Microbiota and Metabolite Profiling Combined With Integrative Analysis for Differentiating Cheeses of Varying Ripening Ages

Tuning and modeling cheese flavor

Flavor is a major sensory attribute affecting consumers' preference for cheese products. Differences in cheesemaking change the cheese microenvironment, thereby affecting cheese flavor profiles. A framework for tuning cheese flavor is proposed in this study, which depicts the full picture of flavor development and modulation, from manufacturing and ripening factors through the main biochemical pathways to flavor compounds and flavor notes. Taking semi-hard and hard cheeses as examples, this review describes how cheese flavor profiles are affected by milk type and applied treatment, fat and salt content, microbiota composition and microbial interactions, ripening time, temperature, and environmental humidity, together with packaging method and material. Moreover, these factors are linked to flavor profiles through their effects on proteolysis, the further catabolism of amino acids, and lipolysis. Acids, alcohols, ketones, esters, aldehydes, lactones, and sulfur compounds are key volatiles, which elicit fruity, sweet, rancid, green, creamy, pungent, alcoholic, nutty, fatty, and sweaty flavor notes, contributing to the overall flavor profiles. Additionally, this review demonstrates how data-driven modeling techniques can link these influencing factors to resulting flavor profiles. This is done by providing a comprehensive review on the (i) identification of key factors and flavor compounds, (ii) discrimination of cheeses, and (iii) prediction of flavor notes. Overall, this review provides knowledge tools for cheese flavor modulation and sheds light on using data-driven modeling techniques to aid cheese flavor analysis and flavor prediction.

Proteomics Parameters for Assessing Authenticity of Grated Grana Padano PDO Cheese: Results from a Three-Year Survey

Assessing the authenticity of PDO cheeses is an important task because it allows consumer expectations to be fulfilled and guarantees fair competition for manufacturers. A 3-year survey was carried out, analyzing 271 samples of grated Grana Padano (GP) PDO cheese collected on the European market. Previously developed analytical methods based on proteomics approaches were adopted to evaluate the compliance of market samples with selected legal requirements provided by the specification for this cheese. Proteolysis follows highly repeatable pathways in GP cheese due to the usage of raw milk, natural whey starter, and consistent manufacturing and ripening conditions. From selected casein breakdown products, it is possible to calculate the actual cheese age (should be >9 months) and detect the presence of excess rind (should be <18%). Furthermore, due to the characteristic pattern of free amino acids established for GP, distinguishing it from closely related cheese varieties is feasible. Cheese age ranged from 9 to 25 months and was correctly claimed on the label. Based on the amino acid pattern, three samples probably contained defective cheese and there was only one imitation cheese. Few samples (9%) were proven to contain some excess rind. Overall, this survey highlighted that the adopted control parameters can assure the quality of grated GP.

Characterization of the archaeal community in foods: The neglected part of the food microbiota

Despite the large number of studies conducted on archaea associated with extreme environments, the archaeal community composition in food products is still poorly known. Here, we investigated a new insight into exploring the archaeal community in several food matrices, with a particular focus on determining whether living archaea were present. A total of 71 samples of milk, cheese and its derived brine, honey, hamburger, clam, and trout were analyzed by high-throughput 16S rRNA sequencing. Archaea were detected in all the samples, ranging from 0.62 % of microbial communities in trout to 37.71 % in brine. Methanogens dominated 47.28 % of the archaeal communities, except for brine, which was dominated by halophilic taxa affiliated with the genus Haloquadratum (52.45 %). Clams were found to be a food with high richness and diversity of archaea and were targeted for culturing living archaea under different incubation time and temperature conditions. A subset of 16 communities derived from culture-dependent and culture-independent communities were assessed. Among the homogenates and living archaeal communities, the predominant taxa were distributed in the genera Nitrosopumilus (47.61 %) and Halorussus (78.78 %), respectively. A comparison of the 28 total taxa obtained by culture-dependent and culture-independent methods enabled their categorization into different groups, including detectable (8 out of 28), cultivable (8 out of 28), and detectable-cultivable (12 out of 28) taxa. Furthermore, using the culture method, the majority (14 out of 20) of living taxa grew at lower temperatures of 22 and 4 °C during long-term incubation, and few taxa (2 out of 20) were found at 37 °C during the initial days of incubation. Our results demonstrated the distribution of archaea in all analyzed food matrices, which opens new perspectives to expand our knowledge on archaea in foods and their beneficial and detrimental effects.

