ADRIA Développement

Changes with time of a population of Bacillus weihenstephanensis KBAB4 and Bacillus licheniformis AD978 dormant spores into germinated spores and vegetative cells were followed by flow cytometry, at pH ranges of 4.7 to 7.4 and temperatures of 10°C to 37°C for B. weihenstephanensis and 18°C to 59°C for B. licheniformis Incubation conditions lower than optimal temperatures or pH led to lower proportions of dormant spores able to germinate and extended time of germination, a lower proportion of germinated spores able to outgrow, an extension of their times of outgrowth, and an increase of the heterogeneity of spore outgrowth time. A model based on the strain growth limits was proposed to quantify the impact of incubation temperature and pH on the passage through each physiological stage. The heat treatment temperature or time acted independently on spore recovery. Indeed, a treatment at 85°C for 12 min or at 95°C for 2 min did not have the same impact on spore germination and outgrowth kinetics of B. weihenstephanensis despite the fact that they both led to a 10-fold reduction of the population. Moreover, acidic sporulation pH increased the time of outgrowth 1.2-fold and lowered the proportion of spores able to germinate and outgrow 1.4-fold. Interestingly, we showed by proteomic analysis that some proteins involved in germination and outgrowth were detected at a lower abundance in spores produced at pH 5.5 than in those produced at pH 7.0, maybe at the origin of germination and outgrowth behavior of spores produced at suboptimal pH.IMPORTANCE Sporulation and incubation conditions have an impact on the numbers of spores able to recover after exposure to sublethal heat treatment. Using flow cytometry, we were able to follow at a single-cell level the changes in the physiological states of heat-stressed spores of Bacillus spp. and to discriminate between dormant spores, germinated spores, and outgrowing vegetative cells. We developed original mathematical models that describe (i) the changes with time of the proportion of cells in their different states during germination and outgrowth and (ii) the influence of temperature and pH on the kinetics of spore recovery using the growth limits of the tested strains as model parameters. We think that these models better predict spore recovery after a sublethal heat treatment, a common situation in food processing and a concern for food preservation and safety.

Data Mining aims at extracting maximum of knowledge from huge databases. It is realized by an automatic process or by data visual exploration with interactive tools. Automatic data mining extracts all the patterns which match a set of metrics. The limit of such algorithms is the amount of extracted data which can be larger than the initial data volume. In this article, we focus on association rules extraction with Apriori algorithm. After the description of a characterization model of a set of association rules, we propose to explore the results of a Data Mining algorithm with an interactive visual tool. There are two advantages. First it will visualize the results of the algorithms from different points of view (metrics, rules attributes...). Then it allows us to select easily inside large set of rules the most relevant ones.