (doi: https://doi.org/10.3389/fmicb.2019.01510) and one based on an interaction term (doi: http://dx.doi.org/10.1016/S0168-1605(01)00640-7) were evaluated.

A stochastic approach for modelling the effects of temperature on the growth rate of Bacillus cereus sensu lato.

A stochastic model that predicts the maximum specific growth rate (µmax) of Bacillus cereus sensu lato as a function of temperature was developed. The model integrates the intra-species variability by incorporating distributions of cardinal parameters (Tmin, Topt, Tmax) in the model. Growth rate data were generated for 22 strains, covering 5 major phylogenetic groups of B. cereus, and their cardinal temperatures identified. Published growth rate data were also incorporated in the model fitting, resulting in a set of 33 strains. Based on their cardinal temperatures, we identified clusters of Bacillus cereus strains that show similar response to temperature and these clusters were considered separately in the stochastic model. Interestingly, the µopt values for psychrotrophic strains were found to be significantly lower than those obtained for mesophilic strains. The model developed within this work takes into account some correlations existing between parameters (µopt, Tmin, Topt, Tmax). In particular, the relationship highlighted between the b-slope of the Ratkowsky model and Tmin (doi: https://doi.org/10.3389/fmicb.2017.01890) was adapted to the case of the popular Cardinal Temperature Model. This resulted in a reduced model in which µopt is replaced by a function of Tmin, Topt and 2 strain-independent parameters. A correlation between the Tmin parameter and the experimental minimal growth temperature was also highlighted and integrated in the model for improved predictions near the temperature growth limits. Compared to the classical approach, the model developed in this study leads to improved predictions for temperatures around Tmin and more realistic tails for the predicted distributions of µmax. It can be useful for describing the variability of the Bacillus cereus Group in Quantitative Microbial Risk Assessment (QMRA). An example of application of the stochastic model to Reconstituted Infant Formulae (RIF) was proposed.

Modelling the effect of oxygen concentration on bacterial growth rates.

Predicting the microbial safety of food products stored in modified atmosphere packaging implies taking into account the effect of oxygen reduction on microbial growth. According to their respiratory-type, the micro-organisms are not impacted similarly by the oxygen concentration. The aim of this article was to quantify and model the oxygen effect on the growth rates of 5 bacterial species: Listeria monocytogenes and Bacillus weihenstephanensis (facultative anaerobic), Pseudomonas fluorescens (strict aerobic), Clostridium perfringens and Clostridium sporogenes (strict anaerobic). The results showed the oxygen concentration doesn't modify the behavior of both facultative anaerobic strains. The growth rate of P. fluorescens decreased with the oxygen concentration, but the effect is only noticeable when the oxygen concentration fell below 3% in the gaseous phase. Conversely, the oxygen acted as a growth inhibitor for both Clostridium species. But total inhibition is reached only for 3.26% and 6.61% respectively for C. sporogenes and C. perfringens. Two models have been fitted for both respiratory-types, the first is the Monod model considering oxygen as a substrate for growth, and the second is the classic inhibitory model based on minimal inhibitory concentration.

Modeling carbon dioxide effect in a controlled atmosphere and its interactions with temperature and pH on the growth of L. monocytogenes and P. fluorescens.

The effect of carbon dioxide, temperature, and pH on growth of Listeria monocytogenes and Pseudomonas fluorescens was studied, following a protocol to monitor microbial growth under a constant gas composition. In this way, the CO2 dissolution didn't modify the partial pressures in the gas phase. Growth curves were acquired at different temperatures (8, 12, 22 and 37 °C), pH (5.5 and 7) and CO2 concentration in the gas phase (0, 20, 40, 60, 80, 100% of the atmospheric pressure, and over 1 bar). These three factors greatly influenced the growth rate of L. monocytogenes and P. fluorescens, and significant interactions have been observed between the carbon dioxide and the temperature effects. Results showed no significant effect of the CO2 concentration at 37 °C, which may be attributed to low CO2 solubility at high temperature. An inhibitory effect of CO2 appeared at lower temperatures (8 and 12 °C). Regardless of the temperature, the gaseous CO2 is sparingly soluble at acid pH. However, the CO2 inhibition was not significantly different between pH 5.5 and pH 7. Considering the pKa of the carbonic acid, these results showed the dissolved carbon under HCO3- form didn't affect the bacterial inhibition. Finally, a global model was proposed to estimate the growth rate vs. CO2 concentration in the aqueous phase. This dissolved concentration is calculated according to the physical equations related to the CO2 equilibriums, involving temperature and pH interactions. This developed model is a new tool available to manage the food safety of MAP.

Design of challenge testing experiments to assess the variability of Listeria monocytogenes growth in foods.

The assessment of the evolution of micro-organisms naturally contaminating food must take into account the variability of biological factors, food characteristics and storage conditions. A research project involving eight French laboratories was conducted to quantify the variability of growth parameters of Listeria monocytogenes obtained by challenge testing in five food products. The residual variability corresponded to a coefficient of variation (CV) of approximately 20% for the growth rate (µ(max)) and 130% for the parameter K = µ(max) × lag. The between-batch and between-manufacturer variability of µ(max) was very dependent on the food tested and mean CV of approximately 20 and 35% were observed for these two sources of variability, respectively. The initial physiological state variability led to a CV of 100% for the parameter K. It appeared that repeating a limited number of three challenge tests with three different batches (or manufacturers) and with different initial physiological states seems often necessary and adequate to accurately assess the variability of the behavior of L. monocytogenes in a specific food produced by a given manufacturer (or for a more general food designation).

Modelling the influence of single acid and mixture on bacterial growth.

Depending on environmental factors, the prediction of bacterial growth is made difficult by the complexity of foodstuff. Although the influence of temperature, pH, and water activity are usually taken into account, models have to be completed with the influence of acid mixture. Nine strains of Listeria spp., four Salmonella spp., one Staphylococcus aureus, one Escherichia coli, and Listeria innocua ATCC 33090 were used for this study to extend model proposed by [Le Marc, Y., Huchet, V., Bourgeois, C., Guyonnet, J., Mafart, P., Thuault, D., 2002. Modelling the growth kinetics of Listeria as a function of temperature, pH and organic acid concentration. International Journal of Food Microbiology 73, 219-237]. Derived from data of [Houtsma, P.C., Kusters, B.J., De Wit, J.C., Rombouts, F.M., Zwietering, M.H., 1994. Modelling growth rates of Listeria innocua as a function of lactate concentration. International Journal of Food Microbiology 24, 113-123] and our own data, the extended model described accurately different effects of addition of acid salts in the medium (decrease of water activity and pH, variation of undissociated weak acid form, and variation of synergetic effect between environmental factors). This previous model was implemented to describe the observed variability of behaviour of the different studied strains. alpha reflected the general behaviour of species (sensitiveness to low or high undissociated acid concentration), and MIC(U) reflected the various resistances of strains. From this simple model, a new model was built for describing the effects of concentrations of several mixed acids on bacterial growth rates. Simulations of growth were carried out from three acids mixtures by inputting parameter estimates previously obtained. Despite a very variable effect of investigated acids on growth, the new model yielded fair predictions.