Sophie Jeanson

Spatial distribution of bacterial colonies in a model cheese.

ABSTRACT In most ripened cheeses, bacteria are responsible for the ripening process. Immobilized in the cheese matrix, they grow as colonies. Therefore, their distribution as well as the distance between them are of major importance for ripening steps since metabolites diffuse within the cheese matrix. No data are available to date about the spatial distribution of bacterial colonies in cheese. This is the first study to model the distribution of bacterial colonies in a food-type matrix using nondestructive techniques. We compared (i) the mean theoretical three-dimensional (3D) distances between colonies calculated on the basis of inoculation levels and considering colony distribution to be random and (ii) experimental measurements using confocal microscopy photographs of fluorescent colonies of a Lactococcus lactis strain producing green fluorescent protein (GFP) inoculated, at different levels, into a model cheese made by ultrafiltration (UF). Enumerations showed that the final numbers of cells were identical whatever the inoculation level (104 to 107 CFU/g). Bacterial colonies were shown to be randomly distributed, fitting Poissons model. The initial inoculation level strongly influenced the mean distances between colonies (from 25 μm to 250 μm) and also their mean diameters. The lower the inoculation level, the larger the colonies were and the further away from each other. Multiplying the inoculation level by 50 multiplied the interfacial area of exchange with the cheese matrix by 7 for the same cell biomass. We finally suggested that final cell numbers should be discussed together with inoculation levels to take into account the distribution and, consequently, the interfacial area of colonies, which can have a significant influence on the cheese-ripening process on a microscopic scale.

Dynamic analysis of the Lactococcus lactis transcriptome in cheeses made from milk concentrated by ultrafiltration reveals multiple strategies of adaptation to stresses.

ABSTRACT Lactococcus lactis is used extensively for the production of various cheeses. At every stage of cheese fabrication, L. lactis has to face several stress-generating conditions that result from its own modification of the environment as well as externally imposed conditions. We present here the first in situ global gene expression profile of L. lactis in cheeses made from milk concentrated by ultrafiltration (UF-cheeses), a key economical cheese model. The transcriptomic response of L. lactis was analyzed directly in a cheese matrix, starting from as early as 2 h and continuing for 7 days. The growth of L. lactis stopped after 24 h, but metabolic activity was maintained for 7 days. Conservation of its viability relied on an efficient proteolytic activity measured by an increasing, quantified number of free amino acids in the absence of cell lysis. Extensive downregulation of genes under CodY repression was found at day 7. L. lactis developed multiple strategies of adaptation to stressful modifications of the cheese matrix. In particular, expression of genes involved in acidic- and oxidative-stress responses was induced. L. lactis underwent unexpected carbon limitation characterized by an upregulation of genes involved in carbon starvation, principally due to the release of the CcpA control. We report for the first time that in spite of only moderately stressful conditions, lactococci phage is repressed under UF-cheese conditions.

Milk acidification by Lactococcus lactis is improved by decreasing the level of dissolved oxygen rather than decreasing redox potential in the milk prior to inoculation

Although redox potential is very rarely taken into account in food fermentation it could be as influential as pH on bacterial activities. Lactococcus lactis is already known to exhibit a powerful reducing activity in milk but its reduction activity was shown to occur prior to its acidification activity with a potential interaction between these two lactococcal activities. Therefore, acidification lag-type phase could be shortened by decreasing the redox potential of milk before inoculation. As the redox potential is highly dependent on the dissolved oxygen level, our objective was to study their separate and combined influences on acidification and growth kinetics of pure L. lactis strains in milk. Results showed that high level of dissolved oxygen is significantly more influential on growth, and even more on acidification kinetics, than initial decreased redox potential of milk. Reduction of milk was drastic and mostly due to bacterial activity. The redox potential of milk only dropped when dissolved oxygen was entirely consumed. When there was no dissolved oxygen from the beginning, L. lactis immediately decreased the redox potential of milk and acidified afterwards. When the level of dissolved oxygen was initially high, acidification and reduction of milk occurred at the same time. Acidification kinetics was then biphasic with a slower rate during the aerobic stage and a faster rate during the anaerobic stage. The seven strains tested demonstrated diversity in both their acidification kinetics and their adaptation to high level of dissolved oxygen, independent of their growth kinetics. To conclude, we have shown that the level of dissolved oxygen in milk has a dramatic influence on acidification kinetics and could be used to control acidification kinetics in dairy industries.

