Heat resistance of five spoilage microorganisms in a carbonated broth.

Despite their acidic pH, carbonated beverages can be contaminated by spoilage microorganisms. Thermal treatments, before and/or after carbonation, are usually applied to prevent the growth of these microorganisms. However, the impact of CO2 on the heat resistance of spoilage microorganisms has never been studied. A better understanding of the combined impact of CO2 and pH on the heat resistance of spoilage microorganisms commonly found in carbonated beverages might allow to optimize thermal treatment. Five microorganisms were selected for this study: Alicyclobacillus acidoterrestris (spores), Aspergillus niger (spores), Byssochlamys fulva (spores), Saccharomyces cerevisiae (vegetative cells), and Zygosaccharomyces parabailii (vegetative cells). A method was developed to assess the impact of heat treatments in carbonated media on microbial resistance. The heat resistances of the five studied species are coherent with the literature, when data were available. However, neither the dissolved CO2 concentration (from 0 to 7 g/L), nor the pH (from 2.8 to 4.1) have an impact on the heat resistance of the selected microorganisms, except for As. niger, for which the presence of dissolved CO2 reduced the heat resistance. This study improved our knowledge about the heat resistance of some spoilage microorganisms in presence of CO2.

Large-scale multivariate dataset on the characterization of microbiota diversity, microbial growth dynamics, metabolic spoilage volatilome and sensorial profiles of two industrially produced meat products subjected to changes in lactate concentration and packaging atmosphere.

Data in this article provide detailed information on the diversity of bacterial communities present on 576 samples of raw pork or poultry sausages produced industrially in 2017. Bacterial growth dynamics and diversity were monitored throughout the refrigerated storage period to estimate the impact of packaging atmosphere and the use of potassium lactate as chemical preservative. The data include several types of analysis aiming at providing a comprehensive microbial ecology of spoilage during storage and how the process parameters do influence this phenomenon. The analysis includes: the gas content in packaging, pH, chromametric measurements, plate counts (total mesophilic aerobic flora and lactic acid bacteria), sensorial properties of the products, meta-metabolomic quantification of volatile organic compounds and bacterial community metagenetic analysis. Bacterial diversity was monitored using two types of amplicon sequencing (16S rRNA and GyrB encoding genes) at different time points for the different conditions (576 samples for gyrB and 436 samples for 16S rDNA). Sequencing data were generated by using Illumina MiSeq. The sequencing data have been deposited in the bioproject PRJNA522361. Samples accession numbers vary from SAMN10964863 to SAMN10965438 for gyrB amplicon and from SAMN10970131 to SAMN10970566 for 16S.

Convergence of Bigelow and Arrhenius models over a wide range of heating temperatures.

The heat resistance of the bacterial spores of Moorella thermoacetica, Clostridium sporogenes, Geobacillus stearothermophilus and Bacillus coagulans was determined over a wide range of temperatures using the capillary method and thermoresistometer Mastia. The results showed that the two experimental methods gave similar heat resistance values excepted for Geobacillus stearothermophilus. The effect of temperature on thermal resistance was evaluated using the Arrhenius and Bigelow models. The fit of the heat sensitivity parameters of the Arrhenius and Bigelow models on the heat resistance parameter values obtained over a wide temperature range was equally good. Despite the apparent mathematical incompatibility of the two equations, it is recognized that they yield the same goodness of fit. This paper finds a mathematical reason for this convergence and explains why inside a temperature range of at least 100 °C, no significant difference in the quality of fit between these two models can be found.

Dispersed phase volume fraction, weak acids and Tween 80 in a model emulsion: Effect on the germination and growth of Bacillus weihenstephanensis KBAB4 spores.

In foodstuffs, physico-chemical interactions and/or physical constraints between spores, inhibitors and food components may exist. Thus, the objective of this study was to investigate such interactions using a model emulsion as a microbial medium in order to improve bacterial spore control with better knowledge of the interactions in the formulation. Emulsions were prepared with hexadecane mixed with nutrient broth using sonication and were stabilized by Tween 80 and Span 80. The hexadecane ratio was either 35% (v/v) or 50% (v/v) and each emulsion was studied in the presence of organic acid (acetic, lactic or hexanoic) at two pH levels (5.5 and 6). Self-diffusion coefficients of emulsion components and the organic acids were measured by Pulsed Field Gradient-Nuclear Magnetic Resonance (PFG-NMR). The inhibition effect on the spore germination and cell growth of Bacillus weihenstephanensis KBAB4 was characterized by the measure of the probability of growth using the most probable number methodology, and the measure of the time taken for the cells to germinate and grow using a single cell Bioscreen® method and using flow cytometry. The inhibition of spore germination and growth in the model emulsion depended on the dispersed phase volume fraction and the pH value. The effect of the dispersed phase volume fraction was due to a combination of (i) the lipophilicity of the biocide, hexanoic acid, that may have had an impact on the distribution of organic acid between hexadecane and the aqueous phases and (ii) the antimicrobial activity of the emulsifier Tween 80 detected at the acidic pH value. The interface phenomena seemed to have a major influence. Future work will focus on the exploration of these phenomena at the interface.

mRNA biomarkers selection based on Partial Least Square algorithm in order to further predict Bacillus weihenstephanensis acid resistance.

