Evaluation of Enzymatic Cleaning on Food Processing Installations and Food Products Bacterial Microflora.

Biofilms are a permanent source of contamination in food industries and could harbor various types of microorganisms, such as spoiling bacteria. New strategies, such as enzymatic cleaning, have been proposed to eradicate them. The purpose of this study was to evaluate the impact of enzymatic cleaning on the microbial flora of installations in a processing food industry and of the final food product throughout its shelf life. A total of 189 samples were analyzed by classical microbiology and 16S rDNA metagenetics, including surface samples, cleaning-in-place (CIP) systems, and food products (at D0, Dend of the shelf life, and Dend of the shelf life +7 days). Some surfaces were highly contaminated with spoiling bacteria during conventional cleaning while the concentration of the total flora decreased during enzymatic cleaning. Although the closed circuits were cleaned with conventional cleaning before enzymatic cleaning, there was a significant release of microorganisms from some parts of the installations during enzymatic treatment. A significant difference in the total flora in the food products at the beginning of the shelf life was observed during enzymatic cleaning compared to the conventional cleaning, with a reduction of up to 2 log CFU/g. Metagenetic analysis of the food samples at the end of their shelf life showed significant differences in bacterial flora between conventional and enzymatic cleaning, with a decrease of spoiling bacteria (Leuconostoc sp.). Enzymatic cleaning has improved the hygiene of the food processing instillations and the microbial quality of the food throughout the shelf life. Although enzymatic cleaning is not yet commonly used in the food industry, it should be considered in combination with conventional sanitizing methods to improve plant hygiene.

Modeling the Growth and Interaction Between Brochothrix thermosphacta, Pseudomonas spp., and Leuconostoc gelidum in Minced Pork Samples.

The aim of this study was to obtain the growth parameters of specific spoilage micro-organisms previously isolated in minced pork (MP) samples and to develop a three-spoilage species interaction model under different storage conditions. Naturally contaminated samples were used to validate this approach by considering the effect of the food microbiota. Three groups of bacteria were inoculated on irradiated samples, in mono- and in co-culture experiments (n = 1152): Brochothrix thermosphacta, Leuconostoc gelidum, and Pseudomonas spp. (Pseudomonas fluorescens and Pseudomonas fragi). Samples were stored in two food packaging [food wrap and modified atmosphere packaging (CO2 30%/O2 70%)] at three isothermal conditions (4, 8, and 12°C). Analysis was carried out by using both 16S rRNA gene amplicon sequencing and classical microbiology in order to estimate bacterial counts during the storage period. Growth parameters were obtained by fitting primary (Baranyi) and secondary (square root) models. The food packaging shows the highest impact on bacterial growth rates, which in turn have the strongest influence on the shelf life of food products. Based on these results, a three-spoilage species interaction model was developed by using the modified Jameson-effect model and the Lotka Volterra (prey-predator) model. The modified Jameson-effect model showed slightly better performances, with 40-86% out of the observed counts falling into the Acceptable Simulation Zone (ASZ). It only concerns 14-48% for the prey-predator approach. These results can be explained by the fact that the dynamics of experimental and validation datasets seems to follow a Jameson behavior. On the other hand, the Lotka Volterra model is based on complex interaction factors, which are included in highly variable intervals. More datasets are probably needed to obtained reliable factors, and so better model fittings, especially for three- or more-spoilage species interaction models. Further studies are also needed to better understand the interaction of spoilage bacteria between them and in the presence of natural microbiota.

Assessment of Spoilage Bacterial Communities in Food Wrap and Modified Atmospheres-Packed Minced Pork Meat Samples by 16S rDNA Metagenetic Analysis.