First mass spectrometry metabolic fingerprinting of bacterial metabolism in a model cheese.

Metabolic fingerprinting is an untargeted approach which has not yet been undertaken to investigate cheese. This study is a proof of concept, concerning the ability of mass spectrometry (MS) metabolic fingerprinting to investigate modifications induced by bacterial metabolism in cheese over time. An ultrafiltrated milk concentrate was used to manufacture model cheeses inoculated with Lactococcus lactis LD61. Metabolic fingerprints were acquired after 0, 8 and 48h from two different fractions of the metabolome: the water-soluble fraction using liquid chromatography-high resolution-MS and a volatile fraction using gas chromatography-MS. Metabolic fingerprints differed significantly over time. Forty-five metabolites were identified, including well-known cheese metabolites, such as 12 amino acids and 25 volatile metabolites, and less studied ones, such as four vitamins, uric acid, creatine and l-carnitine. These results showed the relevance of cheese MS fingerprinting to generate new findings and to detect even slight differences between two conditions.

First assessment of diffusion coefficients in model cheese by fluorescence recovery after photobleaching (FRAP).

Mass transfer of solutes like salt, moisture and metabolites, is very important for the final quality of cheese, through the control of the brining and ripening processes. Numerous studies have reported salt and water transfer properties in cheese, but few have dealt with other solutes. Moreover, most diffusion coefficients have been obtained by macroscopic and destructive methods. We developed the fluorescence recovery after photobleaching (FRAP) technique on a confocal microscope to measure in situ and at the microscopic scale diffusion properties inside cheese. A model matrix based on ultrafiltrated milk was used. FITC-dextran molecules were chosen as models of migrant solutes. Diffusion coefficients were estimated with a modelling approach which takes into account diffusion during the bleach phase. The FITC-dextrans (4 and 20 kDa) were able to migrate in the proteinic network, but their mobility was 2.2-3 times lower than in water, depending on their size.

Bacterial Colonies in Solid Media and Foods: A Review on Their Growth and Interactions with the Micro-Environment

Bacteria, either indigenous or added, are immobilized in solid foods where they grow as colonies. Since the 80s, relatively few research groups have explored the implications of bacteria growing as colonies and mostly focused on pathogens in large colonies on agar/gelatine media. It is only recently that high resolution imaging techniques and biophysical characterization techniques increased the understanding of the growth of bacterial colonies, for different sizes of colonies, at the microscopic level and even down to the molecular level. This review covers the studies on bacterial colony growth in agar or gelatine media mimicking the food environment and in model cheese. The following conclusions have been brought to light. Firstly, under unfavorable conditions, mimicking food conditions, the immobilization of bacteria always constrains their growth in comparison with planktonic growth and increases the sensibility of bacteria to environmental stresses. Secondly, the spatial distribution describes both the distance between colonies and the size of the colonies as a function of the initial level of population. By studying the literature, we concluded that there systematically exists a threshold that distinguishes micro-colonies (radius < 100–200 μm) from macro-colonies (radius >200 μm). Micro-colonies growth resembles planktonic growth and no pH microgradients could be observed. Macro-colonies growth is slower than planktonic growth and pH microgradients could be observed in and around them due to diffusion limitations which occur around, but also inside the macro-colonies. Diffusion limitations of milk proteins have been demonstrated in a model cheese around and in the bacterial colonies. In conclusion, the impact of immobilization is predominant for macro-colonies in comparison with micro-colonies. However, the interaction between the colonies and the food matrix itself remains to be further investigated at the microscopic scale.

The efficacy of nisin can drastically vary when produced in situ in model cheeses

Nisin, a bacteriocin produced by strains of Lactococcus lactis, has a broad inhibitory effect against Gram-positive bacteria. This study investigated the efficacy of nisin Z against Lactobacillus sakei when produced by a nisin-producing strain L. lactis in model cheeses manufactured with ultrafiltrated milk. These cheeses, containing 0, 4 or 10% of gelatin in their dry matter, were inoculated with both strains. Measurement of Lb. sakei loss of viability was an indirect indicator of nisin in situ efficacy. After 24 h, the loss of viability of Lb. sakei was from 0.73 ± 0.14 to 3.30 ± 0.60 log(10) cfu g(-1) in the cheeses with 0 and 10% of gelatin, respectively, indicating a better in situ efficacy of nisin when gelatin was incorporated. However, the concentration of nisin produced by Lactococcus was similar (3.5 μg g(-1)) in all model cheeses when measured using an enzyme-linked immune sorbent assay (ELISA). The growth of Lactococcus was slightly improved when gelatin was incorporated, leading to a higher lactate concentration, which is one of the factors explaining the increased nisin efficacy. These results reinforced previous observations that prediction of nisin efficacy in complex food systems remains difficult.

