Spatial Distribution of Lactococcus lactis Colonies Modulates the Production of Major Metabolites during the Ripening of a Model Cheese

The rotation of primary starter culture mixtures results in batch-to-batch variations during Gouda cheese production

Industrial production of Gouda cheeses mostly relies on a rotated use of different mixed-strain lactic acid bacteria starter cultures to avoid phage infections. However, it is unknown how the application of these different starter culture mixtures affect the organoleptic properties of the final cheeses. Therefore, the present study assessed the impact of three different starter culture mixtures on the batch-to-batch variations among Gouda cheeses from 23 different batch productions in the same dairy company. Both the cores and rinds of all these cheeses were investigated after 36, 45, 75, and 100 weeks of ripening by metagenetics based on high-throughput full-length 16S rRNA gene sequencing accompanied with an amplicon sequence variant (ASV) approach as well as metabolite target analysis of non-volatile and volatile organic compounds. Up to 75 weeks of ripening, the acidifying Lactococcus cremoris and Lactococcus lactis were the most abundant bacterial species in the cheese cores. The relative abundance of Leuconostoc pseudomesenteroides was significantly different for each starter culture mixture. This impacted the concentrations of some key metabolites, such as acetoin produced from citrate, and the relative abundance of non-starter lactic acid bacteria (NSLAB). Cheeses with the least Leuc. pseudomesenteroides contained more NSLAB, such as Lacticaseibacillus paracasei that was taken over by Tetragenococcus halophilus and Loigolactobacillus rennini upon ripening time. Taken together, the results indicated a minor role of leuconostocs in aroma formation but a major impact on the growth of NSLAB. The relative abundance of T. halophilus (high) and Loil. rennini (low) increased with ripening time from rind to core. Two main ASV clusters of T. halophilus could be distinguished, which were differently correlated with some metabolites, both beneficial (regarding aroma formation) and undesirable ones (biogenic amines). A well-chosen T. halophilus strain could be a candidate adjunct culture for Gouda cheese production.

The effect of production parameters on the spatial distribution of bacterial cells in the sausage meat matrix

In this work, the effect of processing conditions created with common meat technology equipment, on the spatial distribution of a green fluorescent protein producing -Escherichia coli in sausage meat was evaluated using confocal fluorescence microscopy and expressed with the help of the dispersion index. The results indicated that the reduction in mean particle size by prolonged comminution improved the distribution of cells in the sausage meat. Furthermore, higher fat content seemed to favor a random distribution, although not significantly. Independent of the any variation of the sausage meat production parameters, Listeria monocytogenes was effectively controlled in fermented sausages, although a theoretically less homogenous distribution of the starter culture in the sausage meat, tended to improve the effect, however, insignificantly. An early onset of the quorum-sensing-driven bacteriocin production in poorly distributed larger colonies may have been the reason for this. No differences in the composition of the microbiome between sausages with poor and good distribution of the starter culture were observed.

Omics Approaches to Assess Flavor Development in Cheese

Cheese is characterized by a rich and complex microbiota that plays a vital role during both production and ripening, contributing significantly to the safety, quality, and sensory characteristics of the final product. In this context, it is vital to explore the microbiota composition and understand its dynamics and evolution during cheese manufacturing and ripening. Application of high-throughput DNA sequencing technologies have facilitated the more accurate identification of the cheese microbiome, detailed study of its potential functionality, and its contribution to the development of specific organoleptic properties. These technologies include amplicon sequencing, whole-metagenome shotgun sequencing, metatranscriptomics, and, most recently, metabolomics. In recent years, however, the application of multiple meta-omics approaches along with data integration analysis, which was enabled by advanced computational and bioinformatics tools, paved the way to better comprehension of the cheese ripening process, revealing significant associations between the cheese microbiota and metabolites, as well as their impact on cheese flavor and quality.

Predictive modeling of the early stages of semi-solid food ripening: Spatio-temporal dynamics in semi-solid casein matrices

A mechanistic, spatio-temporal model to predict early stage semi-solid food ripening, exemplary for semi-solid casein matrices, was created using software based on the finite element method (FEM). The model was refined and validated by experimental data obtained during 8 wk of ripening of a casein matrix that was inoculated by one single central injection of starter culture. The resulting spatio-temporal distributions of lactococci strains, lactose, lactic acid/lactate and pH allowed us to optimize a number of parameters of the predictive model. Using the optimized model, the agreement between simulation and experiment was found to be satisfactory, with the pH matching best. The predictive model unveiled that effective diffusion of substrate and metabolites were crucial for an eventual homogeneous distribution of the measured substances. Hence, while using the optimized parameters from the single injection model, an injection technology for starter culture to inoculate and ferment casein matrices homogeneously was developed by means of solving another optimization problem with respect to injection positions. The casein matrix inoculated by the proposed injection pattern (21 injections, distance = 19 mm) showed sufficient homogeneity (bacterial activity and pH distribution) after the early stages of ripening, demonstrating the potential of application of the injection technology for fermentation of casein-based foods e.g. cheese.

