Discriminative power of DNA-based, volatilome, near infrared spectroscopy, elements and stable isotopes methods for the origin authentication of typical Italian mountain cheese using sPLS-DA modeling.

Origin authentication methods are pivotal in counteracting frauds and provide evidence for certification systems. For these reasons, geographical origin authentication methods are used to ensure product origin. This study focused on the origin authentication (i.e. at the producer level) of a typical mountain cheese origin using various approaches, including shotgun metagenomics, volatilome, near infrared spectroscopy, stable isotopes, and elemental analyses. DNA-based analysis revealed that viral communities achieved a higher classification accuracy rate (97.4 ± 2.6 %) than bacterial communities (96.1 ± 4.0 %). Non-starter lactic acid bacteria and phages specific to each origin were identified. Volatile organic compounds exhibited potential clusters according to cheese origin, with a classification accuracy rate of 90.0 ± 11.1 %. Near-infrared spectroscopy showed lower discriminative power for cheese authentication, yielding only a 76.0 ± 31.6 % classification accuracy rate. Model performances were influenced by specific regions of the infrared spectrum, possibly associated with fat content, lipid profile and protein characteristics. Furthermore, we analyzed the elemental composition of mountain Caciotta cheese and identified significant differences in elements related to dairy equipment, macronutrients, and rare earth elements among different origins. The combination of elements and isotopes showed a decrease in authentication performance (97.0 ± 3.1 %) compared to the original element models, which were found to achieve the best classification accuracy rate (99.0 ± 0.01 %). Overall, our findings emphasize the potential of multi-omics techniques in cheese origin authentication and highlight the complexity of factors influencing cheese composition and hence typicity.

Ecological diversity and associated volatilome of typical mountain Caciotta cheese from Italy.

Traditional products are particularly appreciated by consumers and among these products, cheese is a major contributor to the Italian mountainous area economics. In this study, shotgun metagenomics and volatilomics were used to understand the biotic and abiotic factors contributing to mountain Caciotta cheese typicity and diversity. Results showed that the origin of cheese played a significant role; however, curd cooking temperature, pH, salt concentration and water activity also had an impact. Viral communities exhibited higher biodiversity and discriminated cheese origins in terms of production farms. Among the most dominant bacteria, Streptococcus thermophilus showed higher intraspecific diversity and closer relationship to production farm when compared to Lactobacillus delbrueckii. However, despite a few cases in which the starter culture was phylogenetically separated from the most dominant strains sequenced in the cheese, starter cultures and dominant cheese strains clustered together suggesting substantial starter colonization in mountain Caciotta cheese. The Caciotta cheese volatilome contained prominent levels of alcohols and ketones, accompanied by lower proportions of terpenes. Volatile profile not only demonstrated a noticeable association with production farm but also significant differences in the relative abundances of enzymes connected to flavor development. Moreover, correlations of different non-homologous isofunctional enzymes highlighted specific contributions to the typical flavor of mountain Caciotta cheese. Overall, this study provides a deeper understanding of the factors shaping typical mountain Caciotta cheese, and the potential of metagenomics for characterizing and potentially authenticating food products.

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.

Authenticity and Typicity of Traditional Cheeses: A Review on Geographical Origin Authentication Methods.

Food fraud, corresponding to any intentional action to deceive purchasers and gain an undue economical advantage, is estimated to result in a 10 to 65 billion US dollars/year economical cost worldwide. Dairy products, such as cheese, in particular cheeses with protected land- and tradition-related labels, have been listed as among the most impacted as consumers are ready to pay a premium price for traditional and typical products. In this context, efficient food authentication methods are needed to counteract current and emerging frauds. This review reports the available authentication methods, either chemical, physical, or DNA-based methods, currently used for origin authentication, highlighting their principle, reported application to cheese geographical origin authentication, performance, and respective advantages and limits. Isotope and elemental fingerprinting showed consistent accuracy in origin authentication. Other chemical and physical methods, such as near-infrared spectroscopy and nuclear magnetic resonance, require more studies and larger sampling to assess their discriminative power. Emerging DNA-based methods, such as metabarcoding, showed good potential for origin authentication. However, metagenomics, providing a more in-depth view of the cheese microbiota (up to the strain level), but also the combination of methods relying on different targets, can be of interest for this field.

Active Rumen Bacterial and Protozoal Communities Revealed by RNA-Based Amplicon Sequencing on Dairy Cows Fed Different Diets at Three Physiological Stages.

Seven Italian Simmental cows were monitored during three different physiological stages, namely late lactation (LL), dry period (DP), and postpartum (PP), to evaluate modifications in their metabolically-active rumen bacterial and protozoal communities using the RNA-based amplicon sequencing method. The bacterial community was dominated by seven phyla: Proteobacteria, Bacteroidetes, Firmicutes, Spirochaetes, Fibrobacteres, Verrucomicrobia, and Tenericutes. The relative abundance of the phylum Proteobacteria decreased from 47.60 to 28.15% from LL to DP and then increased to 33.24% in PP. An opposite pattern in LL, DP, and PP stages was observed for phyla Verrucomicrobia (from 0.96 to 4.30 to 1.69%), Elusimicrobia (from 0.32 to 2.84 to 0.25%), and SR1 (from 0.50 to 2.08 to 0.79%). The relative abundance of families Succinivibrionaceae and Prevotellaceae decreased in the DP, while Ruminococcaceae increased. Bacterial genera Prevotella and Treponema were least abundant in the DP as compared to LL and PP, while Ruminobacter and Succinimonas were most abundant in the DP. The rumen eukaryotic community was dominated by protozoal phylum Ciliophora, which showed a significant decrease in relative abundance from 97.6 to 93.9 to 92.6 in LL, DP, and PP, respectively. In conclusion, the physiological stage-dependent dietary changes resulted in a clear shift in metabolically-active rumen microbial communities.