Nisin quantification by ELISA allows the modeling of its apparent diffusion coefficient in model cheeses.

The diffusion of small solutes in cheese is of key importance for most enzymatic reactions involved in the ripening process. However, only a limited amount of data is available on salt diffusion and practically none on peptide diffusion. Nisin, a bacteriocin peptide, migrated in model cheeses made from ultrafiltered (UF) retentate. A profile concentration device and an enzyme-linked immunosorbent assay (ELISA), specifically developed for nisin quantification in cheese, were used to model the apparent diffusion coefficients for nisin according to Ficks law. This average coefficient was 49.5 μm(2)/s in UF cheese (n = 2). When 10% gelatin was added to the retentate, this value decreased to 34.4 μm(2)/s (n = 2). The two cheeses differed in their macrostructure (rheology) and microstructure (confocal microscopy). This study provides the first apparent diffusion coefficients for a peptide in cheese and supports the hypothesis that composition and structure influence the diffusion of small solutes such as peptides.

Contribution of Lactococcus lactis reducing properties to the downregulation of a major virulence regulator in Staphylococcus aureus, the agr system

ABSTRACT Staphylococcus aureus is a major cause of food poisoning outbreaks associated with dairy products, because of the ingestion of preformed enterotoxins. The biocontrol of S. aureus using lactic acid bacteria (LAB) offers a promising opportunity to fight this pathogen while respecting the product ecosystem. We had previously established the ability of Lactococcus lactis, a lactic acid bacterium widely used in the dairy industry, to downregulate a major staphylococcal virulence regulator, the accessory gene regulator (agr) system, and, as a consequence, agr-controlled enterotoxins. In the present paper, we have shown that the oxygen-independent reducing properties of L. lactis contribute to agr downregulation. Neutralizing lactococcal reduction by adding potassium ferricyanide or maintaining the oxygen pressure constant at 50% released agr downregulation in the presence of L. lactis. This downregulation still occurred in an S. aureus srrA mutant, indicating that the staphylococcal respiratory response regulator SrrAB was not the only component in the signaling pathway. Therefore, this study clearly demonstrates the ability of L. lactis reducing properties to interfere with the expression of S. aureus virulence, thus highlighting this general property of LAB as a lever to control the virulence expression of this major pathogen in a food context and beyond.

Colonial vs. planktonic type of growth: mathematical modeling of microbial dynamics on surfaces and in liquid, semi-liquid and solid foods.

Predictive models are mathematical expressions that describe the growth, survival, inactivation, or biochemical processes of foodborne bacteria. During processing of contaminated raw materials and food preparation, bacteria are entrapped into the food residues, potentially transferred to the equipment surfaces (abiotic or inert surfaces) or cross-contaminate other foods (biotic surfaces). Growth of bacterial cells can either occur planktonically in liquid or immobilized as colonies. Colonies are on the surface or confined in the interior (submerged colonies) of structured foods. For low initial levels of bacterial population leading to large colonies, the immobilized growth differs from planktonic growth due to physical constrains and to diffusion limitations within the structured foods. Indeed, cells in colonies experience substrate starvation and/or stresses from the accumulation of toxic metabolites such as lactic acid. Furthermore, the micro-architecture of foods also influences the rate and extent of growth. The micro-architecture is determined by (i) the non-aqueous phase with the distribution and size of oil particles and the pore size of the network when proteins or gelling agent are solidified, and by (ii) the available aqueous phase within which bacteria may swarm or swim. As a consequence, the micro-environment of bacterial cells when they grow in colonies might greatly differs from that when they grow planktonically. The broth-based data used for modeling (lag time and generation time, the growth rate, and population level) are poorly transferable to solid foods. It may lead to an over-estimation or under-estimation of the predicted population compared to the observed population in food. If the growth prediction concerns pathogen bacteria, it is a major importance for the safety of foods to improve the knowledge on immobilized growth. In this review, the different types of models are presented taking into account the stochastic behavior of single cells in the growth of a bacterial population. Finally, the recent advances in the rules controlling different modes of growth, as well as the methodological approaches for monitoring and modeling such growth are detailed.