Function-Driven Design of Lactic Acid Bacteria Co-cultures to Produce New Fermented Food Associating Milk and Lupin

Designing bacterial co-cultures adapted to ferment mixes of vegetal and animal resources for food diversification and sustainability is becoming a challenge. Among bacteria used in food fermentation, lactic acid bacteria (LAB) are good candidates, as they are used as starter or adjunct in numerous fermented foods, where they allow preservation, enhanced digestibility, and improved flavor. We developed here a strategy to design LAB co-cultures able to ferment a new food made of bovine milk and lupin flour, consisting in: (i) in silico preselection of LAB species for targeted carbohydrate degradation; (ii) in vitro screening of 97 strains of the selected species for their ability to ferment carbohydrates and hydrolyze proteins from milk and lupin and clustering strains that displayed similar phenotypes; and (iii) assembling strains randomly sampled from clusters that showed complementary phenotypes. The designed co-cultures successfully expressed the targeted traits i.e., hydrolyzed proteins and degraded raffinose family oligosaccharides of lupin and lactose of milk in a large range of concentrations. They also reduced an off-flavor-generating volatile, hexanal, and produced various desirable flavor compounds. Most of the strains in co-cultures achieved higher cell counts than in monoculture, suggesting positive interactions. This work opens new avenues for the development of innovative fermented food products based on functionally complementary strains in the world-wide context of diet diversification.

Altering textural properties of fermented milk by using surface-engineered Lactococcus lactis

Lactic acid bacteria are widely used for the fermentation of dairy products. While bacterial acidification rates, proteolytic activity and the production of exopolysaccharides are known to influence textural properties of fermented milk products, little is known about the role of the microbial surface on microbe-matrix interactions in dairy products. To investigate how alterations of the bacterial cell surface affect fermented milk properties, 25 isogenic Lactococcus lactis strains that differed with respect to surface charge, hydrophobicity, cell chaining, cell-clumping, attachment to milk proteins, pili expression and EPS production were used to produce fermented milk. We show that overexpression of pili increases surface hydrophobicity of various strains from 3-19% to 94-99%. A profound effect of different cell surface properties was an altered spatial distribution of the cells in the fermented product. Aggregated cells tightly fill the cavities of the protein matrix, while chaining cells seem to be localized randomly. A positive correlation was found between pili overexpression and viscosity and gel hardness of fermented milk. Gel hardness also positively correlated with clumping of cells in the fermented milk. Viscosity of fermented milk was also higher when it was produced with cells with a chaining phenotype or with cells that overexpress exopolysaccharides. Our results show that alteration of cell surface morphology affects textural parameters of fermented milk and cell localization in the product. This is indicative of a cell surface-dependent potential of bacterial cells as structure elements in fermented foods.

GC-MS Based Metabolomics and NMR Spectroscopy Investigation of Food Intake Biomarkers for Milk and Cheese in Serum of Healthy Humans

The identification and validation of food intake biomarkers (FIBs) in human biofluids is a key objective for the evaluation of dietary intake. We report here the analysis of the GC-MS and 1H-NMR metabolomes of serum samples from a randomized cross-over study in 11 healthy volunteers having consumed isocaloric amounts of milk, cheese, and a soy drink as non-dairy alternative. Serum was collected at baseline, postprandially up to 6 h, and 24 h after consumption. A multivariate analysis of the untargeted serum metabolomes, combined with a targeted analysis of candidate FIBs previously reported in urine samples from the same study, identified galactitol, galactonate, and galactono-1,5-lactone (milk), 3-phenyllactic acid (cheese), and pinitol (soy drink) as candidate FIBs for these products. Serum metabolites not previously identified in the urine samples, e.g., 3-hydroxyisobutyrate after cheese intake, were detected. Finally, an analysis of the postprandial behavior of candidate FIBs, in particular the dairy fatty acids pentadecanoic acid and heptadecanoic acid, revealed specific kinetic patterns of relevance to their detection in future validation studies. Taken together, promising candidate FIBs for dairy intake appear to be lactose and metabolites thereof, for lactose-containing products, and microbial metabolites derived from amino acids, for fermented dairy products such as cheese.

Symposium review: Interaction of starter cultures and nonstarter lactic acid bacteria in the cheese environment

The microbiota of ripening cheese is dominated by lactic acid bacteria, which are either added as starters and adjunct cultures or originate from the production and processing environments (nonstarter or NSLAB). After curd formation and pressing, starters reach high numbers, but their viability then decreases due to lactose depletion, salt addition, and low pH and temperature. Starter autolysis releases cellular contents, including nutrients and enzymes, into the cheese matrix. During ripening, NSLAB may attain cell densities up to 8 log cfu per g after 3 to 9 mo. Depending on the species and strain, their metabolic activity may contribute to defects or inconsistency in cheese quality and to the development of typical cheese flavor. The availability of gene and genome sequences has enabled targeted detection of specific cheese microbes and their gene expression over the ripening period. Integrated systems biology is needed to combine the multiple perspectives of post-genomics technologies to elucidate the metabolic interactions among microorganisms. Future research should delve into the variation in cell physiology within the microbial populations, because spatial distribution within the cheese matrix will lead to microenvironments that could affect localized interactions of starters and NSLAB. Microbial community modeling can contribute to improving the efficiency and reduce the cost of food processes such as cheese ripening.

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 80's, 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.