Although several studies have focused on the dynamics of bacterial food community, little is known about the variability of batch production and microbial changes that occur during storage. The aim of the study was to characterize the microbial spoilage community of minced pork meat samples, among different food production and storage, using both 16S rRNA gene sequencing and classical microbiology. Three batches of samples were obtained from four local Belgian facilities (A-D) and stored until shelf life under food wrap (FW) and modified atmosphere packaging (MAP, CO2 30%/O2 70%), at constant and dynamic temperature. Analysis of 288 samples were performed by 16S rRNA gene sequencing in combination with counts of psychrotrophic and lactic acid bacteria at 22°C. At the first day of storage, different psychrotrophic counts were observed between the four food companies (Kruskal-Wallist test, p-value < 0.05). Results shown that lowest microbial counts were observed at the first day for industries D and A (4.2 ± 0.4 and 5.6 ± 0.1 log CFU/g, respectively), whereas industries B and C showed the highest results (7.5 ± 0.4 and 7.2 ± 0.4 log CFU/g). At the end of the shelf life, psychrotrophic counts for all food companies was over 7.0 log CFU/g. With metagenetics, 48 OTUs were assigned. At the first day, the genus Photobacterium (86.7 and 19.9% for food industries A and C, respectively) and Pseudomonas (38.7 and 25.7% for food companies B and D, respectively) were dominant. During the storage, a total of 12 dominant genera (>5% in relative abundance) were identified in MAP and 7 in FW. Pseudomonas was more present in FW and this genus was potentially replaced by Brochothrix in MAP (two-sided Welch's t-test, p-value < 0.05). Also, a high Bray-Curtis dissimilarity in genus relative abundance was observed between food companies and batches. Although the bacteria consistently dominated the microbiota in our samples are known, results indicated that bacterial diversity needs to be addressed on the level of food companies, batches variation and food storage conditions. Present data illustrate that the combined approach provides complementary results on microbial dynamics in minced pork meat samples, considering batches and packaging variations.

The use of 16S rRNA gene metagenetic monitoring of refrigerated food products for understanding the kinetics of microbial subpopulations at different storage temperatures: the example of white pudding.

In order to control food losses and wastage, monitoring the microbial diversity of food products, during processing and storage is important, as studies have highlighted the metabolic activities of some microorganisms which can lead to spoilage. Knowledge of this diversity can be greatly improved by using a metagenetic approach based on high throughput 16S rRNA gene sequencing, which enables a much higher resolution than culture-based methods. Moreover, the Jameson effect, a phenomenon described by Jameson in 1962, is often used to classify bacterial strains within an ecosystem. According to this, we have studied the bacterial microbiota of Belgian white pudding during storage at different temperatures using culture-dependent and independent methods. The product was inoculated with a mix of dominant strains previously isolated from this foodstuff at the end of its shelf life (Carnobacterium maltaromaticum, Lactobacillus fuchuensis, Lactobacillus graminis, Lactobacillus oligofermentans, Lactococcus lactis, Leuconostoc mesenteroides, Raoultella terrigena and Serratia sp.). Daily during 16days, the absolute abundance of inoculated strain was monitored by combining total count on plate agar and metagenetic analysis. The results were confirmed by qPCR analysis. The growth of each species was modelled for each temperature conditions, representative of good or bad storage practices. These data allowed the bacterial strains subdivision into three classes based on criteria of growth parameters for the studied temperature: the "dominant", the "subdominant" and the "inhibited" bacterial species, according to their maximal concentration (Nmax, log CFU/g), growth rate (µmax, 1/h) and time to reach the stationary phase (TRSP, days). Thereby, depending on the storage conditions, these data have permitted to follow intrinsically the evolution of each strain on the bacterial ecosystem of Belgian white pudding. Interestingly, it has shown that the reliability of the Jameson effect can be discussed. For example, at 4°C when Lactococcus lactis and Serratia sp. stopped growth at day 12, at the same time Carnobacterium maltaromaticum reached its maximal concentration and entered its stationary phase. In opposition to this, it can be noticed that in the same condition, the "sub-dominant" organisms continued their growth independently of the "dominant" species behaviour. In this case, the Jameson effect was not illustrated. This pattern is described for all storage conditions with the same strain classifications. These results highlighted the importance of combining metagenetic analysis and classical methods, with modelling, to offer a new tool for studying the evolution of microorganisms present in perishable food within different environmental conditions.

Development of a quantitative microbial risk assessment for human salmonellosis through household consumption of fresh minced pork meat in Belgium.

A quantitative microbial risk assessment (QMRA) according to the Codex Alimentarius Principles is conducted to evaluate the risk of human salmonellosis through household consumption of fresh minced pork meat in Belgium. The quantitative exposure assessment is carried out by building a modular risk model, called the METZOON-model, which covers the pork production from farm to fork. In the METZOON-model, the food production pathway is split up in six consecutive modules: (1) primary production, (2) transport and lairage, (3) slaughterhouse, (4) postprocessing, (5) distribution and storage, and (6) preparation and consumption. All the modules are developed to resemble as closely as possible the Belgian situation, making use of the available national data. Several statistical refinements and improved modeling techniques are proposed. The model produces highly realistic results. The baseline predicted number of annual salmonellosis cases is 20,513 (SD 9061.45). The risk is estimated higher for the susceptible population (estimate 4.713 x 10(-5); SD 1.466 x 10(-5)) compared to the normal population (estimate 7.704 x 10(-6); SD 5.414 x 10(-6)) and is mainly due to undercooking and to a smaller extent to cross-contamination in the kitchen via cook's hands.