Universal drivers of cheese microbiomes

The culinary value, quality, and safety of cheese are largely driven by the resident bacteria, but comparative analyses of the cheese microbiota across cheese types are scarce. We present the first global synthesis of cheese microbiomes. Following a systematic literature review of cheese microbiology research, we collected 16S rRNA gene amplicon sequence data from 824 cheese samples spanning 58 cheese types and 16 countries. We found a consistent, positive relationship between microbiome richness and pH, and a higher microbial richness in cheeses derived from goat milk. In contrast, we found no relationship between pasteurization, geographic location, or salinity and richness. Milk and cheese type, geographic location, and pasteurization collectively explained 65% of the variation in microbial community composition. Importantly, we identified four universal cheese microbiome types, driven by distinct dominant taxa. Our study reveals notable diversity patterns among the cheese microbiota, which are driven by geography and local environmental variables.

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.

Developments in effective use of volatile organic compound analysis to assess flavour formation during cheese ripening

In the burgeoning demand for optimization of cheese production, ascertaining cheese flavour formation during the cheese making process has been the focal point of determining cheese quality. In this research reflection, we have highlighted how valuable volatile organic compound (VOC) analysis has been in assessing contingent cheese flavour compounds arising from non-starter lactic acid bacteria (NSLAB) along with starter lactic acid bacteria (SLAB), and whether VOC analysis associated with other high-throughput data might help provide a better understanding the cheese flavour formation during cheese process. It is widely known that there is a keen interest to merge all omics data to find specific biomarkers and/or to assess aroma formation of cheese. Towards that end, results of VOC analysis have provided valuable insights into the cheese flavour profile. In this review, we are pinpointing the effective use of flavour compound analysis to perceive flavour-forming ability of microbial strains that are convenient for dairy production, intertwining microbiome and metabolome to unveil potential biomarkers that occur during cheese ripening. In doing so, we summarised the functionality and integration of aromatic compound analysis in cheese making and gave reflections on reconsidering what the role of flavour-based analysis might have in the future.

Impact of lactic acid bacteria and their metabolites on the techno-functional properties and health benefits of fermented dairy products

After conversion of lactose to lactic acid, several biochemical changes occur such as enhanced protein digestibility, fatty acids release, and production of bioactive compounds etc. during the fermentation process that brings nutritional and quality improvement in the fermented dairy products (FDP). A diverse range of lactic acid bacteria (LAB) is being utilized for the development of FDP with specific desirable techno-functional attributes. This review contributes to the knowledge of basic pathways and changes during fermentation process and the current research on techniques used for identification and quantification of metabolites. The focus of this article is mainly on the metabolites responsible for maintaining the desired attributes and health benefits of FDP as well as their characterization from raw milk. LAB genera including Lactobacillus, Streptococcus, Leuconostoc, Pediococcus and Lactococcus are involved in the fermentation of milk and milk products. LAB species accrue these benefits and desirable properties of FDP producing the bioactive compounds and metabolites using homo-fermentative and heterofermentative pathways. Generation of metabolites vary with incubation and other processing conditions and are analyzed and quantified using highly advanced and sophisticated instrumentation including nuclear magnetic resonance, mass-spectrometry based techniques. Health benefits of FDP are mainly possible due to the biological roles of such metabolites that also cause technological improvements desired by dairy manufacturers and consumers.