In order to integrate omics data to quantitative microbiological risk assessment in foods, gene expressions may serve as bacterial behaviour biomarkers. In this study an integrative approach encompassing predictive modelling and mRNAs quantifications, was followed to select molecular biomarkers to further predict the acid resistance of Bacillus weihenstephanensis. A multivariate analysis was performed to correlate the acid bacterial resistance and the gene expression of vegetative cells with or without exposure to stressing conditions. This mathematical method provides the advantage to take gene expressions and their interactions into account. The use of the Partial Least Squares algorithm allowed the selection of nine genes as acid resistance biomarkers among thirty targeted genes. According to their involvement in the general acid stress response of Bacillus, these genes were assigned to three different biological modules namely, metabolic rearrangements, general stress response and oxidative stress response. The oxidative stress response appeared as the major activated biological module in B. weihenstephanensis cells submitted to acid stress conditions. Furthermore, as a firstly described model, the developed concept showed promising results to further be used to predict bacterial resistance using gene expression. Thus, this study underlines the possibility to integrate the bacterial physiology state, using omics biomarkers, into bacterial behaviour modelling and provide mechanistic understanding in acid bacterial resistance mechanisms.

Bacillus cereus cell response upon exposure to acid environment: toward the identification of potential biomarkers.

Microorganisms are able to adapt to different environments and evolve rapidly, allowing them to cope with their new environments. Such adaptive response and associated protections toward other lethal stresses, is a crucial survival strategy for a wide spectrum of microorganisms, including food spoilage bacteria, pathogens, and organisms used in functional food applications. The growing demand for minimal processed food yields to an increasing use of combination of hurdles or mild preservation factors in the food industry. A commonly used hurdle is low pH which allows the decrease in bacterial growth rate but also the inactivation of pathogens or spoilage microorganisms. Bacillus cereus is a well-known food-borne pathogen leading to economical and safety issues in food industry. Because survival mechanisms implemented will allow bacteria to cope with environmental changes, it is important to provide understanding of B. cereus stress response. Thus this review deals with the adaptive traits of B. cereus cells facing to acid stress conditions. The acid stress response of B. cereus could be divided into four groups (i) general stress response (ii) pH homeostasis, (iii) metabolic modifications and alkali production and (iv) secondary oxidative stress response. This current knowledge may be useful to understand how B. cereus cells may cope to acid environment such as encountered in food products and thus to find some molecular biomarkers of the bacterial behavior. These biomarkers could be furthermore used to develop new microbial behavior prediction tools which can provide insights into underlying molecular physiological states which govern the behavior of microorganisms and thus opening the avenue toward the detection of stress adaptive behavior at an early stage and the control of stress-induced resistance throughout the food chain.

An integrative approach to identify Bacillus weihenstephanensis resistance biomarkers using gene expression quantification throughout acid inactivation.

The aim of this study was to define an integrative approach to identify resistance biomarkers using gene expression quantification and mathematical modelling. Mid-exponentially growing cells were transferred into acid conditions (BHI, pH 4.6) to obtain inactivation kinetics, performed in triplicate. The inactivation curve was fitted with a mixed Weibull model. This model allowed to differentiate two subpopulations with various acid resistances among the initial population. In parallel, differential gene expression was quantified by RT-qPCR. While narL was down-regulated throughout acid inactivation, sigB and katA were up-regulated. sigB expression up-regulation peak was correlated to the less resistant subpopulation when katA up-regulation, was correlated to the more resistant subpopulation. Moreover, differences in population structure were highlighted between each replicate. The higher proportion of the more resistant subpopulation was linked to a higher katA gene expression. These results suggest that sigB and katA might be used as different types of biomarkers, for instance to track moderate and high acid-resistance, respectively. The use of this approach combining RT-qPCR and predictive modelling to track cellular biomarker variations appears as an interesting tool to take into account physiological cell responses into mathematical modelling, allowing an accurate prediction of microbial behaviour.